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ISSN 0219-8908 Published in October 2010 Economic Policy Group Monetary Authority of Singapore http://www.mas.gov.sg All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanised, photocopying, recording or otherwise, without the prior written permission of the copyright owner except in accordance with the provisions of the Copyright Act (Cap. 63). Application for the copyright owner's written permission to reproduce any part of this publication should be addressed to: Economic Policy Group Monetary Authority of Singapore 10 Shenton Way MAS Building Singapore 079117 Printed by Xpress Print Singapore

Monetary Authority of Singapore Economic Policy Group

Contents

Preface i

Highlights ii-iii

Monetary Policy Statement iv-v

1 Macroeconomic Developments

1.1 External Developments 2

1.2 Domestic Economy 6

1.3 Macroeconomic Policy 16

Box A: Review of MAS Money Market Operations in FY2009/10 26

2 Wage-Price Dynamics

2.1 Labour Market Conditions 32

2.2 Consumer Price Developments 34

Box B: Why so Different? Singapore’s Recent Labour Market Dynamics 38

3 Outlook

3.1 External Outlook 46

3.2 Outlook for the Singapore Economy 50

3.3 Labour Market 57

3.4 Inflation 60

Special Features

Special Feature A: Is Free Trade Green? 66

Special Feature B: Is China a Sustainable Source of Demand for East Asia? 72

Special Feature C: The Mysteries of Trend 82

Statistical Appendix 90

List of Selected Publications 99

Macroeconomic Review, October 2010


LIST OF ABBREVIATIONS

ACU Asian Currency Unit

AUM assets under management

COE Certificate of Entitlement

CPI consumer price index

CSP community, social & personal

DBU Domestic Banking Unit

DLI Domestic Liquidity Indicator

EAI Economic Activity Index

EPG Economic Policy Group

ESC Economic Strategies Committee

FI Fiscal Impulse

FX foreign exchange

GDP gross domestic product

GHG greenhouse gases

GST goods and services tax

IMF International Monetary Fund

ISM Institute of Supply Management

IRs Integrated Resorts

M&A merger & acquisition

M&OE marine & offshore engineering

m-o-m month-on-month

MCB Minimum Cash Balance

MMO Money Market Operations

MPS Monetary Policy Statement

NEER nominal effective exchange rate

NODX non-oil domestic exports

OECD Organisation of Economic Cooperation and Development

OPEC Organisation of the Petroleum Exporting Countries

PCE private consumption expenditure

PMI Purchasing Managers’ Index

q-o-q quarter-on-quarter

REER real effective exchange rate

SA seasonally-adjusted

SAAR seasonally-adjusted annualised rate

SGS Singapore Government Securities

SRI Special Risk-Sharing Initiative

T&S transport & storage

TSC transport, storage & communications

y-o-y year-on-year

ytd year-to-date

Preface i


Preface

The Macroeconomic Review is published twice a year in conjunction

with the release of the MAS Monetary Policy Statement. The Review

documents the Economic Policy Group’s (EPG) analysis and

assessment of macroeconomic developments in the Singapore

economy, and shares with market participants, analysts and the wider

public the basis for the policy decisions conveyed in the Monetary

Policy Statement. It also features in-depth studies undertaken by EPG

on important economic issues facing Singapore.

The Review was edited by Associate Professor Peter Wilson, and

continued to feature our collaborations with various academics.

In this issue, we are pleased to have Professor Peter Phillips of Yale

University write about “The Mysteries of Trend” in Special Feature C.

We are also grateful to Mr Ravi Balakrishnan, the IMF Resident

Representative in Singapore, for contributing Box B, and Assistant

Professor Davin Chor from the School of Economics, Singapore

Management University, for his collaboration on Special Feature B.

Additionally, the Review has benefited from the advice of Professor

Jun Yu of the Singapore Management University on the econometric

work used in Chapter 2. Professors Max Corden of Johns Hopkins

University and Roger Sandilands of Strathclyde University also

provided useful comments for Special Feature A.

The data used in the Review were drawn from the following

government agencies, unless otherwise stated: BCA, CAAS, CPF Board,

DOS, EDB, HDB, IE Singapore, LTA, MOF, MOM, MTI, STB and URA.

The Review may be accessed in PDF format on the MAS website:

http://www.mas.gov.sg/publications/macro_review/index.html.

The Review may also be purchased at major bookstores, online

(http://asp.marketasia.com.sg/Spore/sporeindex.asp), or on an annual

subscription basis (details can be found on the last page).

ii Macroeconomic Review, October 2010


Highlights

After a strong start in the first half of 2010, the global recovery has lost momentum in recent months,

partly due to the scaling back of government stimulus packages and the fading of inventory restocking

effects. Looking ahead, the outlook for Singapore’s key trading partners will remain uneven. Notably, the

advanced economies will continue to face significant hurdles in transiting from public

sector-driven to private demand-led growth. Thus, while the risk of the developed economies slipping

back into recession has generally receded, final demand is likely to remain sluggish. Meanwhile,

Asia ex-Japan, which has led the global recovery so far, continues to enjoy healthy growth. There are,

however, risks related to rising capital inflows to the region which bear close monitoring. Against this

backdrop, the Singapore economy began to see signs of moderation in the middle of the year, following

exceptionally strong GDP growth in the first half. Nonetheless, the level of activity is projected to remain

high across a broad range of industries.

Chapter 1 of this Review presents an overview of recent economic developments in Singapore and the

external economies. In line with the weaker international environment and temporary plant shutdowns in

the local pharmaceutical industry, economic growth in Singapore underwent a downshift in the second

half of this year. This was most evident in trade-related activities, including those linked to electronics.

In the same chapter, we trace how monetary and fiscal policy settings were recalibrated to ensure

sustainable growth and price stability over the medium term, including a pre-emptive tightening of

monetary policy in April and October, as well as the gradual phasing out of the Jobs Credit Scheme and

Special Risk-Sharing Initiative.

In Chapter 2, we review recent labour market and price developments, which indicate that the labour

market has tightened significantly, especially in the services sectors, where job vacancy rates are at

near-record highs. Although external sources of price inflation have been benign, domestic inflationary

pressures have increased in the first three quarters of this year, particularly the prices of non-traded

items, such as accommodation and services. This chapter also contains a box item by Ravi Balakrishnan of

the IMF which looks at Singapore’s labour market dynamics and tries to explain why the labour market in

Singapore has been so resilient since the onset of the Great Recession. While Singapore’s relatively strong

employment growth can partly be explained by the output turnaround and a high response of

employment to output fluctuations, also important are wage flexibility, the positive effects of the

Jobs Credit Scheme and underlying sector-specific factors in the labour-intensive construction industry.

Chapter 3 focuses on the economic outlook, both domestically and externally. Given an expected

slowdown in growth in the advanced countries, domestic demand in Asia ex-Japan will be a key driver of

growth for the region, including Singapore. For 2010 as a whole, Singapore’s GDP is on track to grow by

13% to 15%. The domestic economy will continue to expand in 2011, but at a slower pace in line with its

growth potential. Compared to this year, when the manufacturing sector experienced a sharp surge in

activity, GDP growth next year will be driven more by the services sector. At the same time, productivity

growth will likely play a less dominant role next year, while employment growth continues apace.

As an extension of our work in previous issues of the Review on the importance of final demand in

advanced developed countries to Asian economies, we include a Special Feature examining whether

export-driven economies in the region have diversified their sources of growth away from the G3 towards

China. The findings suggest that, prior to the crisis, East Asian exports were heavily dependent on G3

demand while the Chinese market had a much smaller, albeit rising, impact. During the crisis itself,

however, there is evidence of weaker synchronicity between East Asia and the G3 economies. But this

may be due to the transitory buffer provided by policy-induced demand in China, rather than evidence of

decoupling between East Asia and the G3. This Review also includes a Special Feature which explores the

Highlights iii


simple, but emotive, issue of whether free trade is good for the environment, by introducing

environmental issues into a standard microeconomic framework.

Finally, we conclude this Review with a Special Feature by Professor Peter C. B Phillips on “The Mysteries

of Trend” in which he discusses the elusive nature of trends and illustrates the extent of the difficulties in

learning about trend phenomena in time series data, even when the time-series available are far longer

than those usually available in economics.

The next issue of the Review will be released in April 2011.

Economic Policy Group

Monetary Authority of Singapore

27 October 2010

iv Macroeconomic Review, October 2010

14 October 2010

Monetary Policy Statement

INTRODUCTION 1. In April this year, MAS re-centred the exchange rate policy band at the prevailing level of the S$NEER, and shifted the policy band from that of a zero percent appreciation path to one of modest and gradual appreciation. This policy decision took into account the strong rebound of the Singapore economy from the downturn and incipient inflationary pressures emanating from domestic and external sources.

Chart 1 S$ Nominal Effective Exchange Rate (S$NEER)

Apr Jul Oct Jan Apr Jul Oct

98

99

100

101

102

103

104

105

106

Inde

x (3

Apr

200

9 =

100)

indicates release of Monetary Policy Statement

Appreciation

Depreciation

2009 2010

2. Since then, the S$NEER (Chart 1) has fluctuated in the upper half of the policy band, reflecting investors’ assessment of the more favourable growth outlook for Asia compared to the weaker prospects of the advanced economies. Against conditions of abundant liquidity globally, the domestic three-month interbank rate has eased further to 0.50% as at end-September this year.

OUTLOOK FOR 2010 3. Following the exceptionally strong pace of expansion in the first half of this year, the Singapore economy contracted by 19.8% on a quarter-on-quarter seasonally adjusted annualised basis in Q3 2010, according to the Advance Estimates released by the Ministry of Trade and Industry today. This reflected a sharp pullback in pharmaceutical output and some moderation in the underlying growth momentum in the rest of the economy, particularly in the trade-related industries1/. The downshift in economic growth in the second half of the year was largely expected as the temporary boost from inventory restocking waned and some pharmaceutical plants switched to the production of a different value-mix of active ingredients. Notwithstanding the sequential contraction in Q3, the economy recorded growth of 15.5% year-on-year in the first three quarters of this year. For 2010 as a whole, GDP is on track to grow by 13% to 15%.


Monetary Policy Statement v

4. Looking ahead, economic activity in the major industrial economies is likely to expand at a slower pace, following a fairly brisk recovery from the recession. Unemployment remains elevated and credit growth subdued. With fiscal consolidation underway, the pace of transition to private demand-led growth in the G3 economies is expected to be gradual. In Asia, growth will be supported by robust domestic demand and a resilient financial sector. While some slowdown is expected, overall economic conditions in the region should stay firm. Against this backdrop, the level of economic activity in Singapore is projected to remain high across a broad range of industries although growth could further ease in the near term. In 2011, the domestic economy will continue to expand but at a more sustainable rate in line with its growth potential. 5. Domestic CPI inflation rose significantly from 0.9% in Q1 2010 to 3.1% in Q2, and edged up further to 3.2% in July-August. While inflation has been largely driven by higher car and commodity prices so far this year, other domestic sources of cost pressures have emerged amidst buoyant economic conditions. For instance, the costs of accommodation and domestic-oriented services accounted for more than half of CPI inflation on a sequential basis in July-August. With the economy already operating at close to full employment, labour cost pressures have picked up and will persist into 2011. Externally, food commodity prices have risen, in part due to the recent supply disruptions. More of these costs could potentially be passed on to consumers in a strengthened domestic economy. Even as base effects dissipate, the build-up in sequential price increases will cause the headline CPI inflation rate to rise to around 4% by the end of 2010 and stay high in the first half of 2011 before moderating.

MONETARY POLICY 6. The Singapore economy will continue to expand, although at a slower and more sustainable pace after recovering robustly from the downturn. At the same time, domestic cost pressures are rising, given the high level of resource utilisation in the economy and tight labour market in particular, as well as the diminishing boost from the cyclical uplift in productivity seen earlier this year. Thus, the balance of risks is weighted towards inflation going forward. 7. MAS will therefore continue with the policy of a modest and gradual appreciation of the S$NEER policy band in the period ahead. However, the slope of the policy band will be increased slightly, with no change to the level at which the band is centred. The policy band will at the same time be widened slightly in view of the volatility across international financial markets. This policy stance will remain supportive of economic growth while seeking to cap CPI inflation at 2-3% in 2011 from 2.5-3.0% in 2010, and ensure medium-term price stability. The MAS underlying inflation measure, which excludes the cost of accommodation and private road transport, is expected to average around 2% in 2010 and 2-3% next year.

1 / These include manufacturing (excluding pharmaceuticals), wholesale trade and transport & storage services.


Chapter 1 Macroeconomic

Developments

2 Macroeconomic Review, October 2010


1.1 External Developments The Global Rebound Slows

A flagging recovery.

Global economic activity recovered further in the second quarter of 2010. However, with the exception of the Eurozone, the pace of growth has slowed. Overall, real GDP in Singapore’s major trading partners expanded by a weaker 5.0% q-o-q SAAR in Q2 2010 compared to 6.8% in Q1. This deceleration was especially pronounced in the US and Japan, but it was also evident in Asia, which had led the global rebound.1 Nevertheless, Asian growth continued to outstrip that of the G3. (Table 1.1) As a result, the region’s GDP was around 10% above its pre-crisis peak as at Q2 2010, while G3 output remained slightly below the levels reached prior to the crisis. A confluence of three factors contributed to the moderation of global growth. First, the waning of fiscal stimulus measures in the US and Asia, as well as the need for budgetary tightening in the Eurozone, removed significant support for global aggregate demand. Second, the one-off boost from the inventory restocking cycle had faded as a result of the inevitable pullback from the expansion in production seen during the early stages of the recovery. Third, the sovereign debt crisis in the peripheral Eurozone economies had led to a tightening of credit channels and stoked fears of a renewed world recession. However, the risks on this front appear to have subsided somewhat, although credit spreads for some of the affected countries remain quite wide.

Growth in the G3 has been uneven, with the US and Japan slowing in Q2 …

In the US, real GDP growth slowed to 1.7% q-o-q SAAR in Q2 this year, markedly lower than the 3.7% posted in Q1. (Chart 1.1) The main drag on growth was a large increase in imports and a consequent decline in net exports, which shaved 3.5% points off the headline GDP figure. (Chart 1.2) Private consumption

Table 1.1 GDP Growth

(%)

2009 2010

H1 Q1 Q2

Growth over preceding

period, SAAR Total* -0.7 6.5 6.8 5.0 G3* -3.6 3.0 3.1 2.4 Asia* 1.7 8.6 9.2 6.2 US -2.6 3.5 3.7 1.7 Eurozone -4.0 1.8 1.3 3.9 Japan -5.2 3.7 5.0 1.5 Hong Kong -2.8 8.3 8.9 5.9 Korea 0.2 6.0 8.8 5.8 Taiwan -1.9 11.3 10.9 7.2 Thailand -2.2 11.1 13.9 0.6 Philippines 1.1 10.9 16.1 5.3 y-o-y Indonesia 4.5 5.9 5.7 6.2 Malaysia -1.7 9.5 10.1 8.9 China 9.1 11.1 11.9 10.3 India 6.7 8.7 8.6 8.8

Source: CEIC, Datastream and EPG, MAS estimates * Weighted by shares in Singapore’s NODX.

Chart 1.1 G3 GDP Growth

Source: Datastream

1 Asia comprises China, Hong Kong, India, Indonesia, Malaysia, the Philippines, South Korea, Taiwan and Thailand.

2007 2008 2009 2010-20

-15

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US

Eurozone

Japan

Macroeconomic Developments 3


expanded modestly by 2.2% in Q2 on a q-o-q SAAR basis and households made progress in restoring their balance sheets, with the personal savings rate rising to 6.1%. (Chart 1.3) More encouragingly, private fixed investment increased by 19%, spurred by robust growth in corporate spending on equipment and software and a turnaround in residential investment. However, the labour market remained weak, with the unemployment rate at 9.6% in September, significantly higher than the pre-crisis average of around 5%. Non-farm payrolls had slipped slightly in recent months largely due to a fall in government employment. While private sector employment trended higher by an average of 91,000 a month in Q3, overall job creation is generally regarded as below the level necessary to absorb new entrants into the workforce. Following a solid expansion of 5.0% q-o-q SAAR in Q1, Japan’s GDP growth decelerated sharply to 1.5% in Q2. Personal consumption expenditure was flat as employment and income growth lagged the export-led recovery that began in mid-2009. In contrast, business fixed investment in Q2 rose by a robust 6.4% on a q-o-q SA basis, on the back of a pickup in corporate profits and a revival of business sentiment. Despite the strong yen, export growth in Q2 came in at 26% q-o-q SAAR, due to healthy demand from China and other Asian economies, especially for IT products and capital machinery.

… while the Eurozone accelerated, mostly due to the core economies.

The Eurozone economy grew by an impressive 3.9% on a q-o-q SAAR basis in Q2 2010, up from 1.4% in the previous quarter. This was principally attributed to strong manufacturing exports in the core countries, in particular, France and Germany, aided by the depreciation of the euro over the past few quarters.2 Domestic demand also held up well in Q2 despite the crisis in sovereign debt markets, with retail sales and spending on consumer durables remaining firm in August. Nevertheless, there was a marked divergence in the performance of the larger economies in the group, such as France and Germany, and the smaller,

Chart 1.2 Contribution to US GDP Growth

Source: US Bureau of Economic Analysis

Chart 1.3 US Personal Savings Rate

Source: US Bureau of Economic Analysis

2 The Euro NEER has depreciated by 11.4% since October 2009.

2007 2008 2009 2010 Q2 -10

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Government ConsumptionResidential Investments

Net Exports of Goods and Services

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Avg 2000-05= 2.9%



peripheral members, such as Greece and Spain. (Chart 1.4) In particular, the latter had not benefited from the surge in exports that lifted growth in the larger Eurozone economies.

Growth in Asia ex-Japan has likely peaked. Asia ex-Japan is at a more advanced phase of recovery relative to the G3, having exited the recession earlier and having rebounded more rapidly. Growth appeared to have peaked in Q1, and has slowed to a more sustainable rate. (Chart 1.5) The prior pace of expansion was especially unsustainable in the trade-dependent economies, such as Korea and Taiwan, as much of the earlier boost came from inventory replenishment arising from robust IT demand. In comparison, growth has been more stable in the domestic-oriented economies of China, India and Indonesia, underpinned by continued strength in consumption and investment spending. Having grown by nearly 10.3% y-o-y in Q2 2010, the Chinese economy advanced by 9.6% in Q3. Correspondingly, retail sales and fixed asset investment growth moderated from their earlier highs, although they remained firm in Q3. (Chart 1.6) Real estate investment, in particular, has stayed buoyant, notwithstanding the slew of government measures to rein in asset price inflation in the big cities. On the external front, export growth eased to 32% y-o-y in Q3 in tandem with the slowing global economy, after rising to above 40% in Q2. Since the onset of the global financial crisis, the continued strength of Chinese domestic demand has been an important source of support for the regional economies. The role played by China in propping up intra-Asian trade and growth is analysed in a recent study by EPG and reported in Special Feature B. Specifically, the study quantifies the relative contributions of final demand in China and the G3 to the growth of EA-83 exports of machinery partsand components in real terms. The results confirm that Chinese final demand, lifted by the government’s fiscal stimulus package, provided an important buffer for EA-8 intermediate exports amidst the sharp retrenchment in G3 demand at the depth of the financial crisis. (Chart 1.7) Correspondingly, the slower

Chart 1.4 Industrial Production in the Eurozone

Source: Datastream and EPG, MAS estimates

Chart 1.5 Asia ex-Japan GDP Growth*

Source: CEIC * The trade-dependent economies are Hong Kong, Korea, Malaysia, Taiwan and Thailand and the domestic-oriented economies comprise China, India, Indonesia and the Philippines.

Chart 1.6 Chinese Fixed Asset Investment

and Retail Sales

Source: CEIC

3 EA-8 refers to Hong Kong, Indonesia, Malaysia, the Philippines, Singapore, South Korea, Taiwan and Thailand.

2007 2008 2009 201070

80

90

100

110

70

Inde

x (J

an 2

007=

100)

, SA

Aug

Germany

France

Greece

Spain

Italy

Portugal

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% G

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Q2

Domestic-oriented Economies

2008 2009 201010

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% G

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th

Sep

Retail Sales

Fixed Asset Investment (ytd)



growth of final demand in China since Q3 2009 has resulted in some sequential moderation in EA-8 exports.

Regional differences were also seen in inflation trends.

Stronger economic growth in Asia has resulted in a higher rate of CPI inflation compared to the G3, with recent data showing increasingly divergent trends. (Chart 1.8) Overall, inflation in both regions has picked up on a y-o-y basis since late 2009, owing to low base effects as well as the ongoing recovery of the global economy. In the G3, spare capacity and high unemployment have continued to restrain price and wage pressures, with headline CPI inflation at a relatively subdued 1.0% y-o-y in August 2010. Indeed, at these low levels, with core prices remaining largely unchanged over the past year or so, disinflation has emerged as a significant risk in the US. In its latest commentary, the Federal Reserve noted that underlying inflation was at a level somewhat below that judged to be consistent with its mandate to promote maximum employment and price stability over the longer run. In Japan, deflation risks have also come to the fore, prompting renewed monetary easing measures from the Bank of Japan. Fears of disinflation in the core Eurozone economies, however, have been assuaged by the recent uptick in economic activity. In contrast, CPI inflation in Asia (ex-Japan and India)4 climbed steadily over the past year, from below zero in Q3 2009 to 3.3% in the first two months of Q3 2010. Production across the region has expanded at a rapid clip since mid-2009, and the consequent narrowing of output gaps has contributed to the rise in inflationary pressures. In addition, the pickup in energy prices towards the latter part of 2009, and in food prices recently, also has had a more pronounced impact on headline inflation in the Asian economies, given the larger weights of these commodities in their CPI baskets. Nevertheless, the appreciation in regional currencies over the past few quarters have helped to dampen imported inflation. (Chart 1.9)

Chart 1.7 Contribution of China and G3 Final Demand

to Growth of EA-8 Intermediate Exports

Source: GTA and EPG, MAS estimates * Includes country-specific influences and exchange rate changes.

Chart 1.8 Global CPI Inflation

Source: CEIC and EPG, MAS estimates

Chart 1.9

NEER of Selected Asian Economies

Source: CEIC and IMF

4 India is excluded because it has experienced markedly different inflation trends from the rest of the region. Inflation in

India reached a peak of 11.0% in April 2010 due to heightened food inflation and pressures from rising demand amidst the strong pickup in the economy. In August, it fell to 8.5% due to favourable base effects and improved weather conditions, which lowered food price inflation.

2008 Q3 2009 Q3 2010-20

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G3

Other Factors*

Export Growth

2008 2009 2010-2

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G3

Asia ex-Japan and India

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00),

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rage

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Indonesia

Malaysia

Philippines

Thailand

South Korea

China



1.2 Domestic Economy Resilience Beyond the Recovery

The economy continued to expand strongly in Q2.

Amidst continued growth in the external economies, the Singapore economy strengthened further in the second quarter of this year. On a q-o-q SAAR basis, the economy expanded by 27.3% in Q2 2010, on the heels of an unprecedented increase of 45.9% in the previous quarter. This brought GDP levels for the first half of 2010 to about 18% higher than in the same period a year ago. The strong sequential growth in Q2 was due largely to a surge of more than 300% in pharmaceuticals production, as manufacturers continued to increase output of high value-added active pharmaceutical ingredients. (Chart 1.10) The uplift was also extended to the rest of the economy, with the other trade-related, financial and tourism-related sectors recording fairly robust growth. Chart 1.11 shows that all the major sectors had surpassed their pre-crisis peaks by Q2 2010. Not only was the recovery synchronised across different sectors of the economy, it was also broad-based from the expenditure perspective. (See page 13 for more details.)

Singapore’s rebound was the strongest in the region.

The steep upward trajectory in economic activity in the recent rebound was fuelled mainly by the cyclical upturn in global demand. However, the boost from the resumption of global economic activity appeared to have been more pronounced in Singapore than in the rest of the region. By the end of Q2 2010, the Singapore economy had rebounded some 27% from its GDP trough in Q1 2009, the largest climb amongst the regional economies over the same period. Singapore also recorded the largest increase from its previous pre-crisis peak. (Chart 1.12)

Chart 1.10 Singapore’s GDP Growth

Source: EPG, MAS estimates

Chart 1.11 Q2 GDP Levels compared with

Previous Peak

Q2 20100

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IT-relatedNon-IT RelatedPharmaceuticals

Asset Market-relatedOthers

Trade-related

Manufacturing 20%

Construction 47%

Wholesale& Retail

4.1%

Business 14%

Financial 13%

Tspt, Storage & Comms0.3%

Pre-crisis GDP Peak (Q1 2008)



Using a variant of shift-share analysis, EPG decomposed Singapore’s GDP rebound into three components: the external effect, the competitive effect and the industry-mix effect.5 The results suggest that the strong rebound was largely due to the “external” effect shown by the red segment in Chart 1.13. This captures the average rebound of 15% points enjoyed by all regional economies arising from the cyclical upturn in global trade and financial market activity. The blue portion of the bar captures the additional growth of about 12% points from Singapore’s “competitiveness”, reflecting the domestic industries’ ability to more strongly leverage on the turnaround in external demand conditions. Finally, the slightly negative green sliver of the bar represents the industry-mix effect, which points to Singapore’s marginally lower share of high-growth industries (in this case, manufacturing) in its economy compared to its competitors during this period.6 The stronger sectoral performance of the Singapore economy compared to the region in this current rebound is shown by the clustering of sectors in the upper triangle of Chart 1.14. Notably, the domestic manufacturing sector saw a 68% rebound over the period Q1 2009 to Q2 2010, almost twice the 35% average growth rate for the region as a whole. Further disaggregation shows that this was underpinned by both the electronics and pharmaceuticals segments. The domestic electronics industry, which has shifted towards higher value-added semiconductor production in recent years, was well-positioned to benefit from the recent upswing in the global IT cycle. From a global perspective, the semiconductor industry outperformed IT end-products such as PCs and handsets in the recent recovery. (Chart 1.15) This could be due to the shortage of semiconductors arising from underproduction prior to the crisis in 2008-09. The shortage was exacerbated by more aggressive destocking, as well as the closure of several semiconductor plants during the crisis.

Chart 1.12 (a) GDP Recovery from Trough*

Source: CEIC and EPG, MAS estimates * Covers the period Q1 2009 – Q2 2010.

(b) GDP Comparison with Pre-crisis Peak

Chart 1.13 Decomposition of Singapore’s GDP Growth


5 The external effect identifies the portion of Singapore’s GDP growth arising from factors in the external environment that

are common to all regional economies. This is calculated as the product of overall regional growth and Singapore’s GDP in Q1 2009 (i.e. the trough of the recession). The competitive effect captures the growth differential between each sector in Singapore and its regional equivalent, multiplied by Singapore’s GDP in Q1 2009. Finally, the industry mix component is estimated as the differential between the regional sector growth rate and the overall regional growth rate, multiplied by Singapore’s GDP in Q1 2009.

6 In general, Singapore has a higher-than-average share in sectors such as financial and business services, commerce, and transport, storage & communications (TSC). These sectors recorded moderate growth averaging 7-9% across the region in the post-crisis period. However, Singapore is slightly below the regional average in manufacturing share, a sector that saw strong regional growth of 35%.

Thailan

d

Indonesia

Malays

ia

Philippines

Korea

Taiwan

Singapore

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Competitive External Industry-mix

Q1 2009 - Q2 2010



As such, when the global economy emerged from the recession in Q2 last year, semiconductor sales saw a stronger rebound than end-product sales due to greater inventory restocking. Singapore, with a high share of semiconductor exports compared to the region, benefited significantly from this. Meanwhile, several of Singapore’s services industries have been upgrading to cater to the growing middle to high income segments in the region. Financial services, for example, has seen a shift towards higher value-added activity in recent years, particularly in the front-office operations within the wealth advisory cluster, as financial institutions re-position themselves to capitalise on the region's growing affluence. The Credit Suisse Global Wealth Report 2010 estimated Asia-Pacific wealth to have increased 85% over the last decade to US$62 trillion in 2010, outpacing global wealth growth of 72%. Some financial institutions have responded to the increased demand for fund management services by ramping up hiring to serve both the mass market wealth and the high net worth segments. In addition, the first half of the year saw a series of capacity additions across the manufacturing and services sectors in Singapore. These provided a step-up in activity that coincided with the wider cyclical upturn. In the manufacturing sector, pharmaceuticals production was buoyed by the opening of Roche's US$500 million biologics plant late last year. Singapore’s competitive edge in the services sector was also sharpened with the opening of Resorts World Sentosa in January and Marina Bay Sands in April this year, which provided a boost to the tourism-related industries. Following the opening of the two Integrated Resorts (IRs), for instance, visitor arrivals increased to an average of about 2.8 million per quarter, up from 2.5 million previously. (Chart 1.16) Coupled with higher local spending, this in turn translated into strong growth in hotel and restaurant revenues, casino and theme park earnings, as well as taxes and levies. The retail trade and transport sectors benefited as well. These developments bode well for the Singapore economy in the medium term and suggest that the domestic corporate sector has the ability to continuously re-position itself to capitalise on new growth trends. In Chapter 3, we consider further how these developments will support GDP growth next year.

Chart 1.14 Domestic Sectoral Growth Compared to the Region*

Source: CEIC and EPG, MAS estimates * Covers the period Q1 2009 – Q2 2010.

Chart 1.15

Global IT Sales

Source: Gartner, Goldman Sachs Research and World Bank

0 10 20 30 40 50 60 70Asia's Growth (%)

0

10

20

30

40

50

60

70

Sing

apor

e's

Gro

wth

(%)

Manufacturing

OverallCommerce

TSCOthers

Fin & Biz

Primary

SGP growth > Asia growth

Asia growth > SGP growth

PCs

Handsets

Semiconductors

2006 2007 2008 2009 2010F90

95

100

105

110

115

120

125In

dex

(200

6=10

0)



Chart 1.16 IRs’ Contribution to H1 2010 GDP Growth

Transiting to Sustainable Growth

A downshift in activity began in H2 2010.

Economic activity in Singapore slowed in the second half of 2010. According to the Advance Estimates, the Singapore economy contracted by 19.8% q-o-q SAAR in Q3, largely due to a fall in manufacturing value-added of 57.0%. (Chart 1.17) The construction sector also declined by 11.7%. Meanwhile, growth in the services sector slowed significantly to 1.6% q-o-q SAAR, after two quarters of double-digit sequential gains. Most of the decline in the manufacturing sector stemmed from a sharp pullback in pharmaceuticals output, which was due to a switch in the product mix for the quarter, as well as some plant maintenance shutdowns. Excluding pharmaceuticals manufacturing, the economy was estimated to have contracted marginally, following the 12% growth in the preceding quarter.

Chart 1.17

Singapore’s GDP Growth

2.3

2.4

2.5

2.6

2.7

2.8M

illio

nVisitor Arrivals

-5

0

5

10

15

YOY

% G

row

thBefore:Average of Q2-Q4 2009

After:Average ofQ1-Q2 2010

Hotels & Restaurants Other Services Taxes on Products

2008Q3 2009 Q3 2010 Q3-30

-15

0

15

30

45

60

Per C

ent

QOQ SAAR

YOY Growth



EPG’s new monthly activity index points to May 2010 as a turning point.

The contraction in Q3 2010 was corroborated by EPG’s newly constructed Economic Activity Index (EAI), which showed economic activity peaking in May this year. (Chart 1.18) EAI is a monthly composite index which aggregates a set of coincident indicators across different sectors of the economy, weighted by their economic importance. Figure A presents the main indicators used to compile the EAI, colour-coded according to their monthly sequential growth rates. As these indicators are available at a higher frequency, EAI complements the quarterly advance GDP estimates from DOS and provides useful information on monthly movements within any given quarter. After an uninterrupted run-up since November 2009, the index started to decline in June 2010, led chiefly by falling pharmaceutical production. Excluding pharmaceutical production, the index shows an almost continuous upward trend since February 2009, leveling off somewhat in April this year.

Chart 1.18 EPG’s Economic Activity Index (EAI)

Figure A

EPG’s Economic Activity Index – Selected Indicators

Mar Apr May Jun Jul Aug Overall Monthly GDP

Trade-related Indicators Overall Trade-related

Index of Industrial Production Non-oil Re-exports (Real) Sea Cargo Air Cargo

Financial Indicators Overall Financial

DBU Loans ACU Loans Stock Market Turnover Forex Turnover Others*

Others Tourist Arrivals IDD Call Minutes Retail Sales Volume Certified Payments

* EPG, MAS estimates.

2008 Jul 2009 Jul 2010 Aug90

100

110

120

130

Inde

x (2

009=

100)

, SA

Overall GDP

GDP ex- Pharmaceuticals

Month-on-month decline

Increased at a slower pace

Increased at a faster pace



Apart from pharmaceuticals, the slowdown was most evident in trade-related activities.

As seen in Figure A, the downshift in economic activity was most evident in the trade-related sectors, such as manufacturing and transport & storage (T&S), which saw activity moderating alongside the broader slowdown in the external environment. In particular, domestic electronics production softened in Q3, following the initial boost from inventory restocking and pent-up final demand after the downturn. (Chart 1.19) Indeed, as the global IT industry entered a period of consolidation alongside the convergence of inventory and production levels with final demand, growth momentum cooled. The Federal Reserve Bank ofSan Francisco’s US Tech Pulse Index,7 which tracks the health of the US technology sector, also captures the moderation in economic activity in Q3 following the steep recovery in the first half of the year. (Chart 1.20)

Financial services growth also moderated. Coincident with renewed risk aversion in global financial markets, Singapore’s financial services sector was weighed down by a pullback in the sentiment-driven segments in Q3. Although average stock market turnover volumes rose 11% q-o-q, this was largely due to a surge in the last two weeks of September arising from “window-dressing” activity. (Chart 1.21) Average daily trading volumes had otherwise trended down since peaking in Q2 2009, falling from 2.4 billion units to 1.7 billion units in Q3 2010. Transaction volumes in the foreign exchange (FX) markets were also capped by the ongoing uncertainty about the global economic recovery, recording an average 4.5% m-o-m decline in July and August.

Chart 1.19 IT-related Activities

* EPG, MAS estimates.

Chart 1.20 US Tech Pulse Index

Source: Federal Reserve Bank of San Francisco

Chart 1.21 Stock Market Performance

Source: SGX

7 The US Tech Pulse Index, compiled by the Federal Reserve Bank of San Francisco, is an index of coincident indicators of

activity in the US IT sector. The indicators used are investment in IT goods, consumption of personal computers and software, employment in the IT sector as well as industrial production of, and shipments by, the technology sector. The index extracts the common trend that drives these series.

2008 Q3 2009 Q3 2010 Q360

70

80

90

100

110

120

100

Inde

x (Q

1 20

08=1

00),

SA

Air Cargo Handled*

Electronics Production

Re-exports of Electronics (Real)

2000 2002 2004 2006 2008 2010Sep-60

-40

-20

0

20fr

om H

isto

rical

Ave

rage

% D

evia

tion

of 1

2-m

th G

row

th R

ate

2008 2009 201010

20

30

40

50

60

70

Bill

ion

Uni

ts

1500

1800

2100

2400

2700

3000

3300

Inde

x

Volume (LHS) STI (RHS)

Sep



On the financial intermediation front, growth in domestic lending eased in Q3. (Chart 1.22) Overall loan volumes in August expanded by just 0.3% m-o-m,compared to 1.7% in July on the back of sluggish interbank lending and a milder expansion in the consumer credit segment. Consumer lending grew by 1.3% in August, down from 1.9% in July, on slower gains in housing & bridging loans and a sixth consecutive month of decline in car loans. Meanwhile, business lending rose in August, but lending to trade-related segments, such as manufacturing and commerce, weakened. In addition, narrowing interest margins have continued to weigh on intermediation activity. Likewise, offshore lending (ACU) also registered a slower 1.5% m-o-m increase in August, following 1.7% and 3.4% expansions in July and June respectively. This was due to a moderation in ACU non-bank lending activity, reflecting the decline in demand for funding from the US and Europe following softer global business sentiment in Q3.

Retail sales volumes stabilised while visitor arrivals eased.

While growth in financial and trade-related services eased in Q3 2010, the retail trade sector saw retail sales volumes growing by an average of 2.6% m-o-m SA after sizeable declines in Q2. Vehicle sales picked up in July and August, following a drop of 78% q-o-q SAAR in the previous quarter on COE quota reductions. Excluding vehicles, retail sales volumes continued to edge up steadily, expanding by an average of 0.9% m-o-m SA in the earlier months of Q3, driven chiefly by better sales at department stores and mass-market retailers. In Q3, there were emerging signs that this year’s resurgence in tourist flows, which had propelled the air transport and hospitality industries in H1, was cooling. In the first two months of Q3, visitor arrivals fell, led by fewer arrivals from ASEAN. (Chart 1.23) This was in contrast to the 27% q-o-q SAAR surge in the previous quarter. Correspondingly, in August, hotel occupancy slipped below 83% for the first time since Dec 2009.

Chart 1.22 Overall ACU and DBU Loans

Chart 1.23 Visitor Arrivals and Hotel Occupancy


2008Jul 2009 Jul 2010460

480

500

520

540

$ B

illio

n

660

690

720

750

780

US$

Bill

ion

DBU (LHS) ACU (RHS)

Aug

2008 2009 2010

-30

-15

0

15

30

45

QO

Q S

AA

R %

Gro

wth

65

70

75

80

85

90

% ,

SA

Hotel Occupancy Rate (RHS)

Jul-Aug

Visitor Arrivals (LHS)



The slowdown in the domestic economy in Q3 was expected.

Alongside the softening in the external environment and the dissipation of the inventory restocking effect, the slowdown in the domestic economy in Q3 this year was largely expected. These short-term adjustments are not indicative of an imminent relapse into broad-based weakness in the economy, and the level of economic activity is expected to remain high in the quarters ahead. This will be discussed in greater detail in Chapter 3.

An Expenditure Perspective

The recovery has been broad-based from the expenditure perspective.

While the preceding section features the Singapore economy from the industry perspective, the following section traces the recovery profile from the expenditure angle. Following the trough in Q1 2009, all major expenditure components, including private consumption, net exports and fixed investment, have turned around and played a part in fuelling the strong GDP expansion in the first half of 2010. (Chart 1.24) Net exports featured most prominently, accounting for slightly more than half of H1 GDP growth. Over the same period, the inventory component contributed a sixth to GDP growth. Private consumption, which underwent a shallow and brief downturn, recovered in Q2 2009 along with the overall economy. It grew by 6.3% in H1 2010 on a y-o-y basis, accounting for less than one-sixth of overall GDP growth.

Exports and private investment saw a stronger rebound in this recovery.

A comparison of the recent upturn with that following the Asian Financial Crisis and the 2001 IT Downturn point to somewhat different recovery characteristics, as depicted in Chart 1.25.

Chart 1.24 Contribution to GDP Growth

2006 2007 2008 2009 2010 H1-10

0

10

20

to Y

OY

Gro

wth

% P

oint

Con

trib

utio

n

Pte Consumption ExpenditureGovt Consumption ExpenditureGross Fixed Capital FormationChanges in Inventories

Net ExportsStatistical DiscrepGDP



While all three recoveries were facilitated by the rebound in exports of goods and services, the recovery from the trough was steepest in the current upturn. Nonetheless, this has to be seen in the context of the sharper fall-off in exports during the recent recession. As such, exports of goods and services were only 5.3% above their pre-crisis peak in Q2 2010, five quarters from the GDP trough compared to 7.2% at the same stage of the GDP cycle in 1999 in the aftermath of the Asian Financial Crisis. Meanwhile, imports also made a relatively rapid comeback in the recent upturn, driven by stronger demand for IT components and capital equipment. The relatively stronger growth in imports during the last recession meant that net exports played a smaller role in the current recovery than in the past. Compared to the previous two recessions, private fixed investment was more resilient in this cycle. The Asian Financial Crisis coincided with a retraction in domestic construction activity; the period following the 2001 IT Downturn was also characterised by weak domestic demand and a severe decline in fixed investment. In contrast, expenditure on construction & works was a pillar of strength throughout the recent recession, offsetting the initial slump in fixed

investment of machinery & equipment, and continued to grow in H1 2010. Meanwhile, the pickup in the latter was steeper in this recovery and was associated with stronger imports of capital equipment. This suggests that businesses had pushed ahead with their expansion plans amidst a strong rebound in sentiment. Indeed, expectation surveys have indicated a steady improvement in the business outlook since late-2008.8 Nonetheless, the growth in overall fixed investment was weighed down by a slump in the transport equipment component, which was due to a pullback following a surge in these typically lumpy investments in 2007 and 2008. Finally, private consumption expenditure (PCE) remained relatively stable throughout the recent recession and subsequent recovery, matching, in part, the resilience of the domestic labour market. In the Asian Financial Crisis, it fell further and was followed by a prolonged recovery from the trough. The steady PCE notwithstanding, retail sales slumped and have not recovered in any significant way. In fact, private consumption had outperformed retail sales since the onset of the downturn and well into the recovery phase, suggesting some support for private consumption growth from demand for services.

8 The manufacturing sector’s six-month outlook in EDB’s Survey of Business Expectations of the Manufacturing Sector

improved from a net balance of -57% in Q4 2008 to a high of 29% in Q1 2010. Similarly, over the same period, the services sector’s six-month outlook in DOS’ Business Expectations Survey (Services Sector) turned more optimistic from a net balance of -53% to 36%.



Chart 1.25 Expenditure Components across Past Recessions

Exports

Gross Fixed Capital Formation

Expenditure on Machinery and Equipment

Imports

Expenditure on Construction & Works

Retail Sales Volumes and PCE

Peak P+3 P+6 P+980

90

100

110

120

Inde

x (G

DP

Peak

=100

), SA

Asian Financial Crisis (Peak=Q3 1997)

2001 IT Downturn (Peak=Q4 2000)

Recent Recession (Peak=Q1 2008)

Peak P+3 P+6 P+980

90

100

110

Inde

x (G

DP

Peak

=100

), SA


2001 IT Downturn (Peak=Q4 2000) Recent Recession

(Peak=Q1 2008)

Peak P+3 P+6 P+960

80

100

120

Inde

x (G

DP

Peak

=100

), SA




Peak P+3 P+6 P+980

85

90

95

100

105

Inde

x (G

DP

Peak

=100

), SA




Peak P+3 P+6 P+960

80

100

120

140In

dex

(GD

P Pe

ak=1

00),

SA




2008 Q3 2009 Q3 2010 Q280

85

90

95

100

105

110

Inde

x (Q

1 20

08=1

00),

SA

Retail Sales Volume

Private Consumption Expenditure



1.3 Macroeconomic Policy

Singapore’s macroeconomic policies provided countercyclical support during the downturn.

When Singapore slid into recession in 2008, the macroeconomic policy stance was adjusted to provide support to the domestic economy in the face of the significant deterioration in external demand. In October 2008, MAS eased monetary policy by shifting to a zero percent appreciation of the Singapore dollar nominal effective exchange rate (S$NEER) policy band in response to the weak economic environment, continued stresses in the financial markets and easing inflationary pressures. This was followed by a downward re-centering of the policy band to the prevailing level of the S$NEER in April 2009. The responses of monetary policy were deliberately graduated and underpinned by the core objective of maintaining price stability in the medium term, with the exchange rate as an anchor of stability for a small and open economy. In comparison, fiscal policy – as contained in the Resilience Package in the FY2009 Budget – contributed more significantly to the required adjustments in the overall macroeconomic stance during the downturn. The monetary and fiscal policy stance is proxied by the Domestic Liquidity Indicator (DLI)9 and Fiscal Impulse (FI) measure10 respectively. Chart 1.26 plots these measures against the output gap. A positive output gap signals that output is above potential, leading to inflationary pressures as the economy faces bottlenecks in meeting demand. Conversely, a negative output gap indicates that the economy is producing below capacity, resulting in the easing of cost and price pressures. Points above the horizontal axis denote a positive output gap and an expansionary policy stance, and vice versa for points below the axis. Movements in DLI and/or FI in the opposite direction to the output gap indicate that macroeconomic policy is countercyclical. It is evident from the chart that macroeconomic policies in Singapore have been expansionary during periods of adverse economic conditions since 1990, includingthe recent recession.

Chart 1.26 DLI, FI and Output Gap


9 The DLI is a measure of overall monetary conditions, which reflects changes in the S$NEER and three-month domestic

interbank rate. 10 See the January 2002 issue of the Review for more details on the methodology used to calculate the FI measure.

1990 1994 1998 2002 2006-4

-2

0

2

4

6

-4

-2

0

2

4

6

% o

f GD

P

Contractionary

% o

f Pot

entia

l GD

P

2009

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hang

e ov

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ous

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Expansionary

% o

f Pot

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l GD

P

Contractionary

Expansionary

FI Measure (LHS) Output Gap (RHS)DLI (LHS)



The macroeconomic policy stance was tightened in line with the strong

economic recovery. The Singapore economy recovered swiftly towards late 2009 and early 2010. By Q1 2010, it had recouped the GDP that was lost over the recent recession. Output had risen by 17% from the trough in Q1 2009, and was about 7% above the previous peak level. Given this, the Singapore authorities began to withdraw the monetary and fiscal stimulus that had been put in place during the crisis, returning policy settings to levels deemed conducive to sustainable growth and medium-term price stability. On fiscal policy, the government had announced late last year its plans for the gradual phasing out of two key components of the Resilience Package – the Jobs Credit Scheme and the Special Risk-Sharing Initiative (SRI). Relatedly, the focus of the FY2010 Budget shifted from recession relief to restructuring the economy through investments in skills, building capabilities and encouraging innovation. This followed from the recommendations of the Economic Strategies Committee (ESC), and was aimed primarily at shifting the economy towards productivity-driven growth. The Budget therefore contained measures to spur the upgrading of the workforce, such as the expansion of the Continuing Education and Training Scheme, additional transfers for low-wage workers to encourage them to stay on in the workforce, and new incentives for low-wage workers to undergo training. Various schemes to encourage companies to invest in productivity were also announced. These included the Productivity and Innovation Credit Scheme, the National Productivity Fund, tax incentives for qualifying mergers and acquisitions (M&As) and higher levies for unskilled foreign labour. (See the April 2010 issue of the Review for more details on the FY2010 Budget measures.)

In April 2010, MAS pre-emptively tightened monetary policy by re-centering the S$NEER policy band upwards and restoring its modest and gradual appreciation path. This policy shift marked the end of the accommodative monetary policy stance in place since October 2008 and was judged to be appropriate given the strong recovery path of the economy at that time. In October 2010, MAS tightened further by shifting to a slightly steeper appreciation of the S$NEER policy band without altering the level at which the band was centred. At the same time, the policy band was widened slightly. The policy decision was made on the assessment that the level of economic activity would remain high, as the domestic economy would continue to expand, albeit at a slower and more sustainable pace. At the same time, domestic cost pressures have been rising amidst high rates of resource utilisation in the economy. Strong income growth has also placed upward pressure on the prices of some domestic non-tradable consumption items. Given these upside pressures to inflation, MAS deemed it appropriate to tighten monetary policy at this juncture to dampen external inflation – particularly from global food commodity prices – as well as to provide the necessary macroeconomic restraint on domestic economic activity, thereby ensuring that cost and price pressures do not become entrenched.11 The October policy decision also took into account the volatility of international financial markets given the lingering effects of the global financial crisis. In sum, following the withdrawal of the accommodative monetary stance in April, MAS’ latest monetary policy decision continues to be guided by the medium-term orientation of price stability, and is calibrated to support the economy’s transition to a more mature phase of expansion. (Chart 1.27 traces the evolution of monetary policy, as indicated by movements in the S$NEER, against the backdrop of growth and inflation developments.)

11 See Box C in the April 2008 issue of the Review for further discussion on the monetary policy transmission channels in

Singapore.



Chart 1.27 Key Macroeconomic Variables and Changes in the Monetary Policy Stance

-2

0

2

4

6

8

CPI Inflation

YOY

% G

row

th

-6

-4

-2

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Output Gap% o

f Pot

entia

l GD

P

2004 2005 2006 2007 2008 2009 2010

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Real GDP Growth

YOY

% G

row

th

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S$NEER

Inde

x (Q

1 20

04=1

00)

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100

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112

116

120

Re-centre

Modest & Gradual

Appreciation

Increase Slope

Slightly

Increase Slope & Widen Band

Slightly

Neutral Policy

Modest & Gradual Appre-ciation

Re-centre

Maintain



The S$NEER fluctuated in the upper half of the policy band in the past six months.

Since the April 2010 policy review, the S$NEER has fluctuated in the upper half of the exchange rate policy band. (Chart 1.28) Regional currencies have rallied in recent months, following some softness in May due to heightened fears of a sovereign debt default in the peripheral Eurozone countries. This reflected broad-based US$ weakness and the inflow of global liquidity to the region, as investors sought higher yields amidst stronger growth prospects in Asia.

The S$REER appreciated but has remained below its pre-Asian Financial Crisis level.

The S$ real effective exchange rate (S$REER) is a measure of the S$NEER adjusted for price and cost differentials between Singapore and its trading partners. Using the CPI as the price deflator, the S$REER is estimated to have risen slightly by 0.9% in Q1 and 2.7% in Q2. (Chart 1.29) Nonetheless, it is still some 3% below its pre-Asian Financial Crisis level. In the prior decade, the appreciation in the S$REER was the result of a strengthening in the nominal exchange rate, while the domestic CPI grew more slowly than that of our trading partners. In comparison, the appreciation in the S$NEER since 2005 has been slower, although it has continued to account for the bulk of the trend increase in the S$REER. Meanwhile, domestic consumer prices have risen slightly faster than the foreign CPI, unlike in the pre-Asian Financial Crisis period. (See shaded portions in Chart 1.29.)

Liquidity conditions have tightened since May this year.

From April to September, the DLI was positive, suggesting a tightening in overall liquidity conditions alongside the return to a modest and gradual appreciation stance of the S$NEER. (Chart 1.30) Changes in the DLI were predominantly driven by the exchange rate component, while the three-month domestic interbank rate remained at low levels since the beginning of last year. Indeed, the benchmark interest rate stayed at 0.69% between January 2009 and April 2010, before edging down to a historical low of 0.56% since May this year and further southwards to 0.50% at end-September. (Chart 1.31)

Chart 1.28 S$NEER

Chart 1.29 S$NEER, S$REER and Relative CPI

* EPG, MAS estimates

Chart 1.30 Domestic Liquidity Indicator

* EPG, MAS estimates

Apr Apr Apr Apr Apr Apr Apr

96

100

104

108

112

116

Inde

x (9

Apr

200

4=10

0)

Appreciation

Depreciation

2004 200820072005 2006 20102009Oct

Q21985 1991 1997 2003 2010

60

80

100

120

140

160

80

Inde

x (Q

1 19

85=1

00)

REER*

Relative CPI*

NEERAppreciation

Depreciation

Apr Jul Oct Jan Apr Jul

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0.2

0.4

0.6

Cha

nge

from

Pre

viou

s Q

uart

er Tightening

Easing

Sep2010

Exchange Rate Changes

InterestRate Changes

2009

DLI*



In comparison, the three-month US$ SIBOR picked up from 0.25% at the end of January to 0.54% by the end of June, before falling back to 0.29% at end-September. As a result, the domestic interest rate, while continuing to trade at a premium to the US$, saw a narrowing of the differential to near zero in May and June. However, as market expectations shifted back to that of a prolonged low interest rate environment in the US, the differential widened back to 0.21% by the end of September. Due to the record low domestic interbank rate, deposit rates have been depressed at low levels, and have been largely unchanged since the beginning of the year. (Chart 1.32) Mortgage rates pegged to the S$ SIBOR have fallen, although some banks had raised the spread over the base rate. Nonetheless, increasing competition in mortgage lending will continue to put pressure on consumer home loan rates.

Credit growth picked up in line with the economic expansion.

In line with the low interest rate environment and the expansion of the Singapore economy, domestic credit growth has become firmer in 2010. In particular, business loans began to expand y-o-y from April, with average growth rising to about 4% in the three months to August. Supported by a revival in housing loans, consumer loan growth also accelerated in the first eight months of the year. (Chart 1.33) Accordingly, the loan-to-deposit ratio edged up to 0.73 in August from 0.71 in Q1 2010, following a sharp decline from its peak of 0.80 in Q3 2008. M1 growth remained firm while M2 and M3 growth

eased in the low interest rate environment. Through the process of bank intermediation, the money supply adjusts to facilitate transactions in the economy. A higher level of economic activity requires a corresponding increase in money supply, either through an increase in the monetary base, or through the money multiplier.

Chart 1.31 3-month Domestic Interbank Rate

and US$ SIBOR

Chart 1.32 Deposit Rates

Note: This is the simple average of the top 10 banks’ deposit rates.

Chart 1.33 Domestic Credit to the Private Sector

2005 2006 2007 2008 2009 2010 End of Month

-1

0

1

2

3

4

5

6

% P

er A

nnum

Sep

3-monthUS$ SIBOR

3-month Domestic Interbank

Interest Rate Differential

2000 2002 2004 2006 2008 2010SepEnd of Period

0.0

0.5

1.0

1.5

2.0

2.5

% P

er A

nnum

SavingsDeposit Rate

12-month Fixed Deposit

Rate

2006 Jul 2007 Jul 2008 Jul 2009 Jul 2010

-10

0

10

20

30

40

YOY

% G

row

th

Aug

Domestic Credit toPrivate Sector

ConsumerLoans

BusinessLoans



In Singapore, nominal GDP and the monetary base have tracked each other fairly closely except during the recent recession, when an increase in banks’ demand for reserve balances resulted in a surge in the monetary base. (Chart 1.34) Growth in the monetary base subsequently slowed as risk aversion eased, before picking up once more as the economy moved into the expansion phase. The latest data for July and August show the growth in the monetary base surging again as the level of economic activity remained high in Q3. Recent movements in money aggregates have been consistent with the pattern of recovery in economic activity and the fluctuations in the money multiplier. Short-run fluctuations in the M2 multiplier have tended to track cyclical changes in nominal GDP quite closely, with the multiplier falling as the economy goes into recession, and rising during the ensuing recovery. (Chart 1.35) As of August 2010, the multiplier has risen more slowly as compared to the first half of the year, mirroring the downshift in economic activity in Q3. Growth in the broader monetary aggregates, M2 and M3, has thus eased below rates last seen during the trough in Q2 2008. (Chart 1.36) In comparison, the M1 multiplier continued to increase in Q3 and growth in narrow money only moderated slightly in July and August. Both components of M1, namely demand deposits and currency in active circulation, have increased over the first eight months of the year. (Chart 1.37) In the initial phase of the crisis, demand deposits might have been held to preserve liquidity. However, they have since continued to rise, given the strong economic recovery. Currency in active circulation has also increased in tandem. This suggests that the growth in firm and household incomes has translated into strong demand for M1 for transactional purposes.

Chart 1.34 Monetary Base and Nominal GDP

* August data for monetary base; EPG, MAS estimates for nominal GDP.

Chart 1.35 Money Multipliers and Nominal GDP

* August data for money multiplier; EPG, MAS estimates for nominal GDP.

Chart 1.36 Monetary Aggregates

2004 2006 2008 2010

75

100

125

150

175

200

Inde

x (Q

1 20

04=1

00)

Nominal GDP

Q3*

Monetary Base

0

2

4

6

8

10

12

Mon

etar

y B

ase

Mon

ey a

s a

ratio

of

2004 2006 2008 2010 Q3*

-10

-5

0

5

10

15

20

YO

Y %

Gro

wth

Nominal GDP M1 Money Multiplier

M1 Money Multiplier

M2 Money Multiplier

M2 Money Multiplier

2006 2007 2008 2009 2010

5

10

15

20

25

YOY

% G

row

th

Jul-Aug

M1

M2

M3



MAS’ sterilisation has effectively absorbed the liquidity impact of its intervention operations.

Singapore has seen strong capital inflows since H2 2009, amidst broad-based weakness of the US$ and the relatively positive outlook for the Singapore economy. In such instances, MAS may intervene in the foreign exchange markets to dampen upward pressures on the S$. Such intervention operations lead to an increase in foreign assets on MAS’ balance sheet (via the purchase of US$ from banks) (Chart 1.38) and a corresponding rise in banks’ current accounts with MAS on the liability side (through the credit of S$ to banks). These larger current account balances, in turn, expand the monetary base. To offset the liquidity impact of its intervention operations, MAS engages in sterilisation via SGS reverse repos, FX reverse swaps, and direct borrowing. Box A provides a review of MAS’ Money Market Operations (MMOs) in FY2009/10. As a result of these measures, banks’ current accounts with the MAS are relatively unaffected by MAS’ intervention operations. Sterilisation operations thus help to smooth out large fluctuations in the growth of the monetary base and in broad money creation. (Chart 1.39)

Chart 1.37 Components of M1

Chart 1.38 MAS’ Balance Sheet, Assets

Chart 1.39

MAS’ Balance Sheet, Liabilities

2009 Jul 2010 Aug

90

100

110

120

130

140

Inde

x (J

an 2

009=

100)

, SA

Currency in Active Circulation

Demand Deposits

2009 Jul 2010 Aug

-16

-8

0

8

16

Cha

nges

($ B

illio

n)

Net Foreign AssetsDomestic Credit to Government

2009 Jul 2010 Aug

-16

-8

0

8

16

Cha

nges

($ B

illio

n)

Monetary BaseGovernment Deposits

Other Items (Net)



Fiscal Policy

Government operating revenue increased with the upturn in economic activity.

Government operating revenue increased from $18.8 billion in H1 2009 to $22.3 billion in the first half of this year. As a proportion of GDP, it rose from 15.0% to 15.3%. Stamp duty, income tax, GST, as well as fees & charges each contributed about 20% to the increase in the government’s coffers. (Chart 1.40) The government received $9.4 billion from income tax in H1 2010, $0.7 billion more than in the same period last year. A larger amount of revenue was collected from corporate income tax and statutory boards, notwithstanding the reduction in the corporate income tax rate from 18% to 17% with effect from Year of Assessment 2010. GST, which is the second largest component of operating revenue after income tax, also increased by $0.6 billion on a year-ago basis to $3.7 billion in H1 2010. Of all the revenue components, the strongest surge was recorded for stamp duty, which more than doubled to $1.4 billion in the first half of 2010 compared to that in the preceding year. This mirrored the swift and strong recovery of the residential property market from its trough in Q2 last year. (Chart 1.41) Nevertheless, revenue raised from stamp duty was still below its $2.1 billion peak in H1 2007.12 In terms of non-tax revenue, i.e. fees & charges, the bulk of the increase was due to receipts from Certificates of Entitlement (COEs). As a result of the reduction in quotas this year, COE premiums for cars surged about fourfold in H1 on a y-o-y basis. (Chart 1.42) Even though new car registrations tumbled by about 38% over the same period, the higher premiums led to a greater amount of COE collections.

Chart 1.40 Components of Operating Revenue

Chart 1.41 Private Residential Property Transactions

and Stamp Duty Collections

Chart 1.42 COE Premiums and New Car Registrations

12 Stamp duty collections in H1 2007 were also boosted by the withdrawal of the stamp duty deferment concession with

effect from December 2006.

Income Taxes

GST

Fees & Charges

Assets Taxes

Stamp Duties

Betting Taxes

Motor Vehicle Taxes

0 2 4 6 8 1$ Billion

0

2009 H1 2010 H1

Customs & Excise Duties

1996 1999 2002 2005 2008-100

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200

300

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% G

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2010H1

Revenue from Stamp Duty

Private Residential Property Transactions

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$ Th

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Average COE Premiums for

Cars (RHS)

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New Car Registrations

(LHS)



Operating and development expenditure also rose, but by a lesser extent than revenue.

Government spending rose by $1.5 billion to $22.4 billion (15.4% of GDP) in H1 2010, largely driven by the increase in operating expenditure, including that on manpower, equipment and supplies. Operating expenses were $1.1 billion higher at $16.8 billion (11.5% of GDP), with increases recorded across all Ministries. In particular, the Ministry of National Development recorded the largest expansion in operating expenditure mainly due to the Public Housing Development Programme. (Chart 1.43) The Ministry of Community Development, Youth and Sports also saw a considerable rise in operating spending, part of which could be attributed to the hosting of the Youth Olympic Games. Meanwhile, the government spent $5.6 billion (3.9% of GDP) on development items in H1 2010, $0.3 billion more than in the first half of last year. The bulk of the increase was incurred by the Ministry of Trade and Industry, mainly to support ESC-related projects such as R&D and industry development activities. (Chart 1.44) This was partially offset by the decline in expenses on transport infrastructure over the same period. The basic balance remained in deficit this year, with

the overall fiscal stance close to neutral. Overall, the government recorded a slight primary deficit13 of $55 million in H1 2010, compared to $2.2 billion recorded in the same period a year ago. Including special transfers but excluding top-ups to endowment and trust funds, the basic deficit amounted to $2.4 billion, down from $4.6 billion in H1 2009. (Chart 1.45) These special transfers largely comprise payouts under the Jobs Credit Scheme.

Chart 1.43 Selected Components of Operating Expenditure

Chart 1.44 Selected Components of

Development Expenditure

Chart 1.45 Basic Surplus/Deficit

13 The primary surplus/deficit is defined as operating revenue (excluding net investment income/returns contribution) less

the sum of operating and development expenditure.

Education

Health

0 2 4 6 8$ Billion

2009 H1 2010 H1

Security &External Relations

CommunityDevelopment

National Development

Transport

Trade & Industry

Education

Health

0.0 0.5 1.0 1.5 2.0 2.5$ Billion

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The Fiscal Impulse (FI) measure provides a useful indication of the initial stimulus to aggregate demand arising from fiscal policy, and takes into account not just the primary balance but also targeted special transfers that impact the cash flow of households and businesses. The FI is estimated to be -0.6% of GDP for CY2010 implying a close to neutral fiscal policy stance. (Chart 1.46) This is consistent with the fact that many of the fiscal measures included in Budget FY2010 are essentially supply-side in nature and have longer-term objectives in positioning Singapore for productivity-driven growth over the medium term.

Chart 1.46 Fiscal Impulse Measure


1990 1995 2000 2005 2010F-4

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Box A Review of MAS Money Market Operations in FY2009/101/

This box reviews the conduct of MAS’ Money Market Operations (MMOs) in FY2009/10. As explained in the monograph on “Monetary Policy Operations in Singapore” published in April 2007, MAS’ MMOs are undertaken to manage liquidity within the banking system and are distinct from the implementation of exchange rate policy. A brief description of how MMOs are conducted is first provided, followed by a review of the banks’ demand for cash balances with MAS, and the behaviour of autonomous money market factors in FY2009/10. An examination of the MMOs conducted during this period completes this box. MMOs in Singapore As a result of Singapore’s open capital account and its exchange rate-centred monetary policy, domestic interest rates and the money supply are endogenous. Accordingly, MAS’ MMOs are not targeted at any level of interest rate or money supply. Instead, they are aimed at ensuring that there is sufficient liquidity in the banking system to meet banks’ demand for reserve and settlement balances. MMOs are conducted daily by the Monetary Management Division in MAS. The amount of liquidity in the banking system is estimated by taking into consideration the banking sector’s demand for funds and the net liquidity impact of autonomous money market factors. Money market transactions are then carried out, after which market and liquidity conditions are monitored throughout the day. Banks’ Demand for Cash Balances Banks hold cash balances with MAS to meet reserve requirements and for settlement purposes. In particular, banks in Singapore are required to maintain a Minimum Cash Balance (MCB) equivalent to 3% of their liabilities base with MAS on a two-week average basis. Banks may also use their cash balances to fulfil other regulatory (e.g. liquid asset) requirements, hence banks’ demand for cash balances may also vary between periods. In FY2009/10, banks’ demand for balances to meet reserve requirements expanded due to the resumption of growth in banks’ liabilities base. (Chart A1) The increase in the banks’ liabilities base reflected the recovery of bank intermediation activity as a result of strong economic growth in the post-crisis period.

Chart A1 Average Reserve Requirements over a Two-week Maintenance Period

1/ This box is contributed by the Monetary & Domestic Markets Management Department at MAS.

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Demand for Settlement Balances MAS also takes into account banks’ demand for settlement balances when planning its MMOs, apart from meeting banks’ demand for reserve balances. Based on historical experience, an average liquidity buffer of about 0.1% to 0.3% in excess of reserve requirements over the two-week maintenance period has generally been adequate for meeting banks’ demand for business-as-usual settlement balances. Patterns in Banks’ Daily Demand for Cash Balances with MAS Although banks are required to keep an average MCB ratio of 3% over the two-week maintenance period, their daily effective MCB ratios can fluctuate between 2% and 4% of their liability base, giving them more flexibility in their liquidity management. Hence, there may be day-to-day variations in banks’ demand for cash balances with MAS within each maintenance period. Chart A2 illustrates the daily fluctuations in cash balances within an average maintenance period in FY2009/10. As observed since our last review in 2009, higher cash balances are usually kept during the start of the maintenance period as banks want to avoid being caught short of cash towards the end of the period. As a result, the daily cash balances required by the banking system during the last few days of a typical maintenance period are generally lower.

Chart A2 Daily MCB Ratio over a Typical Two-week Maintenance Period in FY2009/10

Money Market Factors

Liquidity Impact of Autonomous Money Market Factors Chart A3 shows the liquidity impact of each of the autonomous money market factors, which include (i) public sector operations, (ii) currency in circulation, and (iii) Singapore Government Securities (SGS) issuance, redemption and coupon payments, over FY2009/10. Public sector operations include the Government’s and CPF Board’s net transfers of funds between their accounts with MAS and their deposits with commercial banks. In FY2009/10, the liquidity impact of the autonomous money market factors had been net contractionary, largely due to public sector operations and SGS issuance. Public sector operations had consistently been contractionary throughout the year. The impact of SGS issuance was most significant in Q2 and Q3 of 2009, while the impact of currency in circulation was negligible.

1 2 3 4 5 6 7 8 9 10 11 12 13 14Day

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Chart A3 Liquidity Impact of Autonomous Money Market Factors

Over FY2009/10, MAS' MMOs took into consideration the impact of autonomous money market factors and MAS’ foreign exchange (FX) intervention operations on liquidity. During FY2009/10, banks have generally taken a more conservative stance, holding an effective average minimum cash balance of about 3.2% of liability base during the two-week maintenance period. (Chart A4)

Chart A4 Effective Average Two-week MCB Ratios

Instruments for MMOs For its MMOs, MAS uses three key instruments to inject and withdraw liquidity into the banking system, namely, (i) FX swaps or reverse swaps; (ii) SGS repos or reverse repos; and (iii) clean lending or borrowing. Chart A5 illustrates the distribution of MMOs amongst the instruments as at the end of FY2009/10.

2009 Q2 Q3 Q4 2010 Q1

0

Contractionary (-) : Withdrawal of liquidity from banking system

Expansionary (+) : Injection of liquidity into banking system

Public Sector OperationsCurrency in CirculationSingapore Government Securities

Mar Jul Sep Nov Jan Mar

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Chart A5

Distribution of MMOs by Instrument

FY 2009/10

FX Reverse Swap

Borrowing

60%

FX Reverse Swap

FY 2008/09

Borrowing

59%

SGSReverse

Repo

2%

41%

38%


Chapter 2 Wage-Price Dynamics



2.1 Labour Market Conditions Higher Manpower Demand in Services

Employment growth continued in H1 2010, driven by hiring in the services sector.

Following the turnaround in employment in Q3 2009, firms continued to add headcount for the rest of the year and into H1 2010. (Chart 2.1) The relatively stronger gains of 61,400 in H1 2010, compared to H2 2009, were driven primarily by the services sectors – these accounted for 96 out of every 100 jobs created, much higher than the average ratio of 63 per 100 jobs over the period 2005-07. Notably, hiring in financial services almost equalled that before the crisis, fuelled by Asia’s strong demand for wealth advisory and regional intermediation services. The opening of the two IRs also boosted employment in community, social & personal services (CSP) and business services, by filling positions for hospitality staff, accountants, legal advisors, etc. (Chart 2.2) In contrast, construction employment expanded by just 1,600 in H1 2010, compared to 12,000 in H2 2009. The slowdown was largely due to the completion of the IRs, although public infrastructure projects, such as the MRT Downtown Line and Marina Coastal Highway, provided some support to employment in Q2 2010. Likewise, job creation was weak in the manufacturing sector. About 3,000 jobs were added in Q1 2010, but firms were quick to cut employment in Q2 following the onset of the Eurozone sovereign debt crisis and more uncertain prospects for the G3 economies. In particular, job losses persisted in the transport equipment cluster in H1 on account of weak order books, while several other manufacturing industries also reduced employment in Q2 2010. Reflecting greater caution on the part of employers, EPG’s employment diffusion index declined to 75.9 in Q2 2010, from 87.0 in Q1. (Chart 2.3)

Chart 2.1 Total Employment Changes

Chart 2.2 Employment Changes by Sector in H1 2010

Note: Business Services comprise Real Estate & Leasing Services, Professional Services and Administrative & Support Services.

Chart 2.3 Employment Diffusion Index

Source: EPG, MAS estimates Note: The index is equal to 100 when all industries are increasing employment and zero when all are decreasing employment. A reading of 50 indicates an equal number of industries that are increasing and decreasing employment.

H1 H2 H1 H2 H1

-40

0

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80

120

160

Thou

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2008 2009 2010

Total Emp61,400

Biz Svc20,000

CSP17,700

Fin Svc8,700

Info & Com4,300

Wsale & Retail3,600

T&S2,800

Hotels & Rest1,700

Constr1,600

Svc58,800

Mfg800

ElecNon-elec-2,100 2,900

Others200

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Wage-Price Dynamics 33


Employment growth could have been influenced by industry-specific factors.

The uneven pace of employment growth across the key sectors in the recent economic downturn and subsequent recovery suggests that industry-specific factors played a significant part in labour market dynamics. Recent econometric work by EPG decomposed employment growth into common cyclical and (industry) idiosyncratic components. It suggests that idiosyncratic factors had been important in explaining employment changes in industries such as non-electronics manufacturing and construction. Box B takes up this issue further and discusses the roles of overall output fluctuations and underlying sector-specific factors in Singapore’s employment performance.

The labour market has remained tight ... With the resident labour force participation rate remaining at a near-historical high of 65.4% even during the recession in 2009, the cumulative rise in employment over the past four quarters led to a further tightening of the labour market. This was reflected in the resident unemployment rate edging down from 3.3% in Q4 2009 to 3.2% in Q1 2010 and remaining unchanged in Q2. As a result of tighter labour market conditions, many firms faced constraints in hiring, especially in the services industries, which experienced near-record high job vacancy rates. (Chart 2.4)

... resulting in strong wage increases. With the domestic economy operating at close to full employment, wages picked up sharply in H1 2010. Overall seasonally adjusted nominal wages rose by a total of 6.1% over the two quarters, pushing the average wage level above its pre-crisis peak. (Chart 2.5) In particular, while the manufacturing and construction sectors held off pay increases in Q2 2010, most of the services industries continued to raise wages as competition for workers intensified. (Chart 2.6)

Chart 2.4 Job Vacancy Rates in the Services Sectors

Chart 2.5 Nominal Wage Index


Chart 2.6 Nominal Wage Growth by Industry


2000 2002 2004 2006 2008 2010 H10

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Community, Social & Personal Services

Financial Services

Hotels & Restaurants

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Manufacturing

Construction

Business Services

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2010 Q1 2010 Q2

Community, Social & Personal Services



2.2 Consumer Price Developments Sources of Price Increases Broadened

Headline CPI inflation increased over the first three quarters of 2010 ...

Following the sharp turnaround in the domestic economy and the attendant rise in resource utilisation, cost and price pressures have emerged. Headline CPI inflation, measured on a year-ago basis, rose significantly from 0.9% in Q1 2010 to 3.1% in Q2 and 3.4% in Q3. The MAS underlying inflation measure, which excludes the costs of accommodation and private road transport, also increased from 0.1% in Q1 to 2.2% in Q3. (Chart 2.7) In the first three quarters of 2010, CPI inflation and the MAS underlying inflation measure averaged 2.4% and 1.3% respectively.

… alongside strong sequential price gains … The recent higher y-o-y inflation rates reflected in part the low base last year when the CPI recorded its sharpest decline in over 20 years. Notwithstanding this, the sequential increase in the CPI in the last two quarters was substantial at 1.2%, compared to a 10-year historical average of 0.4%. These increases brought the CPI to 2.2% above its pre-crisis peak in Q4 2008. In comparison, in previous recessions, it took a further three quarters just for the CPI to recover to its pre-crisis peaks. (Chart 2.8)

… across a broad range of consumer items. The sequential increase in the CPI was initially led by the jump in private road transport cost in Q2. After private road transport cost had broadly stabilised in recent months, the combined rise in the costs of a wide range of items drove up the CPI. Indeed, as much as 83% of the CPI basket saw price increases in Q3, a percentage reached only once before in the last decade in 2007. (Chart 2.9) In particular, the costs of domestic non-tradable items, including accommodation and services, rose strongly in Q3. (Chart 2.10)

Chart 2.7 CPI Inflation and MAS Underlying

Inflation Measure

Chart 2.8

Profile of CPI in Post-recession Periods

Chart 2.9

Percentage of CPI Items with Sequential Price Increases

2007 2008 2009 2010 Sep-2

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% G

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CPI Inflation

0 2 4 6 8 10 12Number of Quarters after Peak in CPI

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PI =

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COE premiums surged in Mar-Apr 2010 and remained high thereafter.

The cost of private road transport, excluding petrol, increased by 9.0% q-o-q in Q2, after staying largely unchanged in Q1. This was due to the jump in car prices as COE premiums surged following the announcement of a larger-than-expected cut in the COE quota in March.1 The 33% reduction in the quota for Apr-Jul 2010 caused COE premiums to rise by a further 30% in April to $39,000, after a similar rise in March. While premiums subsequently corrected in line with the slump in new car demand, they remained about 50% above the level prevailing before the quota cut. (Chart 2.11)

Chart 2.10 Contributions to q-o-q Increase in CPI


Chart 2.11 Car COE Premiums and Cost of

Private Road Transport Excluding Petrol

Accommodation cost rose on the back of a turnaround in market rentals …

Accommodation cost in the CPI fell in Q2-Q4 2009, following the decline in residential property rentals.2 Rental demand was hit by the financial crisis as the number of foreigners working in Singapore, who are the main group of potential lessees, fell in 2009 and their housing budgets were cut. The government’s disbursement of additional rebates for Service & Conservancy Charges and rentals of HDB flats to help residents cope with the economic downturn also brought down accommodation cost. As rentals turned around at the end of last year, CPI accommodation cost began to recover after a short lag. In Q3 this year, it rose by a significant 2.3%, accounting for more than a third of the sequential increase in the CPI. (Chart 2.10)

1 This was due to a change in the formula for determining the COE quota to take into account the actual number of

deregistered vehicles in the preceding six months, instead of the projected number over the next 12 months. 2 Residential property rentals are used in the computation of the cost of rented accommodation and the imputed cost of

owner-occupied housing in the CPI.

Q1 Q2 Q32010

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0.8

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1.6

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... while prices of consumer services climbed as the domestic economy recovered.

The prices of consumer services also picked up in line with the strong performance of the domestic economy and improved consumer sentiment. The cost of recreation, which is the third largest category in the CPI after housing and food, continued to edge higher after the holiday season in Q4 last year, due to firm domestic demand as well as a recovery in global airfares and hotel room rates. In particular, Singapore Airline’s (SIA) passenger load factor returned to its pre-crisis level in Q3 2009, prompting the airline to raise fares three times since April this year. (Chart 2.12) Indeed, the International Air Transport Association (IATA) estimated that economy fares were on average 15% higher in September this year, compared to the low in 2009. Education and healthcare institutions also raised prices this year due to cost pressures, after holding back price increases during the downturn. Child care centres, commercial education institutions and public tertiary establishments raised their fees in January, July and August, following the commencement of their new academic years. Healthcare services, ranging from dental and outpatient to specialist treatment, also saw price increases. Even during the downturn, the costs of services had held up, in contrast to the price declines witnessed in the other items in the CPI. Indeed, in the last three recessions, average services costs continued to rise when the economy contracted while the overall CPI actually fell for a number of consecutive quarters. (Chart 2.13)

Chart 2.12 SIA Passenger Load Factor

Source: SIA

Chart 2.13 Average q-o-q Changes in the CPI and Services Costs around the Peak in GDP

Note: The three recessions include the Asian Financial Crisis, 2001 IT Downturn and the recent recession.

2007 2008 2009 2010 Sep60

65

70

75

80

85

90

Per C

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-6 -4 -2 0 2 4 6Number of Quarters around Peak in GDP

-1.0

-0.5

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r Cen

t

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Services Costs




External sources of inflation have been relatively benign.

Meanwhile, external sources of inflation have been relatively benign this year, given the uncertainties in the global economy. Global oil prices, which had moved upwards to about US$85 in April 2010, corrected following the onset of the Eurozone sovereign debt crisis and further signs of continued sluggish growth in the G3 economies. In the last six months, oil prices have been largely stable, mostly within the range of US$75-85. (Chart 2.14) As a result, electricity tariffs were raised only slightly in April and July before being cut in October for the first time in a year. Over the same period, petrol pump prices generally inched downwards. Nevertheless, compared to a year ago, the prices of oil-related items in Q3 were some 12% higher because of the sharp correction in prices of these items in H1 2009.

Chart 2.14 WTI Oil Prices

Source: Bloomberg

2007 2008 2009 2010 Sep30

60

90

120

150

US$

per

bar

rel



Box B Why so Different? Singapore’s Recent Labour Market Dynamics1/

Singapore’s labour market has demonstrated remarkable resilience since the start of the Great Recession. The unemployment rate registered one of the lowest increases among advanced economies (Chart B1) during the recession phase and employment growth has outstripped rates seen elsewhere in the region, not to mention in OECD countries. (Chart B2) Employment dynamics have also been very different from those seen in previous downturns, including the Asian Financial Crisis and 2001 IT Downturn. (Chart B3) To try and explain why, this box applies the approach in the IMF Spring 2010 World Economic Outlook (WEO) to Singapore and also explores the importance of wage flexibility, sectoral shocks and the Jobs Credit Scheme introduced in the 2009 Budget.

Chart B1

Changes in the Unemployment Rate during the Great Recession

Source: IMF staff calculations

Chart B2 Employment Growth since the start of the

Great Recession by Country

Chart B3 Employment Growth during

Recent Recessions in Singapore

Source: CEIC, Haver Analytics, IMF staff calculations and Source: EPG, MAS estimates EPG, MAS estimates

1/ This box was contributed by Ravi Balakrishnan, the IMF Resident Representative based in Singapore. The views

expressed in this box are those of the author and should not be interpreted as those of the IMF or MAS.

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Asian Financial Crisis

2001 IT Downturn

Great Recession


A low impact of output growth on unemployment The first step in explaining Singapore’s labour market dynamics during the Great Recession and subsequent recovery is to look at the impact of output fluctuations. This is captured in the well-known relationship, Okun’s Law, which has the following simple form: (1)

where α is an intercept term and β (beta) is the elasticity of the unemployment rate with respect to output, which was estimated by Okun (1962) to be around 0.3 for the United States during the early post-World War II period. The value of is the minimum level of output growth needed to reduce the

unemployment rate given labour force and labour productivity growth. However, equation (1) is a simplification in that it takes no account of adjustment lags. To allow for these, we follow the procedure of Chapter 3 of the Spring 2010 WEO and estimate a general dynamic version of Okun’s law.2/ Having lagged effects allows the long-term impact of output growth on the unemployment rate to be significantly larger than the short-run impact since, for example, employers may delay firing workers until it becomes clear that a demand shock is long-lasting rather than temporary. Chart B4 compares the long-term impact, or unemployment beta, for Singapore to that of other advanced economies in the run-up to the Great Recession.3/ As can be seen, Singapore has one of the lowest betas – nearly eight times lower than that of Spain.

Chart B4 Dynamic Unemployment Betas during the

20 years preceding the Great Recession


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1.0

ß

But a high impact of output growth on employment The WEO chapter suggests that stricter employment protection legislation (EPL) and higher unemployment benefits lead to lower betas. While the OECD does not produce a measure of EPL for Singapore, “doing business” indicators produced by the World Bank suggest that the cost of hiring and firing workers is extremely low in Singapore – indeed, according to the Bank’s Rigidity of Employment Index, Singapore ranks first of the 183 countries in terms of the environment for employing workers. Moreover, Singapore does not provide unemployment benefits. Thus, something else must be driving the low beta. 2/ This procedure uses an optimal lag length criterion to determine the dynamic specification. 3/ For most countries, a window spanning 20 years up to a GDP peak is used. The window is sometimes shorter given

data availability. This is the case for Singapore given that the most recent GDP peak was in the first quarter of 2008 and quarterly labour market data are only available from the first quarter of 1992.



Could wage flexibility help explain the low unemployment beta? The evidence from this cycle suggests that Singapore has a high degree of downward wage flexibility and that this may have reduced job losses in the face of the steep output decline during the recession. (Chart B5) If this has been true more generally over the last two decades, it could be a key reason why the unemployment beta is so low. Japan, which like Singapore has a large share of bonuses and paid overtime in contracted pay and is considered to have a high degree of wage flexibility, also has a low beta. However, to test this hypothesis would require micro data, which is beyond the scope of this box.

Chart B5 Real Wage Growth since the Start of the Recession by Country

Source: CEIC, Haver Analytics and IMF staff calculations

Thailand

Philippines

Hong Kong

Taiwan

Japan

Singapore

-6 -4 -2 0 2 4 6% Change from GDP Peak, SA

Following an output drop, another parameter which can be adjusted (instead of firing workers) is the amount of hours worked per employee. Chart B6 shows that hours per employee in Singapore generally adjust more in the manufacturing sector than in other sectors during recessions, and that the adjustment in manufacturing hours has been bigger this time around (this also holds true for overtime hours). However, it is difficult to assess whether this has contributed to Singapore’s low beta since comparable data across countries for hours worked is not readily available.

Chart B6 Paid Hours Worked in Singapore,

Great Recession and Average of Previous Two Slowdowns

0 1 2 3 4 5 6 7 8 9Number of Quarters from GDP Peak

-6

-4

-2

0

2

from

GD

P Pe

akC

umul

ativ

e %

Cha

nge

Manufacturing AverageConstruction AverageServices Average

ManufacturingConstructionServices




What about the structure of the labour market? As unemployment rate fluctuations capture both employment and labour force dynamics, foreign worker flows may be lowering the impact of output fluctuations on unemployment. For example, during recessions, job losses among foreign workers may not show up as unemployment given that they quickly drop out of the labour force once their visa expires (usually within 30 days after they have lost their jobs) and have to return home. Indeed, substantial foreign worker flows would be consistent with a low unemployment beta and a high employment beta. To test this, equation (1) is estimated using the log change in total employment as the dependent variable. As Chart B7 shows, Singapore has the highest employment beta, which contrasts starkly with its low unemployment beta. A high employment beta is also consistent with Singapore having low hiring and firing costs.

Chart B7 Dynamic Employment Betas during the 20 years preceding the Great Recession


What explains the exceptional employment growth during this cycle? Charts B2 and B3 show that employment growth has been much stronger in Singapore during this cycle both when comparing across cycles and across the region. And, as Chart B8 shows, output dynamics have been similar across the region during this cycle, with many countries experiencing V-shaped recoveries. A higher employment response to output fluctuations in Singapore – consistent with the evidence in Chart B7 – could help explain relatively stronger employment growth during the recovery but not during the recession. Thus, we need to look for other explanations to get a more complete picture.

Chart B8

GDP Growth since the Start of the Great Recession by Country

Source: CEIC and IMF staff calculations

Den

mar

k

Irela

nd

New

Zea

land

Italy

Japa

n

Aus

tria

Port

ugal

Fran

ce

Uni

ted

Stat

es

Nor

way

Bel

gium

Can

ada

Ger

man

y

Net

herla

nds

Uni

ted

Kin

gdom

Finl

and

Spai

n

Swed

en

Sing

apor

e

0.0

0.5

1.0

1.5

2.0

ß


-10

-5

0

5

10

15

from

GD

P Pe

ak, S

AC

umul

ativ

e %

Cha

nge

Philippines

Hong Kong

Japan

Malaysia

Singapore


The composition of employment growth in Singapore has been very different during this cycle relative to previous ones. Construction employment growth has been extremely strong following the latest recession compared to previous downturns when it was significantly negative. (Chart B9) Services employment growth has also been stronger than what we have seen during the last two cycles. Construction employment not declining following such a deep recession sits oddly with both the fact that it is typically much more sensitive to economic activity than other sectors and that construction wages have risen at a brisk pace.4/ (Chart B10) This apparent paradox is resolved when we look at sector level output dynamics, which confirm that construction activity not only led the recovery but grew during the recent recession, in stark contrast to previous ones. (Chart B11) This suggests structural and other one-off factors may be at work, such as a firm residential property market and the continuing work on other major projects, for example, the IRs.

Chart B9 Employment Growth in Singapore by Sector,



-20

-10

0

10

20

30

from

GD

P Pe

akC

umul

ativ

e %

Cha

nge



Chart B10

Real Wage Growth in Singapore by Sector, Great Recession and 2001 IT Downturn



-10

-5

0

5

10

from

GD

P Pe

ak, S

AC

umul

ativ

e %

Cha

nge

Manufacturing (2001)Construction (2001)Services (2001)


4/ The higher sensitivity of construction employment to changes in real output is confirmed for Singapore when looking

at estimates of Okun’s law using log changes in sector employment as the dependent variable.



Chart B11 VA Growth in Singapore by Sector,



-40

-20

0

20

40

60

from

GD

P Pe

ak, S

AC

umul

ativ

e %

Cha

nge



The downward wage flexibility illustrated in Chart B5 has also likely played its part, by being used as a margin for adjustment rather than employment losses in the downturn phase and encouraging more hiring when the recovery kicked in. Such downward flexibility appears to have increased over time, as wage cuts were higher during the Great Recession than during the Asian Financial Crisis or the 2001 IT Downturn. (Chart B12)

Chart B12

Real Wage Growth in Singapore during Recent Recessions

Source: CEIC, Haver Analytics and IMF staff calculations

-10

-5

0

5

10

GD

P Pe

ak to

Tro

ugh,

SA

% C

hang

e fr

om

Asian Financial Crisis

2001 IT Downturn

Great Recession

Last but not least, the Jobs Credit Scheme likely helped support employment growth in 2009.5/ The scheme offered a job subsidy for existing employees aimed largely at maintaining employment rather than creating new jobs and was equivalent to a 9% point cut in the employer CPF contribution rate. In covering the first $2,500 of monthly wages (the median wage), it may have helped maintain low pay jobs for local workers. However, its role in recent employment growth is difficult to assess. While the empirical literature suggests that job subsidies tend to be more effective in highly uncertain environments, such as in the immediate aftermath of the Great Recession, it also points to large deadweight losses as employers receive the subsidy for workers they would otherwise have kept. Moreover, a cut in the employer CPF rate of 10% points was implemented after the Asian Financial Crisis but subsequent employment growth was much weaker than this time around.

5/ This was a credit equivalent to 12% of the first S$2,500 of the monthly wages of each employee who was on the

Central Provident Fund payroll and was paid quarterly to employers.



Conclusion Singapore’s employment performance following the Great Recession has been exceptional. While the relatively strong employment growth during the recovery can partly be explained by the strength of the output turnaround and a high response of employment to output fluctuations, this cannot account for why employment did not decline during the recession phase. Other factors must have been at work, including a construction boom, wage flexibility and the impact of the Jobs Credit Scheme. Looking ahead, while overall output dynamics will clearly be important for employment prospects, underlying sector-specific factors, such as the performance of the labour-intensive construction sector and the extent to which Singapore continues to expand its services sector, will also be key drivers.

References IMF (2010), “Unemployment Dynamics during Recessions and Recoveries: Okun’s Law and Beyond”, World Economic Outlook, April. Okun, A M (1962), "Potential GNP: Its Measurement and Significance", Proceedings of the Business and Economics Section of the American Statistical Association, American Statistical Association, pp. 98-104.


Chapter 3 Outlook



3.1 External Outlook

Transiting to the New Normal

Subdued growth is expected in

the developed world.

Following a buoyant first half, growth in the world

economy is expected to slow in H2 2010 and early next

year, although an outright recession is unlikely.

Production and trade data in recent months are already

signalling a moderation in global economic activity.

Going forward, leading indicators also point to a

continuing downshift in both manufacturing and

services output. (Chart 3.1)

The impending growth slowdown should be viewed in

the broader context of recoveries from severe financial

crises. Historically, crisis-affected economies reverted

to their previous states only after a sluggish and

protracted recovery process.1 It is therefore to be

expected that the current revival in the US and the

Eurozone will be much slower and weaker, compared

to the rebound from recent recessions that were not

triggered by a financial crisis. (Charts 3.2 and 3.3) As a

result, muted economic growth is likely to be the norm

in the developed world for some time to come as

households, businesses and financial institutions

deleverage, while private sector balance sheets are

restored to health.

In addition, governments in the crisis-hit countries will

have to cope with the legacy of the intervention

measures taken to contain the fallout from the crisis.

Further dislocations in the financial and sovereign debt

markets cannot be ruled out given the need to fund the

budgetary shortfalls resulting from reduced tax

revenues. In the US, fiscal balances are fast

deteriorating and clear consolidation plans will be

needed to maintain fiscal sustainability. In Europe,

several countries have announced fiscal austerity

measures, to be implemented from H2 2010. These

policies will likely be contractionary over the short

term, even as they help to lay the foundation for

renewed growth in the long run.

Chart 3.1

J.P. Morgan Global Purchasing Manager

Indices for New Orders/Business

Source: Markit Economics

Chart 3.2

US GDP Recoveries

Source: CEIC

1 Reinhart, C. and Reinhart, V. (2010), “After the Fall”, Federal Reserve Bank of Kansas City Economic Policy Symposium

Volume, Macroeconomic Challenges: The Decade Ahead.

2007 2008 2009 2010 Sep

20

30

40

50

60

70

Ind

ex

, S

A

Manufacturing

Services

0 1 2 3 4 5 6 7 8


94

96

98

100

102

104

Ind

ex

(P

re-r

ec

es

sio

n L

ev

el=

10

0),

SA

Early 1990s

Great Recession

Early 1980s

Dot-com Bust

Outlook 47


The US recovery remains a jobless one ...

Incoming data for the US signal a period of slower

economic growth. The US Composite Leading Index

peaked in May this year and the ISM indices for both

manufacturing and non-manufacturing have descended

from their highs earlier in the year to 54.4 and 53.2,

respectively, for September. However, these readings

are still consistent with a continued expansion of the

overall economy and should allay fears of a double-dip

recession.

Weighed down by a languishing housing market and

persistent labour market weakness, consumer

confidence has moved sideways in recent months and

has yet to attain its pre-crisis levels. A continued

“jobless recovery” will discourage consumption

spending as households facing reduced incomes

struggle to pay off debt. Of greater concern is that

long-term unemployment has trended higher,

compared to both short-term unemployment and to

past recessions, suggesting a serious mismatch

between jobs and workers. (Chart 3.4)

Meanwhile, businesses are adopting a wait-and-see

approach in view of the political uncertainties before

the mid-term elections. The policy gridlock should be

resolved by end-2010, paving the way for continued

fiscal support through an extension of the Bush tax

cuts. A resolution will provide a fillip to non-residential

investment in 2011, in addition to the stimulus from a

very accommodative monetary policy environment.

Given these uncertainties, the US is now expected to

grow at 2.7% in 2010 and 2.4% in 2011, a downward

revision from the 3.3% and 3.1% estimated six months

ago. (Table 3.1)

... while growth in the Eurozone will slow

as fiscal consolidation begins.

The Eurozone, which grew with unexpected vigour in

H1, is likely to continue on a recovery path, albeit at a

more moderate and sustainable pace. In the near

term, export competitiveness will be supportive of

growth but fiscal consolidation will dampen domestic

demand. Indeed, the ZEW Indicator of Economic

Sentiment has now shown declines for six consecutive

months since April 2010. (Chart 3.5) Unemployment

rates within the region also remain high, with the

peripheral countries performing worse. (Chart 3.6)

Chart 3.3

Eurozone GDP Recoveries

Source: CEIC

Chart 3.4

US Unemployment across Recessions

Source: CEIC

ST: Short-term unemployment, 15-26 weeks.

LT: Long-term unemployment, more than 26 weeks.

Table 3.1

Forecasts of GDP Growth (%)

2009 2010 2011

Total* -0.7 5.0 4.0

Developed Countries* -3.6 2.3 1.9

US -2.6 2.7 2.4

Eurozone -4.0 1.6 1.4

Japan -5.2 3.0 1.2

NIE-3* -1.9 6.6 4.3

Hong Kong -2.8 5.7 4.5

Korea 0.2 6.1 4.2

Taiwan -1.9 8.3 4.2

ASEAN-4* 0.4 6.8 5.2

Indonesia 4.5 6.0 6.2

Malaysia -1.7 7.1 5.0

Thailand -2.2 7.6 4.3

Philippines 1.1 6.7 4.8

China 9.1 9.9 9.0

India** 7.4 8.3 8.4

Source: Consensus Economics Inc.

* Weighted by shares in Singapore’s NODX.

** Fiscal year ending March.

0 1 2 3 4 5 6 7 8


94

96

98

100

102

104

Ind

ex

(P

re-r

ec

es

sio

n L

ev

el=

10

0),

SA

Early 1990s

Great Recession

Early 1980s

0 2 4 6 8 10 12


0

100

200

300

400

500

600

Ind

ex

(P

re-r

ec

es

sio

n L

ev

el=

10

0),

SA

Early 1980s Recession, STEarly 1980s Recession, LT

Early 1990s Recession, LT Early 1990s Recession, ST

Great Recession, LT Great Recession, ST



Fiscal austerity plans announced so far aim for a

reduction in fiscal balances estimated at 1% of

Eurozone GDP over 2010 and 2011. As a result, fiscal

stimulus will soon give way to consolidation, thus

exerting a drag on growth, especially in the peripheral

countries. Although this will be offset to some extent

by a weaker euro, the boost from net exports is

expected to be modest given sluggish global demand,

and will mostly accrue to the larger Eurozone countries.

The recovery in the Japanese economy thus far has

been mostly led by exports as domestic demand has

remained weak. Looking ahead, the impending

slowdown in the US and anticipated moderation in

Europe later in the year are set to restrain Japan’s

export growth despite strong final demand growth

in Asia. Further, the sharp appreciation of the yen will

continue to exert downward pressure on Japanese

exports. According to the latest Tankan survey for large

manufacturers, the business conditions index is

expected to fall to -1 in Q4 from 8 in Q3, suggesting

a deterioration in the outlook for Q4 due in part to the

strong yen. (Chart 3.7) Overall, Japan’s GDP growth is

expected to slow to 1.2% in 2011, after a relatively

strong 3.0% in 2010.

Asia ex-Japan will be a key pillar of support

for the global economy.

Even as the industrial economies transit to a period of

slower growth, the near-term outlook in Asia ex-Japan

remains positive, although growth has started to ease

to a more sustainable rate from the heady pace seen in

H1 2010. The moderation reflects, to some extent,

a slowing of growth in the domestic demand-oriented

economies, such as China and India, especially

following the dissipation of the effects of stimulus

measures in China. Nevertheless, accommodative

monetary policies and firm domestic demand will

underpin economic activity in the region.

The Chinese economy, in particular, will continue to be

the regional growth engine. The latest PMI data, which

rose from 51.7 in August to 53.8 in September,

was accompanied by firm retail sales, alleviating

concerns that credit tightening measures and an

external slowdown would lead to a significant

deceleration in growth. Private consumption will likely

remain strong, given firm labour market conditions,

rising wages and pro-consumption policy initiatives,

the latter a part of continuing efforts to rebalance

growth away from external drivers. Concomitantly,

Chart 3.5

ZEW Indicator of Economic Sentiment

Source: ZEW

Chart 3.6

Eurozone Unemployment Rates

Source: CEIC

Chart 3.7

Japan Tankan Diffusion Indices for

Manufacturers

Source: CEIC

Note: The diffusion index refers to the percentage of

favourable responses less unfavourable responses.

2009 Apr Jul Oct 2010 Apr Jul Oct

-40

-20

0

20

40

60

80

Ne

t %

Ba

lan

ce

Germany

Eurozone

2007 2008 2009 2010

0

5

10

15

20

25P

er

Ce

nt

Aug

Ireland

Germany

France

Greece

Spain

Italy

Portugal

2005 2006 2007 2008 2009 2010

-80

-60

-40

-20

0

20

40

-20-20

% P

oin

t

Q4f

Medium-sized Enterprises

Large Enterprises

Small Enterprises

Outlook 49


investment spending in China is projected to hold firm

in line with a steady improvement in business

sentiment. (Chart 3.8) Thus, Chinese domestic

demand appears poised, not only to support the

country’s own growth, but also to play an increasingly

important role in propelling the region’s exports,

ranging from commodities, intermediate inputs and

final goods, to services such as tourism and wealth

management.

The smaller, export-driven Asian economies, such as

South Korea and Taiwan, are expected to see a more

distinct pullback in growth, in line with slackening

external conditions and softer global IT demand.

Nevertheless, GDP growth will continue to be

underpinned by three factors. First, intra-regional

trade will benefit from robust final demand in the

larger economies of the region. (Chart 3.9) Second,

the sharp upswing over the past year or so is

translating into stronger autonomous domestic

demand. Third, large capital inflows into the region

have continued to fuel activities and prices in the asset

markets, which could also pose a risk to the inflation

outlook.

Inflationary pressures remain significant in Asia

but benign in advanced economies.

Given the firmer growth trajectory and generally

brighter economic outlook, inflation in Asia ex-Japan is

vulnerable to further surprises on the upside. Domestic

inflationary pressures are already being felt in a

number of Asian countries operating at, or near

to, pre-crisis capacity utilisation rates. (Chart 3.10)

For example, wage pressures have picked up strongly in

economies such as China and South Korea. Moreover,

food and other commodity prices are expected to rise

given the recent spate of supply disruptions, although

the moderation in GDP growth in the region should

ease some of these price pressures.

For the advanced economies, deflation is still a notable

tail risk. Even as the output gap continues to close due

to losses in productive capacity during the crisis, price

pressures are likely to be minimal as domestic demand

remains weak and resource utilisation rates low.

Inflation should stay benign until much of the slack in

the economy has been taken up.

Chart 3.8

China’s Business Climate Index

Source: CEIC

Chart 3.9

Asian Exports and Leading Indicators

Source: CEIC

* Asia ex-Japan refers to ASEAN-3, NIE-3, China and

India.

Chart 3.10

Capacity Utilisation

Source: CEIC

2006 2007 2008 2009 2010

100

110

120

130

140

150

Ind

ex

Q3

2007 2008 2009 2010

-30

-20

-10

0

10

20

30P

er

Ce

nt

-30

-20

-10

0

10

20

30

3M

/3M

(%

)

Sep

China New Orders less Inventories

Exports SA, Asia ex-Japan

(RHS)

US ISM New Orders less Inventories

2007 2008 2009 2010

60

70

80

90

100

110

Ind

ex

(2

00

5=

10

0),

3M

MA

Aug

Japan

Malaysia

Eurozone

US

Korea

Thailand



3.2 Outlook for the Singapore Economy

Stronger Services Contribution Next Year

The Singapore economy will continue to grow in

2011, but at a more sustainable rate.

The Singapore economy began to display signs of

moderating in the middle of this year, following an

unprecedented expansion in H1, in line with a loss

of recovery momentum around the world. Looking

ahead, while the risk of the global economy relapsing

into recession has subsided, final demand in the

developed economies is expected to remain sluggish.

In comparison, the outlook for Asia ex-Japan economies

is more positive. Although growth in the region will

likely slow, it should continue to be supported by firm

domestic demand.

Against this backdrop, the level of economic activity in

Singapore is projected to remain high across a broad

range of industries but it could ease further in the near

term. For 2010 as a whole, GDP is on track to grow by

13% to 15% while in 2011, the domestic economy will

continue to expand but at a more sustainable rate in

line with its growth potential.

In 2011, the drivers of growth will be somewhat

different. While manufacturing and services

contributed fairly evenly to GDP growth in 2010,

services will play a bigger role next year, on the back of

a relatively sanguine outlook for the region. From the

supply-side perspective, the bulk of GDP growth in

2010 can be attributed to strong gains in productivity,

while the support from employment growth would be

smaller. Next year, however, as growth slows,

productivity will likely play a reduced role, while the

contribution of employment will increase, with a

significant number of jobs being created in the services

sector. Section 3.3 below discusses the labour market

outlook in greater detail.

Outlook 51


Manufacturing growth will slow as soft spots

have emerged in the global IT industry …

After a sharp rebound from the trough, the domestic

manufacturing sector is likely to take a breather going

into 2011 as demand in the global IT industry has

shown signs of softening recently.

Some vulnerable spots in IT final demand have

emerged in recent months, stemming largely from

weakness in the consumer segment. As shown in

Chart 3.11, US retail sales of electronics products began

to taper off July after a steady climb since mid-2009,

as economic uncertainty negatively impacted demand.

In particular, PC sales have been weak, with worldwide

PC shipments recording a 7.6% increase in Q3 2010,

significantly below market consensus of around 13%.

Although deep pockets of buyer interest remain in key

IT gadgets such as smartphones and tablets,

this segment is still relatively small compared with the

consumer market for PCs.

The drag from the consumer segment has rippled

through the IT supply chain, resulting in slower orders

for semiconductor firms further upstream, a reversal

from the shortages and extended production lead

times of the last few quarters. Thus, rising downstream

inventory has started to push up upstream inventories,

although overall inventory levels are still below

pre-crisis levels. (Chart 3.12) Mirroring developments

in the end demand segment, PC-related chip sales have

been the worst hit, with 1Gb DRAM spot prices

contracting by 19% q-o-q in Q3 after reaching a

peak in Q2 2010. (Chart 3.13) Meanwhile, sales of

handset-linked semiconductors and NAND flash, which

is the type of memory chip favoured in smartphones

and tablets, have held steady.

… but a collapse in the global IT industry is unlikely.

Notwithstanding the near-term weakness, downstream

end demand for IT products will remain well-supported

through 2011. A downturn in the global IT industry

similar in scale to the 2001 collapse is unlikely.

Even though consumer demand from the G3

economies will remain patchy, emerging economies

will continue to drive growth in key IT end

markets next year. In particular, the extension of

China’s subsidy programme for consumer electronics

until end-2011 bodes well for electronics retail sales in

China. (Chart 3.11) Corporate IT spending is also

Chart 3.11

US and China Retail Sales of Electronics

Source: CEIC and EPG, MAS estimates

Chart 3.12

Global IT Inventory Levels

Source: Company reports

Chart 3.13

Price of 1Gb DRAM Chips

Source: DRAMeXchange

2009 Apr Jul Oct 2010 Apr Aug

80

90

100

110

120

130

140

Ind

ex

(J

an

20

09

=1

00

),S

A

China

US

2008 Q3 2009 Q3 2010 Q2

70

80

90

100

110In

de

x (

Q1

20

08

=1

00

)

End Demand

Semiconductor

2008Q3 2009 Q3 2010 Q3

0

1

2

3

US

$ P

er

Ch

ip



expected to hold up, driven by the ongoing PC upgrade

cycle in developed countries, as well as continued

enterprise formation in emerging markets. According

to Gartner, global corporate IT spending is expected to

increase by 3.1% next year, from 2.4% in 2010.

In addition, supply-side conditions remain conducive;

while PC and handset inventory levels rose by about 9%

in Q2, they remained roughly 10% below their peak

levels in Q3 2008. Overall, global PC and handset

demand is expected to grow by 8-10% in 2011,

only slightly under the double-digit growth projections

for this year. (Chart 3.14) In comparison, growth in the

upstream semiconductor segment is expected to soften

substantially from 32% in 2010 to around 6% in 2011,

due in part to the dissipation of the inventory

restocking effect.

These adjustments in the global semiconductor

industry will have a disproportionate impact on

Singapore, which has a larger exposure to that

segment. (Chart 3.15) As a result, activity in the

domestic electronics segment is likely to moderate in

the second half of this year, before recovering gradually

next year. Although upstream IT demand in 2011 will

not see the expansion of H1 2010, it is nonetheless still

forecast to post moderate gains, in line with end

demand growth. In addition, supply-side expansions

could provide some support to growth next year,

such as new production lines by hard disk media

company Showa Denko and wafer fab expansions by

GlobalFoundries and UMC.

Growth in the chemicals and marine clusters

will be capped by a supply overhang.

Most of the other segments in the manufacturing

sector should achieve slower, but still healthy growth

next year. For example, the domestic petrochemical

industry has been able to leverage on strong Asian

demand in the current recovery. Chart 3.16 shows that

Singapore’s domestic exports of petrochemicals have

been rising steadily since Q4 last year, underpinned

by robust demand from regional economies.

Going forward, the domestic petrochemicals industry

will continue to expand amidst steady Asian demand.

In addition, the domestic chemicals cluster will receive

a boost from ExxonMobil’s ethylene cracker, where

start-up activities will be phased in beginning in late

2010 through 2011. Nonetheless, the pace of

expansion will be capped by a broader supply glut in

the global chemicals sector. The global ethylene

Chart 3.14

Global IT Forecast

Source: Gartner and iSuppli

Chart 3.15

Proportion of Semiconductors

in Industrial Production

Source: CEIC

Chart 3.16

Domestic Exports of Petrochemicals

PCs Handsets

-20

-10

0

10

20

30

40

Gro

wth

(%

)

2009 2010F 2011F

Semiconductors

Upstream Downstream

Taiwan Singapore Malaysia Korea Thailand

0

5

10

15

20

25

30

% S

hare

2009 Q2 Q3 Q4 2010 Q2 Q3

-50

0

50

100

% P

oin

t C

on

trib

uti

on

to

YO

Y G

row

th

East Asia ex-Japan G3 Others

Outlook 53


industry, which is a barometer of the performance of

the petrochemicals industry as a whole, is suffering

from a massive supply overhang as a result of new

plants having come on stream in the past two years,

primarily in the Middle East and China.

The build-up in capacity will continue further over the

next two years. (Chart 3.17)

In the marine & offshore engineering (M&OE) industry,

local shipyards’ net order books have been run down to

lower levels this year, weighed down by cautious

sentiment and subdued oil prices during the global

financial crisis. The Deepwater Horizon oil spill in the

Gulf of Mexico in April 2010 also led to a six-month

moratorium on deepwater drilling, further depressing

oil exploration and production activity. This is indicated

by a dip in local shipyards’ net order books this year to

date, following a sharp decline last year. (Chart 3.18)

The general shortfall in orders is expected to translate

into further slippage in production next year as the

timeline delivery for oil rigs typically spans 1-3 years.

(Chart 3.19) Nonetheless, there could be some boost

from growth in the aerospace segment, alongside the

strong demand for air travel in Asia.

Services will play a larger role in 2011.

Given the generally positive outlook for Asia, services

industries catering to domestic demand in the region

will continue to grow strongly. While there is evidence

to suggest that Asia is becoming a larger final market

for merchandise exports, the region is also becoming

an important end market for services. Chart 3.20

shows that the region’s share of global consumption

of services has been rising steadily since the beginning

of the decade, and is likely to continue into next

year. In particular, Asia’s imports of financial and

trade-related services have seen double-digit growth

over the last decade.

On the domestic front, the services sector could

potentially account for up to two-thirds of Singapore’s

GDP next year, up from around 50% this year.

In particular, the financial, trade-related and

tourism-related sectors are likely to see stronger

growth, as these sectors are highly geared towards

Asian markets and in total will contribute slightly over

half to GDP growth next year.

Chart 3.17

Ethylene Capacity Additions

Source: CMAI

Chart 3.18

Shipyard Net Order Books

Source: Keppel Corp and SembCorp Marine

* As at mid-October 2010.

Chart 3.19

Rig Delivery Schedule

Source: Keppel Corp and SembCorp Marine

2008 2009 2010 2011 2012

0

3

6

9

12

Mil

lio

n M

etr

ic T

on

s

Singapore

Taiwan

India

Thailand

S Korea

Middle East

China

Forecast

2003 2004 2005 2006 2007 2008 2009 2010*

0

4

8

12

16

20

24$

Bil

lio

n

2006 2007 2008 2009 2010 2011 2012

0

4

8

12

16

20

Nu

mb

er



Trade-related services should continue

to benefit from the region’s growth.

While trade-related services could be dampened by the

slowdown in the global IT industry, activities that are

related to domestic demand in Asia should continue to

ride on the region’s growth. For example, the

container shipping industry, which consists mainly of

the transportation of consumer durables and capital

equipment, is closely tied to private consumption and

investment in the region. According to shipping

consultancy firm Drewry, worldwide container growth

is likely to settle at 7% per annum over the next five

years, in line with historical trends. This represents a

return to stability for the industry, following the fall-off

during the crisis. The Asian market will continue to be

a key driver of growth, accounting for an average of

71% of global container growth next year. (Chart 3.21)

… as will demand for domestic financial services.

Riding on Asia’s robust growth prospects, the outlook

for the domestic financial services sector remains

bright, given Singapore’s role as a regional financing

and wealth management hub. ACU non-bank lending

is likely to hold up, buoyed by the heightened

demand for infrastructure and corporate financing in

Asia. (Chart 3.22)

The fund management industry is also projected to

grow further, bolstered by rising wealth levels in the

region. According to the BCG Global Wealth 2010

Report, Asia-Pacific (ex-Japan) wealth will be the fastest

growing over the next half-decade, at nearly twice the

global rate of 5.8% from end-2009 through 2014.

Correspondingly, AUM (assets under management) in

the region is expected to rise by 11% per annum on

average, exceeding Europe’s 5.5% and North America’s

4.4% respectively. (Chart 3.23) The rapid growth in

regional wealth will increase demand for wealth

management services in Singapore as well as in priority

and private banking activities.

Chart 3.20

East Asia ex-Japan’s Share of Global Imports

of Services

Source: IMF Balance of Payments

Chart 3.21

Container Growth Forecast, by Region

Source: Drewry Container Forecaster, Q3 2010

Chart 3.22

ACU Non-bank Lending, by Region

2000 2002 2004 2006 2008

9.5

10.0

10.5

11.0

11.5

12.0

% S

ha

re

2009 2010 Q3 2011 Q3 2012

-10

-5

0

5

10

15

20

% P

oin

t C

on

trib

uti

on

to

YO

Y G

row

th

Asia W. Europe N. America Others

Q3

Forecast

Q1

2009 Q2 Q3 Q4 2010 Q2 Aug

-4

-2

0

2

4

6

% P

oin

t C

on

trib

uti

on

to

QO

Q G

row

th

East Asia Europe Americas

Outlook 55


At the same time, the financial sector will continue to

be supported by its core intermediation and insurance

clusters, which have remained relatively resilient

throughout the recent crisis. Domestic non-bank

lending should continue to record healthy growth,

in line with the broader economic recovery.

While consumer lending may see a moderation in

growth following the implementation of the property

cooling measures in late August, it will be supported by

the drawing down of mortgage loans in the existing

pipeline. In addition, business lending should continue

to recover in view of a generally supportive external

environment. (Chart 3.24)

Tourism-related industries will be

supported by Asian demand

and Singapore’s improved facilities.

Meanwhile, Singapore’s tourism-related industries,

including hotels & restaurants, retail trade,

air transport and gaming, will benefit from firm

regional consumer spending. Indeed, since Q1 2009,

East Asian visitors, who form the lion’s share of visitor

arrivals to Singapore, have been increasing at a faster

rate than tourists from other markets. (Chart 3.25)

Visitor inflows from the region have also been buoyed

by the opening of the two IRs and shopping malls.

As a result, Singapore’s share of tourist arrivals into

Asia ex-Japan2 rose from 4.1% in Q1 2009 to 4.6% in

Q2 2010. (Chart 3.26)

There are lingering risks in the

external environment.

The Singapore economy will hit a soft patch in the

immediate quarters ahead amidst a still-fragile global

recovery. Nonetheless, the domestic economy should

recover gradually into 2011, stemming from relatively

sanguine prospects for the regional economies.

In particular, trade-related services and the

tourism-linked industries should be boosted by strong

private consumption and investment in Asia.

Chart 3.23

Global AUM Projections

Source: BCG Global Wealth Report, 2010

* Compounded annual growth rate.

Chart 3.24

DBU Non-bank Lending

Chart 3.25

Visitor Arrivals to Singapore by Markets

2 Asia ex-Japan comprises China, Hong Kong, India, Indonesia, Korea, Malaysia, the Philippines, Singapore, Taiwan and

Thailand.

0

2

4

6

8

10

12

14

US

$ T

rill

ion

0

2

4

6

8

10

12

14

Pe

r C

en

t

Increase in AUM CAGR (RHS)*

Europe NorthAmerica

Asia Pacificex-Japan

2008Sep 2009 2010

90

100

110

120

130

Ind

ex

(S

ep

20

08

=1

00

)

-1

0

1

2

3

MO

M %

Gro

wth

Business (LHS)

Consumer (LHS)

Non-bank Loans Growth (RHS)

AugJul

2009 Q2 Q3 Q4 2010 Q2 Jul-Aug

90

100

110

120

130

140

Ind

ex

(Q

1 2

00

9=

10

0)

Rest of World

East Asia



While the risk of another round of financial

contagion arising from sovereign defaults and a

sharper-than-expected downturn in the advanced

economies has ebbed somewhat, other risks related to

the inflow of capital into Asia have risen. An upsurge in

inflationary pressures that leads to a disorderly reversal

of flows could occur if regional economies are not able

to intermediate these flows efficiently. While banks,

corporates and households are in a healthy position,

having built up their balance sheets after the Asian

Financial Crisis, developments in credit and asset

markets bear close monitoring.

Taking these factors into account, the Singapore

economy is forecast to grow in line with its potential

next year.

Chart 3.26

Singapore’s Share of Visitor Arrivals

into Asia ex-Japan

Source: CEIC

2009 Apr Jul Oct 2010 Apr

3.8

4.0

4.2

4.4

4.6

4.8

Pe

r C

en

t

Jun

Outlook 57


3.3 Labour Market

Sustained Job Creation

Job creation will continue to be supported

by the services sectors …

In the near term, the current pace of hiring in the

labour market is likely to be sustained. According to

the latest Manpower Employment Outlook Survey,

a quarter of the 699 employers polled intend to add

workers in Q4 2010, while only 3% expect to cut jobs

and the bulk of respondents plan to maintain

headcount. This is similar to the survey results from

the previous three quarters. (Chart 3.27)

Job creation in most services sectors will remain

strong. In particular, employment growth in the

tourism-related industries such as retail trade and

hotels & restaurants will be supported by the high

number of visitor arrivals. The information &

communications sector will also hire more workers,

driven by the increased spending on IT and

telecommunication services. In the financial services

sector, demand for workers in private banking will

continue to be boosted by Asia’s strong growth

prospects, although hiring could abate in other

segments as a significant proportion of the hiring plans

made earlier in the year had already been realised.

… as hiring in manufacturing and construction

will be modest.

In comparison, job creation will continue to be modest

in the construction sector due to the lack of major

private projects in the pipeline. The recent steps taken

by the government to cool the property market may

also moderate building activity in the private residential

segment in the short term.

Within the manufacturing sector, hiring sentiment is

likely to stay subdued in the non-electronics industries,

given the lingering uncertainties over the global

economy. In particular, there could be further job

losses in the transport equipment industry, as order

books remain weak. In comparison, job gains in the

electronics industry are likely to be supported by the

Chart 3.27

Employment Outlook

Source: Manpower Inc.

2009Q4 2010Q1 Q2 Q3 Q4

0

20

40

60

80

100

Pe

r C

en

t

Don't Know No Change Decrease Increase



sustained global demand for IT gadgets, such as

smartphones and tablets, especially during the festive

season.

Competition for service workers

will drive up wages …

Strong demand for service workers amidst the

tight labour market will cause staff turnover

to increase and wage pressures to build up.

The former is already evident from the increase in the

recruitment and resignation rates in most services

sectors. (Chart 3.28)

The increase in services wages will boost overall wage

growth over the next few quarters before it eases as

the low base effects dissipate. For both 2010 and 2011,

nominal wage growth will be relatively strong

compared to the average of about 3% in the last ten

years.

… while labour productivity growth will ease

to a more moderate pace …

Meanwhile, labour productivity growth is likely to slow

after surging by 15% y-o-y in H1 2010. Compared to the

recovery period following the Asian Financial Crisis and

2001 IT Downturn, the initial increase in productivity at

the turn of the business cycle this time round was much

weaker. This reflected the resilience in the labour

market as firms held on to workers during the

downturn in part due to the Jobs Credit Scheme.

However, subsequently, labour productivity growth

picked up sharply on the back of a surge in

manufacturing output. (Chart 3.29) Based on the

profile in the previous two recessions, labour

productivity growth should moderate substantially in

the next few quarters.

… which will result in an increase in

unit labour cost.

Slower productivity growth, strong wage pressures and

changes in labour-related policies3 will result in an

increase in Unit Labour Cost (ULC) over the next few

quarters, thereby reversing some of its previous

decline. (Chart 3.30)

Chart 3.28

(a) Average Recruitment Rates in the

Services Sectors

(b) Average Resignation Rates in the

Services Sectors

Chart 3.29

Labour Productivity Growth

across Recessions

* Past two recessions refer to the Asian Financial Crisis

and 2001 IT Downturn.

3 These include the increase in the foreign worker levy and employers’ CPF contribution, as well as the withdrawal of the

Jobs Credit Scheme.

2005 2006 2007 2008 2009 2010 Q2

0

2

4

6

Pe

r C

en

t Wholesale & Retail

Transport & StorageFinancial Services


Information & Communications

2005 2006 2007 2008 2009 2010 Q2

0

2

4

6

Pe

r C

en

t

Wholesale & Retail

Transport & StorageFinancial Services



1 2 3 4 5 6 7

Number of Quarters from GDP Trough

-10

0

10

20

YO

Y %

Gro

wth

Average of Past Two Recessions* Recent Recession

Outlook 59


In the medium term, labour productivity should be

boosted by a higher quality workforce.

Nonetheless, in the medium term, labour productivity

should be boosted by government measures aimed at

achieving an average productivity growth target of

2-3%.

Recently, several new initiatives have been introduced

to enhance the capabilities of the labour force.

Notably, the national Continuing Education and

Training (CET) system has been further enhanced,

with its scope broadened to include more

programmes for professionals, managers, executives

and technicians (PMETs). For example, the new

Productivity Initiatives in Services and Manufacturing

(PRISM) will offer a suite of productivity-related

courses, including master classes, seminars and training

courses, for both the manufacturing and services

sectors.

In addition, the Ministry of Manpower (MOM) is

looking to raise the quality of foreign workers.

To this end, some administrative changes were made to

its foreign worker policy in July this year. For example,

in order for non-Malaysian work permit holders in the

hospitality industry to qualify for skilled levy status,

they must pass an English language proficiency test,

in addition to meeting existing requirements for

academic and skill qualifications.

Chart 3.30

Unit Labour Cost Index

2006 2007 2008 2009 2010 Q2

95

100

105

110

115

120

125

Ind

ex

(2

00

5=

10

0),

SA



3.4 Inflation

Shifting to Domestic Drivers

CPI inflation will remain high before

moderating in H2 2011.

After reaching 3.4% in Q3 2010, headline CPI inflation

will continue to increase in the next quarter on account

of strong domestic cost pressures, notably the costs of

accommodation and domestic services. In comparison,

external sources of inflation will be generally capped by

the weakness in the global economy. CPI inflation is

expected to climb to around 4% at the end of 2010 and

stay high in H1 2011 before moderating.

Increases in residential property rentals will drive

CPI accommodation cost higher.

Accommodation cost in the CPI will rise in the next few

quarters, given the tight supply in the residential rental

market. The supply constraints are more apparent in

the public housing segment, with HDB rentals

mostly holding steady even during the economic

downturn. (Chart 3.31) In the private residential

property market, vacancy rates remained low at 5.2%

in Q3 2010 compared to the ten-year average of

7.2%, despite the new supply that has come on

stream.4 (Chart 3.32)

At the same time, demand for rental properties is

projected to remain healthy, driven by the continued,

albeit slower, inflow of Employment Pass Holders and

Permanent Residents.

On the whole, accommodation cost could add more

than half a percentage point to CPI inflation next year.

Chart 3.31

HDB Median Sublet Rents

Chart 3.32

Private Residential Property Vacancy Rates

4 Around 10,000 new private residential units are expected to be completed by the end of this year, much higher than the

average of 6,600 per year in the last decade.

2007Q3 2008 2009 2010 Q3

1000

1250

1500

1750

2000

2250

$ P

er

Mo

nth

3-room

Executive

5-room4-room

2002 2004 2006 2008 2010Q3

0

2

4

6

8

10

Pe

r C

en

t

Average of 2000-2009 Vacancy Rates

Outlook 61


Meanwhile, services inflation will pick up

due to higher labour costs ...

As noted in the previous section, the labour market

has been tight, resulting in wage pressures, especially

in the services sectors. Given the high proportion

of labour cost in services, overall business cost has

also risen. 5 Indeed, the Unit Services Cost Index,

which is EPG’s internal gauge of cost pressures in

the services sector, rose firmly by 4.6% in H1

this year, despite commercial rentals being largely

unchanged. (Charts 3.33 and 3.34)

Going forward, cost pressures in the services sectors

could intensify. Sustained demand for services workers

as firms continue to perform strongly, together with

near-record high job vacancy rates, will push up wages.

The increases in foreign worker levies and the

employers’ CPF contribution rate, together with the

withdrawal of the Jobs Credit Scheme, will also add to

labour cost. In addition, office rentals picked up more

significantly in Q3 despite the supply that has been

coming on stream since the beginning of this year.

(Chart 3.34) This points to firm demand from the

services sectors which is likely to be sustained.

Thus, even with the larger expected increase in supply

next year, office rentals could rise further.

In 2011, services costs could contribute up to 1% point

or about a third of overall CPI inflation.

... and strong underlying demand.

Over the medium term, there are other underlying

factors that will continue to drive services inflation

higher. Notably, the demand for various services such

as recreation, education and healthcare will rise further

in tandem with the increased affluence of the general

population and changes in demographics, namely the

expansion in the population size and population

ageing.6 The higher demand and the move to improve

service quality will exert upward pressure on firms’

operating costs. Besides, labour productivity growth in

services has remained lower than in manufacturing

Chart 3.33

Unit Services Cost Index


Chart 3.34

Rental Indices for Office & Shop Space

in the Central Region

5 For instance, the share of remuneration in operating expenditure is around 40% for community, social & personal

services, which includes educational, healthcare, recreational and household-related services in the National Accounts.

Source: Department of Statistics (2008), Economic Surveys Series, The Services Sector.

6 Based on DOS’ Household Expenditure Surveys, the percentage of a typical household’s spending on services such as

health and education climbed to more than 10% in 2008, from about 8% a decade ago.

2006 2007 2008 2009 2010Q2

105

110

115

120

125

130

Ind

ex

(2

00

2=

10

0),

SA

2006 2007 2008 2009 2010

80

100

120

140

160

180

200

220In

de

x (

Q4

19

98

=1

00

)

Office Space

Shop Space

Q3



due in part to lower capital intensity, which will result

in cost increases more likely to be passed on to

consumers. (Table 3.2)

Indeed, in the industrialised countries, the inflation

rate in services has outstripped that in the

goods-producing industries, partly due to differences in

productivity growth.

Car prices will broadly stabilise.

In comparison, car prices are unlikely to increase

significantly going forward. In recent bidding exercises,

the average COE premium stabilised at around

$38,000, providing growing evidence of moderating

demand for cars.7 (Chart 3.35) With car demand

unlikely to rebound strongly as the economy slows,

COE premiums are not expected to increase

significantly despite the expected decline in the COE

quota arising from the fall in the number of vehicle

de-registrations.8

Nonetheless, given base effects, car prices will continue

to contribute substantially to CPI inflation until

February 2011. The cost of private road transport,

excluding petrol, will add about 0.5% point to CPI

inflation in 2011 following the 1-1.5% point

contribution this year. This contrasts starkly with the

2000-08 period when the vehicle population growth

rate was higher at 3% and private road transport,

excluding petrol, was a drag on headline inflation.

External sources of inflation will largely come

through higher food prices ...

Domestic food prices rose modestly in the first nine

months this year after staying largely unchanged for

the most part of 2009. This reflects the relatively

benign global food prices in H1 this year, as measured

by the UN FAO Food Price Index. (Chart 3.36)

However, global food prices have climbed in recent

months following a series of weather-related supply

disruptions in various parts of the world. In particular,

the recent emergence of the La Niña phenomenon,

Table 3.2

Average Labour Productivity

Growth Rates (%)

Overall

Economy

Manufacturing

Industries

Services

Industries

1990-99 3.1 6.7 3.2

2000-09 1.3 1.9 1.3

Chart 3.35

Car COE Bids, Supply Quotas and Premiums

Chart 3.36

FAO Food Price Index

Source: FAO

7 An average of 4,241 bids was received per month in Apr-Sep 2010 for car COEs, a sharp drop from the 10-year average of

9,490.

8 Monthly vehicle de-registrations fell to an average of 1,773 vehicles in the last six months, less than half the average of

the last 10 years.

2002 2004 2006 2008 2010

0

10

20

30

40

50

$ T

ho

us

an

d

0

4

8

12

16

20

Nu

mb

er

(Th

ou

sa

nd

)

Total Monthly Quota (RHS)

Bids Received for Car COEs (RHS)

Weighted Average Car COE Premium (LHS)

Oct

2006 2007 2008 2009 2010

100

120

140

160

180

200

220

Ind

ex

(2

00

2-2

00

4=

10

0)

Sep

Outlook 63


which is expected to intensify and last at least until

early 2011, has affected crop harvests in several of

Singapore’s key food suppliers.9

These supply disruptions, together with the pickup in

domestic demand during the festive periods, could lead

to upward pressures on domestic food prices in the

next two quarters. Domestic food price inflation could

thus accelerate from about 1.5% this year to 2.5%

in 2011. This would be higher than the 0.9% average

increase in 2000-06, though much lower than the 7.7%

registered in 2008 when global inventories across

major commodities fell to record lows.10

... since global oil prices are unlikely

to rise significantly.

Global oil prices are expected to fluctuate largely

within the range of US$75-85 until the end of 2011,

given the anaemic growth outlook in the G3 economies

and the expected slowdown in emerging markets,

notably China. (Chart 3.37) In addition, the level of

global oil inventories remains high by historical

standards and there is significant spare production

capacity amongst OPEC members to cope with any

upside in demand. (Chart 3.38)

CPI inflation and the MAS underlying inflation

measure are forecast to reach 2-3% in 2011.

On a sequential basis, the CPI will continue to rise,

albeit at a more moderate pace compared to the last

two quarters. (Chart 3.39) The build-up in the

sequential price increases will result in CPI inflation

reaching around 4% on a year ago basis at the end of

2010. It will likely stay high in H1 2011 before

moderating to around 2% in H2. (Chart 3.40)

For the whole year, headline CPI inflation is projected

to be 2.5-3% in 2010 and 2-3% in 2011.

Chart 3.37

WTI Crude Oil Price Forecasts

Source: Bloomberg

* Bloomberg Weighted Analyst Average.

** Nymex WTI Futures on 25 October 2010.

*** EIA Forecasts on 13 October 2010.

Chart 3.38

OECD Crude Oil Inventory Levels and

OPEC Crude Oil Spare Production Capacity

Source: EIA

9 The La Niña weather phenomenon, caused by a fall in water temperature in the tropical Pacific, brings wetter-than-

normal weather to South Asia and Southeast Asia, droughts in South America and more cyclones in the Atlantic. Excessive

rain since July has already hampered production of crops ranging from cocoa to rice in Indonesia and Pakistan. Moreover,

South American nations, such as Brazil and Argentina, may experience dryness in the next few months that could reduce

soya bean and wheat crops.

10

Even with the recent weather-related supply disruptions, IMF’s estimate for 2011’s end-year global stock-to-use ratio for

major food crops is about 21%, well above the historical-low of 16% in 2008 which was caused by a combination of

weather-related supply disruptions, increased diversion of food crops to biofuel production and higher input costs due to

the surge in oil prices.

2007 2008 2009 2010 2011

30

60

90

120

150

US

$ P

er

Ba

rre

l

Nymex Spot

Analyst*

Futures**

EIA Forecasts***

Dec

Forecast

2006 2007 2008 2009 2010 2011

50

55

60

65

Da

ys

of

Su

pp

ly

0

2

4

6

Mil

lio

n b

pd

Inventories (LHS) Spare Capacity (RHS)

Dec

Forecast



The MAS underlying inflation measure, which excludes

the costs of accommodation and private road

transport, is expected to rise to 2-3% next year,

from around 2% this year.

Close to half of the CPI inflation this year will come

from private road transport cost and another

one-third from oil/food commodity prices. Next year,

the domestic non-tradables, namely services and

accommodation, will account for about half of CPI

inflation while food prices will account for about a fifth.

Indeed, the average inflation rate of domestic

non-tradables for the period 2007-11 will be much

higher than that in 2000-06, due to changing dynamics

in the domestic-oriented industries. Apart from the

underlying factors driving services inflation and

changes in the government’s motor vehicle policy,

accommodation cost will adjust more quickly to

developments in the residential rental market.

The latter is due to the change in the pricing indicator

for owner-occupied housing cost in the CPI from

Annual Values to timely rental data. 11 Externally,

food prices will also face upward pressures due to

more frequent weather-related supply disruptions

amidst increased demand from emerging economies.12

Chart 3.39

Forecasts of Sequential CPI Increases


Chart 3.40

CPI Inflation and MAS Underlying Inflation

Measure Forecasts


11

Annual Values are estimated by the Inland Revenue Authority of Singapore for taxation purposes.

12

More frequent occurrences of extreme weather conditions are expected as the interval between the El Niño/La Niña

Southern Oscillation (ENSO) cycles appears to have shortened from 5-8 years in the past few decades to 3-5 years in more

recent times.

2006 2007 2008 2009 2010 2011

90

95

100

105

110

115

Ind

ex

(2

00

9=

10

0)

-2

-1

0

1

2

3

QO

Q %

Gro

wth

CPI (LHS)

Sequential Increase in CPI (RHS)

Forecast

Q4

2007 2008 2009 2010 2011

-2

0

2

4

6

8

YO

Y %

Gro

wth

MAS Underlying Inflation Measure

CPI Inflation

Q4

Forecast

Special Features



Is Free Trade Green?11 Introduction The literature on the nexus between trade and the environment is vast (Dean, 1992). A number of prominent economists, such as Bhagwati (1988) and Subramanian (1992) fall into the “no linkages” camp arguing that questions of free trade should be de-linked from those of the environment, otherwise, protectionism could easily wreck the global trading system under the guise of environmental concerns. According to this point of view, governments intent on improving the environment would do better to adopt targeted environmental policies instead of trade policies. Dean (1992, p. 22), for example, argues that “trade barriers will be, at best, a second-best means of reducing environmental damage… Any case for more gradual liberalisation of trade should be based on estimates of the costs of maintaining barriers versus the benefits of delayed environmental damage.”

Pollution as an Externality

The debate continues because economists have yet to satisfactorily create the frameworks in which to incorporate nature as an input into production or to value the utility of an un-spoilt environment, although there have been increasing attempts to do so. (World Bank, 2005). This Special Feature explores the simple, but emotive, question – is free trade green? – by introducing environmental issues into a standard microeconomic analysis of an autarchic economy which is then opened up to trade with the rest of the world. The general finding is that although free trade can be compatible with environmental policies designed to reduce negative environmental effects arising from both production and consumption, this is only true under certain assumptions.

In the standard microeconomic production model, output of any good involves combining factor inputs, such as labour, capital, and land with given technology. The quality of the environment does not appear in the production function, nor is pollution regarded as an output of production. Yet, pollution is the by-product of several types of production and, ceteris paribus, environmental degradation follows. Take the example of a firm that produces a single good X which generates sulphur dioxide as a by-product and when released into the environment, causes acid rain which damages buildings and trees. Unless the firm explicitly takes this pollution effect into account when planning the number of units of X to

produce, the costs of environmental degradation are external to the firm and pollution is an externality. Who bears the cost of this externality? Other firms and households around the site of the pollution will likely be affected and potentially other countries, should the acid rain be transmitted across borders. Since the polluting firm itself only bears the private cost of producing X by paying for the factor inputs used, there is a wedge between private costs and social costs. In this particular case, social costs exceed private costs and too much of good X is produced.

1 This Special Feature has benefited from comments and discussions with Professor Roger Sandilands of Strathclyde

University and Professor W. Max Corden, Emeritus Professor of International Economics, Johns Hopkins University.

Special Feature A

Special Features 67


Production and Pollution in Autarchy2

The logical solution to this problem would be for the government to introduce policies to reduce the production of good X by imposing limits on its production or through other means of incentivising firms to reduce output, such as taxing or fining polluting firms under the “polluters pay” principle (Tulkens and Schoumaker, 1975) or imposing environmental standards that firms have to comply with. These policies bring the private cost of production closer to the social cost and reduce the profit-maximising level of output, as firms have to “internalise” the taxes and fines or the costs of investing in pollution abatement technology or “greener” methods of production. Chart 1 depicts a small, autarchic economy A, producing two kinds of goods: X and Y, which are more capital- and labour-intensive in production, respectively. Suppose initially the production of both goods is polluting. Citizens in country A consume a bundle containing both X and Y and maximise their utility on the highest attainable indifference curve (U0) tangential to the production possibility frontier, PPA0. Both

producers and consumers are in simultaneous equilibrium producing and consuming the combination X0 and Y0. Since there is no international trade, consumers are constrained to consume the combination of the two goods in exactly the same proportion as they are produced, with producer and consumer relative price ratios identical at P0. Now, assume that the government is concerned about consumer welfare and pollution. Consequently, the government by diktat constrains the amount of capital and labour used in production in the economy, while holding constant the technologies used and the relative proportions of X and Y in total output. Firms thus scale down the volume of X and Y they produce in proportion, represented by a lower production possibility frontier, PPA1, which represents an inward shift of PPA0. This environmentally friendlier outcome comes at a price — there are underutilised resources at the “shadow” PPA1 and consumers consume less of each good (X1, Y1) on the lower utility curve U1; hence, their overall utility declines.

Chart 1 Economy A under Autarchy with Constrained Production

2 Some of the assumptions in this section may seem unnecessarily restrictive. These assumptions have been adopted for

the purposes of illustrating a simple case of reducing pollution when in autarchy, and will be relaxed in subsequent sections.

U0

PPA0

P0

U1

Y0

X1

Y1

X0 PPA1

Y (labour-intensive)

X (capital-intensive)



The Free Trade Scenario Case 1: Pollution and Production under Free Trade What happens to production, and thus pollution, when economy A, which is producing along PPA1, liberalises trade? Here we utilise the framework developed in Copeland and Taylor (2003), with the plausible simplifying assumption that X and Y vary in their pollution intensity, with X being more polluting in production than Y and Y’s pollution is negligible. Additionally, it is assumed that economy A is relatively more abundant in capital than in labour and has a comparative advantage in the capital-intensive good X. Copeland and Taylor introduce a pollution-production schedule beneath the horizontal axis by mapping the amount of output produced into the volume of pollution discharged, denoted by the line Z.3 Under autarchy economy A produces a basket of goods (X1, Y1), generating Z1 units of pollution in the process. (Chart 2) The implication is that economy A could ostensibly trade its way to a superior basket of goods by opening the economy up to trade with the rest of the world. Given A’s comparative advantage in capital-intensive goods, A will specialise in the production of X, the more polluting good. On opening up to trade, the relative price of X is higher than in autarchy, represented by a steeper price line P1.

The economy now produces the bundle X2, Y2 along its constrained production possibility frontier PPA1 and can export some of good X to the world market in return for imports of good Y. Consumers will now be able to consume a bundle X3 and Y3 and reach a higher utility curve U2 than in autarchy, depending on the extent to which relative prices change.4 However, the post-trade outcome is not “greener” for economy A, as the composition of production has shifted in favour of the more polluting good. Production of X2 units generates more pollution as compared to autarchy, while there is no perceptible fall in pollution from importing more of good Y. The reverse would also be true: were economy A labour-abundant, it would have a comparative advantage in producing the labour-intensive good Y. Not only would consumers enjoy higher welfare after trade but pollution would also be lower in the economy. This brings us to the general conclusion that trade liberalisation per se for a particular country is not unambiguously more (or less) environmentally-friendly; much depends on the underlying comparative advantage of the economy, the pollution characteristics of the two goods and their relative capital and labour intensities and the changes in the terms of trade brought about when the economy opens up to international trade. These outcomes are summarised in Table 1.

3 This assumes a positive monotonic relationship between pollution and production of the polluting good. 4 The extent to which the slope of the international terms of trade line differs from the pre-trade price ratio will determine

the outcome. The greater the difference, the higher the indifference curve attainable. This holds true even if the international price ratio is flatter than in autarchy (rise in the relative price of Y) since the economy would produce more of Y and trade it for greater consumption of X.

Special Features 69


Chart 2 Economy A with Constrained Production but Trading5

Table 1 The Environmental Impact of Free Trade (Production)

Relative Prices with Trade Relative price of X rises

(A has comparative advantage in X) Relative price of Y rises

(A has comparative advantage in Y)

Pollution intensity in production

Production of X is more polluting

1. Opening up to trade results in production of more of X and less of Y.

“Less green” outcome

2. Opening up to trade results in production of less of X and more of Y.

“Greener” outcome

Production of Y is more polluting

3. Opening up to trade results in production of more of X and less of Y.


4. Opening up to trade results in production of less of X and more of Y.


5 Production and/or consumption of X are polluting but that of Y is negligible.

X1 X2X3

Z2

Pollution (Z)

Z1

U0

PPA1

P1

U1

Y1

Y3

Y2

U2

Z3

X

Z

Y


Case 2: Pollution and Consumption under Free Trade The outcomes here are analogous to Case 1. Not all goods are equal in their pollution-intensity in consumption. For example, consuming a transcontinental flight would generate more carbon dioxide emissions than a bicycle ride. If there is no pollution in production, the same Copeland and Taylor framework in Chart 2 can be adapted to ascertain the outcomes when the consumption of X is assumed to be polluting but the consumption of Y is not. Additionally, it is assumed that the shape of consumers’ indifference curves remains unchanged, and consumers do not take the impact of pollution into account in the utility derived from consumption. Under autarchy, Z1 units of pollution are produced when X1 is consumed. Assume that trade liberalisation results in a rise in the relative price of good X. (Chart 2) With free trade, the “greener” outcome (Z3) is realised in economy A if consumers end up consuming the basket of goods denoted by (X3, Y3). However, this would only occur if the change in relative consumer prices as a result of opening economy A up to trade induces consumers to purchase less of X and more of Y. Should relative prices move differently, the “greener” consumption outcome may not materialise. Table 2 summarises the circumstances under which free trade would be better for the environment.

The picture becomes more complicated if consumption and production is assumed to be polluting simultaneously. The impact of free trade on pollution is ambiguous in all circumstances, as the impact of comparative advantage and production on pollution pulls in an opposite direction from the consumption effect. For example, a rise in the relative price of X results in more production but less consumption of X in economy A. Thus, a “green” outcome would depend on the relative pollution intensity of consumption and production. Finally, even if economy A is able to attain the “greener” outcomes under free trade in Tables 1 and 2, the situation must run in the opposite direction for its trade partner country B in a two-country world. It may be the case, for instance, that technological differences or ecological endowments between the two economies differ so vastly that firms and consumers in economy B are able to undertake greater production or consumption of the more polluting good without degrading the environment. Otherwise, it would be difficult to avoid accusations that economy A’s “greening” attempts have resulted in an environmental “beggar-thy-neighbour” effect that redistributes pollution across borders. What is best for one country may not be best for the world as a whole — this seems to be as true for pollution as it is for monetary policy and tariffs on traded goods.

Table 2 The Environmental Impact of Free Trade (Consumption)

Relative Prices with Trade Relative price of X rises Relative price of Y rises

Pollution intensity in

consumption

Consumption of X is more polluting

Opening up to trade results in consumption of less of X and

more of Y.


Opening up to trade results in consumption of more of X and

less of Y.


Consumption of Y is more polluting

Opening up to trade results in consumption of less of X and

more of Y.


Opening up to trade results in consumption of more of X and

less of Y.



Special Features 71


Conclusion Free trade can be compatible with environmental concerns, but this is only true under certain assumptions. Environmental effects stemming from changes in production and/or consumption when engaging in international trade may complement the standard gains from trade, but equally, a sufficiently large negative environmental

impact could offset these gains for an individual country. In the face of such externalities, countries concerned about environmental damage would be better off dealing with pollution directly via, for example, an optimal tax, while retaining free trade to maximise the welfare gains from international exchange.

References Antweiler, W, Copeland, B R and Taylor, M S (1998), “Is Free Trade Good for the Environment?”, NBER Working Paper No. 6707. Bhagwati, J (1988), Protectionism, The MIT Press. Copeland, B R and Taylor, M S (2003), “Trade, Growth and the Environment”, NBER Working Paper No. 9823. Dean, J M (1992), “Trade and the Environment: A Survey of the Literature”, Background Paper for the World Development Report 1992. Subramanian, A (1992), “Trade Measures for Environment: Nearly an Empty Box?”, World Economy, Vol. 15(1), pp. 135-52. Tulkens, H and Schoumaker, F (1975), “Stability Analysis of an Effluent Charge and the ‘Polluters Pay’ Principle”, Journal of Public Economics, Vol. 4(3), pp. 245-69. World Bank, (2005), Where is the Wealth of Nations?: Measuring Capital for the 21st Century.



Is China a Sustainable Source of Demand

for East Asia?1

Introduction

Previous issues of the Review have carried special

features examining the importance of final demand

in advanced developed countries to Asian

economies. In the October 2007 issue, the US-Asia

decoupling hypothesis was tested using a variety of

statistical techniques. While little evidence of

structural decoupling was found, it was shown that

the two regions could nevertheless experience

weaker synchronicity in the short run. A further

study in October 2009 arrived at a similar

conclusion that the real export growth of Asian

economies was still strongly hinged to OECD final

demand but indirectly through a complex pattern of

cross-border production networks. The sharp

decline in trade following Lehman Brothers’ collapse

in late 2008, in particular, could be mostly

attributed to the synchronous and severe

contraction of economic activity in the developed

countries.2

Asia’s dependence on the G3 economies, however,

appears to have weakened amidst the recent global

financial crisis. The region rebounded strongly even

as private consumption and investment growth in

the G3 was restrained by the deleveraging process

undertaken by households and firms. At the same

time, domestic demand in China and other parts of

Asia remained robust throughout the crisis period.

The question thus arises as to whether

export-driven economies in this region are

beginning to diversify their sources of growth,

depending less on the G3 and more on China.

Trade data for the last two years appear to offer

empirical support for such a view, since the

region’s exports to China recovered much faster

than those to the G3. However, analysis of this

issue is complicated by the widespread presence

of cross-border production networks in Asia and

the dual role played by China, both as an assembly

base and as a consumer of final products.

This Special Feature uses a pooled regression to

ascertain whether China has emerged as an

important source of final demand for East Asia

(EA-8).3 Given China's dual role as an assembly

base and a source of demand, the study focuses

on explaining East Asia’s real exports of machinery

parts and components to the world. The choice of

dependent variable was also motivated by the fact

that trade flows in Asian countries are heavily

influenced by production networks, most of which

are located in Asia itself. This modelling

framework yields estimates of the differential

impact on Asian exports of the Chinese market

vis-à-vis the G3, thus allowing counter-factual

simulations to quantify the buffer provided by

China’s stimulus measures to Asian economies

during the recovery from the global financial crisis.

1 This Special Feature was written in consultation with Assistant Professor Davin Chor from the School of Economics,

Singapore Management University.

2 See also Pula and Peltonen (2009), Athukorala (2010), IMF (2010), Kalra (2010) and Kuroiwa and Kuwamori (2010) for

evidence on the continued importance of the developed economies as key sources of final demand for East Asian exports,

notwithstanding a secular rise in intra-Asian trade flows.

3 The EA-8 consists of Hong Kong, Indonesia, Malaysia, the Philippines, Singapore, South Korea, Taiwan, and Thailand.

Special Feature B

Special Features 73


Cross-Border Production Networks and Final Demand

The Role of Cross-Border Production

Networks

Over the past decade, trade linkages in East Asia

have strengthened significantly alongside the

emergence of China as a global manufacturing

base. Intra-Asian trade flows expanded at an

average annual rate of 13% over the period

2000-09, outpacing world export growth of 8.9%

during the same period. The integration of

regional trade is most clearly manifested in the

rise of cross-border production networks for parts

and components used in machinery and transport

equipment. In this international form of vertical

specialisation, a component is manufactured in

one country before being exported to another for

testing or assembly, using components imported

from yet other countries. The finished product is

then transported to the final source of demand,

which may reside in countries not involved in the

original production chain.

To investigate the determinants of EA-8 exports of

machinery parts and components to the world,

export data for each country is compiled using the

detailed Harmonised System (HS) codes published

by Ando and Kimura (2005).4

These exports

account for about a quarter of total regional trade

and are dominated by electronic components and

accessories. Notably, the average share of

electronics in exports of machinery parts and

components ranges from 57% in the case of

Thailand to 83% for Malaysia. With regard to the

destination, about 45% of such exports were

bound for Asia in the early 2000s, while the G3

accounted for another 45%. Over the last few

years, however, the share of Asia has risen to

almost 60% along with the rapid expansion of

cross-border production networks in the region.

In comparison, the share of the G3 has shrunk to

less than a quarter.

Ultimately, intermediate inputs into machinery

and transport equipment are driven by end-user

demand around the world. The analysis here

restricts attention to final demand in the

Chinese and G3 markets, which are the four

largest economies in the world. Retail sales are

used as a proxy for private consumption

demand, while investment demand is

represented by gross fixed capital formation in

the G3 and fixed asset investment in the case of

China.5 Final goods demand is then defined as

the sum of consumption and investment

expenditures in real terms.

Evolution of EA-8 Exports and Final Demand

EA-8 exports of intermediate parts and

components have grown steadily over the past

decade except for two large dips during the 2001

IT Downturn and the recent global financial

crisis. (Chart 1) The rapid expansion prior to the

collapse in 2008 was underpinned by strong G3

final goods demand. When the crisis struck

in 2008, G3 demand fell sharply from its peak

in 2007 as consumer and business confidence

plummeted. The decline was quickly

transmitted to the export-dependent economies

in Asia and its effects amplified by the

proliferation of cross-border production

networks in the Asian region, leading to large

contractions in the electronics trade and

intra-regional exports.6

4 Machinery and equipment is made up of products in codes HS84 to HS92, comprising general machinery, electric

machinery, transport equipment and precision machinery. Parts and components of machinery and equipment are

compiled from a list of nearly 150 product categories at the HS 6-digit level. The data is sourced from the Global Trade

Atlas. Total exports of such components are used except for Singapore and Hong Kong, where domestic exports are used

instead. The export data for the eight economies is denominated in local currency and deflated by export price indices,

with the exception of Indonesia and the Philippines, where the producer price index is used.

5 National income statistics for China are not available on a quarterly basis.

6 See Box A in the April 2009 issue of the Review.



In contrast to the cutbacks in the G3, strong

income growth and a burgeoning consumer

market in China – especially in electronic and

electrical products – supported the rapid

expansion of demand, which strengthened further

during the crisis due to the large fiscal stimulus

package implemented by the Chinese government.

In particular, fixed asset investment surged as the

Chinese authorities accelerated the pace of

industrialisation and infrastructure building to

contain the fall-out from the global downturn on

the Chinese economy. (Chart 2)

Against this backdrop, East Asia’s exports have

rebounded decisively since Q2 2009, providing

tentative evidence of China’s growing role as a

source of final demand for the region. In terms

of relative importance, China’s share of total

final goods demand had nearly quadrupled from

6% in 2000 to 23% by 2009, exceeding that of

Japan. (Chart 3) Conversely, the share of the US

had declined from 44% to 35%.

Chart 1

EA-8 Exports of Machinery Parts and Components

and G3 Final Demand


Chart 2

Final Demand in China

Chart 3

Shares of Total Final Demand*

Source: EPG, MAS estimates Source: CEIC and EPG, MAS estimates

* Calculated as shares of combined Chinese and G3

total final demand.

2000 2003 2006 2009

80

100

120

140

160

180

200

Ind

ex (

Q1 2

000=

100),

in

US

$

96

100

104

108

112

116

120

Ind

ex (

Q1 2

000=

100),

in

US

$

G 3 D em and (R H S )

E A -8 E xp o rts (LH S )

Q 4

2000 2002 2004 2006

0

2000

4000

6000

8000

RM

B B

illi

on

, 2

00

5 p

ric

es

, S

A

Fixed Asset Investment Retail Sales

2009 Q4 Eurozone Japan US China

0

10

20

30

40

50

Pe

r C

en

t

2000 2009

Special Features 75


Econometric Methodology

In order to analyse the contribution of China’s final

demand to East Asia’s exports of intermediate

goods vis-à-vis that of the G3, it is initially assumed

that the respective impact is the same for all

EA-8 countries and time periods. (This assumption

is investigated further below through rolling

regressions.) Hence, a pooled regression is used to

explain total exports of machinery parts and

components �� of each country � over the

period Q1 2000 to Q4 2009.

The key explanatory variables in the regression

equation are final goods demand in China and the

G3 �� ,� , ��,��, the price competitiveness

of country � as represented by the real effective

exchange rate ��, trade openness ��

and the size of real GDP ��.7 The equation

can be expressed as:

ln�� ln�� ,�� ! �" ln��,��! �� ln�� ! �# ln��! �$ ln�� ! ∑&��'(�)(*�)+'�! ,�-*.�/01�23 4! 5�-*.�/01� �32637� ! 8�� 1�

The trade openness and real GDP variables are

included to reflect known factors that may

influence the volume of a country’s exports. Other

unobserved country idiosyncratic effects are

subsumed under the country-specific intercepts

and linear time trends �-*.�/01�23 4 ,-*.�/01� �32637��. To deal with seasonality, a set

of quarterly seasonal dummy variables

�(�)(*�)+'� is also added to the regression.

The relative importance of China and G3 final

demand can be indirectly inferred from ordinary

least squares estimates of � and �" . These

parameters are akin to the income elasticities

commonly estimated in standard export demand

equations.

The estimated coefficient for �� is analogous to

the price elasticity and it provides an indication

of the average sensitivity of Asian exports to the

real exchange rate.8

Equation (1) is also estimated using a rolling time

window to assess how the relative importance of

China and G3 final demand has evolved over the

past decade, as well as to check on parameter

stability. Furthermore, interaction dummies are

included to compare the impact of China versus

G3 final demand prior to, and during the latest

crisis. Accordingly, equation (1) is re-specified

as:

ln�� :-0�(�( ! � ln�� ,��! � ;-0�(�( < ln�� ,��=! �" ln��,��! �" ;-0�(�( < ln��,��=! �� ln�� ! �# ln��! �$ ln�� ! ∑&��'(�)(*�)+'�! ,�-*.�/01�23 4! 5�-*.�/01� �32637� ! 8�� 2�

where the variable -0�(�( is a time dummy,

which takes the value of 1 for the crisis period

from Q4 2008 to Q4 2009, and is zero otherwise.

In addition to signalling the onset of the sharp

decline in trade, the -0�(�( variable is intended

to capture the implementation of the

exceptional stimulus by the Chinese authorities

to mitigate the impact of the financial crisis on

the domestic economy. The coefficients of the

interaction terms, � and �" , thus indicate

whether there were significant changes in the

final demand elasticities during the crisis period.

7 Trade openness is defined as the ratio of total nominal trade to nominal GDP. Data for all the explanatory variables is

sourced from CEIC except for the REER series, which is from the IMF.

8 Tests of statistical significance on the regression estimates are performed using robust standard errors that take explicit

account of potential heteroskedasticity and cross-sectional correlation in the disturbance term.



Results and Inferences

Pooled Estimates

The full sample results for the pooled regression

(1) show that the estimated coefficients for final

demand are of the right sign and are highly

significant. (Table 1) With regard to their

magnitudes, a 1% increase in G3 final goods

demand is associated with a 1.7% increase in EA-8

exports of machinery parts and components.

In comparison, a 1% increase in China’s demand

raises exports by only 1.4%. The country-specific

control variables, such as real GDP and trade

openness are also highly significant and of the

correct signs.9 However, the export elasticity with

respect to the real exchange rate is statistically

insignificant, indicating that intermediate goods

are not sensitive to relative price changes,

probably because they contain a high proportion

of imported inputs.

Although the results seem to suggest that final

demand in China and the G3 economies have a

roughly similar impact on regional exports of

intermediate goods, it is crucial to note that the

estimated elasticity for China could be

overstated due to the introduction of stimulus

measures by the Chinese authorities during the

global recession.10

Moreover, the relative

importance of Chinese final demand compared

to the G3 is likely to have evolved over a period

of time as trade patterns shifted and economic

structures changed.

This issue of parameter instability is further

investigated through rolling regressions of

equation (1). Chart 4 shows the rolling estimates

for China and G3 demand elasticities, � and �"

respectively, using a 20-quarter fixed window.

Table 1

Regression Results for Equation (1)

Q1 2000 to Q4 2009

Dependent Variable: ?@�ABCD�

Key Explanatory

Variable Coefficient Standard Error

^

ln�� 1.69** 0.44

ln�� 1.43** 0.42

ln�� 0.71** 0.23

ln�� 0.91** 0.18

ln�� −0.67 0.52

Diagnostics

R-squared 0.998

No. of observations 320

Standard error of regression 0.128


^ White heteroskedasticity-consistent standard error.

** Significant at the 1% level.

9 A potential problem of reverse causality could arise from the use of GDP as a regressor, leading to biased estimates for

the regression parameters. However, this is less likely in this instance, given that the dependent variable is exports of a

particular group of products, rather than the total exports of a country. Moreover, including lagged GDP (by one period)

does not change the results materially.

10

Conversely, the G3 elasticity would have been higher had it not been for the sharp contraction in G3 final demand during

this period.

Special Features 77


Chart 4

Rolling Regression Estimates for EF and EG

(a) China Final Goods Demand (EF)

(b) G3 Final Goods Demand (EG)


Note: Each observation in the chart corresponds to the

end-point of a 20-quarter rolling regression.


Note: Each observation in the chart corresponds to the

end-point of a 20-quarter rolling regression.

Two key findings emerge from the rolling

regression results. First, there was a discernible

pickup in China’s final demand elasticity prior to

the crisis, even though the 95% confidence interval

showed that � was not significant yet. A tentative

interpretation for this result is that Chinese

domestic demand has been emerging gradually as

a source of growth for East Asia during the past

decade. Nevertheless, the impact on exports of

machinery parts and components is fairly modest

compared to G3 final demand, which was boosted

by credit-induced booms in the developed world

over the period Q4 2006 to Q3 2007.

Second, the Chinese impact became statistically

significant during the financial crisis after �

reached a maximum value of two in late 2008.

In comparison, the sensitivity of EA-8 exports to

G3 demand fell considerably and turned

insignificant. This switching of roles reflects the

part played by China as a pivotal source of support

during the global recession, which partially offset

the pullback in G3 final demand. The decline in

the G3 countries itself might also be viewed as a

reversion to the historical norm following the

bursting of the credit bubble.

Taken together, the results from the rolling

regressions suggest a possible structural break

in the final demand parameters some time

prior to the global financial crisis. Accordingly,

the Quandt-Andrews test for parameter stability

with an unknown breakpoint yields a t-statistic

of 11.26 at Q1 2005, firmly rejecting the null

hypothesis of parameter stability at the 1% level.

This in turn suggests a break in the parameters in

Q1 2005.11

The break date coincided with the decision taken

by the Chinese authorities in December 2004 to

rebalance the sources of economic growth by

expanding domestic consumption, followed by

reforms to the exchange rate regime in Q3 2005.

However, it is important not to infer too much

from the exact location of the break, given that

the test could also detect gradual evolution of

the regression parameters. Indeed, these results

are consistent with the time-varying coefficients

of the rolling regressions.

11

The test considers the value of the largest F-statistic from a sequence of Chow structural change tests on possible break

dates in the central 70% of the sample. Critical values are from Andrews (1993).

2004Q4 2005Q4 2006Q4 2007Q4 2008Q4 2009Q4

-2

-1

0

1

2

3

4

5

Pe

r C

en

t

95% Confidence Interval

2004Q4 2005Q4 2006Q4 2007Q4 2008Q4 2009Q4

-5

0

5

10

15

20

Pe

r C

en

t

95% Confidence Interval



Crisis Effects

Table 2 reports the results of the augmented

specification in equation (2). The findings confirm

the earlier observation that there could be a

significant difference in the final demand elasticity

for China prior to, and during, the crisis years.

Specifically, a 1% increase in demand is only

associated with an increase of 0.9% in EA-8 exports

pre-crisis but during the crisis, the leverage

provided by Chinese demand strengthened

significantly due to the implementation of

the stimulus measures. The additional impact is

estimated to be 0.7%, as captured by

the interaction dummy -0�(�( < ln�� ,�� .

This brings the overall impact of a 1% increase in

China’s final goods demand to 1.6% during the

crisis period.

In comparison, there is no discernable change in

the G3 final demand elasticity during the

downturn, given that the variable

-0�(�( < ln��,�� is not statistically significant.

Instead, a 1% increase in G3 demand is now

estimated to have led to an increase of 2.3% in

EA-8 exports during the pre-crisis period when

accounting for the financial crisis. (Chart 5)

Nevertheless, the estimate of the interaction

term with G3 demand indicates a moderation in

impact with the onset of the crisis.

The results thus confirm that G3 demand has

been a more important source of growth than

Chinese final demand for EA-8 exports prior to

the trade collapse in 2008, as inferred from

a much larger elasticity compared to China.

This also corroborates earlier findings in the

literature on the importance of extra-regional

markets for Asian exports. During the financial

crisis itself, however, there has been greater

synchronisation between China’s final demand

and EA-8 exports, probably due to heavy

pump-priming carried out by the Chinese

authorities.

Table 2

Regression Results for Equation (2): Q1 2000 to Q4 2009

Dependent Variable: ?@�ABCD�

Key Explanatory

Variable Coefficient Standard Error

^

ln�� 2.29* 1.08

-0�(�( < ln�� −0.67 1.28

ln�� 0.87** 0.20

-0�(�( < ln�� 0.71* 0.33

-0�(�( −0.89 12.2

ln�� 0.67** 0.23

ln�� 0.82** 0.18

ln�� −0.72 0.53

Diagnostics

R-squared 0.998

No. of observations 320

Standard error of regression 0.128


^ White heteroskedasticity-consistent standard error.

* Significant at the 5% level. ** Significant at the 1% level.

Special Features 79


Chart 5

Impact of a 1% Change in Final Goods Demand on EA-8 Exports

G3 China0

1

2

3

Pe

r C

en

t

Prior to Crisis Crisis period

2.3

0 .9

0 .7

Source: EPG, MAS estimates Simulation

Using equation (2), a counterfactual simulation is

performed to quantify the support provided by

China to EA-8 exports of machinery parts and

components during the global financial crisis.

Under the baseline scenario, the model is

simulated using actual values of the explanatory

variables. The predicted path of EA-8 exports is

then compared with the trajectory generated

under a counterfactual scenario, where China’s

demand is assumed to grow during the crisis at its

average historical rate, i.e. in the absence of the

government stimulus. (Chart 6)

The impact of the stimulus package is then

estimated as the percentage deviation of

predicted exports under the counterfactual

scenario from the projections using the actual

evolution of Chinese demand. Chart 7 plots this

difference over the crisis period. The results

show that EA-8 exports would have declined by

37% from their previous peak at the depth of the

crisis in Q1 2009 in the absence of the Chinese

stimulus, compared with the actual outcome of

a 31% decline.

Chart 6

Simulated China Final Goods Demand

Chart 7*

Simulated EA-8 Exports

Source: CEIC and EPG, MAS estimates Source: EPG, MAS estimates

* The percentage deviation from the baseline scenario is

applied to the actual trajectory of EA-8 exports over the

period Q4 2008 to Q4 2009.

2004 2005 2006 2007 2008 2009

2000

3000

4000

5000

6000

7000

8000

RM

B B

illi

on

, 2

00

5 p

ric

es

Actual

Counter-factual

Q4 2007Q4 2008Q4 2009Q4

60

70

80

90

100

110

20

05

Pri

ce

s,

in U

S$

Te

rms

Ind

ex

(Q

4 2

00

7=

10

0),

Actual

Counterfactual

22%

Peak



It thus appears that China’s private consumption

and investment spending had been an important

source of demand for East Asian exports

throughout the crisis period. While the stimulus

measures could not completely offset the

precipitous decline in G3 demand, they

nevertheless served to prop up China’s economic

growth and stimulate demand for regional exports.

In the absence of the discretionary boost to final

demand, the ensuing rebound in EA-8 exports

would likely have occurred later and would have

been more subdued. In particular, the volume of

exports would have been 22% below actual during

the initial phase of the turnaround and would have

been lower than its pre-crisis level by the end of

2009.12

(Chart 7)

Sum-up

This Special Feature has applied a pooled

regression model to analyse the relative

importance of final demand in China and the G3

for exports of machinery parts and components to

the world from eight East Asian economies.

The findings suggest that EA-8 exports were

heavily dependent on G3 demand while the

Chinese market had a much smaller but rising

impact prior to the global financial crisis.

However, during the crisis, there is some evidence

of weaker synchronicity between East Asia and the

G3 economies, which probably reflects the

transitory buffer provided by policy-induced

demand in China.

The support provided by China during the global

downturn should, however, not be taken as

conclusive evidence that Chinese final demand

has become a sustainable and independent source

of growth for the East Asian economies.

The heightened impact of China’s demand on EA-8

exports might in fact be transitory, given that

the bulk of the Chinese stimulus package was

geared towards the building of infrastructure.

With the completion of these projects, final

goods demand in China may well revert to

historical trend growth, in the absence of further

measures to stimulate private consumption.

Beyond the crisis, ongoing reforms to increase

the role of domestic demand will only come

about gradually. Nonetheless, in the longer

term, the rapidly expanding Chinese consumer

market, coupled with its deep regional trade

linkages, will provide immense potential for

China to contribute to an enduring rebalancing

of the global economy.

12

IMF (2010) also reports similar results. Specifically, the positive spillovers from a lower saving ratio in China on the Asian

region would have cushioned the impact of the crisis by about one-third.

Special Features 81


References

Ando, M and Kimura, F (2005), “The Formation of International Production and Distribution Networks in

East Asia” in Ito, T & Rose, A (eds.), International Trade, NBER-East Asia Seminar on Economics, Vol. 14,

pp. 177–213.

Athukorala, P (2010), “Production Networks and Trade Patterns in East Asia: Regionalisation or

Globalisation”, ADB Working Paper Series on Regional Economic Integration No. 56.

Andrews, D (1993), “Tests for Parameter Instability and Structural Change with Unknown Change Point”,

Econometrica, Vol. 61, pp. 821–856.

IMF (2010), “Leading the Global Recovery: Rebalancing for the Medium Term”, Regional Economic

Outlook: Asia and Pacific, April.

Kalra, S (2010), “ASEAN: A Chronicle of Shifting Trade Exposure and Regional Integration”, IMF Working

Paper No. WP/10/119.

Kuroiwa, I and Kuwamori, H (2010), “Shock Transmission Mechanism of the Economic Crisis in East Asia:

An Application of International Input-Output Analysis”, Institute of Developing Economies Discussion Paper

No. 220.

Pula, G and Peltonen, T (2009), “Has Emerging Asia Decoupled? An Analysis of Production and Trade

Linkages Using the Asian International Input-Output Table”, ECB Working Paper No. 993.



The Mysteries of Trend1 by Peter C. B. Phillips2 The Hamlet of Econometrics

“A statistician is a fellow that draws a line through a set of points based on unwarranted

assumptions with a foregone conclusion.”

“No one understands trends. Everyone sees them in data.”

Trends are ubiquitous in economic discourse, they figure prominently in media commentary, they play a role in much economic theory, and they have been intensively studied in econometrics for three decades. Yet the empirical economist, forecaster, and policy maker have little guidance from theory about the source and nature of trend behaviour. They have even less guidance about practical formulations, and they are heavily reliant on a limited class of stochastic trend, deterministic drift, and structural break models to use in applications.

A vast econometric literature has emerged but the nature of trend remains elusive. In spite of being the dominant characteristic in much economic data, having a role in policy assessment that is often vital, and attracting intense academic and popular interest that extends well beyond the subject of economics, trends are little understood. Like the protagonist in Shakespeare’s most famous play, trend remains unfathomable and inscrutable, the Hamlet of econometrics. No one knows what it will do next. This Special Feature discusses some implications of these limitations, mentions some research opportunities, and briefly illustrates the extent of the difficulties in learning about trend phenomena even when the time series are far longer than those that are available in economics.

What is Trend? Trend is a simple five letter word. Its use is ubiquitous in economics, dominating macroeconomic discourse on growth and productivity which, as Paul Krugman3 once said, in the long run affect almost everything in economics. The concept is equally pervasive in modern microeconomics and all the applied subfields of economics, where intertemporal comparisons play a major role in economic

theories of behaviour and in subsequent assessments of policy effectiveness, covering issues as sociologically diverse as the impact of abortion rights legislation on crime, schooling on earnings, and no-fault legislation on divorce statistics. In the world of finance, trend is just as vital and important because it is the drift in asset prices that provides the allure of long-term capital appreciation and rewards risky investment.

1 A longer version of this Special Feature is available from the author's website (http://korora.econ.yale.edu). Partial

research support is acknowledged from the NSF under Grant No. SES 09-56687. 2 Peter C. B. Phillips is Sterling Professor of Economics and Professor of Statistics at Yale University and Distinguished Term

Professor at Singapore Management University. 3 “Productivity isn't everything, but in the long run it is almost everything” is the opening line in Krugman (1995).

Special Feature C

Special Features 83


The dictionary definition of the word trend originates from a nineteenth century usage4 as “the general course of events or prevailing tendency” – a seemingly simple concept that is readily apprehended by all. Or is it? Is our apprehension of the concept so unambiguous that it needs no explicit definition beyond that of our general understanding derived from its dictionary meaning? Media commentaries as well as professional economic discussion frequently take the meaning of the term for granted and proceed to lever policy argument on the basis of this presumption. How often, for instance, do we hear senior public economists like the Chairman of the Federal Reserve, Governors of central banks and Treasury Secretaries describing the context for economic policy decisions by speaking of the data in expressions such as “if current trends continue ...” or “a newly-emergent trend is ...” or “long-term trends indicate ...”. It is one of the ironies of economics that while these commonly-used phrases appear to carry a measure of technical precision that lends professional import to discussion, that precision (and presumably some of the credibility that comes with it) is illusory. Leaving aside the issue of what is really meant or intended by the word “trend” (whose popular meaning has changed significantly over the last few centuries and whose scientific meaning is seldom given), the attendant epithets (such as current, emergent, or long-term in the usages cited) seem to lend precision to the concept, thereby creating a misleading impression of scientific import in their usage. Misleading, because it is impossible to have clarity in these expressions without making the component terms themselves unambiguous: what is a trend, and how are the terms current, newly emergent, and long term to be interpreted? In short, is it possible to measure and discuss with clarity any quantity that is undefined? Econometricians have been battling with these ideas over the last 30 years and know how imprecise the terms are. How is it then that such a fundamental concept as trend, whose use is so widespread in the elite quantitative

journals and public economic forums, can be so imprecise in discourse, so little understood and so often misleading in practice? The ubiquity of the word trend and its imprecision are by no means confined to economic discourse. Imprecisions in usage arise everywhere across the social, behavioural and business sciences to the natural sciences and from popular discussion in the media to scientific work. In some cases, as in the assessment of climate change (to which we turn below), trend measurement has major societal and planetary consequences, as well as economic and policy implications. One explanation for the ubiquitous usage lies in a natural human desire to bring order to disorder when seeking to understand (or model) the world around us. When we see a cloud of data points plotted against time, our minds bring order to that disorder by drawing a line through the points – representing the data in a way that seeks to satisfy an innate need to understand its primary features. We want to know what has been, where we are now, and most of all, where we are going. A trend line satisfies these primitive requirements. It summarises where we have been, shows where we are now in relation to the past, and, most of all, reveals a hint of where we are going. The lines we draw in our minds, like those we draw on paper or fit by econometric methods, are typically smooth and the derivative is a direction vector for the future. Lines through the data reveal features like a long-run tendency to increase over time, a cyclical pattern, or turning points that can be associated with known events, thereby helping to reinforce their value to us. Parametric and nonparametric trend regression and smoothing techniques like Whittaker (1923) graduation (known in macroeconomics as Hodrick-Prescott filtering) are simply technical mechanisms that formalise this mental process of representation and ex-post discovery.

4 According to the Online Etymology Dictionary (http://www.etymonline.com/) this usage in the sense of "general

tendency" is recent and dates from 1884. The older meaning of the word (a verb) dates from 1598 – "to run or bend in a certain direction, as of a river or coastline" – and is based on the Middle English "trenden" which meant "to roll about, turn, or revolve" – certainly a different meaning from "the general course of events" as we presently understand the term. Given this etymology, the modern notion of a stochastic trend seems to possess an atavistic link with the earlier usage.


Whether the device is the eye, the hand, or the technical apparatus of econometrics, trend fitting leads to a curve through a set of points that is typically continuous and smooth, or at least piecewise so. These properties facilitate the exercise and they offer advantages in potential interpretation, suggesting the existence of a generating mechanism for which continuous differentiability is a basic feature, subject perhaps to an occasional structural shift. Such a "trend" is manufactured from the data and easily apprehended. But how realistic is such a heroically simplified representation of a mechanism that by its very nature resists understanding, when even the vocabulary of description defies scientific clarity? For when we speak of current trends continuing, do we simply assert that a line drawn through a given set of points continues into the future? If so, which line or curve and which set of current points? Do we mean the last three data points, the last five or the last ten? And how well does the proposition that emerges withstand these changes in formulation?

Technical market analysis, which is so common in the popular financial press, abounds with such lines, giving readers a visual directory of upper and lower trend support lines, long-term containment triangles, resistance levels, and many other data-manufactured lines, all purporting to represent some fundamental feature of a series and its evolution. As the definition of a statistician that heads this Special Feature implies, much data analysis of trending time series is of this kind, often resting on unstated and unwarranted assumptions that are not tested. How then are we to value and interpret such analysis? And what better alternatives do formal econometric methods offer the empirical researcher and policy maker whose decisions often rely on trend evaluation in relation to alternate policies? A partial answer to these questions has been provided by the econometrics of stochastic trends, structural breaks, and nonstationary time series which has produced toolrooms of new methodology for analysing trends. This machinery allows practitioners to cope with trend processes that are inherently random or subject to random shifts, as well as many practical trend models that are misspecified.

Stochastic Trend To the wide professional community of applied economists working in macroeconomics and international finance, the most influential and practically useful transformation in the last three decades in econometrics has been the unit root and cointegration revolution. This revolution changed the way the profession thought about trend by emphasizing the role of stochastic elements in the trend mechanism and by formulating a technically well-defined concept of long-run behaviour that did not remove randomness. In the mid 1980s, functional limit laws and integral functionals of Brownian motion took time series econometrics in a firestorm that swept through all the mainline economics journals.

The new thinking swiftly penetrated econometric teaching and empirical practice, creating a vast new literature of applied economics sophisticated in its use of modern econometric technology and nonstandard limit theory. Beyond economics, the methods became a major export of econometrics to other social and business sciences. Their rapid acceptance and widespread use across many disciplines affirmed the importance of an idea whose time had come – a random trending mechanism that could be used to study commonality in movement over time among many series and deliver estimates of long-run linkages and adjustments, as well as transient dynamics.


Special Features 85

In their limiting forms – Brownian motion, fractional motions, diffusions, and semi-martingales – these trends form continuous stochastic processes but they are not smooth and they have inherently unpredictable elements. Change and randomness form a critical element in their composition. In this respect they differ from the trend lines that our minds draw when we are confronted with a cloud of points. Correspondingly, when econometric time trend regressions or smoothing algorithms draw lines through data manifesting stochastic trends, we obtain spurious regressions which give a misleading view of the nature of the trend and its direction. The econometric methods developed in studying these phenomena enabled us to explain precisely what conventional trend line regressions do deliver in the context of such misspecification (Phillips, 1986; Durlauf and Phillips, 1988) and how comovement may be efficiently estimated (Johansen, 1988; Phillips and Hansen, 1990; Phillips, 1991). These methods opened the door to a new arena of empirical research and policy discussion that has been enormously productive and has created a new standard of professional econometric practice and empirical policy analysis.

In this new standard, spurious regressions have a well defined pejorative meaning, usually taken in contrast to cointegrating regression. But cointegrating regressions do not model or explain trends, they simply co-relate trending time series under given assumptions about the form of the trending mechanism. These assumptions are necessary for many econometric methods but they are inevitably approximations in view of the complex and poorly understood nature of the forces that determine trends in the data. The result is inescapable – trend misspecification and some degree of spurious regression.

Spurious modelling of trends may be inevitable but it is far from useless. If it were, then there would be little value in much applied macroeconomic work, where trend misspecification must be taken as universal. Here (and elsewhere in applied work) convenience is frequently a decisive factor heightening the appeal of devices like polynomial time trend regression and simple smoothing operations such as the Whittaker-Hodrick-Prescott filter. Like least squares regression, these methods still form the backbone of much empirical work and they do not yield their ground easily to more sophisticated alternatives such as various forms of nonparametric fitting using both time and frequency approaches (e.g., Corbae, Ouliaris and Phillips, 2003; Shimotsu and Phillips, 2005). Nor do more sophisticated methods necessarily address the root issue of misspecification. But nonparametric approaches in the frequency domain can be helpful in that they distinguish the memory component in the data as an important individual feature and they permit general formulations of trending processes in terms of the asymptote of the spectral density in the immediate locality of the zero frequency. These asymptotic forms hold for many different classes of trend, both deterministic and random. So they appeal in terms of their generality. Correspondingly, general representations hold for the discrete Fourier transform of the time series in the region of the zero frequency and therefore furnish sample information about the nature and strength of the trend.



Recent research (Phillips, 1998; 2005) I have been pursuing has shown that trend misspecification need not be fatal, even when using smooth polynomials to model stochastic trends. In such cases, the regression coefficients remain random even in infinite samples and may be interpreted as the random coefficients that arise in projecting the limiting stochastic trend process on subspaces furnished by basis functions, such as the time polynomials used in regression. Similar properties hold in the case of breaking trend basis functions. We can, in fact, think of these models as coordinate approximations to an always more complex (and random) underlying trend function. In effect, the time polynomials or other regressors act as basis functions forming a sieve space (an approximating space using an infinite family of functions) for a stochastic process. The random coefficients then reflect the randomness in the trend process itself. It is also possible to use these coordinate regression functions in a meaningful way for prediction – in the limit, these predictors can even reproduce martingale like forms, as shown in Phillips (2005). In effect, smooth deterministic functions can represent nondifferentiable (unpredictable) martingales in the limit when we allow for random coefficients. The coordinate basis approach may also be used to model and capture co-movement among such time series in a very general way, extending the notion of reduced rank regression that is now commonly used in applied econometric modelling to a stochastic process context. In practice, therefore, while economists and financial analysts frequently see trends in the data and wish to use estimates of these trends in policy projections, the econometric modelling of such trends is demanding and failure can have major implications for policy. When the

trend-generating mechanism is poorly captured in an empirical model, forecasts carry forward the poor approximation. The phenomenon is familiar to empirical researchers and forecasters who see the incoming data drift away from their model projections as the horizon increases. Quick model adaptation to the random wandering, unpredictable element of trend (witness the original medieval meaning of the word) then becomes a critical feature in good applied modelling and needs to be accounted for in forecasting and policy analysis, as many experienced practitioners acknowledge.

Econometric analysis of model adaptation mechanisms to capture changes and account for shifts in location and trend soon after they occur are becoming part of a new armoury for forecasters (Phillips and Ploberger, 1994; Andrews, 2003; Clements and Hendry, 2006; Castle et al, 2010). Recent analysis by Ploberger and Phillips (2003) provides a limit theory which explains how much harder it is to get closer to a true generating mechanism with nonstationary components than it is one with only stationary covariates. A corollary of this theory is that forecasting is an order of magnitude harder for trending data because the optimal forecast is harder to estimate even when the form of true trend model is known.

The moral is that if trend terms are present in our models we need to be sure that they are relevant, well estimated, and quickly adapted to change. Otherwise, they can be powerfully wrong in forecasting and mislead policy. As the second header to this Special Feature intimates, trends have an elusive quality: no one understands the mechanism, but everyone sees evidence of it in the data.

Economic Policy and Climate Trend National economic policies are commonly motivated by long-term goals and correspondingly reflect perceived trends in various indicators of societal needs. Similar considerations drive global policy agreements on financial stability, trade,

and economic cooperation. Trend assessment is inevitably part of all such policy decisions. Nowhere is this more evident at present than in the ongoing global discussion of policy on climate change.


Special Features 87


Underlying all discussion and policy enactment is the science of climate change – understanding the natural processes, external forces and human activity that may affect long-term climate. There is broad scientific agreement about human impact on the level of greenhouse gases (GHG) in the atmosphere, manifested in the popular “hockey stick” graphic that shows the trend in GHG over the last two centuries as a sharp spike against the blade of little change over the previous two millennia. There is also agreement, but less unanimity, about the quantitative impact of GHG emissions on climate. Evidence available from ice core data5 over the past half million years confirms a strong and persistent association but the causal mechanism and time lags involved are complex and little understood. Economic policy analysis has to assess the cost of doing nothing or too little about climate change against the cost and potential gains of implementing GHG abatement strategies like emissions trading and carbon taxation. Caught up in this policy debate are major questions of trend determination: how GHG emissions will affect climate over the next century and what impact on the trend the different abatement measures may have. Economic analysis, national economic policy and successful global cooperation all rely on estimates of climate trend. The horizons cover everything from a few years to generations in the future.6 The difficulties and uncertainties involved in these trend projections are simply enormous. For comparison, climatological data extend over geologic time frames and are measured in thousand year or million year units. Against this time frame, economic time series seems woefully short, especially when it comes to studying trend behaviour. Yet many of the same problems (such as the inherent random elements in trend, shortfalls in theory guidance, and ambiguities between trend and cycle) continue to manifest themselves. Having more data, in effect, does not always lead to improvement in analysis or understanding. Sometimes, especially with trending time series, the advent of more data

simply means more to explain. As in economics, it is the synergy of good theory, data, and statistical methodology that is most likely to enhance understanding. No present climatological (or planetary) simulation models are capable of generating climate trajectories of the type that have been observed over long geologic periods. Neither do the models or methods currently in use in studying trends in econometrics measure up to the task of modelling these series. Paleoclimate data over many millions of years raise the difficulties of trend modelling to an entirely different level. Trend is a complex phenomenon with features that turn out to be endogenous to the sample size. As we lengthen the time span of observation, what first appears as a pattern of drift later becomes absorbed into a cycle with a longer period or even manifests as volatility. The pattern continues to repeat itself over different time scales, extending back with presently available data as far as half a billion years. Is trend itself then a phenomenon that is relative to time scale? If so, when we model trend how do we take account of the wider picture presented by a longer time frame when that data is not available to us? And what form of asymptotic theory is appropriate in a finite sample where the trend form is random and endogenous to the sample size? These are hard questions that push the limits of present understanding. In the absence of data, the answers must lie in good theory, better econometrics and fast algorithms for adapting models that are inevitably misspecified. To capture the random forces of change that drive a trending process, we need sound theory, appropriate methods, and relevant data. In practice, we have to manage under shortcomings in all of them. It is at least some comfort for the econometrician and economic policy maker to know that these manifold difficulties of modelling trend are not confined to economics.

5 Petit et al. (1999) provide a record and statistical analysis of various GHG levels as well as temperature and dust particles

obtained from ice core samples covering the past 420,000 years from the Vostok station in Antarctica. 6 Over such time frames even the choice of the discount factor can have major implications (Nordhaus, 2007).


Trends and Truth Picasso once said that art is a lie that tells the truth. Even the most ardent proponent of the merits of economic theory could hardly claim the same of economic models. Good economic models are lies that may reveal a kernel of insight about reality. Recognition of this shortcoming is as important as apprehending the truth that no one understands trends. The role of econometrics is to find that kernel of insight in the data and put it to work to aid forecasting and policy. If we are fortunate, some of the mysteries of trend, including its inherent random nature, may be revealed in the process.

References Andrews, D W K (2003), “End-of-Sample Instability Tests”, Econometrica, Vol. 71(6), pp. 1661-1694. Castle, J L, Fawcett, N W P and Hendry, D F (2010), “Forecasting with Equilibrium-Correction Models during Structural Breaks”, Journal of Econometrics, Vol. 158(1), pp. 25-36. Corbae, D, Ouliaris, S and Phillips, P C B (2002), “Band Spectral Regression with Trending Data”, Econometrica, Vol. 70(3), pp. 1067-1110. Clements, M P and Hendry, D F (2006), "Forecasting with Breaks", pp. 605-657, in G. Elliott, C.W.J. Granger and A. Timmermann (eds), Handbook of Economic Forecasting, Elsevier. Durlauf, S N and Phillips, P C B (1988), “Trends versus Random Walks in Time Series Analysis”, Econometrica, Vol. 56(6), pp. 1333-1354. Johansen, S (1988), “Statistical Analysis of Cointegration Vectors”, Journal of Economic Dynamics and Control, Vol. 12(2-3), pp. 231-254. Krugman, P (1995), The Age of Diminished Expectations, The MIT Press, Cambridge, Massachusetts. Nordhaus, W (2007), “Critical Assumptions in the Stern Review on Climate Change”, Science, Vol. 317, pp. 201-202. Petit, J R, Jouzel, J, Raynaud, D, Barkov, N I, Barnola, J M, Basile, I, Bender, M, Chappellaz, J, Davis, J, Delaygue, G, Delmotte, M, Kotlyakov, V M, Legrand, M, Lipenkov, V, Lorius, C, Pépin, L, Ritz, C, Saltzman, E, Stievenard, M (1999), “Climate and Atmospheric History of the Past 420,000 years from the Vostok Ice Core, Antarctica”, Nature, Vol. 399, pp. 429-436. Phillips, P C B (1986), “Understanding Spurious Regressions in Econometrics”, Journal of Econometrics, Vol. 33(3), pp. 311-340. Phillips, P C B (1991), “Optimal Inference in Cointegrated Systems”, Econometrica, Vol. 59(2), pp. 283-306.


Special Features 89


Phillips, P C B (1998), “New Tools for Understanding Spurious Regressions”, Econometrica, Vol. 66(6), pp. 1299-1326. Phillips, P C B (2003), “Laws and Limits of Econometrics”, Economic Journal, Vol. 113(486), pp. C26-C52. Phillips, P C B (2005), “Challenges of Trending Time Series Econometrics”, Mathematics and Computers in Simulation, Vol. 68(5-6), pp. 401-416. Phillips, P C B and Hansen, B E (1990), “Statistical Inference in Instrumental Variables Regression with I(1) Processes”, Review of Economic Studies, Vol. 57(1), pp. 99-125. Phillips, P C B and Ploberger, W (1994), “Posterior Odds Testing for a Unit Root with Data–Based Model Selection”, Econometric Theory, Vol. 10(3-4), pp. 774-808. Ploberger, W and Phillips, P C B (2003), “Empirical Limits for Time Series Econometric Models”, Econometrica, Vol. 71(2), pp. 627-673. Shimotsu, K and Phillips, P C B (2005), “Exact Local Whittle Estimation of Fractional Integration”, Annals of Statistics, Vol. 33(4), pp. 1890-1933. Whittaker, E T (1923), “On a new Method of Graduation”, Proceedings of the Edinburgh Mathematical Association, Vol. 78, pp. 81-89.


Statistical Appendix Table 1: Real GDP Growth by Sector Table 2: Real GDP Growth by Expenditure Table 3: Consumer Price Index Table 4: Labour Market (I) Table 5: Labour Market (II) Table 6: External Trade Table 7: Non-oil Domestic Exports by Selected Countries Table 8: Electronics Leading Index Table 9: Balance of Payments – Current Account Table 10: Balance of Payments – Capital & Financial Accounts Table 11: Exchange Rates Table 12: Singapore Dollar Nominal Effective Exchange Rate Index Table 13: Domestic Liquidity Indicator Table 14: Monetary Table 15: Fiscal


91

TABLE 1: REAL GDP GROWTH by sector

Period Total

Manu-facturing

Financial Services

Business Services

Con- struction

Wholesale & Retail Trade

Hotels & Rest-aurants

Transport

&

Storage

Informa-tion &

Comms Total

Manu-facturing

Financial Services

Business Services

Con- struction

Wholesale & Retail Trade

Hotels & Rest-aurants

Transport

&

Storage

Informa-tion &

Comms

Year-on-Year % Change Seasonally-adjusted Quarter-on-Quarter Annualised % Change

2008 1.8 -4.2 5.7 9.4 20.1 3.1 0.8 2.2 6.1 2009 -1.3 -4.1 1.3 4.5 16.2 -8.2 -1.5 -7.0 1.2

2008 Q1 7.4 12.3 14.6 9.8 8.5 7.7 2.7 4.3 5.7 17.6 74.0 -6.4 7.8 -2.4 24.5 8.3 -0.9 7.5

Q2 2.7 -5.6 7.7 10.8 22.7 6.4 1.4 5.0 6.6 -12.5 -52.3 6.3 11.7 57.7 -2.6 -1.0 5.9 6.3 Q3 0.0 -11.0 3.9 9.6 25.6 3.3 -0.7 2.8 6.8 -3.0 -9.4 -1.9 6.6 29.2 -10.8 -6.1 -3.0 8.5 Q4 -2.5 -10.7 -1.9 7.4 23.2 -4.7 -0.1 -3.2 5.3 -9.0 -12.8 -5.2 3.8 15.4 -24.3 -1.7 -13.9 -1.5

2009 Q1 -8.9 -23.8 -7.6 6.2 25.5 -14.3 -4.0 -10.5 1.8 -11.0 -9.3 -26.2 2.8 5.9 -15.7 -7.3 -27.7 -4.7 Q2 -1.7 -0.4 0.7 4.0 18.1 -11.8 -4.3 -10.1 1.3 18.5 35.4 49.6 3.1 22.9 5.8 -1.2 8.3 3.5 Q3 1.8 7.6 3.5 3.7 11.7 -7.5 0.2 -7.2 -0.1 11.1 23.6 9.5 5.1 3.9 7.8 11.8 10.0 2.3 Q4 3.8 2.2 8.5 4.2 11.5 1.5 2.0 0.1 1.6 -1.0 -27.0 14.6 5.9 13.6 8.8 4.9 16.4 5.3

2010 Q1 16.9 37.9 19.1 6.6 9.7 16.9 7.0 7.9 2.3 45.7 199.1 7.2 12.4 0.5 53.2 13.2 -2.1 -1.2 Q2 18.8 44.5 10.2 6.4 11.5 18.9 10.4 7.6 2.8 24.0 60.1 9.7 2.8 29.2 11.1 12.3 7.0 5.0

Source: Singapore Department of Statistics

TABLE 2: REAL GDP GROWTH by expenditure Year-on-Year % Change

Period Total

Demand

Domestic Demand Exports of Goods

& Services Imports of Goods

& Services Total Consumption Gross Fixed Capital Formation

Total Private Public Total Private Public

2008 6.5 14.7 3.9 2.7 8.4 13.6 13.3 15.6 4.1 9.2 2009 -8.0 -4.9 2.1 0.4 8.2 -3.3 -5.9 17.2 -9.0 -11.0

2008 Q1 12.6 22.9 5.6 5.8 5.0 29.2 34.8 -3.4 9.7 14.8

Q2 9.0 14.7 5.0 5.7 1.3 25.3 25.6 22.8 7.3 12.7 Q3 7.7 17.3 4.2 2.3 12.4 15.3 14.1 25.3 5.1 11.3 Q4 -2.3 5.9 0.7 -2.7 15.4 -9.9 -13.4 23.6 -5.0 -0.9

2009 Q1 -14.6 -5.0 -2.8 -3.1 -1.9 -12.6 -16.7 20.8 -17.6 -15.9 Q2 -11.3 -5.4 0.0 -3.2 17.1 -6.1 -8.5 17.3 -13.1 -15.4 Q3 -6.4 3.0 4.6 2.1 14.3 1.1 -0.4 11.9 -9.1 -9.9 Q4 0.5 -11.4 7.0 6.0 10.9 6.0 4.1 18.6 4.8 -2.6

2010 Q1 17.7 11.4 8.6 5.9 15.3 10.6 9.4 17.8 20.0 16.9 Q2 19.8 9.7 6.4 6.7 5.0 -1.2 -4.3 22.6 23.3 21.1



92

TABLE 3: CONSUMER PRICE INDEX

Period

All Items Food Housing Clothing

& Footwear

Trans-port

Comm-unication

Education &

Stationery

Health Care

Recrea-tion & Others

All Items

Food Housing Clothing

& Footwear

Trans-port

Comm-unication

Education &

Stationery

Health Care

Recrea-tion & Others

2009 = 100 Year-on-Year % Change

2008 99.4 97.7 98.3 99.0 103.2 99.7 99.2 98.0 100.3 6.6 7.7 13.3 1.5 4.2 0.2 3.3 5.6 3.6 2009 100.0 100.0 100.0 99.9 100.0 99.9 100.0 100.0 100.0 0.6 2.3 1.7 0.8 -3.2 0.2 0.8 2.0 -0.3

2008 Q1 96.9 95.6 90.7 99.1 103.9 99.9 99.2 97.0 99.4 6.6 6.7 9.3 2.3 9.4 1.4 3.7 7.3 4.2

Q2 99.1 97.2 96.3 97.8 105.5 99.7 99.6 97.7 100.1 7.5 8.9 12.5 1.2 7.6 0.9 4.8 6.2 4.2 Q3 100.4 98.7 101.1 99.8 103.8 99.6 98.8 98.6 100.4 6.6 8.4 13.3 1.6 3.7 -0.5 2.9 4.7 3.6 Q4 101.2 99.4 105.3 99.4 99.8 99.6 99.0 98.9 101.2 5.8 6.8 17.9 0.8 -3.2 -1.1 1.8 4.2 2.5

2009 Q1 100.2 100.0 102.3 99.4 96.7 100.5 99.8 99.9 100.8 3.4 4.6 12.8 0.3 -7.0 0.6 0.6 3.0 1.4 Q2 99.2 99.8 98.7 98.8 97.8 100.6 99.9 99.7 99.9 0.2 2.6 2.5 1.0 -7.3 0.9 0.3 2.1 -0.1 Q3 100.1 99.9 99.4 100.7 102.2 100.3 100.2 100.1 99.2 -0.3 1.2 -1.6 1.0 -1.6 0.8 1.4 1.5 -1.2 Q4 100.4 100.1 99.6 100.5 103.3 98.3 100.2 100.2 100.0 -0.8 0.8 -5.4 1.1 3.5 -1.3 1.2 1.4 -1.2

2010 Q1 101.1 100.7 100.5 99.4 104.6 97.7 101.7 100.7 100.2 0.9 0.7 -1.7 0.0 8.2 -2.8 1.9 0.8 -0.5 Q2 102.3 101.0 100.9 99.4 110.4 96.9 102.0 101.4 100.8 3.1 1.2 2.2 0.6 12.9 -3.7 2.2 1.7 0.9 Q3 103.4 101.6 102.9 101.1 111.9 98.3 103.3 102.5 101.1 3.4 1.6 3.5 0.4 9.6 -2.0 3.2 2.4 2.0


TABLE 4: LABOUR MARKET (I) Year-on-Year % Change

Period

Average Monthly Earnings

Labour Productivity Unit Labour Cost

All Sectors

Manufacturing Construction Wholesale & Retail Trade


Transport & Storage


Financial Services

Business Services

Overall Economy

Manufacturing

2008 5.4 -7.2 -10.9 -0.8 -1.9 -9.4 -4.9 -1.8 -6.0 -3.9 7.5 13.1 2009 -2.6 -3.9 1.6 3.2 -9.9 -5.0 -7.3 -3.1 -0.6 -0.2 -0.7 -4.6

2008 Q1 10.6 -2.3 2.4 -7.6 2.4 -7.9 -0.6 -3.0 -1.0 -4.2 7.0 -1.7

Q2 3.1 -7.0 -13.3 1.0 0.8 -9.1 -1.8 -1.1 -6.7 -3.5 5.8 16.6 Q3 5.5 -9.0 -17.0 2.2 -1.8 -10.5 -5.9 -1.0 -6.5 -3.9 9.5 21.6 Q4 2.4 -10.4 -14.6 0.9 -8.8 -10.0 -10.8 -2.1 -9.4 -4.2 7.9 18.2

2009 Q1 -3.7 -14.1 -23.5 4.8 -17.0 -11.4 -14.5 -4.5 -12.1 -1.9 9.3 24.4 Q2 -2.2 -4.5 5.7 3.9 -13.4 -8.1 -10.8 -3.7 -0.8 -0.9 -0.3 -10.2 Q3 -3.0 0.6 17.3 1.2 -8.5 -1.3 -5.7 -2.9 3.4 0.8 -5.9 -20.1 Q4 -1.6 2.7 11.1 3.6 0.3 1.2 2.3 -1.2 7.4 1.3 -6.1 -11.5

2010 Q1 3.7 14.4 45.1 4.0 14.8 5.3 9.1 -1.0 12.8 1.6 -7.9 -24.9 Q2 5.8 14.6 46.7 7.1 15.8 5.9 6.9 -3.3 1.5 -0.7 -7.1 -25.8

2 3 2 4 7 6 2 4 7 9 0 6 3 0 1 0 4 2 7 0 1 7 Note: Labour productivity figures are based on SSIC 2005 classification. Source: Singapore Department of Statistics/Central Provident Fund Board


93

TABLE 5: LABOUR MARKET (II) Thousand

Period Changes in Employment

AllSectors

Manufacturing Construction Wholesale & Retail Trade


Transport & Storage


Financial Services

Business Services

Other Services Others

2008 221.6 19.5 64.0 16.4 16.9 13.7 5.7 11.5 36.1 36.1 1.6 2009 37.6 -43.7 25.1 5.9 1.7 -3.8 2.6 3.4 12.8 32.9 0.7

2008 Q1 73.2 11.8 14.5 4.5 3.4 5.7 1.7 3.2 13.3 14.8 0.5

Q2 71.4 10.1 22.4 4.7 2.8 4.7 1.4 4.6 12.9 7.1 0.5 Q3 55.7 4.6 16.5 3.3 4.2 3.7 2.0 3.4 8.6 9.2 0.4 Q4 21.3 -7.0 10.7 4.0 6.4 -0.4 0.6 0.3 1.4 5.1 0.2

2009 Q1 -6.2 -22.1 8.3 -0.8 -2.7 -1.6 0.8 -1.9 2.2 11.5 0.1 Q2 -7.7 -15.9 4.7 -0.9 -2.5 -1.9 0.0 -0.8 2.8 7.1 -0.3 Q3 14.0 -6.4 7.4 1.3 0.4 -0.7 0.8 2.1 2.3 6.4 0.2 Q4 37.5 0.7 4.6 6.2 6.5 0.4 0.9 4.0 5.5 7.9 0.7

2010 Q1 36.5 3.1 -0.4 1.8 -0.1 0.8 1.7 5.5 11.5 12.3 0.4 Q2 24.9 -2.3 2.0 1.8 1.8 2.0 2.6 3.2 8.5 5.4 -0.2

Note: Changes in employment numbers are based on SSIC 2005 classification. Source: Ministry of Manpower

TABLE 6: EXTERNAL TRADE Year-on-Year % Change

Period

Total Trade

Exports

Domestic Exports

Re- exports

Imports

Exports

Domestic Exports

Re- exports

Imports

Total

Oil

Non-oilTotal Oil Non-oil

Total Electronics Non-

electronics At Current Prices At 2006 Prices

2008 9.6 5.8 5.4 41.5 -7.9 -11.6 -5.2 6.2 13.9 3.0 -0.9 8.5 -3.9 7.2 9.6 2009 -19.4 -18.0 -19.2 -34.5 -10.6 -18.0 -5.7 -16.6 -21.0 -10.3 -7.2 -1.5 -9.3 -13.3 -12.7

2008 Q1 16.1 11.5 12.7 52.6 0.6 -4.2 4.1 10.3 21.5 8.6 5.6 4.0 6.1 11.9 14.6

Q2 17.1 13.2 11.2 53.4 -5.5 -7.8 -3.9 15.5 21.4 7.0 -0.6 -3.8 0.6 15.3 12.8 Q3 16.4 11.4 14.5 77.4 -8.6 -14.9 -3.9 8.1 22.2 4.2 0.5 16.0 -4.4 8.1 11.6 Q4 -9.6 -12.0 -15.4 -9.9 -17.7 -18.9 -16.8 -8.1 -7.1 -7.2 -8.6 18.8 -17.0 -5.6 0.5

2009 Q1 -27.7 -27.8 -31.1 -43.1 -25.6 -32.3 -21.3 -24.1 -27.6 -20.3 -19.1 0.6 -25.4 -21.5 -16.7 Q2 -26.9 -25.4 -26.9 -46.3 -14.5 -23.1 -8.8 -23.8 -28.4 -15.4 -10.7 0.1 -14.5 -19.8 -17.7 Q3 -21.4 -20.0 -21.8 -41.5 -7.8 -14.3 -3.5 -17.9 -22.8 -9.7 -5.3 -1.9 -6.6 -14.1 -11.4 Q4 1.2 4.9 7.8 6.9 8.2 -0.2 14.1 1.9 -2.7 5.7 7.6 -4.2 12.8 3.8 -5.0

2010 Q1 26.9 28.2 31.9 56.9 23.1 29.8 19.4 24.5 25.5 22.2 19.7 6.1 25.6 24.8 15.5 Q2 27.8 29.1 33.4 48.0 27.6 34.2 23.9 24.6 26.4 25.6 25.3 15.6 29.2 26.0 21.8 Q3 18.1 20.3 19.3 9.2 23.8 27.1 22.0 21.3 15.7 22.0 19.6 1.7 26.9 24.5 17.5

Source: International Enterprise Singapore


94

TABLE 7: NON-OIL DOMESTIC EXPORTS by selected countries

Period All

Countries

ASEAN NIEs

China

EU

Japan

US Total of which

Total Hong Kong S. Korea Taiwan Indonesia Malaysia Thailand

Year-on-Year % Change

2008 -7.9 -4.1 2.7 -8.8 -12.4 -3.1 0.0 -0.3 -10.9 -2.3 -18.8 -0.3 -22.8 2009 -10.6 -17.5 -19.7 -15.8 -19.6 4.1 4.7 -1.0 7.9 -7.7 -15.3 -20.0 -24.3

2008 Q1 0.6 4.3 0.3 -6.7 5.4 12.2 15.6 18.6 1.1 2.7 -13.3 11.2 -13.6 Q2 -5.5 2.5 6.8 1.4 -8.3 0.6 0.4 4.8 -2.7 1.1 -11.7 -0.9 -21.0 Q3 -8.6 -2.2 11.1 -8.5 -15.2 -2.3 0.9 -0.5 -9.4 1.5 -25.9 -6.6 -29.3 Q4 -17.7 -19.8 -8.1 -20.3 -29.0 -20.1 -14.2 -19.9 -30.5 -13.5 -24.1 -5.0 -27.8

2009 Q1 -25.6 -33.9 -28.9 -28.2 -39.7 -22.1 -17.2 -23.6 -29.6 -14.5 -24.1 -33.7 -42.7 Q2 -14.5 -23.9 -25.8 -23.0 -22.9 -4.3 -4.3 -11.4 2.4 -14.1 -26.0 -28.7 -25.9 Q3 -7.8 -15.2 -22.3 -13.0 -15.0 6.0 5.1 1.9 11.6 -11.7 -11.4 -6.8 -16.8 Q4 8.2 6.7 0.8 2.8 5.3 42.1 38.4 34.4 57.7 11.0 4.5 -7.3 -6.3

2010 Q1 23.1 41.5 54.1 28.8 42.9 64.8 52.6 57.6 99.3 25.3 4.6 28.3 11.2 Q2 27.6 26.1 22.9 26.4 28.3 45.0 42.1 47.8 47.7 42.8 30.5 47.8 23.0 Q3 23.8 10.0 8.5 17.6 11.4 37.2 33.6 38.2 42.9 31.0 52.6 17.4 34.8

% Share of All Countries

2008 100.0 25.1 7.2 9.2 4.6 14.9 7.3 3.7 3.8 10.0 15.3 6.7 12.8 2009 100.0 23.2 6.4 8.6 4.1 17.4 8.6 4.1 4.6 10.4 14.5 6.0 10.8

Source: International Enterprise Singapore

TABLE 8: ELECTRONICS LEADING INDEX

Original Smoothed

Period 1999 = 100 Year-on-Year % Change Quarter-on-Quarter %

Change 1999 = 100 Year-on-Year % Change

Quarter-on-Quarter % Change

2008 65.2 -8.5 65.5 -8.82009 61.5 -5.6 61.5 -6.1

2008Q1 66.5 -10.3 -2.1 66.9 -10.7 -2.4Q2 65.8 -9.2 -1.0 66.2 -9.4 -1.1Q3 64.3 -8.5 -2.4 64.8 -8.7 -2.1Q4 64.0 -5.6 -0.4 64.3 -6.3 -0.8

2009 Q1 58.8 -11.5 -8.1 60.2 -10.1 -6.3Q2 60.3 -8.4 2.5 59.9 -9.4 -0.4Q3 63.4 -1.4 5.0 62.6 -3.4 4.4Q4 63.5 -0.8 0.3 63.4 -1.3 1.3

2010 Q1 63.3 7.6 -0.4 63.3 5.1 -0.2Q2 63.9 5.9 0.9 63.8 6.5 0.9

Source: Monetary Authority of Singapore


95

TABLE 9: BALANCE OF PAYMENTS – Current Account

Current Account Balance Goods Account Services Balance Income Balance

Current Transfers (Net)

S$ Million % of GDP Exports Imports Balance Total Transportation Travel Insurance Government Others

S$ Million

2008 50,673 18.5 483,411 445,985 37,426 19,191 6,764 -6,244 -651 -146 19,468 -1,975 -3,969 2009 47,108 17.8 396,270 352,626 43,644 12,329 6,107 -9,559 -562 -174 16,517 -4,453 -4,413

2008 Q1 12,714 18.8 119,930 109,400 10,531 4,825 1,743 -1,389 -162 -60 4,693 -1,672 -970 Q2 13,528 19.9 126,051 116,614 9,437 4,872 1,411 -1,810 -140 10 5,402 232 -1,013 Q3 14,560 20.8 132,357 120,963 11,393 5,281 1,742 -1,353 -195 -25 5,112 -1,040 -1,073 Q4 9,871 14.5 105,073 99,008 6,065 4,213 1,869 -1,692 -154 -71 4,262 506 -913

2009 Q1 10,253 16.8 86,748 79,641 7,106 3,038 1,447 -1,872 -7 -102 3,572 1,219 -1,110 Q2 11,772 18.3 94,313 83,779 10,534 3,016 1,092 -2,348 -96 14 4,353 -690 -1,089 Q3 11,763 17.1 105,440 93,261 12,179 2,802 1,547 -2,425 -134 -40 3,853 -2,126 -1,092 Q4 13,320 18.8 109,769 95,944 13,825 3,474 2,021 -2,915 -326 -47 4,740 -2,856 -1,123

2010 Q1 12,003 17.0 111,028 99,329 11,699 2,690 994 -1,839 -329 -105 3,971 -1,216 -1,170 Q2 14,942 19.9 121,270 105,640 15,630 2,831 660 -1,843 -215 27 4,202 -2,356 -1,162


TABLE 10: BALANCE OF PAYMENTS – Capital & Financial Accounts S$ Million

Period

Capital &Financial Account Balance

Capital Account (Net)

Financial Account (Net) Net Errors &

Omissions Overall Balance

Official Foreign

Reserves (End of Period)

Total Direct

Investment Portfolio

Investment

Other Investment

Total Banks Others

2008 -34,348 -436 -33,912 27,434 -56,992 -4,354 -13,597 9,243 2,205 18,531 250,346 2009 -29,934 -443 -29,491 15,752 -43,869 -1,374 -8,626 7,252 -718 16,456 263,955

2008 Q1 -1,020 -101 -920 6,068 -11,367 4,379 -5,863 10,242 272 11,965 244,904 Q2 -10,386 -98 -10,289 6,339 -14,599 -2,028 -3,187 1,158 1,149 4,291 240,418 Q3 -17,381 -123 -17,258 4,127 -14,225 -7,160 -2,884 -4,276 679 -2,141 242,230 Q4 -5,560 -115 -5,446 10,900 -16,801 455 -1,664 2,119 106 4,417 250,346

2009 Q1 -15,435 -126 -15,309 2,225 -10,426 -7,108 -5,039 -2,069 1,604 -3,578 253,122 Q2 -11,220 -121 -11,098 4,665 -9,128 -6,635 -19,110 12,475 479 1,031 250,846 Q3 -2,670 -105 -2,566 3,137 -15,253 9,550 4,152 5,399 -2,072 7,021 256,187 Q4 -609 -91 -518 5,724 -9,061 2,819 11,372 -8,553 -729 11,982 263,955

2010 Q1 7,378 -106 7,484 5,097 -5,998 8,385 11,530 -3,146 1,664 21,045 275,749 Q2 490 -118 608 8,685 -7,835 -242 4,106 -4,349 -1,746 13,687 279,829

Source: Singapore Department of Statistics/Monetary Authority of Singapore


96

TABLE 11: EXCHANGE RATES

End of Period

Singapore Dollar Per

USDollar

Pound Sterling

EURO 100 Swiss

Franc 100 Japanese

Yen Malaysian

Ringgit Hong Kong

Dollar 100 New

Taiwan Dollar 100 Korean

Won Australian

Dollar

2008 1.4392 2.0769 2.0258 135.91 1.5924 0.4155 0.1857 4.3887 0.1143 0.9959 2009 1.4034 2.2541 2.0163 135.59 1.5194 0.4097 0.1810 4.3656 0.1204 1.2567

2008 Q1 1.3799 2.7529 2.1807 138.43 1.3814 0.4326 0.1773 4.5375 0.1390 1.2658

Q2 1.3616 2.7142 2.1493 133.65 1.2819 0.4168 0.1745 4.4846 0.1304 1.3101 Q3 1.4314 2.5775 2.0558 130.71 1.3732 0.4140 0.1843 4.4343 0.1178 1.1445 Q4 1.4392 2.0769 2.0258 135.91 1.5924 0.4155 0.1857 4.3887 0.1143 0.9959

2009 Q1 1.5194 2.1771 2.0153 132.72 1.5450 0.4166 0.1960 4.4741 0.1096 1.0463 Q2 1.4498 2.4129 2.0464 134.09 1.5115 0.4116 0.1871 4.4128 0.1134 1.1761 Q3 1.4141 2.2662 2.0674 136.73 1.5752 0.4069 0.1825 4.3963 0.1199 1.2431 Q4 1.4034 2.2541 2.0163 135.59 1.5194 0.4097 0.1810 4.3656 0.1204 1.2567

2010 Q1 1.4028 2.1143 1.8789 131.41 1.5016 0.4285 0.1807 4.4163 0.1238 1.2830 Q2 1.4013 2.1108 1.7113 129.44 1.5822 0.4302 0.1800 4.3546 0.1142 1.1928 Q3 1.3175 2.0872 1.7919 134.80 1.5760 0.4269 0.1698 4.2172 0.1155 1.2748


TABLE 12: SINGAPORE DOLLAR NOMINAL EFFECTIVE EXCHANGE RATE INDEX Index (3 Apr 2009=100)

As at Week Ending

Index As at

Week Ending Index

As atWeek Ending

Index As at

Week Ending Index

As atWeek Ending

Index As at

Week Ending Index

2009 Apr 3 100.00 2009 Jul 3 100.42 2009 Oct 2 100.62 2010 Jan 8 101.40 2010 Apr 1 101.54 2010 Jul 2 102.75 9 99.57 10 99.91 9 101.43 15 101.34 9 101.51 9 103.25

17 100.16 17 100.27 16 101.30 22 101.11 16 102.65 16 103.15 24 100.48 24 100.71 23 101.32 29 101.26 23 103.15 23 103.31 30 100.87 31 100.65 30 101.36 Feb 5 100.59 30 103.60 30 103.64

May 8 101.04 Aug 7 100.48 Nov 6 101.37 12 101.19 May 7 102.53 Aug 6 103.73 15 100.40 14 100.27 13 101.41 19 101.36 14 103.63 13 103.79 22 100.67 21 100.46 20 101.39 26 101.43 21 102.64 20 103.98 29 100.91 28 100.50 26 101.41 Mar 5 101.50 27 103.12 27 104.02

Jun 5 100.54 Sep 4 100.40 Dec 4 101.40 12 101.52 Jun 4 103.41 Sep 3 104.25 12 100.39 11 100.66 11 101.43 19 101.54 11 103.37 9 104.40 19 100.45 18 100.85 18 101.42 26 101.54 18 103.80 17 104.43 26 100.25 25 100.64 24 101.23 25 103.05 24 104.43

31 101.46 Oct 1 104.51 8 04.441



97

TABLE 13: DOMESTIC LIQUIDITY INDICATOR Change from 3 Months Ago

Period Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2007 0.177 0.038 0.044 -0.182 -0.549 -0.666 -0.304 0.192 0.388 0.574 0.642 0.621 2008 0.039 -0.141 -0.107 0.432 0.577 0.593 0.239 -0.326 -0.316 -0.532 -0.317 -0.284 2009 -0.292 -0.233 -0.424 -0.129 0.204 0.242 0.180 -0.042 0.106 0.223 0.292 0.182 2010 0.027 -0.120 -0.063 0.165 0.378 0.344 0.168 0.211 0.333

0 027 0 120 0 063 0 165 0 377 0 343 0 167 0 210 Source: Monetary Authority of Singapore

Note: The DLI is a measure of overall monetary conditions, reflecting changes in the S$NEER and domestic 3-month interbank rate. A positive (negative) number indicates a tightening (easing) monetary policy stance from the previous quarter. Please refer to the June 2001 issue of MAS ED Quarterly Bulletin for more information.

TABLE 14: MONETARY

End of Period

Money Supply Interest Rates

Narrow Money

M1

Broad Money

M2

Broad Money

M3

Reserve Money

Narrow Money

M1

Broad Money

M2

Broad Money

M3

Reserve Money

Prime Lending

Rate

3-month Interbank

Rate

3-month SIBOR (US$)

Banks

Savings Rate

12-month Fixed

Deposit Rate S$ Billion Year-on-Year % Change % Per Annum

2008 75.7 333.4 342.4 34.1 18.4 12.0 11.6 21.6 5.38 1.00 1.44 0.22 0.70 2009 93.5 371.2 378.5 36.3 23.5 11.3 10.6 6.5 5.38 0.69 0.25 0.15 0.53

2008 Q1 68.9 313.3 322.7 28.7 24.2 11.9 12.5 12.6 5.38 1.31 2.72 0.24 0.71

Q2 73.0 315.7 325.1 29.3 22.2 7.5 7.9 10.3 5.38 1.19 2.81 0.23 0.73 Q3 75.6 324.7 333.8 32.5 24.1 10.4 10.3 20.8 5.38 1.88 3.90 0.23 0.73 Q4 75.7 333.4 342.4 34.1 18.4 12.0 11.6 21.6 5.38 1.00 1.44 0.22 0.70

2009 Q1 85.2 349.3 357.9 34.5 23.7 11.5 10.9 19.9 5.38 0.69 1.20 0.20 0.58 Q2 86.7 356.3 364.4 35.2 18.8 12.9 12.1 19.9 5.38 0.69 0.60 0.17 0.54 Q3 91.2 361.4 368.9 35.4 20.6 11.3 10.5 8.8 5.38 0.69 0.30 0.16 0.53 Q4 93.5 371.2 378.5 36.3 23.5 11.3 10.6 6.5 5.38 0.69 0.25 0.15 0.53

2010 Q1 97.0 380.0 387.1 36.3 13.9 8.8 8.2 5.5 5.38 0.69 0.29 0.14 0.51 Q2 104.5 382.5 389.5 37.0 20.5 7.3 6.9 5.3 5.38 0.56 0.54 0.14 0.48



98


TABLE 15: FISCAL

Period

Operating Revenue Expenditure

Primary Surplus (+)/ Deficit (−)

Less:

Special Transfers

Add: Net Investment

Income/ Returns

Contribution

Budget

Surplus (+)/ Deficit (−)

Total

Tax Revenue

Non-tax Revenue

Total

Operating

Development Total

of which

Income Tax

Asset Taxes

Stamp Duty

GST

S$ Million

FY2007 40,375 36,630 16,621 2,582 3,677 6,165 3,744 32,982 25,952 7,030 7,393 2,142 2,405 7,656 FY2008 41,086 37,709 19,286 2,904 1,432 6,487 3,377 38,091 28,734 9,357 2,996 7,099 4,343 239 FY2009 39,547 36,617 17,211 1,987 2,386 6,914 2,930 41,891 30,909 10,982 -2,344 5,481 7,006 -819

FY2010 (Estimated) 40,726 37,567 17,009 2,715 2,676 6,975 3,159 46,371 33,899 12,472 -5,645 5,150 7,835 -2,960 % of Nominal GDP

FY2007 14.8 13.5 6.1 0.9 1.4 2.3 1.4 12.1 9.5 2.6 2.7 0.8 0.9 2.8 FY2008 15.4 14.1 7.2 1.1 0.5 2.4 1.3 14.3 10.8 3.5 1.1 2.7 1.6 0.1 FY2009 14.4 13.3 6.3 0.7 0.9 2.5 1.1 15.3 11.3 4.0 -0.9 2.0 2.6 -0.3

FY2010 (Estimated) 14.7 13.6 6.1 1.0 1.0 2.5 1.1 16.7 12.2 4.5 -2.0 1.9 2.8 -1.1

Source: Ministry of Finance



List of Selected Publications

Title Frequency Web Links

Inflation Monthly Monthly http://www.mas.gov.sg/eco_research/eco_dev_ana/Inflation_ Monthly.html

Monthly Statistical Bulletin Monthly

http://www.mas.gov.sg/data_room/msb/Monthly_Statistical_ Bulletin.html

Recent Economic Developments Quarterly

http://www.mas.gov.sg/eco_research/eco_dev_ana/Recent_ Economic_Developments.html

Survey of Professional Forecasters Quarterly http://www.mas.gov.sg/eco_research/surveys/Survey.html

Macroeconomic Review Semi-annual http://www.mas.gov.sg/publications/macro_review/index.html

Monetary Policy Statements Semi-annual

http://www.mas.gov.sg/eco_research/policy_issues/Monetary_ Policy_Statements.html

Financial Stability Review Annual http://www.mas.gov.sg/publications/MAS_FSR.html

Economics Explorer Occasional

http://www.mas.gov.sg/eco_research/eco_education/Economic_ Explorer_Series.html

Monographs Occasional http://www.mas.gov.sg/publications/monographs/Info_Papers_and_Monographs.html#monographs

Staff Papers Occasional http://www.mas.gov.sg/publications/staff_papers/index.html

Monographs

Title Date Web Links

Tenets of Effective Regulation Jun 2010

http://www.mas.gov.sg/publications/monographs/Tenets_of_Effective_Regulation.html

MAS’ Framework for Impact and Risk Assessment of Financial Institutions Apr 2007

http://www.mas.gov.sg/publications/monographs/Framework_for_ Impact_and_Risk_Assessment_of_Financial_Institutions.html

Monetary Policy Operations in Singapore Apr 2007

http://www.mas.gov.sg/publications/monographs/Monetary_Policy_ Operations_in_Singapore.html

http://www.mas.gov.sg/publications/monographs/Framework_for_Impact_and_Risk_Assessment_of_Financial_Institutions.html






Title Date Web Links

MAS' Roles and Responsibilities in Relation to Securities Clearing and Settlement Systems in Singapore Aug 2004

http://www.mas.gov.sg/publications/monographs/Securities_ Clearing_Settlement_Systems.html

Objectives and Principles of Financial Supervision in Singapore Apr 2004

http://www.mas.gov.sg/publications/monographs/Financial_ Supervision.html

Singapore’s Exchange Rate Policy Feb 2001

http://www.mas.gov.sg/publications/monographs/Singapore_ Exchange_Rate_Policy.html

Staff Papers

Paper No. Date Title

50 Jun 2009 An Empirical Analysis of Exchange Rate Pass-Through in Singapore

49 Dec 2008 Risks and Regulation of Islamic Banks: A Perspective from a Non-Islamic Jurisdiction

48 Nov 2007 Ten Years from the Financial Crisis: Managing the Challenges Posed by Capital Flows

47 Aug 2007 Perspectives on Growth: A Political-Economy Framework

46 Jun 2007 Fertility & The Real Exchange Rate

45 May 2007 A Survey of Recent Discourse on the Global Imbalances

44 Apr 2007 Checking Out: Exit from Currency Unions

43 Apr 2006 Singapore's Exchange Rate-Centered Monetary Policy Regime and Its Relevance for China

42 Dec 2005 China's Rise as a Manufacturing Powerhouse: Implications for Asia

41 Dec 2005 The Welfare Analysis of a Free Trade Zone: Intermediate Goods and the Asian Tigers

40 Sep 2005 Macroeconomic Stability in Developing Countries: How Much is Enough?

39 Jul 2005 Two Decades of Macromodelling at the MAS

38 Dec 2004 Macroeconomic Determinants of Banking Financial Performance and Resilience in Singapore




37 Dec 2004 Managed Floating and Intermediate Exchange Rate Systems: The Singapore Experience

36 Dec 2004 The Long-Run Real Effective Real Exchange Rate of Singapore: A Behavioural Approach

35 Nov 2004 Review of Literature & Empirical Research: Is Board Diversity Important for Corporate Governance and Firm Value?

34 Aug 2004 FSAP Stress Testing: Singapore’s Experience

33 Aug 2004 Singapore’s Balance of Payments, 1965 to 2003: An Analysis

32 Jul 2004 Case Study on Pan-Electric Crisis

31 Jun 2004 Singapore’s Unique Monetary Policy: How Does It Work?

30 May 2004 Using Leading Indicators to Forecast the Singapore Electronics Industry

29 Mar 2004 Review of Literature & Empirical Research on Corporate Governance

28 Feb 2004 Why Has There Been Less Financial Integration In Asia Than In Europe?

27 Feb 2004 Does The WTO Make Trade More Stable?

26 Jan 2004 Education for Growth: The Premium on Education and Work Experience in Singapore

25 Jun 2003 Investigating the Relationship between Exchange Rate Volatility and Macroeconomic Volatility In Singapore

24 Sep 2002 Do We Really Know That The WTO Increases Trade?

23 Sep 2002 Assessing Singapore’s Export Competitiveness Through Dynamic Shift-Share Analysis

22 Aug 2002 The Effect of Common Currencies on International Trade: Where Do We Stand?

21 Dec 2000 Kicking the Habit and Turning Over A New Leaf: Monetary Policy in East Asia After the Currency Crisis

20 May 2000 Financial Market Integration in Singapore: The Narrow and the Broad Views

19 Feb 2000 Exchange Rate Policy in East Asia After The Fall: How Much Have Things Changed?

18 Jan 2000 A Survey of Singapore's Monetary History

17 Nov 1999

Extracting Market Expectations of Future Interest Rates from the Yield Curve: An Application Using Singapore Interbank and Interest Rate Swap Data

16 Sep 1999 Interbank Interest Rate Determination in Singapore and its Linkages to Deposit and Prime Rates

15 Jul 1999 Money, Interest Rates And Income In The Singapore Economy

14 Jun 1999 The Petrochemical Industry in Singapore





13 May 1999 How Well Did the Forward Market Anticipate the Asian Currency Crisis: The Case of Four ASEAN Currencies

12 May 1999 The Term Structure of Interest Rates, Inflationary Expectations and Economic Activity: Some Recent US Evidence

11 Mar 1999 Capital Account and Exchange Rate Management in a Surplus Economy: The Case of Singapore

10 Dec 1998 Measures of Core Inflation for Singapore

9 Oct 1998 Export Competition Among Asian NIEs, 1991-96: An Assessment

8 Oct 1998 The Impact of the Asian Crisis on China: An Assessment

7 Aug 1998 Singapore's Trade Linkages, 1992-96: Trends and Implications

6 May 1998 What Lies Behind Singapore's Real Exchange Rate? An Empirical Analysis of the Purchasing Power Parity Hypothesis

5 May 1998 Singapore’s Services Sector in Perspective: Trends and Outlook

4 Feb 1998 Growth in Singapore's Export Markets, 1991-96: A Shift-Share Analysis

3 Dec 1997 Whither the Renminbi?

2 Aug 1997 Quality of Employment Growth in Singapore: 1983-96

1 Jan 1997 Current Account Deficits in the ASEAN-3: Is there Cause for Concern?

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