Trade Policy, Economic

Performance and Poverty

L Alan Winters Professor of Economics, University of Sussex

Director of UK Trade Policy Observatory

Core readings

• Winters, L .A. (2004) Trade Liberalisation and Economic Performance: An

Overview. The Economic Journal, Vol. 114 (February), pp. F4-F21.

• Winters, L. Alan, Neil McCulloch and Andrew McKay, 2004. Trade

Liberalization and Poverty: The Evidence So Far. Journal of Economic

Literature, Vol. XLII (March), pp. 72-115.

• Winters L A and A Masters (2014) ‘Openness And Growth: Still An Open

Question?’. Journal of International Development, 25(8), 1061-1070, 2014.

• Martuscelli, Antonio and Winters L Alan (2014) ‘Trade Liberalisation and

Poverty: What have we learned in a decade?’, Annual Review of Resource

Economics, vol 6, 2014, DOI: 10.1146/annurev-resource-110713-105054;

also CEPR Discussion Paper No. 9947

http://arjournals.annualreviews.org/eprint/acSwkIAYZ4tni3hWZxPx/full

/10.1146/annurev-resource-110713-105054

• Goldberg, Pinelopi Koujianou; Pavcnik, Nina ‘Distributional Effects of

Globalization in Developing Countries ‘, Journal of Economic Literature,

Volume 45(1) March 2007, pp. 39-82

• Porto, G (2006), "Using Survey Data to Assess the Distributional Effects of

Trade Policy", Journal of International Economics, 70(1): 140-- 2

What is the issue?

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Trade and Growth: Levels vs. Changes

• Income

– Higher vs. growing more rapidly

– Permanent vs. transitory growth effects

Y”

Event

Y

Y’

time

Lo

g (

y)

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Empirical challenges

1. Defining and measuring openness

Binary (Sachs/Warner); (X=M)/GDP

Averages – weights, Anderson-Neary

2. Establishing causation

Liberalisation → growth or vice versa?

3. Separating openness from other policies

the attribution problem

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What have we learned (I) Case studies

• No closed economy has developed post WW2

– Nineteenth century and 1930s low relevance

• Five common features of successful growers:

– Macro stability

– High savings and investment

– Use markets to allocate resources

– Committed, credible, capable government

– Fully exploited world economyGrowth Commission (2008)

6

What have we learned?

(II) Instruments

• Frankel and Romer (AER, 1999) gravity

– Many followers; not always successful

• Noguer and Siscart (2005, JIE)

– More countries in gravity instruments → clarity

• But see Bazzi and Clemens (AEJ-MAC, 2013)

– Strong critique of weak instruments

– Country size is treacherous - little time variance

– Be serious about the exclusion restriction

– This includes GMM and system GMM too!

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Exclusion

• Deaton (2010, JEL)

– instrumentation requires a narrative

• Bazzi and Clemens

– Many studies take the form:

growth = f(x, W); x=g(Z)

– If you estimate: growth = h(y, W*); y=m(Z)

– You strictly have to reject every one of them!

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Other instruments

• Feyrer (2009, NBER WP)

– Time varying instrument for trade

– Importance of difference in sea distance and air distance becomes more significant as air travel cheapens

• Romalis (2007, NBER WP)

– US tariffs (also time varying), but

• Commodity structure;

• Relates trade policy level to output growth

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What have we learned (III) time series

• Mixed results

• Gries, Kraft & Meierrieks (2009, WD)

– GMM

– Individual African economies

– Granger-Hsaio causation

• Wacziarg & Welch (2008, WBER)

– 13 country statistical case studies

• Kneller, Morgan & Kanchanahatakij (‘08, WE)

– Panel of event studies

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What have we learned (IV) Conditions

• Heterogeneity of country studies

• E.g. Chang, Kaltani & Loayza (2009, JDE)

and Bolaky and Freund (JDE, 2008)

– Interactions of openness with

Property

Rights

Financial

Depth

Lab. market

flexibility

Rule of law Education Firm entry

Governance Telecoms Firm exit

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Income, Openness and Regulation(Bolaky-Freund; JDE 2008)

Less regulated half More regulated half

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What have we learned (V) Productivity

• Selectivity

• Imported inputs (Amiti & Koenings (2007,

AER) and AER P&P 2009

• Learning by Exporting (Fernandes & Isgut,

2005, WB; Blalock & Gertler, 2004, JDE)

• Learning to Export (Iacovone, 2009, WB)

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What does this mean for policy?

• Vast majority of growth policy is not trade policy; try to make trade policy simple and unobtrusive

• Treat as decision, not a hypothesis test

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Poverty

Shares in Long-run Poverty Reduction(Kraay, JDE 2006, cross-section)

0% 20% 40% 60% 80% 100%

FGT 0

FGT 1

FGT 2

Watts

Share of poverty reduction

growth sensitivity distribution

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Trade Policy and Poverty – Causal Connections

Trading Domain

Tradables

Pass through, competition

National

Taxes, regulation, distributors, procurement

Regional

Distribution, taxes, regulation, co-ops

Co-operatives, technology, random shocks

Subsis-

tence

World Prices and Quantities

Border Price

Wholesale Price

Tariffs, QRs

Retail Price

Tariff Revenue

Welfare

)

Exchange

Rate

elderly

Household

Welfare Prices, Wages

Endowments,

Profits, Other Income

elderly

young

males

females

Enterprises

Profits Wages

Employment

Tariff Revenue

Taxes

Spending

Conceptual Framework

Winters World Economy (2002)1717

• Do border price shocks get transmitted to poor

households?

• Are markets created or destroyed?

• How well do households respond?

• Do the spillovers benefit the poor?

• Does trade liberalisation increase

vulnerability?

Winters, McCulloch and McKay JEL (2004)

Households and Markets

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Wages and Employment

• Does liberalisation raise wages or employment?

• Is transitional unemployment concentrated on the poor?

Government Revenue and Spending

• Does liberalisation actually cut government revenue?

• Do falling tariff revenues hurt the poor?

1919

Common price vector,

Separability :

– labour-leisure

– labour-use

h h h h

i h i i

u v v

p x p p

Households and Markets

pmvpxvu hhhhhh ,,

2020

, Shepard, Hotellinghhi

i

uq

p

Roy's Indentityh hhi

i h

v vc

p x

log log

net benefit

i hi hih h

i h h

p q cu v

p x x

ve

21

𝜋ℎ

21

-(q-c)

idp

p

dW

ii ii pcqW )(first order approximation of the welfare effect

2222

The Transmission of Border-Price

Shocks

mmw

m trPP )1(int

Pw is the world price

r the exchange rate

tm the proportional tariff or tax and

γm the transaction costs on importables

xxw

x trPP )1(int

2323

• Uses the framework on Mercosur

– Welfare = f(prices, incomes);

– SOE

– traded prices changed by tariffs etc

– Non-traded prices and wages = f(traded prices)

• Estimates based on theory, then simulates

Porto (JIE, 2006)

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Empirical Use of the Framework

• Identity, definition; LHS unobservable

• Observable equivalent Δ(real consumption)

Δrcj = ….. β (Σi wji dlnτi )+ uj

– Second order effects – Omitted variables

– Parameter heterogeneity – Errors of observation

Δrcj = ….. β (exposure) + uj

• Partial studies: pass-through; wage effects, ε25

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Topalova (AEJ-AE, 2010)

• India, 1990s reforms

• Real consumption or poverty rate by region (77)

and district (450)

• Regressed on employment-weighted tariffs and

fixed effects; hence,

– Import-based

– D-i-D – only relative effects

• Greater exposure → worse poverty outcomes

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Refinements

• Standard robustness tests

• Agricultural wages/returns main channel

• Harm is associated with lack of mobility –

regional and sectoral = big issue for the poor

– i.e alternatives to agriculture weakened

• Inflexible labour laws are a key factor

• Export exposure → liberalisation reduces

poverty (Topalova, 2007)

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Some Additional Slides follow

Thank you

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The Widening Skills Gap

When trade may increase the skills premium:

• Initial pattern of protection (Lat Am)

• China has pinned the unskilled wage at very low levels

• Tasks that relocate are relatively unskilled in the North and relatively skilled in the South (Feenstra and Hanson, 1996)

– Outsourcing but not exclusively so

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Complementarity

• Skills and natural resources or capital are complementary

• Liberalisation increases imports of equipment that need skilled labor to work

• Defensive innovation is skill biased –innovation related to size of shock

• Export penetration requires skills (quality higher)

• Intra-sectoral re-allocation – unskilled tasks outsourced (Grossman and Rossi-Hansberg)

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Segmented Labour Markets: Space

• Segmentation seems pretty dominant

• Geographical segmentation – across regions

– Especially for multi-island economies

– Large economies

– Ethnically diverse countries

• Repeats integrated-economy results on smaller

scale

– e.g central highlands of Vietnam and coffee

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• Arguably still more plausible

• Recent boom in research

• Labour as the specific factor

• Workers may share sectoral/firm rents influenced by trade policy; ‘fair wage’ models

• Variation with regional ‘exposure’ to globe:

– Import-competing sectors lose from liberalisation, especially if it reduces regulatory rents

– Export sectors gain

Segmented Labour Markets: Sectors and Firms

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• Heterogeneous firms (Melitz, 2003)

• Exporters more efficient;

– May correlate with use of intermediates (Amiti)

– Liberalisation may increase the gap if it boosts exports

• Heterogeneous workers (within groups)

– Exporters get better workers (Helpman et al)

– Pay better, better at selecting?

• Helps to explain significant inequality withinsectors and occupations

Heterogeneity

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• Egger, Egger, Kreickmeier (Europe)

– exporting firms pay higher wages

• Amiti, Cameron (Indonesia)

– Liberalising imports of intermediates narrows skills premium

• Juhn et al (Mexico in NAFTA)

– Improved market access boosts technology level and so increases relative demand for female workers (brain vs.brawn)

Examples

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Employment

• Sectoral re-allocation vs. unemployment

• Sometimes moves into informality

– especially if labour regulation strict (Goldberg and Pavcnik)

– But informality is not the same as poverty

• Nicita – simulates Madagascar textiles boom

– Identifies workers called to new jobs (out of

informal sector)

– Not always the poor – skills, location,

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