global economics report 2017-04-14

....Global Economics Report

April 14, 2017

Where We Are Now . . . . . . . . . . . . . . . . . . . . . . . 1

Indicators for US Economy . . . . . . . . . . . . . . . . . . . 2

US Economic Heartbeat . . . . . . . . . . . . . . . . . . . . . 4

Global Financial Markets . . . . . . . . . . . . . . . . . . . . 5

US Key Interest Rates . . . . . . . . . . . . . . . . . . . . . . 10

US Inflation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Exchange Rates . . . . . . . . . . . . . . . . . . . . . . . . . . 12

US Banking Indicators . . . . . . . . . . . . . . . . . . . . . . 13

US Employment Indicators . . . . . . . . . . . . . . . . . . . 15

US Business Activity Indicators . . . . . . . . . . . . . . . . 17

S&P 500 Sentiment Analysis . . . . . . . . . . . . . . . . . . 18

US Consumption Indicators . . . . . . . . . . . . . . . . . . 21

US Housing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Global Business Indicators . . . . . . . . . . . . . . . . . . . 24

Global Trade/Export Metrics . . . . . . . . . . . . . . . . . 26

Canadian Indicators . . . . . . . . . . . . . . . . . . . . . . . 27

European Indicators . . . . . . . . . . . . . . . . . . . . . . . 29

Chinese Indicators . . . . . . . . . . . . . . . . . . . . . . . . 31

Global Climate Data . . . . . . . . . . . . . . . . . . . . . . . 32

Where We Are Now

Welcome back to the Global Economics Report. We’ve made a fewchanges to the report – in particular two new features: sentiment anal-ysis (p. 18) and a US economic heartbeat (p. 4). We’ll be making morechanges over the next few months.

Sentiment analysis is a technique that tries to use machine learningto determine the sentiment, positive or negative, of a block of text.In this case, we’re using conference call transcripts for the S&P 500companies. We’re presenting the sentiment of the conference calls (ie.was it an upbeat or downbeat conference call) and plotting that againstoperating earnings for each component. There seems to be a good cor-relation between the two – and as we have much more conference calldata, which is updated more often, this is a good predictor of earningstrends.

The US Economic Heartbeat is a tool for summarizing the positionof the US economy. We’ve been able to get a good monthly dataset

of various measures of the economy and have pulled out the businesscycle component of the data. The tracker shows a consistent patternwhen we are in the midst of a recession – right now the economy feels asthough it could go either way, but when it does break, this tool shouldhelp to identify it as early as possible.

The usual metrics are also presented. One new metric is bank char-geoffs (p. 14) – a measure of bad debts for banks. It is showing a stronguptick in the recent data, which is usually an indicator that somethingis wrong in consumerland.

More to come... and welcome back.Formatting Notes The grey bars on the various charts are OECD

recession indicators for the respective countries.Subscription Info For a FREE subscription to this monthly re-

port, please visit sign up at our website: www.lairdresearch.com

Laird Research, April 14, 2017

http://www.lairdresearch.com/

Indicators for US Economy

Leading indicators are indicators that usually change before theeconomy as a whole changes. They are useful as short-term predictorsof the economy. Our list includes the Philly Fed’s Leading Index whichsummarizes multiple indicators; initial jobless claims and hours worked(both decrease quickly when demand for employee services drops and

vice versa); purchasing manager indicies; trucking indices showing de-mand for transport; new order and housing permit indicies and con-sumer sentiment (how consumers are feeling about their own financialsituation and the economy in general). Red dots are points where anew trend has started.

Leading Index for the US

Inde

x: E

st. 6

mon

th g

row

th

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−2

−1

01

23

median: 1.50Dec 2016: 1.17

Growth

Contraction

Initial Unemployment Claims

1000

's o

f Cla

ims

per

Wee

k

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

200

300

400

500

600

median: 346.62Apr 2017: 247.25

Manufacturing Ave. Weekly Hours Worked

Hou

rs w

orke

d pe

r W

eek

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

3940

4142

4344 median: 40.60

Mar 2017: 41.80

Manfacturing − PMI

Inde

x: S

tead

y S

tate

= 5

0

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

3040

5060

70 median: 52.70Mar 2017: 53.30expanding economy

contracting economy

www.lairdresearch.com April 14, 2017

Leading indicators are indicators that usually change before theeconomy as a whole changes. They are useful as short-term predictorsof the economy. Our list includes the Philly Fed’s Leading Index whichsummarizes multiple indicators; initial jobless claims and hours worked(both decrease quickly when demand for employee services drops and

vice versa); purchasing manager indicies; trucking indices showing de-mand for transport; new order and housing permit indicies and con-sumer sentiment (how consumers are feeling about their own financialsituation and the economy in general). Red dots are points where anew trend has started.

Durable Goods: Manufacturers New Orders

Bill

ions

of D

olla

rs

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

150

200

250

median: 186.49Feb 2017: 235.96

Index of Truck Tonnage

Inde

x

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

100

110

120

130

140

median: 113.50Feb 2017: 138.40

Capex (ex. Defense & Planes)

Bill

ions

of D

olla

rs

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

4050

6070

median: 58.58Feb 2017: 64.74

U. Michigan: Consumer Sentiment

Inde

x 19

66 Q

1 =

100

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

5060

7080

9010

011

0

median: 89.10Mar 2017: 96.90


US Economic Heartbeat

MarketHack Inc. is proud to present our proprietary EconomicHeartbeat index. It uses monthly economic data from 1960 onwardsto create a diffusion index. Each point represents the index value fora given month. Months with a recession are represented by red dots,otherwise they are blue.

The green line is selected to maximize the probability that dots

above the line indicate a recession – especially as it crosses the line.Our current month is shown in Purple at the far right of the series.

The index is based on such as: incomes, employment, industrial pro-duction, prices, housing, orders and inventories and credit/monetarypolicy.

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Good Times

Danger Zone

Rec

essi

on

Recovery

Rec

essi

on

Recovery

Rec

essi

on

Recovery

Rec

essi

on Recovery

Rec

essi

on

Recovery

Rec

essi

on

Recovery

Rec

essi

on

Recovery YOU

AREHERE

Recession monthsNon−recession monthsCurrent month (Jan 2017)


Global Financial Markets

Global Stock Market Returns

Country Index Name Close Date CurrentValue

WeeklyChange

MonthlyChange

3 monthChange

12month

Change

Corr toS&P500

Corr toTSX

North AmericaUSA S&P 500 Apr 13 2,328.9 -1.2% t -1.9% t 2.4% s 11.8% s 1.00 0.66USA NASDAQ Composite Apr 13 5,805.1 -1.3% t -1.2% t 4.1% s 17.3% s 0.89 0.58USA Wilshire 5000 Total Market Apr 13 24,262.6 -1.2% t -1.6% t 1.9% s 13.0% s 0.96 0.66Canada S&P TSX Apr 13 15,535.5 -1.0% t -0.1% t 0.2% s 13.6% s 0.66 1.00Europe and RussiaFrance CAC 40 Apr 13 5,071.1 -1.0% t 1.4% s 3.0% s 12.9% s 0.62 0.53Germany DAX Apr 13 12,109.0 -1.0% t 1.0% s 4.1% s 20.8% s 0.61 0.50Russia Market Vectors Russia ETF Apr 13 20.1 -5.7% t 0.9% s -6.5% t 18.5% s 0.42 0.53AsiaTaiwan TSEC weighted index Apr 13 9,836.7 -0.6% t 1.4% s 4.9% s 13.7% s -0.09 0.01China Shanghai Composite Index Apr 13 3,276.0 -0.2% t 1.2% s 5.2% s 6.8% s 0.06 0.05Japan NIKKEI 225 Apr 13 18,426.8 -0.9% t -6.1% t -4.5% t 12.5% s 0.27 0.28Hong Kong Hang Seng Apr 13 24,261.7 -0.0% t 1.8% s 5.8% s 14.7% s -0.06 0.04Korea Kospi Apr 13 2,148.6 -0.2% t 1.5% s 3.5% s 6.6% s -0.03 -0.07South Asia and AustrailiaIndia Bombay Stock Exchange Apr 13 29,461.4 -1.6% t 0.1% s 8.2% s 15.0% s 0.04 -0.04Indonesia Jakarta Apr 13 5,616.5 -1.1% t 3.8% s 6.5% s 15.7% s -0.13 0.01Malaysia FTSE Bursa Malaysia KLCI Apr 13 1,738.2 -0.1% t 0.9% s 3.9% s 0.9% s 0.03 0.13Australia All Ordinaries Apr 13 5,925.9 0.5% s 2.3% s 2.6% s 15.6% s 0.10 0.16New Zealand NZX 50 Index Gross Apr 13 7,229.8 -0.8% t 0.5% s 2.6% s 6.7% s 0.02 0.09South AmericaBrasil IBOVESPA Apr 13 62,826.0 -2.2% t -4.1% t -1.3% t 18.2% s 0.35 0.49Argentina MERVAL Buenos Aires Apr 12 20,812.2 0.6% s 8.5% s 11.9% s 64.0% s 0.24 0.51Mexico Bolsa index Apr 12 48,955.8 -0.5% t 3.9% s 6.3% s 8.6% s 0.34 0.41MENA and AfricaEgypt Market Vectors Egypt ETF Apr 13 28.3 -1.2% t 1.1% s 3.4% s -27.1% t 0.07 0.14(Gulf States) Market Vectors Gulf States ETF Oct 07 23.0 3.2% s 1.2% s 6.4% s -6.4% t 0.16 0.05South Africa iShares MSCI South Africa Index Apr 13 57.2 5.4% s 0.8% s 3.0% s 8.7% s 0.42 0.44(Africa) Market Vectors Africa ETF Apr 13 21.3 2.0% s 3.5% s 1.2% s 11.7% s 0.31 0.35CommoditiesUSD Spot Oil West Texas Int. Apr 10 $53.1 5.6% s 10.4% s 4.4% s 31.1% s 0.16 0.41USD Gold LME Spot Apr 13 $1,286.1 2.6% s 6.5% s 7.5% s 3.2% s -0.17 -0.14

Note: Correlations are based on daily arithmetic returns for the most recent 100 trading days.


S&P 500 Composite Index

The S&P 500 Composite Index is widely regarded as the best singlegauge of the large cap U.S. equities market. A key figure is the valua-tion level of the S&P500 as measured by the Price/Earnings ratio. Wepresent two versions: (1) a 12-month trailing earnings version which

reflects current earnings but is skewed by short term variances and (2)a cyclically adjusted version which looks at the inflation adjusted earn-ings over a 10 year period (i.e. at least one business cycle). Forecastedearnings numbers are estimates provided by S&P.

S&P 500 Profit Margins and Overall Corporate Profit Margins (Trailing 12 months)

Per

cent

63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

02468

101214

02468101214

Per

cent

Total Corporate Profits (% of GDP) − median: 6.2%, Q4/16: 9.2%Net Profit Margin (S&P 500 Earnings / Revenue) − median: 6.7%, Q4/16: 8.2%

S&P Quarterly Earnings (USD$ Inflation Adjusted to current prices)

63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18E

stim

ates

−5.00 0.00 5.0010.0015.0020.0025.0030.0035.0040.0045.00

−5.00 0.00 5.0010.0015.0020.0025.0030.0035.0040.0045.00

Tech BubbleJapanese Asset Bubble

House BubbleAsian Financial Crisis

US Financial Crisis

Eurozone crisis

Oil Crisis I Oil Crisis II

Gulf WarSavings and Loans Crisis

High Inflation Period

Afganistan/Iraq WarVietnam War

Reported EarningsOperating Earnings

Trailing P/E Ratios for S&P500

63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

0

10

20

30

40

50

0

10

20

30

40

50

Mul

tiple

Mul

tiple

12−month trailing P/E ( median = 17.5, Apr = 23.2)10−year CAPE ( median = 19.7, Apr = 28.6)


S&P 500 Composite Distributions

This is a view of the price performance of the S&P 500 companies.The area of each box is proportional to the market cap, while the colour

is determined by the percentage change in value over the past month.Companies are sorted according to their industry group.

AAPL+0.9%

GOOG−1.4%

MSFT+0.015%

FB+1.4%

V−0.13%

ORCL+3%

INTC−1.9%

CSCO−5%

IBM−6.8%

MA AVGO

QCOM

TXN ACN

ADBE NFLX

CRM

NVDA

ADP

CTSH

HPQ

HPE

MU

EA

FIS

GLW APH

RHT

STX

ADS

CA

IT

BRK−B−8.1%

JPM−9.3%

WFC−14%

BAC−12%

C−5.7%

GS USB

MS−13%

AXP

CB

BLK

AIG

MET

PNC

BK PRU

CME COF

MMC

BBT TRV

SPGI AON

STT ALL

AFL

SYFSTI

MCO

AMP

RF

L

IVZ

AJG

JNJ+0.91%

PFE−1.6%

MRK−4.8%

UNH−1.4%

AMGN−9.3%

MDT−2%

ABBV

CELG LLY BMY

GILD−4.5%

AGN−3%

ABT

TMO

DHR

BIIB

SYK

AET

ANTM

BDX

CI

BSX

ZBH

MYL

EW

ABC

BCRA

LH

WAT

MTD

CNC

AMZN+3.7%

DIS+1.9%

CMCSA

HD+0.08%

MCD

NKE

CHTR+1.5%

PCLN+0.32%

TWX

LOW

FOX

GM

TJX

F

CCL

MAR

TGT CBS

ROST

ORLY

YUM

NWL

OMC

DG

VIAB

LB

DHI

DRI

M

HBI

PG−1.8%

WMT+4.6%

KO+2.4%

PM+3.5%

PEP+2.7%

MO−4.9%

KHC RAI

WBA

CVS COST

MDLZ CL

KMB

STZ

GIS EL

KR

MNST

K

TSN

HSY

TAP

CPB

CLX

GE−2.1%

MMM

BA−4.5%

HON−3.7%

UPS UTX

UNP

LMT GD

CAT FDX

ITW RTN CSX

NOC JCI

DE

LUV

ETN

DAL

WMCMI

PCAR

IR ROP

PH

ROK

AYI

XOM−1.6%

CVX−6.8%

SLB−5%

COP

EOG

OXY

KMI

HAL

PSXPXD

VLO

BHI

NEE

DUK

SO

D

PCG EXC AEP

EIX PPL

ED

SPG

AMT

PSA

CCI

PLD

EQIX

WY

AVB

VTR

BXP O

KIM

DOW DD

ECL LYB PX

PPG

IP

VMC

MLM

BLL

IFF

T−3%

VZ−1.2%

LVLT CTL

Information Technology Financials

Health Care

ConsumerDiscretionary

ConsumerStaples

Industrials

Energy Utilities

Real Estate

MaterialsTelecommunication

Services

<−25.0% −20.0% −15.0% −10.0% −5.0% 0.0% 5.0% 10.0% 15.0% 20.0% >25.0%

% Change in Price from Mar 1, 2017 to Apr 13, 2017

Average Median Median MedianSector Change P/Sales P/Book P/EUtilities 1.5% s 2.2 2.0 21.6Real Estate 0.7% s 8.7 2.8 31.2Consumer Staples 0.0% s 2.6 4.8 25.0Consumer Discretionary -0.2% t 1.6 3.7 18.7Information Technology -0.9% t 3.7 5.0 26.4Health Care -1.7% t 3.7 4.0 27.3

Average Median Median MedianSector Change P/Sales P/Book P/ETelecommunication Services -1.8% t 1.5 2.0 20.5Materials -3.2% t 1.9 4.1 26.5Industrials -3.7% t 1.8 4.2 23.4Energy -3.8% t 3.4 2.0 22.6Financials -8.7% t 2.9 1.5 16.3


US Equity Valuations

A key valuation metric is Tobin’s q: the ratio between the marketvalue of the entire US stock market versus US net assets at replacementcost (ie. what you pay versus what you get). Warren Buffet famouslyfollows stock market value as a percentage of GNP, which is highly(93%) correlated to Tobin’s q.

We can also take the reverse approach: assume the market hasvaluations correct, we can determine the required returns of future es-

timated earnings. These are quoted for both debt (using BBB ratedsecurities as a proxy) and equity premiums above the risk free rate (10year US Treasuries). These figures are alternate approaches to under-standing the current market sentiment - higher premiums indicate ademand for greater returns for the same price and show the level ofrisk-aversion in the market.

Tobin's q (Market Equity / Market Net Worth) and S&P500 Price/Sales

63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

0.25

0.50

0.75

1.00

1.25

1.50

1.75

0.25

0.50

0.75

1.00

1.25

1.50

1.75

Buying assets at a discount

Paying up for growth

Tobin Q (median = 0.77, Dec = 1.00)S&P 500 Price/Sales (median = 1.37, Dec = 1.95)

Equity and Debt Risk Premiums: Spread vs. Risk Free Rate (10−year US Treasury)

63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%Implied Equity Premium (median = 4.1%, Apr = 4.5%)Debt (BBB) Premium (median = 1.6%, Apr = 1.4%)Debt (BAA) Premium [Discontinued Series]


US Mutual Fund Flows

Fund flows describe the net investments in equity and bond mutualfunds as well as ETF’s in the US market, as described in ICI’s “Trendsin Mutual Fund Investing” report. Previously we just looked at mutual

fund flows, but with the global trend to ETF’s, this only presented apartial picture.

US Net New Investment Cash Flow to Mutual Funds & ETFs

US

$ bi

llion

s (m

onth

ly)

2014 2015 2016 2017

−40

−20

020

40

Domestic EquityWorld EquityTaxable BondsMunicipal Bonds

US Net New Investment Cash Flow to Mutual Funds & ETFs

US

$ bi

llion

s (M

onth

ly)

2014 2015 2016 2017

−60

−40

−20

020

4060

Flows to EquityFlows to BondsNet Market Flows


US Key Interest Rates

Interest rates are often leading indicators of stress in the financialsystem. The yield curve show the time structure of interest rates ongovernment bonds - Usually the longer the time the loan is outstanding,the higher the rate charged. However if a recession is expected, thenthe fed cuts rates and this relationship is inverted - leading to negativespreads where short term rates are higher than long term rates.

Almost every recession in the past century has been preceeded by an

inversion - though not every inversion preceeds a recession (just mostof the time).

For corporate bonds, the key issue is the spread between bond rates(i.e. AAA vs BBB bonds) or between government loans (LIBOR vsFedfunds - the infamous “TED Spread”). Here a spike correlates to anaversion to risk, which is an indication that something bad is happen-ing.

US Treasury Yield Curves

For

war

d In

stan

tane

ous

Rat

es (

%)

16 17 18 19 20 21 22 23 24 25 26 27

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.0

0.5

1.0

1.5

2.0

2.5

3.0Apr 12, 2017 (Today)Mar 13, 2017 (1 mo ago)Jan 12, 2017 (3 mo ago)12 Apr 2016 (1 yr ago)

3 Month & 10 Yr Treasury Yields

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

0%

1%

2%

3%

4%

5%

6%

7%

0%

1%

2%

3%

4%

5%

6%

7%10 Yr Treasury3 Mo TreasurySpread

AAA vs. BBB Bond Spreads

2%3%4%5%6%7%8%9%

10%

2%3%4%5%6%7%8%9%10%

Per

cent

AAABBB

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

median: 112.00Apr 2017: 66.00

0100200300400

0100200300400

Spr

ead

(bps

)

LIBOR vs. Fedfunds Rate

0%

1%

2%

3%

4%

5%

6%

7%

0%

1%

2%

3%

4%

5%

6%

7%

Per

cent

3 mos t−billLIBOR

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

median: 36.61Apr 2017: 34.54

0100200300

0100200300

Spr

ead

(bps

)


US Inflation

Generally, the US Fed tries to anchor long run inflation expectationsto approximately 2%. Inflation can be measured with the ConsumerPrice Index (CPI) or the Personal Consumption Expenditures (PCE)index.

In both cases, it makes sense to exclude items that vary quickly likeFood and Energy to get a clearer picture of inflation (usually called

Core Inflation). The Fed seems to think PCI more accurately reflectsthe entire basket of goods and services that households purchase.

Finally, we can make a reasonable estimate of future inflation ex-pectations by comparing real return and normal bonds to construct animputed forward inflation expectation. The 5y5y chart shows expected5 year inflation rates at a point 5 years in the future. Neat trick that.

Consumer Price Index

Per

cent

84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

−1%

0%

1%

2%

3%

4%

5%

6%

−1%

0%

1%

2%

3%

4%

5%

6%

US Inflation Rate YoY% (Aug = 1.1%)US Inflation ex Food & Energy YoY% (Aug = 2.3%)

Personal Consumption Expenditures

Per

cent

(Ye

ar o

ver

Year

)

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−1

01

23

45

6

PCE Inflation Rate YoY% (Aug = 0.96%)PCE Core Inflation YoY% (Aug = 1.7%)

5−Year, 5−Year Forward Inflation Expectation Rate

Per

cent

07 08 09 10 11 12 13 14 15 16 17 18 19 20 21

−1

01

23

45

6

5 year forward Inflation ExpectationActual 5yr Inflation (CPI measure)Actual 5yr Inflation (PCE Measure)


Exchange Rates

10 Week Moving Average CAD Exchange Rates

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

0.62

0.71

0.81

0.90

1.00

1.09

US

A /

CA

D

0.55

0.61

0.66

0.72

0.77

0.82

Eur

o / C

AD

59.

16 7

4.71

90.

2610

5.81

121.

3613

6.91

Japa

n / C

AD

0.38

0.44

0.49

0.55

0.61

0.67

U.K

. / C

AD

0.59

1.10

1.60

2.11

2.61

3.12

Bra

zil /

CA

D

CAD Appreciating

CAD Depreciating

Change in F/X: Aug 1 2016 to Sep 30 2016(Trade Weighted Currency Index of USD Trading Partners)

−3.0%

−1.5%

1.5%

3.0%

Euro−0.7%

UK 1.3%

Japan−1.2%

South Korea−0.9%

China 0.2%

India−0.3%

Brazil−0.8%

Mexico 2.5%

Canada−0.0%

USA 0.2%

Country vs. Average

AppreciatingDepreciating

% Change over 3 months vs. Canada

<−10.0% −8.0% −6.0% −4.0% −2.0% 0.0% 2.0% 4.0% 6.0% 8.0% >10.0%

CAD depreciatingCAD appreciating

ARG−5.4%

AUS 4.4%

BRA 7.6%

CHN 1.6%

IND 3.9%

RUS 2.4%

USA 3.0%

EUR1.6%

JPY6.0%

KRW6.9%

MXN−3.1%

ZAR10.3%


US Banking Indicators

The banking and finance industry is a key indicator of the healthof the US economy. It provides crucial liquidity to the economy in theform of credit, and the breakdown of that system is one of the exac-erbating factors of the 2008 recession. Key figures to track are the

Net Interest Margins which determine profitability (ie. the differencebetween what a bank pays to depositors versus what the bank is paidby creditors), along with levels of non-performing loans (i.e. loan lossreserves and actual deliquency rates).

US Banks Net Interest Margin

3.0

3.5

4.0

4.5

median: 3.93Oct 2016: 3.05

Repos Outstanding with Fed. Reserve

Bill

ions

of D

olla

rs

020

040

060

0

median: 62.03Apr 2017: 357.43

Bank ROE − Assets between $300M−$1B

Per

cent

05

1015

median: 12.68Oct 2016: 9.93

Consumer Credit Outstanding

% Y

early

Cha

nge

−5

05

1015

20

median: 7.41Feb 2017: 6.31

Total Business Loans%

Yea

rly C

hang

e

−20

010

20median: 8.63Feb 2017: 5.39

US Nonperforming Loans

12

34

5

median: 1.95Oct 2016: 1.39

St. Louis Financial Stress Index

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−1

12

34

5 median: −0.001Apr 2017: −1.37

Commercial Paper Outstanding

Trill

ions

of D

olla

rs

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1.0

1.4

1.8

2.2

median: 1.31Apr 2017: 0.98

Residential Morgage Delinquency Rate

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

24

68

10

median: 2.36Oct 2016: 4.15


US Charge-Off Indication

A “charge-off” is an accounting declaration by a creditor that aparticular debt is unlikely to be collected, either in whole or in part.Usually, the creditor is severely delinquent by the time this determina-tion is made. For credit card debt, as an example, this determinationis usually made by the bank after six months without payment.

However, there are charge-offs for a number of different kinds of

loans and increasing charge-offs are an important barometer of thehealth of creditors. In this graph, the various charge-offs are presentedas a percentage of total relevant debt outstanding. For example, creditcard charge-offs as a percentage of total credit card debt owed by con-sumers.

Charge−off Rates for Various Categories (Seasonally Adjusted)

85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

Per

cent

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

3.56%

2.12%

0.47%0.39%0.07%0.01%

Credit Card Loans − All Commercial Banks (median: 4.25%, last: 3.56%)Consumer Loans − All Commercial Banks (median: 2.26%, last: 2.12%)All Loans − All Commercial Banks (median: 0.80%, last: 0.47%)Commercial and Industrial Loans (median: 0.66%, last: 0.39%)Single Family Residential Mortgages (median: 0.17%, last: 0.07%)Commercial Real Estate Loans (Ex− Farmland) (median: 0.16%, last: 0.01%)


US Employment Indicators

Unemployment rates are considered the “single best indicator ofcurrent labour conditions” by the Fed. The pace of payroll growth ishighly correlated with a number of economic indicators.Payroll changesare another way to track the change in unemployment rate.

Unemployment only captures the percentage of people who are inthe labour market who don’t currently have a job - another measure

is what percentage of the whole population wants a job (employed ornot) - this is the Participation Rate.

The Beveridge Curve measures labour market efficiency by lookingat the relationship between job openings and the unemployment rate.The curve slopes downward reflecting that higher rates of unemploy-ment occur coincidentally with lower levels of job vacancies.

Unemployment Rate

Per

cent

79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

median: 6.10Mar 2017: 4.504

56789

1011

4567891011

Per

cent

Beveridge Curve

Unemployment Rate

Hel

p W

ante

d In

dex

3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 11.0

30

40

50

60

70

80

90

100

1101950's1960's1970's1980's1990's2000's2010's

Participation Rate

Per

cent

of P

op.

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

6364

6566

67

median: 66.00Mar 2017: 63.00

Total Nonfarm Payroll Change

Mon

thly

Cha

nge

(000

s)

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−50

00

500

median: 164Mar 2017: 98


There are a number of other ways to measure the health of employ-ment. The U6 Rate includes people who are part time that want afull-time job - they are employed but under-utilitized. Temporary helpdemand is another indicator of labour market tightness or slack.

The large chart shows changes in private industry employment lev-els over the past year, versus how well those job segments typically pay.Lots of hiring in low paying jobs at the expense of higher paying jobsis generally bad, though perhaps not unsurprising in a recovery.

Median Duration of Unemployment

Wee

ks

510

1520

25 median: 8.90Mar 2017: 10.30

(U6) Unemployed + PT + Marginally Attached

Per

cent

810

1214

16

median: 9.70Mar 2017: 8.90

4−week moving average of Initial Claims

Jan

1995

= 1

00

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

5010

015

020

0

median: 106.57Apr 2017: 76.02

Unemployed over 27 weeks

Mill

ions

of P

erso

ns

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

01

23

45

67

median: 0.82Mar 2017: 1.76

Services: Temp Help

Mill

ions

of P

erso

ns

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1.5

2.0

2.5

3.0

median: 2.29Mar 2017: 3.00

0 200 400 600

15

20

25

30

35

40

Annual Change in Employment Levels (000s of Workers)

Ave

rage

wag

es (

$/ho

ur)

Private Industry Employment Change (Mar 2016 − Mar 2017)

ConstructionDurable Goods

Education

Financial Activities

Health Services

Information

Leisure and Hospitality

Manufacturing

Mining and Logging

Nondurable GoodsOther Services

Professional &Business Services

Retail Trade

Transportation

Utilities

Wholesale Trade

Circle size relative to total employees in industry


US Business Activity Indicators

Business activity is split between manufacturing activity and non-manufacturing activity. We are focusing on forward looking business

indicators like new order and inventory levels to give a sense of thecurrent business environment.

Manufacturing: Real Output

YoY

Per

cent

Cha

nge

−10

010

20

median: 7.87Oct 2016: 3.26

Manufacturing − PMI

3540

4550

5560

Mar 2017: 53.30

manufac. expanding

manufac. contracting

Manufacturers' Durable Goods Orders

Bill

ions

of D

olla

rs

150

200

250

Feb 2017: 235.96

Increase in new orders

Decrease in new orders

Non−Manufac. New Orders: Capital Goods

Bill

ions

of D

olla

rs

4050

6070

median: 58.58Feb 2017: 64.74

Average Weekly Hours: Manufacturing

3940

4142

43

median: 41.20Mar 2017: 41.80

Industrial Production: Manufacturing

YoY

Per

cent

Cha

nge

−15

−5

05

10

median: 2.86Feb 2017: 1.50

Inventory to Sales Ratio

Rat

io

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1.1

1.2

1.3

1.4

1.5

1.6

median: 1.37Jan 2017: 1.35

Chicago Fed: Sales, Orders & Inventory

Inde

x

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−0.

50.

00.

5 Feb 2017: 0.08Above ave growth

Below ave growth

Freight Index

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

9510

511

512

5

Feb 2017: 126.40


S&P 500 Sentiment Analysis

Sentiment analysis tries to determine the attitude of a speaker withrespect to some topic or the overall contextual polarity of a document.In this particular case, we are evaluating earnings conference calls forthe S&P 500 companies over the past 10 years.

We use a proprietary sentiment mining model to determine the“sen-timent” from the transcripts of 17,948 conference calls. The object is

to understand how the communication from executives on those con-ference calls changes over time.

The model focuses on “relative sentiment” – the tone relative to thearbitrary date of January 2012. While it is not an exact science, themodels do capture the significant negative sentiment in 2007-2008 andthe subsequent recovery.

−15

00−

500

050

015

00

Normalized Sentiment (Based on 17,948 Earnings Calls)

Sen

timen

t Val

ue (

Inde

x Ja

n 20

12 =

0)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

CDCD: +941

CS

CS: +853

En

En: +662

Fin

Fin: +688

HC HC: +348

Ind

Ind: +759

IT

IT: +715

Mat

Mat: +906

RE

RE: +801

Tel

Tel: +1101

UtUt: +730

(CD) Consumer Discretionary(CS) Consumer Staples(En) Energy(Fin) Financials(HC) Health Care(Ind) Industrials

(IT) Information Technology(Mat) Materials(RE) Real Estate(Tel) Telecommunications Services(Ut) UtilitiesS&P 500

Sentiment Increasing

Sentiment Decreasing

−10

00

100

200

Month over Month Sentiment Change − Apr 2017

+72+49

+88 +98

+5

+162

+69+23

+103 +98

+2

ConsumerDiscretionary

ConsumerStaples Energy Financials

HealthCare Industrials

InformationTechnology Materials

RealEstate

TelecommunicationsServices Utilities


S&P 500 Sentiment (n = 17,948)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$−1.00$0.00

$4.00

$9.00

$14.00

$19.00

$24.00

$29.00

$34.00

$39.00



Sentiment (LHS)Operating Earnings (RHS)S&P Estimates (RHS)

Consumer Discretionary (n = 2,985)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$0.00

$1.00

$3.00

$5.00

$7.00

$9.00

$11.00




Consumer Staples (n = 1,345)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$5.00

$7.00




Energy (n = 1,326)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$−9.00

$−4.00

$0.00$1.00

$6.00

$11.00

$16.00

$21.00




Financials (n = 2,169)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$−14.00

$−9.00

$−4.00

$0.00$1.00

$6.00




Health Care (n = 2,233)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$7.00

$9.00

$11.00

$13.00

$15.00





Industrials (n = 2,318)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$3.00

$5.00

$7.00

$9.00




Information Technology (n = 2,435)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$4.00

$6.00

$8.00

$10.00

$12.00

$14.00

$16.00




Materials (n = 916)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$−3.00

$−1.00

$0.00

$1.00

$3.00

$5.00




Real Estate (n = 990)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$−1.00

$−0.50

$0.00

$0.50

$1.00

$1.50

$2.00

$2.50




Telecommunications Services (n = 252)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$−3.00

$−1.00

$0.00

$1.00

$3.00

$5.00




Utilities (n = 979)

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

−1500

−1000

−500

0

500

1000

1500

2000

$0.00

$2.00

$4.00





US Consumption Indicators

Variations in consumer activity are a leading indicator of thestrength of the economy. We track consumer sentiment (their expec-

tations about the future), consumer loan activity (indicator of newpurchase activity), and new orders and sales of consumer goods.

U. Michigan: Consumer Sentiment

Inde

x 19

66 Q

1 =

100

5060

7080

9011

0

median: 89.10Mar 2017: 96.90

Consumer Loans (All banks)

YoY

% C

hang

e

−10

010

2030

40

median: 7.63Feb 2017: 6.92

AccountingChange

Deliquency Rate on Consumer Loans

Per

cent

age

2.0

3.0

4.0

median: 3.42Oct 2016: 2.15

New Orders: Durable Consumer Goods

YoY

% C

hang

e

−20

020

median: 4.35Feb 2017: −4.20

New Orders: Non−durable Consumer Goods

YoY

% C

hang

e

−20

010

20

median: 3.75Feb 2017: 13.36

Personal Consumption & Housing Index

Inde

x

−0.

40.

00.

20.

4

median: 0.02Feb 2017: −0.03above ave growth

below ave growth

Light Cars and Trucks Sales

Mill

ions

of U

nits

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1012

1416

1820

22

median: 14.91Mar 2017: 16.53

Personal Saving Rate

Per

cent

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

24

68

10

median: 5.70Feb 2017: 5.60

Retail Food and Service Sales

YoY

% C

hang

e (R

eal)

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−10

−5

05

median: 2.45Feb 2017: 2.79


US Housing

Housing construction is only about 5-8% of the US economy, how-ever a house is typically the largest asset owned by a household. Sincepersonal consumption is about 70% of the US economy and house val-ues directly impact household wealth, housing is an important indicatorin the health of the overall economy. In particular, housing investment

was an important driver of the economy getting out of the last fewrecessions (though not this one so far). Here we track housing pricesand especially indicators which show the current state of the housingmarket.

15 20 25 30 35 40

150

200

250

300

Personal Income vs. Housing Prices (Inflation adjusted values)

New

Hom

e P

rice

(000

's)

Disposable Income Per Capita (000's)

February 2017

r2 : 89.9%Range: Jan 1962 − Feb 2017Blue dots > +5% change in next yearRed dots < −5% change in next year

New Housing Units Permits Authorized

Mill

ions

of U

nits

0.5

1.0

1.5

2.0

2.5

median: 1.33Feb 2017: 1.22

New Home Median Sale Price

Sal

e P

rice

$000

's

100

200

300

Feb 2017: 296.20

Homeowner's Equity Level

Per

cent

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

4050

6070

80 median: 66.50Oct 2016: 57.80

New Homes: Median Months on the Market

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

46

810

1214 median: 4.90

Feb 2017: 3.40

US Monthly Supply of Homes

Mon

ths

Sup

ply

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

46

810

12 median: 5.80Feb 2017: 5.40


US Housing - FHFA Quarterly Index

The Federal Housing Finance Agency provides a quarterly surveyon house prices, based on sales prices and appraisal data. This gener-ates a housing index for 355 municipal areas in the US from 1979 topresent. We have provided an alternative view of this data looking atthe change in prices from the peak in the 2007 time frame.

The goal is to provide a sense of where the housing markets are

weak versus strong.The colours represent gain or losses since the startof the housing crisis (defined as the maximum price between 2007-2009for each city). The circled dots are the cities in the survey, while thebackground colours are interpolated from these points using a loesssmoother.

Change from 2007 Peak − Q2 2016

−50%

−40%

−30%

−20%

−10%

0%

10%

20%

30%

40%

50%

Today's Home Prices

Percentage Change from 2007−2009 Peak

Fre

quen

cy

−75% −50% −25% 0% 25% 50% 75%

Year over Year Change − Q2 2016

−10%

−8%

−6%

−4%

−2%

0%

2%

4%

6%

8%

10%

YoY Change in this quarter

YoY Percent Change

Fre

quen

cy

−15% −10% −5% 0% 5% 10% 15%


Global Business Indicators

Global Manufacturing PMI Reports

The Purchasing Managers’ Index (PMI) is an indicator reflectingpurchasing managers’ acquisition of goods and services. An index read-ing of 50.0 means that business conditions are unchanged, a numberover 50.0 indicates an improvement while anything below 50.0 suggests

a decline. The further away from 50.0 the index is, the stronger thechange over the month. The chart at the bottom shows a moving av-erage of a number of PMI’s, along with standard deviation bands toshow a global average.

Global M−PMI − March 2017

<40.0 42.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0 >60.0

Steady ExpandingContracting

Eurozone56.2

Global PMI53.0

TWN56.2MEX

51.5

KOR48.4

JPN52.4

VNM54.6

IDN50.5

ZAF50.7

AUS57.5

BRA49.6

CAN55.5

CHN51.2

IND52.5

RUS52.4

SAU56.4

USA53.3

Global M−PMI Monthly Change

<−5.0 −4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 4.0 >5.0

PMI Change ImprovingDeteriorating

Eurozone0.8

Global PMI0.0

TWN1.7MEX

0.9

KOR−0.8

JPN−0.9

VNM0.4

IDN1.2

ZAF0.2

AUS−1.8

BRA 2.7

CAN 0.8

CHN−0.5

IND 1.8

RUS−0.1

SAU−0.6

USA−0.9

Purchase Managers Index (Manufacturing) − China, Japan, USA, Canada, France, Germany, Italy, UK, Australia

03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

3040

5060

70

3040

5060

70

Business Conditions Contracting

Business Conditions Expanding


Global Manufacturing PMI Chart

This is an alternate view of the global PMI reports. Here, we lookat all the various PMI data series in a single chart and watch theirevolution over time.

Red numbers indicate contraction (as estimated by PMI) whilegreen numbers indicate expansion.

Mar

15

Apr

15

May

15

Jun

15

Jul 1

5

Aug

15

Sep

15

Oct

15

Nov

15

Dec

15

Jan

16

Feb

16

Mar

16

Apr

16

May

16

Jun

16

Jul 1

6

Aug

16

Sep

16

Oct

16

Nov

16

Dec

16

Jan

17

Feb

17

Mar

17

Australia

India

Indonesia

Viet Nam

Taiwan

China

South Korea

Japan

South Africa

Saudi Arabia

Turkey

Russia

UK

Greece

Germany

France

Italy

Czech Republic

Spain

Poland

Ireland

Netherlands

Eurozone

Brazil

Mexico

Canada

USA

Global PMI 51.7 51.0 51.2 51.0 51.0 50.7 50.7 51.3 51.2 50.7 50.9 50.0 50.6 50.1 50.0 50.4 51.0 50.8 51.0 52.0 52.1 52.7 52.7 53.0 53.0

55.7 54.1 54.0 53.6 53.8 53.0 53.1 54.1 52.8 51.2 52.4 51.3 51.5 50.8 50.7 51.3 52.9 52.0 51.5 53.4 54.1 54.3 55.0 54.2 53.3

48.9 49.0 49.8 51.3 50.8 49.4 48.6 48.0 48.6 47.5 49.3 49.4 51.5 52.2 52.1 51.8 51.9 51.1 50.3 51.1 51.5 51.8 53.5 54.7 55.5

53.8 53.8 53.3 52.0 52.9 52.4 52.1 53.0 53.0 52.4 52.2 53.1 53.2 52.4 53.6 51.1 50.6 50.9 51.9 51.8 51.1 50.2 50.8 50.6 51.5

46.2 46.0 45.9 46.5 47.2 45.8 47.0 44.1 43.8 45.6 47.4 44.5 46.0 42.6 41.6 43.2 46.0 45.7 46.0 46.3 46.2 45.2 44.0 46.9 49.6

52.2 52.0 52.2 52.5 52.4 52.3 52.0 52.3 52.8 53.2 52.3 51.2 51.6 51.7 51.5 52.8 52.0 51.7 52.6 53.5 53.7 54.9 55.2 55.4 56.2

52.5 54.0 55.5 56.2 56.0 53.9 53.0 53.7 53.5 53.4 52.4 51.7 53.6 52.6 52.7 52.0 53.2 53.5 53.4 55.7 57.0 57.3 56.5 58.3 57.8

56.8 55.8 57.1 54.6 56.7 53.6 53.8 53.6 53.3 54.2 54.3 52.9 54.9 52.6 51.5 53.0 50.2 51.7 51.3 52.1 53.7 55.7 55.5 53.8 53.6

54.8 54.0 52.4 54.3 54.5 51.1 50.9 52.2 52.1 52.1 50.9 52.8 53.8 51.0 52.1 51.8 50.3 51.5 52.2 50.2 51.9 54.3 54.8 54.2 53.5

54.3 54.2 55.8 54.5 53.6 53.2 51.7 51.3 53.1 53.0 55.4 54.1 53.4 53.5 51.8 52.2 51.0 51.0 52.3 53.3 54.5 55.3 55.6 54.8 53.9

56.1 54.7 55.5 56.9 57.5 56.6 55.5 54.0 54.2 55.6 56.9 55.5 54.3 53.6 53.3 51.8 49.3 50.1 52.0 53.3 52.2 53.8 55.7 57.6 57.5

53.3 53.8 54.8 54.1 55.3 53.8 52.7 54.1 54.9 55.6 53.2 52.2 53.5 53.9 52.4 53.5 51.2 49.8 51.0 50.9 52.2 53.2 53.0 55.0 55.7

48.8 48.0 49.4 50.7 49.6 48.3 50.6 50.6 50.6 51.4 50.0 50.2 49.6 48.0 48.4 48.3 48.6 48.3 49.7 51.8 51.7 53.5 53.6 52.2 53.3

52.8 52.1 51.1 51.9 51.8 53.3 52.3 52.1 52.9 53.2 52.3 50.5 50.7 51.8 52.1 54.5 53.8 53.6 54.3 55.0 54.3 55.6 56.4 56.8 58.3

48.9 46.5 48.0 46.9 30.2 39.1 43.3 47.3 48.1 50.2 50.0 48.4 49.0 49.7 48.4 50.4 48.7 50.4 49.2 48.6 48.3 49.3 46.6 47.7 46.7

54.4 51.9 52.0 51.4 51.9 51.6 51.8 55.5 52.7 51.9 52.9 50.8 50.7 49.2 50.1 52.1 48.2 53.3 55.4 54.2 53.4 56.1 55.7 54.6 54.2

48.1 48.9 47.6 48.7 48.3 47.9 49.1 50.2 50.1 48.7 49.8 49.3 48.3 48.0 49.6 51.5 49.5 50.8 51.1 52.4 53.6 53.7 54.7 52.5 52.4

48.0 48.5 50.2 49.0 50.1 49.3 48.0 49.5 50.9 52.2 50.9 50.3 49.2 48.9 49.4 47.4 47.6 47.0 48.3 49.8 48.8 47.7 48.7 49.7 52.3

60.1 58.3 57.0 56.1 57.5 58.7 56.5 55.7 56.3 54.4 53.9 54.4 54.5 54.2 54.8 54.4 56.0 56.6 55.3 53.2 55.0 55.5 56.7 57.0 56.4

51.6 51.5 50.1 49.2 48.9 49.3 47.9 47.5 49.6 49.1 49.6 49.1 47.0 47.9 50.2 49.6 49.9 49.8 50.7 50.5 50.8 51.6 51.3 50.5 50.7

50.3 49.9 50.9 50.1 51.2 51.7 51.0 52.4 52.6 52.6 52.3 50.1 49.1 48.2 47.7 48.1 49.3 49.5 50.4 51.4 51.3 52.4 52.7 53.3 52.4

49.2 48.8 47.8 46.1 47.6 47.9 49.2 49.1 49.1 50.7 49.5 48.7 49.5 50.0 50.1 50.5 50.1 48.6 47.6 48.0 48.0 49.4 49.0 49.2 48.4

49.6 48.9 49.2 49.4 47.8 47.3 47.2 48.3 48.6 48.2 48.4 48.0 49.7 49.4 49.2 48.6 50.6 50.0 50.1 51.2 50.9 51.9 51.0 51.7 51.2

51.0 49.2 49.3 46.3 47.1 46.1 46.9 47.8 49.5 51.7 50.6 49.4 51.1 49.7 48.5 50.5 51.0 51.8 52.2 52.7 54.7 56.2 55.6 54.5 56.2

50.7 53.5 54.8 52.2 52.6 51.3 49.5 50.1 49.4 51.3 51.5 50.3 50.7 52.3 52.7 52.6 51.9 52.2 52.9 51.7 54.0 52.4 51.9 54.2 54.6

46.4 46.7 47.1 47.8 47.3 48.4 47.4 47.8 46.9 47.8 48.9 48.7 50.6 50.9 50.6 51.9 48.4 50.4 50.9 48.7 49.7 49.0 50.4 49.3 50.5

52.1 51.3 52.6 51.3 52.7 52.3 51.2 50.7 50.3 49.1 51.1 51.1 52.4 50.5 50.7 51.7 51.8 52.6 52.1 54.4 52.3 49.6 50.4 50.7 52.5

46.3 48.0 52.3 44.2 50.4 51.7 52.1 50.2 52.5 51.9 51.5 53.5 58.1 53.4 51.0 51.8 56.4 46.9 49.8 50.5 54.2 55.4 51.2 59.3 57.5


Global Trade/Export Metrics

The CPB Netherlands Bureau for Economic Policy Analysis pub-lishes the World Trade Monitor. The WTM summarizes worldwidemonthly data on international trade and production. Data is from a

variety of sources, which are normalized into a set of indexed curveswhich show trends in world trade.

World Imports and Exports

Inde

x: 2

010

= 1

00

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

7080

9010

011

012

0

ExportsImports

World Exports by Region

Inde

x: 2

010

= 1

00

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

6070

8090

100

110

120

130

USAJapanEuro Area

Latin AmericaAfrica & Middle EastEmerging Asia


Canadian Indicators

Retail Trade (SA)

YoY

Per

cent

Cha

nge

−5

05

10

median: 4.61Jan 2017: 4.49

Total Manufacturing Sales Growth

YoY

Per

cent

Gro

wth

−20

−10

010

20

median: 3.56Feb 2017: 6.81

Manufacturing New Orders Growth

YoY

Per

cent

Gro

wth

−30

−10

010

2030

median: 4.01Feb 2017: 12.58

1yr vs. 10yr Canada Bond Yields

Yie

ld (

Per

cent

)

02

46

810

median: 5.54Mar 2017: 1.59

10 yr bond1 yr bond

Manufacturing PMI

4850

5254

Mar 2017: 55.50

Sales and New Orders (SA)

YoY

Per

cent

Cha

nge

−20

−10

010

20

SalesNew Orders (smoothed)

Tbill Yield Spread (10 yr − 3mo)

Spr

ead

(Per

cent

)

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−1

01

23

4

median: 1.28Mar 2017: 1.05

Inflation (total and core)

YoY

Per

cent

Cha

nge

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−1

01

23

4

median: 1.86Feb 2017: 2.05

TotalCore

Inventory to Sales Ratio (SA)

Rat

io

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1.3

1.4

1.5

1.6

median: 1.35Feb 2017: 1.34


6.6 6.8 7.0 7.2 7.4 7.6

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

Beveridge Curve (Mar 2011 − Dec 2016)

as.numeric(can.bev$ui.rate)

as.n

umer

ic(c

an.b

ev$v

acan

cies

) Mar 2011 − Dec 2012Jan 2013 − Nov 2016Dec 2016

Unemployment Rate

Job

Vac

ancy

rat

e (I

ndus

tria

l)

Ownership/Rental Price Ratio

Rat

io o

f Acc

omod

atio

n O

wne

rshi

p/R

ent R

atio

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

9010

011

012

013

014

015

0

CalgaryMontrealVancouverToronto

Note: Using prices relative to 2002 as base year

Ownership relatively moreexpensive vs 2002

Rent relatively more expensive vs 2002

Unemployment Rate (SA)

Per

cent

34

56

78

910

Canada 6.7%Alberta 8.4%Ontario 6.4%

Debt Service Ratios (SA)

Per

cent

02

46

810

Total Debt: 6.1%Mortgage: 3.0%Consumer Debt: 6.3%

Housing Starts and Building Permits (smoothed)

YoY

Per

cent

Cha

nge

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−40

−20

020

40

PermitsStarts


European Indicators

Unemployment Rates

Per

cent

age

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

05

1015

2025

30

FR

DEGB

IT

GR

ES

EU

Business Employment Expectations

Inde

x

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−40

−20

010

Industrial Orderbook Levels

Inde

x

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−60

−40

−20

020

Country EmploymentExpect.

Unempl.(%)

BondYields

(%)

RetailTurnover

ManufacturingTurnover

Inflation(YoY

%)

IndustryOrder-book

PMI

Series Dates Mar 2017 Mar 2017 Mar 2017 Feb 2017 Feb 2017 Feb 2017 Mar 2017 Mar 2017� France -4.8 t 10.0 u 1.02 t 114.7 s 107.5 t 1.4 t -10.7 t 53.3 s� Germany 3.9 t 3.9 u 0.35 s NA 118.9 s 2.2 s -1.8 t 58.3 s� United Kingdom Of Great Britain And Northern Ireland 11.9 s 4.5 t 1.13 t 120.4 s NA 1.8 s 6.8 s 54.2 t� Italy 4.3 s 11.5 t 2.40 s 102.6 t NA 1.6 s -6.5 s 55.7 s� Greece 2.7 t 23.5 u 7.17 t NA NA 1.4 t -20.9 s 46.7 t� Spain 4.0 t 18.0 t 1.72 s NA NA 3.0 s -1.8 t 53.9 t� Eurozone (EU28) 4.6 s 8.0 t 1.44 u 112.8 s 115.5 s 1.9 s -4.8 u NA


Government Bond YieldsLo

ng T

erm

Yie

lds

%

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

02

46

810

Economic Sentiment

Inde

x

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

6070

8090

110

130

Consumer Confidence

Inde

x

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−10

0−

60−

200

20Inflation (Harmonized Prices)

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

median: 1.90Feb 2017: 2.00

−1

0

1

2

3

4

5

6

7

Harmonized Inflation: Jan 2017

AUT 2.4%

BGR 0.9%

DEU 2.2%

ESP 3.0%

FIN 1.4%

FRA 1.4%

GBR 1.8%

GRC 1.4%

HRV 1.4%

HUN 2.9%

IRL 0.3%

ISL−0.2%

ITA 1.6%

NOR 2.7%

POL 1.9%

ROU 0.5%

SWE 1.9%

<−1.0%0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% >7.0%

YoY % Change in Prices

PMI: March 2017

<40.042.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0>60.0

Steady ExpandingContracting

BRA49.6

CAN55.5

DEU58.3

ESP53.9

FRA53.3

GBR54.2

GRC46.7

IRL53.6

ITA55.7

MEX51.5

POL53.5

SAU56.4

TUR52.3

USA53.3

RUS52.4

PMI Change: Feb − Mar

<−5.0−4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 4.0 >5.0

PMI Change ImprovingDeteriorating

CAN 0.8

DEU 1.5

ESP−0.9

FRA 1.1

GBR−0.4

GRC−1.0

IRL−0.2

ITA 0.7

POL−0.7

TUR 2.6

USA−0.9

RUS−0.1


Chinese Indicators

Tracking the Chinese economy is a tricky. As reported in the Fi-nancial Times, Premier Li Keqiang confided to US officials in 2007 thatgross domestic product was “man made” and “for reference only”. In-stead, he suggested that it was much more useful to focus on three alter-native indicators: electricity consumption, rail cargo volumes and bank

lending (still tracking down that last one). We also include the PMI- which is an official version put out by the Chinese government anddiffers slightly from an HSBC version. Finally we include the ShanghaiComposite Index as a measure of stock performance.

Manufacturing PMI

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

4045

5055

60

Mar 2017: 51.20

Shanghai Composite Index

Inde

x V

alue

(M

onth

ly H

igh/

Low

)

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

010

0030

0050

00

Apr 2017: 3273.83

Electricity Generated

100

Mill

ion

KW

H (

log

scal

e)

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1000

2000

3000

5000

Feb 2017: 4657.50

Electricity GeneratedLong Term TrendShort Term Average

Consumer Confidence Index

Inde

x

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

100

105

110

median: 104.05Feb 2017: 112.60

Exports

YoY

Per

cent

Cha

nge

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

−20

020

4060

80

median: 17.80Mar 2017: 16.40

Retail Sales Growth

YoY

Per

cent

Cha

nge

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1015

20

median: 12.75Feb 2017: 9.50


Global Climate Data

Temperature and precipitation data are taken from the US NationalClimatic Data Center and presented as the average monthly anomalyfrom the previous 6 months. Anomalies are defined as the difference

from the average value over the period from 1971-2000 for the tem-perature map and over the 20th century for the global temparaturechart.

Average Temperature Anomalies from Sep 2016 - Feb 2017

<−4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 >4.0Anomalies in Celsius WarmerCooler Anomalies in Celcius

−4 −2 0 2 4

Historic Global Temperature Deviations

Deg

rees

Cel

sius

Dev

iatio

ns

−0.

50.

00.

51.

0

Dec 2016: 0.79

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020


Subscription Info The Global Economics Report is published by Laird Research Inc. To sign up for a FREE subscription to this report, pleasevisit our website: LairdResearch.com. Comments or suggestions? We’d love to hear from you!

Disclaimer: This document has been prepared in good faith on the basis of information available at the date of publication without any independentverification. Laird Research Inc. collects its data from public sources which it believes to be accurate, however it does not guarantee or warrantthe accuracy, reliability, completeness or currency of the information in this publication nor its usefulness in achieving any purpose. Readers areresponsible for assessing the relevance and accuracy of the content of this publication. Laird Research Inc. will not be liable for any loss, damage,cost or expense incurred or arising by reason of any person using or relying on information in this publication.

Copyright: This publication is Copyright©2017 by Laird Research Inc. Apart from any use as permitted under the Copyright Act, no part may bereproduced in any form without written permission from Laird Research Inc. Note that the data provided herein is collected from publicly availablesources, such as the Federal Reserve Bank of St. Louis and government releases, and any copyright to that data belongs to the owners.


http://lairdresearch.com/

global economics report 2017-04-14

Economy & Finance