A monthly summary of global economic performance including employment, trade, business conditions, leading indicators and regional data.

1. ....
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 few
changes to the report – in particular two new features: sentiment anal-
ysis (p. 18) and a US economic heartbeat (p. 4). We’ll be making more
changes over the next few months.
Sentiment analysis is a technique that tries to use machine learning
to determine the sentiment, positive or negative, of a block of text.
In this case, we’re using conference call transcripts for the S&P 500
companies. We’re presenting the sentiment of the conference calls (ie.
was it an upbeat or downbeat conference call) and plotting that against
operating earnings for each component. There seems to be a good cor-
relation between the two – and as we have much more conference call
data, which is updated more often, this is a good predictor of earnings
trends.
The US Economic Heartbeat is a tool for summarizing the position
of the US economy. We’ve been able to get a good monthly dataset
of various measures of the economy and have pulled out the business
cycle component of the data. The tracker shows a consistent pattern
when we are in the midst of a recession – right now the economy feels as
though it could go either way, but when it does break, this tool should
help 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 strong
uptick in the recent data, which is usually an indicator that something
is 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

2. Indicators for US Economy
Leading indicators are indicators that usually change before the
economy as a whole changes. They are useful as short-term predictors
of the economy. Our list includes the Philly Fed’s Leading Index which
summarizes 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 financial
situation and the economy in general). Red dots are points where a
new trend has started.
Leading Index for the US
Index:Est.6monthgrowth
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−2−10123
median: 1.50
Dec 2016: 1.17
Growth
Contraction
Initial Unemployment Claims
1000'sofClaimsperWeek
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
200300400500600
median: 346.62
Apr 2017: 247.25
Manufacturing Ave. Weekly Hours Worked
HoursworkedperWeek
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
394041424344
median: 40.60
Mar 2017: 41.80
Manfacturing − PMI
Index:SteadyState=50
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
3040506070
median: 52.70
Mar 2017: 53.30expanding economy
contracting economy
www.lairdresearch.com April 14, 2017 Page 2

3. Leading indicators are indicators that usually change before the
economy as a whole changes. They are useful as short-term predictors
of the economy. Our list includes the Philly Fed’s Leading Index which
summarizes 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 financial
situation and the economy in general). Red dots are points where a
new trend has started.
Durable Goods: Manufacturers New Orders
BillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
150200250
median: 186.49
Feb 2017: 235.96
Index of Truck Tonnage
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
100110120130140
median: 113.50
Feb 2017: 138.40
Capex (ex. Defense & Planes)
BillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
40506070
median: 58.58
Feb 2017: 64.74
U. Michigan: Consumer Sentiment
Index1966Q1=100
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
5060708090100110
median: 89.10
Mar 2017: 96.90
www.lairdresearch.com April 14, 2017 Page 3

4. US Economic Heartbeat
MarketHack Inc. is proud to present our proprietary Economic
Heartbeat index. It uses monthly economic data from 1960 onwards
to create a diffusion index. Each point represents the index value for
a 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/monetary
policy.
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Good Times
Danger Zone
Recession
Recovery
Recession
Recovery
Recession
Recovery
Recession
Recovery
Recession
Recovery
Recession
Recovery
Recession
Recovery
YOU
ARE
HERE
Recession months
Non−recession months
Current month (Jan 2017)
www.lairdresearch.com April 14, 2017 Page 4

5. Global Financial Markets
Global Stock Market Returns
Country Index Name Close Date Current
Value
Weekly
Change
Monthly
Change
3 month
Change
12
month
Change
Corr to
S&P500
Corr to
TSX
North America
USA S&P 500 Apr 13 2,328.9 -1.2% J -1.9% J 2.4% I 11.8% I 1.00 0.66
USA NASDAQ Composite Apr 13 5,805.1 -1.3% J -1.2% J 4.1% I 17.3% I 0.89 0.58
USA Wilshire 5000 Total Market Apr 13 24,262.6 -1.2% J -1.6% J 1.9% I 13.0% I 0.96 0.66
Canada S&P TSX Apr 13 15,535.5 -1.0% J -0.1% J 0.2% I 13.6% I 0.66 1.00
Europe and Russia
France CAC 40 Apr 13 5,071.1 -1.0% J 1.4% I 3.0% I 12.9% I 0.62 0.53
Germany DAX Apr 13 12,109.0 -1.0% J 1.0% I 4.1% I 20.8% I 0.61 0.50
Russia Market Vectors Russia ETF Apr 13 20.1 -5.7% J 0.9% I -6.5% J 18.5% I 0.42 0.53
Asia
Taiwan TSEC weighted index Apr 13 9,836.7 -0.6% J 1.4% I 4.9% I 13.7% I -0.09 0.01
China Shanghai Composite Index Apr 13 3,276.0 -0.2% J 1.2% I 5.2% I 6.8% I 0.06 0.05
Japan NIKKEI 225 Apr 13 18,426.8 -0.9% J -6.1% J -4.5% J 12.5% I 0.27 0.28
Hong Kong Hang Seng Apr 13 24,261.7 -0.0% J 1.8% I 5.8% I 14.7% I -0.06 0.04
Korea Kospi Apr 13 2,148.6 -0.2% J 1.5% I 3.5% I 6.6% I -0.03 -0.07
South Asia and Austrailia
India Bombay Stock Exchange Apr 13 29,461.4 -1.6% J 0.1% I 8.2% I 15.0% I 0.04 -0.04
Indonesia Jakarta Apr 13 5,616.5 -1.1% J 3.8% I 6.5% I 15.7% I -0.13 0.01
Malaysia FTSE Bursa Malaysia KLCI Apr 13 1,738.2 -0.1% J 0.9% I 3.9% I 0.9% I 0.03 0.13
Australia All Ordinaries Apr 13 5,925.9 0.5% I 2.3% I 2.6% I 15.6% I 0.10 0.16
New Zealand NZX 50 Index Gross Apr 13 7,229.8 -0.8% J 0.5% I 2.6% I 6.7% I 0.02 0.09
South America
Brasil IBOVESPA Apr 13 62,826.0 -2.2% J -4.1% J -1.3% J 18.2% I 0.35 0.49
Argentina MERVAL Buenos Aires Apr 12 20,812.2 0.6% I 8.5% I 11.9% I 64.0% I 0.24 0.51
Mexico Bolsa index Apr 12 48,955.8 -0.5% J 3.9% I 6.3% I 8.6% I 0.34 0.41
MENA and Africa
Egypt Market Vectors Egypt ETF Apr 13 28.3 -1.2% J 1.1% I 3.4% I -27.1% J 0.07 0.14
(Gulf States) Market Vectors Gulf States ETF Oct 07 23.0 3.2% I 1.2% I 6.4% I -6.4% J 0.16 0.05
South Africa iShares MSCI South Africa Index Apr 13 57.2 5.4% I 0.8% I 3.0% I 8.7% I 0.42 0.44
(Africa) Market Vectors Africa ETF Apr 13 21.3 2.0% I 3.5% I 1.2% I 11.7% I 0.31 0.35
Commodities
USD Spot Oil West Texas Int. Apr 10 $53.1 5.6% I 10.4% I 4.4% I 31.1% I 0.16 0.41
USD Gold LME Spot Apr 13 $1,286.1 2.6% I 6.5% I 7.5% I 3.2% I -0.17 -0.14
Note: Correlations are based on daily arithmetic returns for the most recent 100 trading days.
www.lairdresearch.com April 14, 2017 Page 5

6. S&P 500 Composite Index
The S&P 500 Composite Index is widely regarded as the best single
gauge 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. We
present 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). Forecasted
earnings numbers are estimates provided by S&P.
S&P 500 Profit Margins and Overall Corporate Profit Margins (Trailing 12 months)
Percent
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
2
4
6
8
10
12
14
0
2
4
6
8
10
12
14
Percent
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
18
Estimates
−5.00
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
−5.00
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
Tech Bubble
Japanese Asset Bubble
House BubbleAsian Financial Crisis
US Financial Crisis
Eurozone crisis
Oil Crisis I Oil Crisis II
Gulf War
Savings and Loans Crisis
High Inflation Period
Afganistan/Iraq WarVietnam War
Reported Earnings
Operating 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
Multiple
Multiple
12−month trailing P/E ( median = 17.5, Apr = 23.2)
10−year CAPE ( median = 19.7, Apr = 28.6)
www.lairdresearch.com April 14, 2017 Page 6

7. 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
SYF
STI
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
BCR
A
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
WM
CMI
PCAR
IR ROP
PH
ROK
AYI
XOM
−1.6%
CVX
−6.8%
SLB
−5%
COP
EOG
OXY
KMI
HAL
PSX
PXD
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
Consumer
Discretionary
Consumer
Staples
Industrials
Energy Utilities
Real Estate
Materials
Telecommunication
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 Median
Sector Change P/Sales P/Book P/E
Utilities 1.5% I 2.2 2.0 21.6
Real Estate 0.7% I 8.7 2.8 31.2
Consumer Staples 0.0% I 2.6 4.8 25.0
Consumer Discretionary -0.2% J 1.6 3.7 18.7
Information Technology -0.9% J 3.7 5.0 26.4
Health Care -1.7% J 3.7 4.0 27.3
Average Median Median Median
Sector Change P/Sales P/Book P/E
Telecommunication Services -1.8% J 1.5 2.0 20.5
Materials -3.2% J 1.9 4.1 26.5
Industrials -3.7% J 1.8 4.2 23.4
Energy -3.8% J 3.4 2.0 22.6
Financials -8.7% J 2.9 1.5 16.3
www.lairdresearch.com April 14, 2017 Page 7

8. US Equity Valuations
A key valuation metric is Tobin’s q: the ratio between the market
value of the entire US stock market versus US net assets at replacement
cost (ie. what you pay versus what you get). Warren Buffet famously
follows 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 has
valuations correct, we can determine the required returns of future es-
timated earnings. These are quoted for both debt (using BBB rated
securities as a proxy) and equity premiums above the risk free rate (10
year US Treasuries). These figures are alternate approaches to under-
standing the current market sentiment - higher premiums indicate a
demand for greater returns for the same price and show the level of
risk-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]
www.lairdresearch.com April 14, 2017 Page 8

9. US Mutual Fund Flows
Fund flows describe the net investments in equity and bond mutual
funds as well as ETF’s in the US market, as described in ICI’s “Trends
in Mutual Fund Investing” report. Previously we just looked at mutual
fund flows, but with the global trend to ETF’s, this only presented a
partial picture.
US Net New Investment Cash Flow to Mutual Funds & ETFs
US$billions(monthly)
2014 2015 2016 2017
−40−2002040
Domestic Equity
World Equity
Taxable Bonds
Municipal Bonds
US Net New Investment Cash Flow to Mutual Funds & ETFs
US$billions(Monthly)
2014 2015 2016 2017
−60−40−200204060
Flows to Equity
Flows to Bonds
Net Market Flows
www.lairdresearch.com April 14, 2017 Page 9

10. US Key Interest Rates
Interest rates are often leading indicators of stress in the financial
system. The yield curve show the time structure of interest rates on
government bonds - Usually the longer the time the loan is outstanding,
the higher the rate charged. However if a recession is expected, then
the fed cuts rates and this relationship is inverted - leading to negative
spreads 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 most
of 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 vs
Fedfunds - the infamous “TED Spread”). Here a spike correlates to an
aversion to risk, which is an indication that something bad is happen-
ing.
US Treasury Yield Curves
ForwardInstantaneousRates(%)
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
3.0
Apr 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 Treasury
3 Mo Treasury
Spread
AAA vs. BBB Bond Spreads
2%
3%
4%
5%
6%
7%
8%
9%
10%
2%
3%
4%
5%
6%
7%
8%
9%
10%
Percent
AAA
BBB
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
median: 112.00
Apr 2017: 66.00
0
100
200
300
400
0
100
200
300
400
Spread(bps)
LIBOR vs. Fedfunds Rate
0%
1%
2%
3%
4%
5%
6%
7%
0%
1%
2%
3%
4%
5%
6%
7%
Percent
3 mos t−bill
LIBOR
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
median: 36.61
Apr 2017: 34.54
0
100
200
300
0
100
200
300
Spread(bps)
www.lairdresearch.com April 14, 2017 Page 10

11. US Inflation
Generally, the US Fed tries to anchor long run inflation expectations
to approximately 2%. Inflation can be measured with the Consumer
Price Index (CPI) or the Personal Consumption Expenditures (PCE)
index.
In both cases, it makes sense to exclude items that vary quickly like
Food and Energy to get a clearer picture of inflation (usually called
Core Inflation). The Fed seems to think PCI more accurately reflects
the 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 an
imputed forward inflation expectation. The 5y5y chart shows expected
5 year inflation rates at a point 5 years in the future. Neat trick that.
Consumer Price Index
Percent
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
Percent(YearoverYear)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−10123456
PCE Inflation Rate YoY% (Aug = 0.96%)
PCE Core Inflation YoY% (Aug = 1.7%)
5−Year, 5−Year Forward Inflation Expectation Rate
Percent
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
−10123456
5 year forward Inflation Expectation
Actual 5yr Inflation (CPI measure)
Actual 5yr Inflation (PCE Measure)
www.lairdresearch.com April 14, 2017 Page 11

12. 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
0.620.710.810.901.001.09
USA/CAD
0.550.610.660.720.770.82
Euro/CAD
59.1674.7190.26105.81121.36136.91
Japan/CAD
0.380.440.490.550.610.67
U.K./CAD
0.591.101.602.112.613.12
Brazil/CAD
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
Appreciating
Depreciating
% 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%
EUR
1.6%
JPY
6.0%
KRW
6.9%
MXN
−3.1%
ZAR
10.3%
www.lairdresearch.com April 14, 2017 Page 12

13. US Banking Indicators
The banking and finance industry is a key indicator of the health
of the US economy. It provides crucial liquidity to the economy in the
form 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 difference
between what a bank pays to depositors versus what the bank is paid
by creditors), along with levels of non-performing loans (i.e. loan loss
reserves and actual deliquency rates).
US Banks Net Interest Margin
3.03.54.04.5
median: 3.93
Oct 2016: 3.05
Repos Outstanding with Fed. Reserve
BillionsofDollars
0200400600
median: 62.03
Apr 2017: 357.43
Bank ROE − Assets between $300M−$1B
Percent
051015
median: 12.68
Oct 2016: 9.93
Consumer Credit Outstanding
%YearlyChange
−505101520
median: 7.41
Feb 2017: 6.31
Total Business Loans
%YearlyChange
−2001020 median: 8.63
Feb 2017: 5.39
US Nonperforming Loans
12345
median: 1.95
Oct 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
−112345
median: −0.001
Apr 2017: −1.37
Commercial Paper Outstanding
TrillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
1.01.41.82.2
median: 1.31
Apr 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
246810
median: 2.36
Oct 2016: 4.15
www.lairdresearch.com April 14, 2017 Page 13

14. US Charge-Off Indication
A “charge-off” is an accounting declaration by a creditor that a
particular 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 determination
is 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 the
health of creditors. In this graph, the various charge-offs are presented
as a percentage of total relevant debt outstanding. For example, credit
card 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
Percent
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%)
www.lairdresearch.com April 14, 2017 Page 14

15. US Employment Indicators
Unemployment rates are considered the “single best indicator of
current labour conditions” by the Fed. The pace of payroll growth is
highly correlated with a number of economic indicators.Payroll changes
are another way to track the change in unemployment rate.
Unemployment only captures the percentage of people who are in
the labour market who don’t currently have a job - another measure
is what percentage of the whole population wants a job (employed or
not) - this is the Participation Rate.
The Beveridge Curve measures labour market efficiency by looking
at 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
Percent
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: 6.10
Mar 2017: 4.50
4
5
6
7
8
9
10
11
4
5
6
7
8
9
10
11
Percent
Beveridge Curve
Unemployment Rate
HelpWantedIndex
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
110
1950's
1960's
1970's
1980's
1990's
2000's
2010's
Participation Rate
PercentofPop.
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
6364656667
median: 66.00
Mar 2017: 63.00
Total Nonfarm Payroll Change
MonthlyChange(000s)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−5000500
median: 164
Mar 2017: 98
www.lairdresearch.com April 14, 2017 Page 15

16. 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 a
full-time job - they are employed but under-utilitized. Temporary help
demand 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 jobs
is generally bad, though perhaps not unsurprising in a recovery.
Median Duration of Unemployment
Weeks
510152025
median: 8.90
Mar 2017: 10.30
(U6) Unemployed + PT + Marginally Attached
Percent
810121416
median: 9.70
Mar 2017: 8.90
4−week moving average of Initial Claims
Jan1995=100
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
50100150200
median: 106.57
Apr 2017: 76.02
Unemployed over 27 weeks
MillionsofPersons
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
01234567
median: 0.82
Mar 2017: 1.76
Services: Temp Help
MillionsofPersons
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
1.52.02.53.0
median: 2.29
Mar 2017: 3.00
0 200 400 600
15
20
25
30
35
40
Annual Change in Employment Levels (000s of Workers)
Averagewages($/hour)
Private Industry Employment Change (Mar 2016 − Mar 2017)
Construction
Durable Goods
Education
Financial Activities
Health Services
Information
Leisure and Hospitality
Manufacturing
Mining and Logging
Nondurable Goods
Other Services
Professional &
Business Services
Retail Trade
Transportation
Utilities
Wholesale Trade
Circle size relative to total employees in industry
www.lairdresearch.com April 14, 2017 Page 16

17. 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 the
current business environment.
Manufacturing: Real Output
YoYPercentChange
−1001020
median: 7.87
Oct 2016: 3.26
Manufacturing − PMI
354045505560
Mar 2017: 53.30
manufac. expanding
manufac. contracting
Manufacturers' Durable Goods Orders
BillionsofDollars
150200250
Feb 2017: 235.96
Increase in new orders
Decrease in new orders
Non−Manufac. New Orders: Capital Goods
BillionsofDollars
40506070
median: 58.58
Feb 2017: 64.74
Average Weekly Hours: Manufacturing
3940414243
median: 41.20
Mar 2017: 41.80
Industrial Production: Manufacturing
YoYPercentChange
−15−50510
median: 2.86
Feb 2017: 1.50
Inventory to Sales Ratio
Ratio
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
1.11.21.31.41.51.6
median: 1.37
Jan 2017: 1.35
Chicago Fed: Sales, Orders & Inventory
Index
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: 0.08
Above 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
95105115125
Feb 2017: 126.40
www.lairdresearch.com April 14, 2017 Page 17

18. S&P 500 Sentiment Analysis
Sentiment analysis tries to determine the attitude of a speaker with
respect to some topic or the overall contextual polarity of a document.
In this particular case, we are evaluating earnings conference calls for
the 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 the
arbitrary date of January 2012. While it is not an exact science, the
models do capture the significant negative sentiment in 2007-2008 and
the subsequent recovery.
−1500−50005001500
Normalized Sentiment (Based on 17,948 Earnings Calls)
SentimentValue(IndexJan2012=0)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
CD
CD: +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
Ut
Ut: +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) Utilities
S&P 500
Sentiment Increasing
Sentiment Decreasing
−1000100200
Month over Month Sentiment Change − Apr 2017
+72
+49
+88 +98
+5
+162
+69
+23
+103 +98
+2
Consumer
Discretionary
Consumer
Staples Energy Financials
Health
Care Industrials
Information
Technology Materials
Real
Estate
Telecommunications
Services Utilities
www.lairdresearch.com April 14, 2017 Page 18

19. 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 Increasing
Sentiment Decreasing
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
www.lairdresearch.com April 14, 2017 Page 19

20. 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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
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
Sentiment Increasing
Sentiment Decreasing
Sentiment (LHS)
Operating Earnings (RHS)
S&P Estimates (RHS)
www.lairdresearch.com April 14, 2017 Page 20

21. US Consumption Indicators
Variations in consumer activity are a leading indicator of the
strength of the economy. We track consumer sentiment (their expec-
tations about the future), consumer loan activity (indicator of new
purchase activity), and new orders and sales of consumer goods.
U. Michigan: Consumer Sentiment
Index1966Q1=100
5060708090110
median: 89.10
Mar 2017: 96.90
Consumer Loans (All banks)
YoY%Change
−10010203040
median: 7.63
Feb 2017: 6.92
Accounting
Change
Deliquency Rate on Consumer Loans
Percentage
2.03.04.0
median: 3.42
Oct 2016: 2.15
New Orders: Durable Consumer Goods
YoY%Change
−20020
median: 4.35
Feb 2017: −4.20
New Orders: Non−durable Consumer Goods
YoY%Change
−2001020
median: 3.75
Feb 2017: 13.36
Personal Consumption & Housing Index
Index
−0.40.00.20.4
median: 0.02
Feb 2017: −0.03above ave growth
below ave growth
Light Cars and Trucks Sales
MillionsofUnits
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
10121416182022
median: 14.91
Mar 2017: 16.53
Personal Saving Rate
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
246810
median: 5.70
Feb 2017: 5.60
Retail Food and Service Sales
YoY%Change(Real)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−10−505
median: 2.45
Feb 2017: 2.79
www.lairdresearch.com April 14, 2017 Page 21

22. 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. Since
personal consumption is about 70% of the US economy and house val-
ues directly impact household wealth, housing is an important indicator
in the health of the overall economy. In particular, housing investment
was an important driver of the economy getting out of the last few
recessions (though not this one so far). Here we track housing prices
and especially indicators which show the current state of the housing
market.
15 20 25 30 35 40
150200250300
Personal Income vs. Housing Prices (Inflation adjusted values)
NewHomePrice(000's)
Disposable Income Per Capita (000's)
February 2017
r2
: 89.9%
Range: Jan 1962 − Feb 2017
Blue dots > +5% change in next year
Red dots < −5% change in next year
New Housing Units Permits Authorized
MillionsofUnits
0.51.01.52.02.5
median: 1.33
Feb 2017: 1.22
New Home Median Sale Price
SalePrice$000's
100200300
Feb 2017: 296.20
Homeowner's Equity Level
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
4050607080
median: 66.50
Oct 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
468101214
median: 4.90
Feb 2017: 3.40
US Monthly Supply of Homes
MonthsSupply
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
4681012
median: 5.80
Feb 2017: 5.40
www.lairdresearch.com April 14, 2017 Page 22

23. US Housing - FHFA Quarterly Index
The Federal Housing Finance Agency provides a quarterly survey
on house prices, based on sales prices and appraisal data. This gener-
ates a housing index for 355 municipal areas in the US from 1979 to
present. We have provided an alternative view of this data looking at
the 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 start
of the housing crisis (defined as the maximum price between 2007-2009
for each city). The circled dots are the cities in the survey, while the
background colours are interpolated from these points using a loess
smoother.
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
Frequency
−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
Frequency
−15% −10% −5% 0% 5% 10% 15%
www.lairdresearch.com April 14, 2017 Page 23

24. Global Business Indicators
Global Manufacturing PMI Reports
The Purchasing Managers’ Index (PMI) is an indicator reflecting
purchasing managers’ acquisition of goods and services. An index read-
ing of 50.0 means that business conditions are unchanged, a number
over 50.0 indicates an improvement while anything below 50.0 suggests
a decline. The further away from 50.0 the index is, the stronger the
change over the month. The chart at the bottom shows a moving av-
erage of a number of PMI’s, along with standard deviation bands to
show 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
Eurozone
56.2
Global PMI
53.0
TWN
56.2MEX
51.5
KOR
48.4
JPN
52.4
VNM
54.6
IDN
50.5
ZAF
50.7
AUS
57.5
BRA
49.6
CAN
55.5
CHN
51.2
IND
52.5
RUS
52.4
SAU
56.4
USA
53.3
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
Eurozone
0.8
Global PMI
0.0
TWN
1.7MEX
0.9
KOR
−0.8
JPN
−0.9
VNM
0.4
IDN
1.2
ZAF
0.2
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
3040506070
3040506070
Business Conditions Contracting
Business Conditions Expanding
www.lairdresearch.com April 14, 2017 Page 24

25. Global Manufacturing PMI Chart
This is an alternate view of the global PMI reports. Here, we look
at all the various PMI data series in a single chart and watch their
evolution over time.
Red numbers indicate contraction (as estimated by PMI) while
green numbers indicate expansion.
Mar15
Apr15
May15
Jun15
Jul15
Aug15
Sep15
Oct15
Nov15
Dec15
Jan16
Feb16
Mar16
Apr16
May16
Jun16
Jul16
Aug16
Sep16
Oct16
Nov16
Dec16
Jan17
Feb17
Mar17
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
www.lairdresearch.com April 14, 2017 Page 25

26. Global Trade/Export Metrics
The CPB Netherlands Bureau for Economic Policy Analysis pub-
lishes the World Trade Monitor. The WTM summarizes worldwide
monthly data on international trade and production. Data is from a
variety of sources, which are normalized into a set of indexed curves
which show trends in world trade.
World Imports and Exports
Index:2010=100
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
708090100110120
Exports
Imports
World Exports by Region
Index:2010=100
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
60708090100110120130
USA
Japan
Euro Area
Latin America
Africa & Middle East
Emerging Asia
www.lairdresearch.com April 14, 2017 Page 26

27. Canadian Indicators
Retail Trade (SA)
YoYPercentChange
−50510
median: 4.61
Jan 2017: 4.49
Total Manufacturing Sales Growth
YoYPercentGrowth
−20−1001020
median: 3.56
Feb 2017: 6.81
Manufacturing New Orders Growth
YoYPercentGrowth
−30−100102030
median: 4.01
Feb 2017: 12.58
1yr vs. 10yr Canada Bond Yields
Yield(Percent)
0246810
median: 5.54
Mar 2017: 1.59
10 yr bond
1 yr bond
Manufacturing PMI
48505254
Mar 2017: 55.50
Sales and New Orders (SA)
YoYPercentChange
−20−1001020
Sales
New Orders (smoothed)
Tbill Yield Spread (10 yr − 3mo)
Spread(Percent)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−101234
median: 1.28
Mar 2017: 1.05
Inflation (total and core)
YoYPercentChange
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−101234
median: 1.86
Feb 2017: 2.05
Total
Core
Inventory to Sales Ratio (SA)
Ratio
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
1.31.41.51.6
median: 1.35
Feb 2017: 1.34
www.lairdresearch.com April 14, 2017 Page 27

28. 6.6 6.8 7.0 7.2 7.4 7.6
1.21.31.41.51.61.71.81.9
Beveridge Curve (Mar 2011 − Dec 2016)
as.numeric(can.bev$ui.rate)
as.numeric(can.bev$vacancies)
Mar 2011 − Dec 2012
Jan 2013 − Nov 2016
Dec 2016
Unemployment Rate
JobVacancyrate(Industrial)
Ownership/Rental Price Ratio
RatioofAccomodationOwnership/RentRatio
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
90100110120130140150
Calgary
Montreal
Vancouver
Toronto
Note: Using prices relative to 2002 as base year
Ownership relatively more
expensive vs 2002
Rent relatively more expensive vs 2002
Unemployment Rate (SA)
Percent
345678910
Canada 6.7%
Alberta 8.4%
Ontario 6.4%
Debt Service Ratios (SA)
Percent
0246810
Total Debt: 6.1%
Mortgage: 3.0%
Consumer Debt: 6.3%
Housing Starts and Building Permits (smoothed)
YoYPercentChange
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−40−2002040
Permits
Starts
www.lairdresearch.com April 14, 2017 Page 28

29. European Indicators
Unemployment Rates
Percentage
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
051015202530
FR
DE
GB
IT
GR
ES
EU
Business Employment Expectations
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−40−20010
Industrial Orderbook Levels
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−60−40−20020
Country Employment
Expect.
Unempl.
(%)
Bond
Yields
(%)
Retail
Turnover
Manufacturing
Turnover
Inflation
(YoY
%)
Industry
Order-
book
PMI
Series Dates Mar 2017 Mar 2017 Mar 2017 Feb 2017 Feb 2017 Feb 2017 Mar 2017 Mar 2017
France -4.8 J 10.0 K 1.02 J 114.7 I 107.5 J 1.4 J -10.7 J 53.3 I
Germany 3.9 J 3.9 K 0.35 I NA 118.9 I 2.2 I -1.8 J 58.3 I
United Kingdom Of Great Britain And Northern Ireland 11.9 I 4.5 J 1.13 J 120.4 I NA 1.8 I 6.8 I 54.2 J
Italy 4.3 I 11.5 J 2.40 I 102.6 J NA 1.6 I -6.5 I 55.7 I
Greece 2.7 J 23.5 K 7.17 J NA NA 1.4 J -20.9 I 46.7 J
Spain 4.0 J 18.0 J 1.72 I NA NA 3.0 I -1.8 J 53.9 J
Eurozone (EU28) 4.6 I 8.0 J 1.44 K 112.8 I 115.5 I 1.9 I -4.8 K NA
www.lairdresearch.com April 14, 2017 Page 29

30. Government Bond YieldsLongTermYields%
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
0246810
Economic Sentiment
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
60708090110130
Consumer Confidence
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−100−60−20020
Inflation (Harmonized Prices)
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
median: 1.90
Feb 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
BRA
49.6
CAN
55.5
DEU
58.3
ESP
53.9
FRA
53.3
GBR
54.2
GRC
46.7
IRL
53.6
ITA
55.7
MEX
51.5
POL
53.5
SAU
56.4
TUR
52.3
USA
53.3
RUS
52.4
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
www.lairdresearch.com April 14, 2017 Page 30

31. 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 that
gross 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 and
differs slightly from an HSBC version. Finally we include the Shanghai
Composite 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
4045505560
Mar 2017: 51.20
Shanghai Composite Index
IndexValue(MonthlyHigh/Low)
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
0100030005000
Apr 2017: 3273.83
Electricity Generated
100MillionKWH(logscale)
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
1000200030005000
Feb 2017: 4657.50
Electricity Generated
Long Term Trend
Short Term Average
Consumer Confidence Index
Index
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
100105110
median: 104.05
Feb 2017: 112.60
Exports
YoYPercentChange
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
−20020406080
median: 17.80
Mar 2017: 16.40
Retail Sales Growth
YoYPercentChange
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
101520
median: 12.75
Feb 2017: 9.50
www.lairdresearch.com April 14, 2017 Page 31

32. Global Climate Data
Temperature and precipitation data are taken from the US National
Climatic Data Center and presented as the average monthly anomaly
from 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 temparature
chart.
Average Temperature Anomalies from Sep 2016 - Feb 2017
<−4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 >4.0
Anomalies in Celsius WarmerCooler Anomalies in Celcius
−4 −2 0 2 4
Historic Global Temperature Deviations
DegreesCelsiusDeviations
−0.50.00.51.0
Dec 2016: 0.79
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
www.lairdresearch.com April 14, 2017 Page 32

33. Subscription Info The Global Economics Report is published by Laird Research Inc. To sign up for a FREE subscription to this report, please
visit 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 independent
verification. Laird Research Inc. collects its data from public sources which it believes to be accurate, however it does not guarantee or warrant
the accuracy, reliability, completeness or currency of the information in this publication nor its usefulness in achieving any purpose. Readers are
responsible 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 be
reproduced in any form without written permission from Laird Research Inc. Note that the data provided herein is collected from publicly available
sources, such as the Federal Reserve Bank of St. Louis and government releases, and any copyright to that data belongs to the owners.
www.lairdresearch.com April 14, 2017 Page 33