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

1. ....
Laird Research - Economics
February 22, 2016
Where we are now . . . . . . . . . . . . . . . . . . . . . . . . 1
Indicators for US Economy . . . . . . . . . . . . . . . . . . . 3
Global Financial Markets . . . . . . . . . . . . . . . . . . . . 4
US Key Interest Rates . . . . . . . . . . . . . . . . . . . . . . 9
US Inflation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
QE Taper Tracker . . . . . . . . . . . . . . . . . . . . . . . . . 11
Exchange Rates . . . . . . . . . . . . . . . . . . . . . . . . . . 12
US Banking Indicators . . . . . . . . . . . . . . . . . . . . . . 13
US Employment Indicators . . . . . . . . . . . . . . . . . . . 14
US Business Activity Indicators . . . . . . . . . . . . . . . . 16
US Consumption Indicators . . . . . . . . . . . . . . . . . . 17
US Housing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Global Housing . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Global Business Indicators . . . . . . . . . . . . . . . . . . . 22
Canadian Indicators . . . . . . . . . . . . . . . . . . . . . . . 24
European Indicators . . . . . . . . . . . . . . . . . . . . . . . 26
Chinese Indicators . . . . . . . . . . . . . . . . . . . . . . . . 28
Global Climate Change . . . . . . . . . . . . . . . . . . . . . 29
Where we are now
Welcome to the Laird Report. We present a selection of economic
data from around the world to help figure where we are today.
There are clear cracks in the foundation of the global economy -
those are highlighted by declines in the volume and quantum of inter-
national trade. A significant portion of that has been the slow rolling
disaster that is the oil price: significant quantities are shipped via ship
and crushed profits from oil producers means that the profits from oil
export have declined. This reduces demand for oil transport – which
seems counter-intuitive because oil price collapse is attributed to over-
supply – which would imply that volumes remain high. However, the
total dollar volume would have declined, so that weighs on measures
of trade (i.e. same volume at a lower price would result in a dollar
decline).
However, one measure that I used to follow is the Baltic Index which
is in the news as it shows the pricing of ships carrying raw materials
– a key leading indicator. That index is now at an all-time low value,
which indicates a slowdown in demand. There’s a reason mining and
oil companies are having a hard time and trade reflects that.
A related trade measure is the Harpex index (for which we do not
have as much historical data). It follows container ship pricing - which
is more closely tied to finished goods demand as it travels from producer
to consumer. As can be seen from the next page, it is also down signif-
icantly from its highs and back to the levels of 2013 (actually slightly
lower).
Note that these data series are very noisy which is why I stopped
following them: the structure of the industry (how many ships are
available) has as much of an effect on pricing as demand and signifi-
cant amounts of capacity have been added and subsequently removed
in the last 10 years.
Europe and the US are having none of this however, with employ-
ment measures still strong and improving. Prices are stable and jobless
measures are declining. Quit rates have increased – with the assump-

2. tion that if more people are quitting to find better jobs they must be
pretty confident in the strength of the local economy. Further, things
like bank non-performing loan measures are declining – businesses are
strengthening, though this is a relative measure to the chaos of five
years ago.
China still seems to be worse than the central planners hoped, but
remains opaque to analysis - their central bank has started removing
details on items like capital flight.
The information moves slowly through the economy – this report
could easily be quarterly – and when early indicators like global trade
keep grinding lower, challenges are coming down the pipe, however good
it looks now. Don’t quit your day job.
Formatting Notes The grey bars on the various charts are OECD
recession indicators for the respective countries. In many cases, the last
available value is listed, along with the median value (measured from
as much of the data series as is available).
Subscription Info For a FREE subscription to this monthly re-
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Laird Research, February 22, 2016
Harpex Index (shipping container pricing index)13
14
15
0100200300400500600
median: 403.07
Feb 2016: 364.13
www.lairdresearch.com February 22, 2016 Page 2

3. 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; new order and housing per-
mit indicies; delivery timings (longer timings imply more demand in
the system) and consumer 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
−3−10123
median: 1.54
Dec 2015: 1.65
Growth
Contraction
Initial Unemployment Claims
1000'sofClaimsperWeek
200400600
median: 349.12
Feb 2016: 273.25
Manufacturing Ave. Weekly Hours Worked
Hours
394041424344
median: 40.60
Jan 2016: 41.80
ISM Manfacturing − PMI
Index:SteadyState=50
3040506070
median: 53.40
Jan 2016: 48.20
expanding economy
contracting economy
Manufacturers' New Orders: Durable Goods
BillionsofDollars
150200250300
median: 185.33
Dec 2015: 225.59
Index of Truck Tonnage
TruckTonnageIndex
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
100120
median: 113.00
Nov 2015: 134.10
Capex (ex. Defence & Planes)
BillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
40506070
median: 57.84
Dec 2015: 65.96
Chicago Fed National Activity Index
IndexValue
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
−4−202
median: 0.07
Dec 2015: −0.22
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
507090110
median: 88.80
Jan 2016: 92.00
www.lairdresearch.com February 22, 2016 Page 3

4. 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 Feb 19 1,917.8 2.8% I 1.9% I -7.9% J -8.6% J 1.00 0.79
USA NASDAQ Composite Feb 19 4,504.4 3.8% I 0.6% I -11.2% J -8.5% J 0.95 0.71
USA Wilshire 5000 Total Market Feb 19 19,624.2 3.1% I 1.8% I -9.2% J -11.4% J 1.00 0.80
Canada S&P TSX Feb 19 12,813.4 3.5% I 6.8% I -4.9% J -15.6% J 0.79 1.00
Europe and Russia
France CAC 40 Feb 19 4,223.0 5.7% I -1.2% J -14.1% J -12.6% J 0.61 0.57
Germany DAX Feb 19 9,388.0 4.7% I -2.9% J -15.3% J -14.7% J 0.56 0.49
United Kingdom FTSE Feb 19 5,950.2 4.3% I 1.2% I -6.0% J -13.6% J 0.66 0.67
Russia Market Vectors Russia ETF Feb 19 14.1 4.1% I 12.3% I -16.4% J -18.8% J 0.63 0.72
Asia
Taiwan TSEC weighted index Feb 19 8,325.0 3.2% I 6.0% I -1.8% J -12.6% J 0.20 0.20
China Shanghai Composite Index Feb 18 2,862.9 4.2% I -1.7% J -19.8% J -11.3% J 0.30 0.26
Japan NIKKEI 225 Feb 19 15,967.2 6.8% I -6.3% J -19.6% J -12.6% J 0.07 0.09
Hong Kong Hang Seng Feb 19 19,285.5 5.3% I -1.8% J -14.3% J -22.4% J 0.24 0.26
Korea Kospi Feb 19 1,916.2 4.4% I 1.4% I -3.7% J -2.3% J 0.18 0.23
South Asia and Austrailia
India Bombay Stock Exchange Feb 19 23,709.2 3.1% I -3.1% J -8.3% J -19.5% J 0.37 0.45
Indonesia Jakarta Feb 19 4,697.6 -0.4% J 4.6% I 4.0% I -13.0% J 0.18 0.28
Malaysia FTSE Bursa Malaysia KLCI Feb 19 1,674.9 1.9% I 2.8% I 0.9% I -7.4% J 0.28 0.31
Australia All Ordinaries Feb 19 5,008.3 4.0% I 1.1% I -5.4% J -14.7% J 0.11 0.20
New Zealand NZX 50 Index Gross Feb 19 6,141.7 3.5% I 0.3% I 2.4% I 7.3% I 0.05 0.08
South America
Brasil IBOVESPA Feb 19 41,543.0 4.4% I 9.2% I -13.7% J -19.0% J 0.47 0.48
Argentina MERVAL Buenos Aires Feb 19 11,826.0 4.9% I 20.7% I -14.2% J 26.0% I 0.54 0.56
Mexico Bolsa index Feb 19 43,375.3 2.3% I 6.3% I -2.8% J 0.3% I 0.71 0.65
MENA and Africa
Egypt Market Vectors Egypt ETF Feb 19 33.2 1.8% I 0.3% I -7.1% J -43.8% J 0.40 0.46
(Gulf States) Market Vectors Gulf States ETF Feb 19 20.2 1.8% I 5.4% I -9.6% J -22.7% J 0.31 0.30
South Africa iShares MSCI South Africa Index Feb 19 46.2 3.8% I 16.5% I -16.2% J -30.9% J 0.69 0.67
(Africa) Market Vectors Africa ETF Feb 19 16.9 1.0% I 11.4% I -10.0% J -32.3% J 0.66 0.74
Commodities
USD Spot Oil West Texas Int. Feb 16 $29.1 3.9% I 2.0% I -30.3% J -45.8% J 0.38 0.57
USD Gold LME Spot Feb 19 $1,221.5 -1.5% J 12.4% I 13.8% I 0.3% I 0.10 0.07
Note: Correlations are based on daily arithmetic returns for the most recent 100 trading days.
www.lairdresearch.com February 22, 2016 Page 4

5. 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
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%, Q3/15: 9.9%
Net Profit Margin (S&P 500 Earnings / Revenue) − median: 6.6%, Q4/15: 8.1%
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
−5.00
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
−5.00
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
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
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90
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97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
0
10
20
30
40
50
0
10
20
30
40
50
Multiple
Multiple
12−month P/E ( median = 17.4, Feb = 20.2)
10−year CAPE ( median = 19.5, Feb = 23.4)
www.lairdresearch.com February 22, 2016 Page 5

6. S&P 500 Composite Distributions
This is a view of the price performance of the S&P 500 index com-
panies. The area of each box is proportional to the company’s market
cap, while the colour is determined by the percentage change in price
over the past month. In addition, companies are sorted according to
their industry group.
AAPL
−8.8%
GOOG
−5.5%
MSFT
−5.4%
FB
+2.3%
V
ORCL
+2.9%
INTC
−16%
IBM
−2.1%
CSCO
MA
−8.3%
QCOM
ACN
TXN EMC
PYPL
ADBE
CRM
ADP
CTSH
AVGO
HPQ
PAYX
EQIX
ADI
CA
ADS
MU
MSI
LLTC
WU
JNJ
+3.7%
PFE
−7.7%
MRK
−4.5%
GILD
−11%
AMGN
−5.2%
UNH
+1%
AGN
MDT
−0.51%
BMY
−4.8%
ABBV
−5.8%
LLY
−12%
CELG
BIIB
−11%
ABT
−10%
TMO
ESRX
−21%
REGN
SYK
MCK AET CI
BDX MYL
CAH
HUM BAX
ZTS
ZBH
EW
A LH
WFC
−9.1%
JPM
−9.1%
BAC
−26%
C
−24%
USB
−4.9%
GS
−17%
AIG
SPG AXP
BLK MS
MET
PNC PSA
AMT
BK
CB
COF
TRV
CME
MMC CCI
ICE
EQR
AON
BBT
AFL
ALL STT
PLD
DFS
VTR
PGR
STI
HCP
MCO
O
ESS
L
WY
PFG
XL CINF
AMZN
−16%
DIS
−7.7%
HD
−7.2%
CMCSA
+3.8%
MCD NKE
SBUX
LOW
−9%
TWX
TWC
PCLN
+3.1%
FOX
TJX
F
GM
TGT
CCL
YUM
VFC
LB
JCI
AZO
CBS
ROST
DG
DLTR
OMC
VIAB
RCL
CMG
SWK
GPC
M
MHK
HOT
TIF
SNI
GT
PG
+4.4%
WMT
+5.2%
KO
+3.2%
PEP
+0.82%
PM
+5.7%
MO
+5.5%
CVS
KHC
+1.1%
WBA
−6.6%
RAI
+9.5%
COST
−6.8%
MDLZ CL
KMB
KR
EL GIS
STZ K
MNST
SYY
HRL
BF−B
HSY
TAP
SJM
CHD
GE
−5.5%
MMM
+6.6%
UPS
BA
−18%
HON
UTX
LMT
+0.19%
UNP
+1.2%
DHR
GD CAT
RTN FDX
NOC
ITW
DAL
EMR ETN
DE WM
AAL
GLW
UAL CMI PH IR
ROK
AME
COL
TXT
XOM
+6.5%
CVX
−2.6%
SLB
+5.3%
OXY
+4.2%
PSX
COP
EOG
KMI
HAL
APC
SE BHI
PXD
FTI
HP
DUK
+4.7%
NEE
+11%
SO
D
AEP
PCG
PPL
SRE PEG
ED EIX
XEL
WEC
ES
DTE
FE
NI
DOW
DD
LYB ECL PX
SHW
IP
NEM
NUE
VMC
AA
ARG
T
+8%
VZ
+12%
Information Technology
Health Care
Financials
Consumer Discretionary
Consumer Staples Industrials
Energy Utilities
Materials
Telecommunications
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 Jan 4, 2016 to Feb 19, 2016
Average Median Median Median
Sector Change P/Sales P/Book P/E
Telecommunications Services 9.4% I 1.5 1.8 13.6
Utilities 6.6% I 1.8 1.8 19.2
Consumer Staples 1.9% I 2.5 5.6 27.2
Industrials -1.7% J 1.4 3.3 17.6
Energy -2.9% J 1.4 1.6 23.1
Average Median Median Median
Sector Change P/Sales P/Book P/E
Materials -4.1% J 1.2 3.7 22.6
Consumer Discretionary -5.0% J 1.5 3.9 17.4
Information Technology -5.3% J 3.2 4.1 21.9
Health Care -6.5% J 3.1 3.7 23.4
Financials -10.9% J 2.4 1.5 15.1
www.lairdresearch.com February 22, 2016 Page 6

7. 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 BAA 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
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01
02
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12
13
14
15
16
17
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 = 0.76, Sep = 0.93)
S&P 500 Price/Sales (median = 1.35, Dec = 1.82)
Equity and Debt Risk Premiums: Spread vs. Risk Free Rate (10−year US Treasury)
63
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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%
8%
9%
10%
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
Implied Equity Premium (median = 4.2%, Jan = 5.2%)
Debt (BAA) Premium (median = 2.0%, Jan = 3.5%)
www.lairdresearch.com February 22, 2016 Page 7

8. US Mutual Fund Flows
Fund flows describe the net investments in equity and bond mutual
funds in the US market, as described in ICI’s “Trends in Mutual Fund
Investing” report. Note however that this is only part of the story as
it does not include ETF fund flows - part of the changes are investors
entering or leaving the market, and part is investors shifting to ETF’s
from mutual funds.
US Net New Investment Cash Flow to Mutual Funds
US$billions(monthly)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
−40−2002040
Domestic Equity
World Equity
Taxable Bonds
Municipal Bonds
US Net New Investment Cash Flow to Mutual Funds
US$billions(Monthly)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
−60−40−200204060
Flows to Equity
Flows to Bonds
Net Market Flows
www.lairdresearch.com February 22, 2016 Page 8

9. 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 BAA 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(%)
15
16
17
18
19
20
21
22
23
24
25
26
0.0
0.5
1.0
1.5
2.0
2.5
0.0
0.5
1.0
1.5
2.0
2.5
Feb 18, 2016 (Today)
Jan 19, 2016 (1 mo ago)
Nov 18, 2015 (3 mo ago)
18 Feb 2015 (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
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. BAA Bond Spreads
4%
5%
6%
7%
8%
9%
4%
5%
6%
7%
8%
9%
Percent
AAA
BAA
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
median: 91.00
Feb 2016: 137.00
0
100
200
300
0
100
200
300
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
median: 36.13
Feb 2016: 31.82
0
100
200
300
0
100
200
300
Spread(bps)
www.lairdresearch.com February 22, 2016 Page 9

10. 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
−1%
0%
1%
2%
3%
4%
5%
6%
−1%
0%
1%
2%
3%
4%
5%
6%
US Inflation Rate YoY% (Jan = 1.3%)
US Inflation ex Food & Energy YoY% (Jan = 2.2%)
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
−10123456
PCE Inflation Rate YoY% (Dec = 0.58%)
PCE Core Inflation YoY% (Dec = 1.4%)
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 February 22, 2016 Page 10

11. QE Taper Tracker
The US has been using the program of Quantitative Easing to pro-
vide monetary stimulous to its economy. The Fed has engaged in a
series of programs (QE1, QE2 & QE3) designed to drive down long
term rates and improve liquidity though purchases of treasuries, mor-
gage backed securites and other debt from banks.
The higher demand for long maturity securities would drive up their
price, but as these securities have a fixed coupon, their yield would be
decreased (yield ≈ coupon / price) thus driving down long term rates.
In 2011-2012, “Operation Twist” attempted to reduce rates without
increasing liquidity. They went back to QE in 2013.
The Fed chairman suggested in June 2013 the economy was recover-
ing enough that they could start slowing down purchases (“tapering”).
The Fed backed off after a brief market panic. The Fed announced in
Dec 2013 that it was starting the taper, a decision partly driven by
seeing key targets of inflation around 2% and unemployment being less
than 6.5%. In Oct 2014, they announced the end of purchases.
QE Asset Purchases to Date (Treasury & Mortgage Backed Securities)
Trillions
0.0
0.5
1.0
1.5
2.0
2.5
0.0
0.5
1.0
1.5
2.0
2.5
QE1 QE2 Operation Twist QE3 TaperTreasuries
Mortgage Backed Securities
Total Monthly Asset Purchases (Treasury + Mortgage Backed Securities)
Billions
−100
−50
0
50
100
150
200
−100
−50
0
50
100
150
200
Month to date Feb 17: $12.3
Inflation and Unemployment − Relative to Targets
Percent
0
2
4
6
8
10
0
2
4
6
8
10
Target Unemployment 6.5%
Target Inflation 2%
U.S. 10 Year and 3 Month Treasury Constant Maturity Yields
Percent
0
1
2
3
4
5
0
1
2
3
4
5
2008 2009 2010 2011 2012 2013 2014 2015
Short Term Rates:
Once at zero, Fed moved to QE
Long Term Rates:
Moving up in anticipation of Taper?
www.lairdresearch.com February 22, 2016 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
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: Jan 4 2016 to Feb 12 2016
(Trade Weighted Currency Index of USD Trading Partners)
−3.0%
−1.5%
1.5%
3.0%
Euro
−4.0%
UK
1.4%
Japan
−5.5%
South Korea
1.0%
China
0.4%
India
2.2%
Brazil
−2.2%
Mexico
9.3%
Canada
−1.1%
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
−33.3%
AUS
2.6%
BRA
−3.8%
CHN
1.2%
IND
−1.0%
RUS
−13.1%
USA
3.5%
EUR
7.7%
JPY
13.0%
KRW
−8.3%
MXN
−5.7%
ZAR
−6.1%
www.lairdresearch.com February 22, 2016 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
Percent
3.03.54.04.5
median: 3.94
2015 Q4: 3.02
Repos Outstanding with Fed. Reserve
BillionsofDollars
0200400600
median: 57.81
Feb 2016: 298.75
Bank ROE − Assets between $300M−$1B
Percent
051015
median: 12.81
2015 Q4: 9.93
Consumer Credit Outstanding
%YearlyChange
−505101520
median: 7.57
Dec 2015: 6.92
Total Business Loans
%YearlyChange
−2001020 median: 8.62
Jan 2016: 10.75
US Nonperforming Loans
Percent
12345
median: 2.05
2015 Q4: 1.55
St. Louis Financial Stress Index
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
0246
median: 0.094
Feb 2016: −0.24
Commercial Paper Outstanding
TrillionsofDollars
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1.01.41.82.2
median: 1.33
Feb 2016: 1.08
Residential Morgage Delinquency Rate
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
246810
median: 2.33
2015 Q4: 5.17
www.lairdresearch.com February 22, 2016 Page 13

14. 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
median: 6.10
Jan 2016: 4.90
4
5
6
7
8
9
10
11
4
5
6
7
8
9
10
11
Percent
4 5 6 7 8 9 10
2.02.53.03.54.0
Beveridge Curve (Unemployment vs. Job Openings)
Unemployment Rate (%)
JobOpenings(%totalEmployment)
Dec 2000 − Dec 2008
Jan 2009 − Nov 2015
Dec 2015
Participation Rate
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
6364656667
median: 66.00
Jan 2016: 62.70
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
−5000500
median: 164.00
Jan 2016: 151.00
www.lairdresearch.com February 22, 2016 Page 14

15. 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: 8.70
Jan 2016: 10.90
(U6) Unemployed + PT + Marginally Attached
Percent
810121416
median: 9.80
Jan 2016: 9.90
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
50100150200
median: 107.34
Feb 2016: 84.01
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
01234567
median: 0.80
Jan 2016: 2.15
Services: Temp Help
MillionsofPersons
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1.52.02.53.0
median: 2.26
Jan 2016: 2.92
−200 0 200 400 600
15
20
25
30
35
40
Annual Change in Employment Levels (000s of Workers)
Averagewages($/hour)
Private Industry Employment Change (Jan 2015 − Jan 2016)
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 February 22, 2016 Page 15

16. 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 Sector: Real Output
YoYPercentChange
−1001020
median: 8.70
2015 Q4: 7.06
ISM Manufacturing − PMI
Index
3040506070
Jan 2016: 48.20
manufac. expanding
manufac. contracting
ISM Manufacturing: New Orders Index
Index
304050607080
Jan 2016: 51.50
Increase in new orders
Decrease in new orders
Non−Manufac. New Orders: Capital Goods
BillionsofDollars
40506070
median: 57.84
Dec 2015: 65.96
Average Weekly Hours: Manufacturing
Hours
3940414243
median: 41.20
Jan 2016: 41.80
Industrial Production: Manufacturing
YoYPercentChange
−15−50510
median: 3.08
Jan 2016: 1.23
Total Business: Inventories to Sales Ratio
Ratio
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1.11.21.31.41.51.6
median: 1.36
Dec 2015: 1.39
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
−0.50.00.5
Dec 2015: −0.02
Above ave growth
Below ave growth
ISM Non−Manufacturing Bus. Activity Index
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
35455565
Jan 2016: 53.90
Growth
Contraction
www.lairdresearch.com February 22, 2016 Page 16

17. 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: 88.80
Jan 2016: 92.00
Consumer Loans (All banks)
YoY%Change
−10010203040
median: 7.50
Jan 2016: 6.16
Accounting
Change
Deliquency Rate on Consumer Loans
Percent
2.03.04.0
median: 3.46
2015 Q4: 2.02
New Orders: Durable Consumer Goods
YoY%Change
−20020
median: 4.19
Dec 2015: 2.80
New Orders: Non−durable Consumer Goods
YoY%Change
−2001020
median: 4.20
Dec 2015: −8.06
Personal Consumption & Housing Index
Index
−0.40.00.20.4
median: 0.02
Dec 2015: −0.07above 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
10121416182022
median: 14.84
Jan 2016: 17.46
Personal Saving Rate
Percent
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
246810
median: 5.50
Dec 2015: 5.50
Real Retail and Food Services Sales
YoY%Change
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
−10−505
median: 2.45
Jan 2016: 2.07
www.lairdresearch.com February 22, 2016 Page 17

18. 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
150200250300
Personal Income vs. Housing Prices (Inflation adjusted values)
NewHomePrice(000's)
Disposable Income Per Capita (000's)
Dec 2015
r2
: 89.6%
Range: Jan 1959 − Dec 2015
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: 1.34
Jan 2016: 1.20
New Home Median Sale Price
SalePrice$000's
100150200250300
Dec 2015: 288.90
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
4050607080
median: 66.50
2015 Q3: 56.70
New Homes: Median Months on the Market
Months
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
468101214
median: 4.90
Dec 2015: 3.00
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
4681012
median: 5.90
Dec 2015: 5.20
www.lairdresearch.com February 22, 2016 Page 18

19. 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 − Q3 2015
−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 − Q3 2015
−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 February 22, 2016 Page 19

20. Global Housing
The Bank for International Settlements has begun collecting global
housing indicies, which are useful for showing what has been happening
with global house prices. Note that these are not all the same data set -
each country measures housing prices in slightly different ways, so they
are only broadly comparable. Black lines are the data series, blue bars
on the right axis show the year over year percent change.
Brazil − Metro All Dwellings
Q12011=100
6080100140
Oct 2015: 140.76
Chile − All Dwellings
Jun 2015: 127.92
Peru (Lima) − All Dwellings
Sep 2015: 188.63
−4002040
Mexico − All Dwellings
Q12011=100
6080100140
Sep 2015: 127.11
China (Beijing) − All Dwellings
Nov 2015: 130.87
Hong Kong − Residential Prices
Nov 2015: 171.01
−4002040
Indonesia − Major Cities housing
Q12011=100
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
6080100140
Sep 2015: 135.00
India − Major Cities housing
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Sep 2015: 205.91
Singapore − All Dwellings
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Sep 2015: 100.00
−4002040
www.lairdresearch.com February 22, 2016 Page 20

21. Philippines (Manila) − Flats
Q12011=100
6080120
Sep 2015: 146.25
Japan − All Dwellings
Oct 2015: 103.90
Australia − All Dwellings
Sep 2015: 126.97
−4002040
New Zealand − All Dwellings Big Cities
Q12011=100
6080120
Sep 2015: 153.58
Turkey − All Dwellings
Nov 2015: 191.35
South Africa − Residential
Dec 2015: 113.54
−4002040
Israel − All Dwellings
Q12011=100
6080120
Oct 2015: 133.33
Korea − All Dwellings
Dec 2015: 113.80
Russia − All Dwellings (Urban)
Sep 2015: 123.98
−4002040
Euro zone − All Dwellings
Q12011=100
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
6080120
Sep 2015: 99.15
Canada − New Houses
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Nov 2015: 109.40
US − New Single Family Houses
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
Dec 2015: 123.48
−4002040
www.lairdresearch.com February 22, 2016 Page 21

22. 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 − January 2016
<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
52.3
Global PMI
50.9
TWN
50.6MEX
52.2
KOR
49.5
JPN
52.3
VNM
51.5
IDN
48.9
ZAF
49.6
AUS
51.5
BRA
47.4
CAN
49.3
CHN
48.4
IND
51.1
RUS
49.8
SAU
53.9
USA
52.4
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
−0.9
Global PMI
0.2
TWN
−1.1MEX
−0.2
KOR
−1.2
JPN
−0.3
VNM
0.2
IDN
1.1
ZAF
0.5
AUS
−0.4
BRA
1.8
CAN
1.8
CHN
0.2
IND
2.0
RUS
1.1
SAU
−0.5
USA
1.2
Purchase Managers Index (Manufacturing) − China, Japan, USA, Canada, France, Germany, Italy, UK, Australia
04
05
06
07
08
09
10
11
12
13
14
15
16
3040506070
3040506070
Business Conditions Contracting
Business Conditions Expanding
www.lairdresearch.com February 22, 2016 Page 22

23. 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.
Jan14
Feb14
Mar14
Apr14
May14
Jun14
Jul14
Aug14
Sep14
Oct14
Nov14
Dec14
Jan15
Feb15
Mar15
Apr15
May15
Jun15
Jul15
Aug15
Sep15
Oct15
Nov15
Dec15
Jan16
Australia
India
Indonesia
Viet Nam
Taiwan
China
Korea
Japan
South Africa
Saudi Arabia
Turkey
Russia
United Kingdom
Greece
Germany
France
Italy
Czech Republic
Spain
Poland
Ireland
Netherlands
Eurozone
Brazil
Mexico
Canada
United States
Global PMI 53.0 53.2 52.4 51.9 52.2 52.6 52.4 52.6 52.2 52.2 51.8 51.6 51.7 52.0 51.7 51.0 51.2 51.0 51.0 50.7 50.7 51.3 51.2 50.7 50.9
53.7 57.1 55.5 55.4 56.4 57.3 55.8 57.9 57.5 55.9 54.8 53.9 53.9 55.1 55.7 54.1 54.0 53.6 53.8 53.0 53.1 54.1 52.8 51.2 52.4
51.7 52.9 53.3 52.9 52.2 53.5 54.3 54.8 53.5 55.3 55.3 53.9 51.0 48.7 48.9 49.0 49.8 51.3 50.8 49.4 48.6 48.0 48.6 47.5 49.3
54.0 52.0 51.7 51.8 51.9 51.8 51.5 52.1 52.6 53.3 54.3 55.3 56.6 54.4 53.8 53.8 53.3 52.0 52.9 52.4 52.1 53.0 53.0 52.4 52.2
50.8 50.4 50.6 49.3 48.8 48.7 49.1 50.2 49.3 49.1 48.7 50.2 50.7 49.6 46.2 46.0 45.9 46.5 47.2 45.8 47.0 44.1 43.8 45.6 47.4
54.0 53.2 53.0 53.4 52.2 51.8 51.8 50.7 50.3 50.6 50.1 50.6 51.0 51.0 52.2 52.0 52.2 52.5 52.4 52.3 52.0 52.3 52.8 53.2 52.3
54.8 55.2 53.7 53.4 53.6 52.3 53.5 51.7 52.2 53.0 54.6 53.6 54.1 52.2 52.5 54.0 55.5 56.2 56.0 53.9 53.0 53.7 53.5 53.4 52.4
52.8 52.9 55.5 56.1 55.0 55.3 55.4 57.3 55.7 56.6 56.2 56.9 55.1 57.5 56.8 55.8 57.1 54.6 56.7 53.6 53.8 53.6 53.3 54.2 54.3
55.4 55.9 54.0 52.0 50.8 50.3 49.4 49.0 49.5 51.2 53.2 52.8 55.2 55.1 54.8 54.0 52.4 54.3 54.5 51.1 50.9 52.2 52.1 52.1 50.9
52.2 52.5 52.8 52.7 52.9 54.6 53.9 52.8 52.6 52.6 54.7 53.8 54.7 54.2 54.3 54.2 55.8 54.5 53.6 53.2 51.7 51.3 53.1 53.0 55.4
55.9 56.5 55.5 56.5 57.3 54.7 56.5 54.3 55.6 54.4 55.6 53.3 56.1 55.6 56.1 54.7 55.5 56.9 57.5 56.6 55.5 54.0 54.2 55.6 56.9
53.1 52.3 52.4 54.0 53.2 52.6 51.9 49.8 50.7 49.0 49.0 48.4 49.9 51.9 53.3 53.8 54.8 54.1 55.3 53.8 52.7 54.1 54.9 55.6 53.2
49.3 49.7 52.1 51.2 49.6 48.2 47.8 46.9 48.8 48.5 48.4 47.5 49.2 47.6 48.8 48.0 49.4 50.7 49.6 48.3 50.6 50.6 50.6 51.4 50.0
56.5 54.8 53.7 54.1 52.3 52.0 52.4 51.4 49.9 51.4 49.5 51.2 50.9 51.1 52.8 52.1 51.1 51.9 51.8 53.3 52.3 52.1 52.9 53.2 52.3
51.2 51.3 49.7 51.1 51.0 49.4 48.7 50.1 48.4 48.8 49.1 49.4 48.3 48.4 48.9 46.5 48.0 46.9 30.2 39.1 43.3 47.3 48.1 50.2 50.0
56.7 56.2 55.3 57.3 57.0 57.5 55.4 52.5 51.6 53.2 53.5 52.5 53.1 54.1 54.4 51.9 52.0 51.4 51.9 51.6 51.8 55.5 52.7 51.9 52.9
48.0 48.5 48.3 48.5 48.9 49.1 51.0 51.0 50.4 50.3 51.7 48.9 47.6 49.7 48.1 48.9 47.6 48.7 48.3 47.9 49.1 50.2 50.1 48.7 49.8
52.7 53.4 51.7 51.1 50.1 48.8 48.5 50.3 50.4 51.5 52.2 51.4 49.8 49.6 48.0 48.5 50.2 49.0 50.1 49.3 48.0 49.5 50.9 52.2 50.9
59.7 58.6 57.0 58.5 57.0 59.2 60.1 60.7 61.8 59.1 57.6 57.9 57.8 58.5 60.1 58.3 57.0 56.1 57.5 58.7 56.5 55.7 56.3 54.4 53.9
50.3 51.5 50.3 47.4 44.3 46.6 45.9 49.0 50.7 52.7 50.5 50.2 49.8 50.0 51.6 51.5 50.1 49.2 48.9 49.3 47.9 47.5 49.6 49.1 49.6
56.6 55.5 53.9 49.4 49.9 51.5 50.5 52.5 51.7 52.4 52.0 52.0 52.2 51.6 50.3 49.9 50.9 50.1 51.2 51.7 51.0 52.4 52.6 52.6 52.3
50.9 49.8 50.4 50.2 49.5 48.4 49.3 50.3 48.8 48.7 49.0 49.9 51.1 51.1 49.2 48.8 47.8 46.1 47.6 47.9 49.2 49.1 49.1 50.7 49.5
49.5 48.5 48.0 48.1 49.4 50.7 51.7 50.2 50.2 50.4 50.0 49.6 49.7 50.7 49.6 48.9 49.2 49.4 47.8 47.3 47.2 48.3 48.6 48.2 48.4
55.5 54.7 52.7 52.3 52.4 54.0 55.8 56.1 53.3 52.0 51.4 50.0 51.7 52.1 51.0 49.2 49.3 46.3 47.1 46.1 46.9 47.8 49.5 51.7 50.6
52.1 51.0 51.3 53.1 52.5 52.3 51.7 50.3 51.7 51.0 52.1 52.7 51.5 51.7 50.7 53.5 54.8 52.2 52.6 51.3 49.5 50.1 49.4 51.3 51.5
51.0 50.5 50.1 51.1 52.4 52.7 52.7 49.5 50.7 49.2 48.0 47.6 48.5 47.5 46.4 46.7 47.1 47.8 47.3 48.4 47.4 47.8 46.9 47.8 48.9
51.4 52.5 51.3 51.3 51.4 51.5 53.0 52.4 51.0 51.6 53.3 54.5 52.9 51.2 52.1 51.3 52.6 51.3 52.7 52.3 51.2 50.7 50.3 49.1 51.1
46.7 48.6 47.9 44.8 49.2 48.9 50.7 47.3 46.5 49.4 50.1 46.9 49.0 45.4 46.3 48.0 52.3 44.2 50.4 51.7 52.1 50.2 52.5 51.9 51.5
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24. Canadian Indicators
Retail Trade (SA)
YoYPercentChange
−50510
median: 4.66
Dec 2015: 2.57
Total Manufacturing Sales Growth
YoYPercentGrowth
−20−1001020
median: 3.79
Dec 2015: −1.59
Manufacturing New Orders Growth
YoYPercentGrowth
−30−100102030
median: 4.17
Dec 2015: −6.54
10yr Government Bond Yields
0246810
median: 5.69
Jan 2016: 1.24
Manufacturing PMI
48505254
Jan 2016: 49.30
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
−101234
median: 1.31
Jan 2016: 0.76
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
−101234
median: 1.92
Jan 2016: 2.01
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
1.31.41.51.6
median: 1.35
Dec 2015: 1.40
www.lairdresearch.com February 22, 2016 Page 24

25. 6.6 6.8 7.0 7.2 7.4 7.6
1.31.41.51.61.71.81.9
Beveridge Curve (Mar 2011 − Oct 2015)
as.numeric(can.bev$ui.rate)
as.numeric(can.bev$vacancies)
Mar 2011 − Dec 2012
Jan 2013 − Sep 2015
Oct 2015
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
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 7.2%
Alberta 7.4%
Ontario 6.7%
Debt Service Ratios (SA)
Percent
0246810
Total Debt: 6.3%
Mortgage: 3.3%
Consumer Debt: 6.2%
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
−40−2002040
Permits
Starts
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26. 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
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
−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
−60−40−20020
Country Employment
Expect.
Unempl.
(%)
Bond Yields
(%)
Retail
Turnover
Manufacturing
Turnover
Inflation
(YoY %)
Industry
Orderbook
PMI
Series Dates Jan 2016 Jan 2016 Jan 2016 Dec 2015 Dec 2015 Dec 2015 Jan 2016 Jan 2016
France -9.1 J 10.2 K 0.84 J 105.1 I 110.4 I 0.3 I -12.5 J 50.0 J
Germany -4.3 J 4.5 K 0.43 J NA 114.6 I 0.2 J -7.7 I 52.3 J
United Kingdom 1.7 J 5.1 K 1.73 J 112.8 J NA 0.1 I -13.4 J 52.9 I
Italy -1.5 J 11.4 K 1.53 J 101.1 I NA 0.1 J -13.4 J 53.2 J
Greece -7.7 J 24.6 J 9.08 I NA NA 0.4 I -26.9 I 50.0 J
Spain -1.0 J 20.8 J 1.72 I NA NA -0.1 I -3.8 J 55.4 I
Eurozone (EU28) -2.3 J 9.0 K 1.42 J 106.8 J 109.8 J 0.1 I -11.1 J NA
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27. Government Bond YieldsLongTermYields%
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
0246810
Economic Sentiment
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
60708090110130
Consumer Confidence
Index
97
98
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
−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
median: 1.90
Dec 2015: 0.20
−1
0
1
2
3
4
5
6
7
Euro Area
US
Harmonized Inflation: Nov 2015
AUT
1.1%
BGR
−0.9%
DEU
0.2%
ESP
−0.1%
FIN
−0.3%
FRA
0.3%
GBR
0.1%
GRC
0.4%
HRV
−0.3%
HUN
1.0%
IRL
0.2%
ISL
0.7%
ITA
0.1%
NOR
2.4%
POL
−0.5%
ROU
−0.7%
SWE
0.7%
<−1.0%0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% >7.0%
YoY % Change in Prices
PMI: January 2016
<40.042.0 44.0 46.0 48.0 50.0 52.0 54.0 56.0 58.0>60.0
Steady ExpandingContracting
BRA
47.4
CAN
49.3
DEU
52.3
ESP
55.4
FRA
50.0
GBR
52.9
GRC
50.0
IRL
54.3
ITA
53.2
MEX
52.2
POL
50.9
SAU
53.9
TUR
50.9
USA
52.4
RUS
49.8
PMI Change: Dec − Jan
<−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
1.8
DEU
−0.9
ESP
2.4
FRA
−1.4
GBR
1.0
GRC
−0.2
IRL
0.1
ITA
−2.4
POL
−1.2
TUR
−1.3
USA
1.2
RUS
1.1
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28. 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
4045505560
Jan 2016: 48.40
Shanghai Composite Index
IndexValue(MonthlyHigh/Low)
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
0100030005000
Feb 2016: 2763.49
Electricity Generated
100MillionKWH(logscale)
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
1000200030005000
Dec 2015: 4910.00
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
98100102104106108110
median: 103.85
Dec 2015: 103.70
Exports
YoYPercentChange
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
−20020406080
median: 18.40
Dec 2015: −1.40
Retail Sales Growth
YoYPercentChange
99
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
101520
median: 12.90
Dec 2015: 11.10
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29. Global Climate Change
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 Jul 2015 - Dec 2015
<−4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 >4.0
Anomalies in Celcius WarmerCooler Anomalies in Celcius
−4 −2 0 2 4
Historic Global Temperature Deviations
DegreesCelciusDeviations
−0.50.00.51.0
Jan 2016: 1.04
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
www.lairdresearch.com February 22, 2016 Page 29