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Dr. Michael Swanson's presentation from the 2014 Minnesota AgriGrowth Council Annual Meeting and Conference
Citation preview
November 2014
Global environment
Local execution
Michael Swanson Ph.D.
Wells Fargo
Key questions
1. What are commodities worth?2. Why are commodities worth that?3. Who gets what share?4. What differentiates the producers?5. What’s your “play”
2
Where does volatility come from?
Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14$0
$1
$2
$3
$4
$5
$6
$7
$8
Minnesota Corn Prices and Cost of Productionper bushel
GRAIN in $ / BUAverage cost of production
3
More money – More risk
4
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013F 2014F$0
$2
$4
$6
$8
$10
$12
$14
$16
$18
MN Farm Income in Billions
Gross expensesNet Farm Income
Loops create cycles
Monetary
Policy
Economy
Fiscal Policy
Agriculture Energy
5
Interest rates and valuations
Federal Reserve Ultra low rates are not about ag They have inflated valuations They have influenced exchange rates
Foreign central banks Respond to the Federal Reserve Focused on their economies
6
Bullish or Bearish? Or wrong?
Apr-73 Apr-78 Apr-83 Apr-88 Apr-93 Apr-98 Apr-03 Apr-08 Apr-13-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%Performance Gap: Actual GDP less Potential
7
Farm the best – Forget the rest
8
$-
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
$9,000 MN South Central Farm Land
Productivity 50s
Productivity 70s
Productivity 90s
Per Acre
42 degrees in Fargo ND
9
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000 MN Ag Land Sales Price$ per acre
Me-dian
Source: U of MN MLE, Wells Fargo
What about Minnesota?
10Jan-93 Jan-95 Jan-97 Jan-99 Jan-01 Jan-03 Jan-05 Jan-07 Jan-09 Jan-11 Jan-13
$-
$100
$200
$300
$400
$500
$600
0
1
2
3
4
5
6
7
8
9"Cash flow v. Opportunity Cost"
Returns w/o labor, mgmt or land15 Fixed Rate Mortgage
Per acre Percent
Keep an eye on the future not past
11Jan-93 Jan-95 Jan-97 Jan-99 Jan-01 Jan-03 Jan-05 Jan-07 Jan-09 Jan-11 Jan-13
$-
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
$14,000
$16,000
$18,000
Implied Net Present Values
How are the cycles linked?
NAFTAEconomy
NAFTAAgriculture
GlobalAgriculture
GlobalEconomy
12
How fast can panic spread?
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015-3%
-2%
-1%
0%
1%
2%
3%
4%
5%
Real GDP GrowthWorld less USAUnited States
13
China
What is the answer to the question?
14
A Standard Pareto Distribution
15
China/Hong Kong
Canada
Mexico
Japan
Korea, South
Taiwan
Indonesia
Germ
any(*)
Philippines
Vietnam
United Kingdom
Netherlands
Turkey
Brazil
Spain
Australia(*)
Egypt
Venezuela
Colombia
Thailand
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
16%
32%
45%54%
59%
61%
Cumulative Agricultural Exports by Country
The Wal*Mart Effect
16
2007 2008 2009 2010 2011 2012 2013 Jan - Sep 2014
-$5
$0
$5
$10
$15
$20
$25
2.6 6.5
9.1
13.8 16.1
22.0 22.7
11.3 2.6
10.3 3.9
5.2
7.1
0.5
(1.1) (3.3)
Net Trade BalanceAg, Forestry and Fishing
ROWChina/HK
Billions
What has happened in 2014 so far?
17
Product 2009 2010 2011 2012 2013Jan - Sep
2013Jan - Sep
2014Chg YTD
Bulk 10.2 13.4 14.1 19.7 17.8 7.7 7.9 0.2$ Intermediate 0.9 2.2 1.9 2.4 3.5 2.5 2.7 0.2$ Consumer Oriented 1.1 1.3 2.2 2.6 3.5 2.0 2.2 0.2$ Forest Products (1.7) (1.5) (0.6) (1.3) (0.7) (0.6) (0.4) 0.1$ Fish Products (1.4) (1.5) (1.4) (1.4) (1.4) (0.9) (1.1) (0.2)$
Grand Total 9.1 13.8 16.1 22.0 22.7 10.6 11.3 0.6$
China/Hong Kong Net Ag Trade in Billions
Which countries drive prices Same commodity different price
Market based signals Policy based signals
Which commodity Protein Energy Minerals
Sell Side Buy Side
18
Compare and contrast
-5
0
5
10
15
20
25
30
35
(2.2)
29.6
US Net Agricultural Trade
IndiaChina/HK
Billions of $s
19
Does India ever find a higher gear?
-
1,000
2,000
3,000
4,000
5,000
6,000
4,832
1,483
GDP in Constant US Dollars
ChinaIndia
Billions
20
Question your assumptions Global demand growth
Population GDP Diet
Global supply growth Acreage Productivity Trade barriers
Policy shocks
21
Productivity
Income
Population
22
The gears work together
The numbers everyone quotes
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
-
1
2
3
4
5
6
7
8
$0
$10
$20
$30
$40
$50
$60
$70
$80
Global Population (left axis)
Global GDP (right axis)
23
Same numbers different dimension
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
-
0.5
1.0
1.5
2.0
2.5
(3)
(2)
(1)
-
1
2
3
4
5
6
7 Global Population (left axis)Global GDP (right axis)
24
Big numbers all around
500
1,000
1,500
2,000
2,500
f(x) = 27.9573375901876 x + 804.315147474748R² = 0.974784532143057
Global Grain ProductionMillions of metric tons
25
The feedback mechanism in action
285
295
305
315
325
335
345
355 Global Grain per CapitaKilograms
26
No one punches harder than the US in the grain world Top 10 countries
86% of the acreage 90% of the production
Remaining 112 countries 14% of acreage 10% of the production
That still misses the point
27
Just like the “Big 10” a mix of champs and chumps
Area Harvested
Production Yield
CountryGrain (1000
HA)Grain (1000
MT)Grain
(MT/HA)% of
acreage% of
productionYield
PunchChina 62,271 343,322 5.5 14.1 21.8 1.5 United States 58,009 404,141 7.0 13.2 25.6 1.9 European Union 57,308 296,740 5.2 13.0 18.8 1.4 India 54,877 135,140 2.5 12.5 8.6 0.7 Russia 38,071 84,401 2.2 8.6 5.3 0.6 Brazil 18,860 86,920 4.6 4.3 5.5 1.3 Australia 18,700 36,920 2.0 4.2 2.3 0.6 Kazakhstan 14,882 15,504 1.0 3.4 1.0 0.3 Canada 14,845 55,894 3.8 3.4 3.5 1.1 Ukraine 14,580 55,930 3.8 3.3 3.5 1.1
28
How much grain does the world need?
Per capita Best measure Substitutes
Grain Meat
Efficiency of conversion Diet Demographics Distribution
29
Trend versus Cycle
1.25
1.45
1.65
1.85
2.05
2.25
2.45
2.65
f(x) = 0.000224580898538896 x + 2.50044468807954R² = 0.0221067393306588
f(x) = 0.00973092497475068 x + 1.43661275307303R² = 0.962728298154432
f(x) = 0.00197519499824517 x + 1.2960218090599R² = 0.650479333602565
Global Supplies Per Capita
GrainsLinear (Grains)
Log of Per Capita
30
You “economic” life is in their hands
Monetary policy When does “cheap” money end? Who is the furthest out of line? Values
China trade Trade policies Internal supply competition
Biofuels policy Energy pricing and arbitrage Lobbyists in action
31