Philip Abbott, Purdue University
Exchange Rates, Prices, and Agricultural Trade:
What Have We Learned?
IATRC sponsored International Track session,
AAEA Annual Meeting
Denver, CO July 27, 2010
Department of Agricultural Economics
Purdue University

Weak dollar has meant strong agricultural exports
Exchange rate depreciation and inflation raise commodity prices
Macroeconomic policy dominates agricultural policy
In determining trade, prices and so farm income
Exchange rate the strongest ag-macro linkage
Exchange rate a key determinant of agricultural outlook (and of recent food crisis price increases)
WASDE reports highlight macro conditions, exchange rates
Financial crisis impacts worked through macro variables
Department of Agricultural Economics
Purdue University

60
40
20
0
120
U.S. Agricultural Trade and the USDA Real Exchange Rate
(RER)
100
80
200
150
100
50
0
Ag Exports Grains, Feeds & Oilseeds Ag Imports Ag Trade Balance RER

Some argued exchange rate unimportant recently
Keith Collins – using USDA ag index
Daryl Ray – trade flows after 1990 unaffected
Others (including me)have asserted important role, at least for macro forces in food crisis –
Abbott, Hurt, Tyner
Some reviews non-committal (its complicated!)
Trostle – USDA
Subsequent time series econometric evidence is contradictory, inconclusive
Department of Agricultural Economics
Purdue University

Strong theoretical foundations
Schuh – Law of One Price (LOP) in partial equilibrium
General equilibrium – real exchange rates
Monetary policy and nominal exchange rates
Recent linkages between agriculture and energy
Inconclusive, mixed empirical evidence – History
Partial equilibrium econometric modeling – 1980s
GE models: real only, long run, neoclassical closure
Marrying macro and commodity models – 1990s
Overshooting applied to ag commodities
Time series econometrics
1980s-90s VARs on monetary policy
Late 2000s - Food crisis explanations
Minimal economic assumptions – let data speak
Department of Agricultural Economics
Purdue University

Exchange rate change not ceteris paribus
Real exchange rate = P tradeables/ P home goods
Cross price effects matter and are difficult to estimate
Substitution means larger commodity elasticities than aggregate ag elasticities – aggregation matters to cross- prices used
Exchange rates and prices are endogenous
Macroeconomic variables also endogenous, including inflation
US a large country in agricultural markets
Endogeneity, market power, diminished trade impacts
Bilateral exchange rates move independently
Some currencies pegged to dollar
Aggregate variables may be driven by multiple mechanisms!!
Quantitative impacts vary – mechanisms matter to differing degrees depending on economic conditions  structural changes
Department of Agricultural Economics
Purdue University

2.000
1.750
1.500
1.250
1.000
0.750
US $ Exchange Rates, 2000-2010
Euro
Chinese Yuan
Brazilian Real
IMF NEER
USDA Ag Index
Japanese Yen
Department of Agricultural Economics
Purdue University

Exchange rate effects on commodity prices
Exchange rate effects on trade
Depends on price linkage, net trade elasticties
What determines exchange rates?
Trade balance
Current account = capital account
Interest rates and capital flows
Safe haven, Petro dollars, Chinese reserves,
Sovereign debt, Commodities as speculative assets…
Monetary policy and inflation
Will focus here on commodity price impacts: the easiest, and essential
Department of Agricultural Economics
Purdue University

3
2.5
2
1.5
1
0.5
0
5
4.5
4
3.5
Crude Oil
Gold
Corn
IMF Commodity Index
IMF NEER
$/Euro
Department of Agricultural Economics
Purdue University

Trade/ LOP Pd = e Pw
Inflationary overshooting Macro linkage
Asset prices, commodity prices flexible
Manufacturing and services prices sticky downward
Inflationary expectations, speculation and commodities as assets
Energy linkages
Ethanol ties corn to crude oil after 2005
Capacity, RFS minimum, blending wall constraints matter
Department of Agricultural Economics
Purdue University

Pd = e Pw (Schuh model)
Ԑ Pd-e = ∂ ln Pd / ∂ ln e = 1 if LOP holds
Trade impacts depend on net export demand elasticity versus domestic elasticties
Smaller impact in large country case
Low price transmission due to endogenous policy or poor market integration could reduce impact
Imperfect exchange rate pass-through
Low stocks make domestic market less elastic
Exchange rate impact greater when stocks are low
Will also affect apparent price impact when Pw is endogenous
Department of Agricultural Economics
Purdue University

6
5
4
8
7
3
2
1
0
0
Domestic Supply Demand Equilibrium
Demand
Supply
Net import demand after depreciation
World Market Equilibrium
Net export supply
= supply - demand e Pw
Net import demand by ROW (foreigners)
5 10
Qs, Qd, E
15 20
Small Country case
M E
LOP ==> Ԑ e = ∂Pd/∂e e/Pd = 1
Department of Agricultural Economics
Purdue University

8
7
6
5
4
3
2
1
0
0
Domestic Supply Demand Equilibrium
Demand
Supply
Net import demand after depreciation
World Market Equilibrium
Net export supply
= supply - demand e Pw
Net import demand by ROW (foreigners)
5 10
Qs, Qd, E
15 20
Large Country case
M E
LOP ==> Ԑ e = ∂Pd/∂e e/Pd < 1
Department of Agricultural Economics
Purdue University

6
5
4
3
8
7
2
1
0
0
Domestic Supply Demand Equilibrium
Demand
Supply
Net import demand after depreciation
World Market Equilibrium
Net export supply
= supply - demand e Pw
Net import demand by ROW (foreigners)
5 10
Qs, Qd, E
15 20
Inelastic stocks demand
M E
Department of Agricultural Economics
Purdue University

$ Corn price index against U.S. stocks-to-use,
September 1990 to December 2008
€ Corn price index against U.S. stocks-touse, September 1990 to December 2008
Apr-08
Jul-96
May-96
Mar-08
Aug-96
Jun-08
Jul-08
May-08
08
Feb-08
Jan-08
,Sep
Oct 08
Dec-07
Nov 08
Dec 08
Nov-07
Sep-07Oct-07 y = 0.5305x
-0.402
R² = 0.4213
May-96
Jul-96
Aug-96
Jun-08
Apr-08
Mar-08 Feb-08
Jan-08
Sep-07
Nov-07
Oct-07 y = 0.4994x
-0.317
R² = 0.4657
U.S. stocks-to-use U.S. stocks-to-use
Department of Agricultural Economics
Purdue University

1990-2010 Stocks t-stat
Crude oil
Corn
Soybeans
Wheat
Rice +
Ԑ Pd-e t-stat
1.62
6.8**
1.11
1.21
0.74
11.6**
13.5**
25.4**
0.66
20.8**
* significant at 10%
** significant at 1%
+ Price data begin in 1990, except for rice, which begins in 2000
Low Abundant on difference
1.62
1.71
1.89
1.53
0.35
0.48
0.66
2.29
13.3**
15.2**
10.4**
4.0**
Department of Agricultural Economics
Purdue University

Overshooting hypothesis – Commodity price impacts exceed exchange rate change in short run since manufacturing prices are sticky
Recessions – prices sticky downward
Loose monetary policy – commodity prices exhibit inflationary expectations first (Frankel)
Commodity boom – inflationary expectations and speculation
Commodity prices other than agriculture began increasing in about
2003, hedge fund investments begin then
Department of Agricultural Economics
Purdue University

Department of Agricultural Economics
Purdue University

Crude oil
Corn
Soybeans
Wheat
Business cycle t-stat
Monetary policy t-stat Commodity boom t-stat
Boom Recession on difference
Tight Loose on difference 90-02, 09-10
03-08 on difference
0.58
0.67
0.76
1.13
2.48
1.45
1.59
1.61
6.6**
6.7**
7.9**
3.5**
Rice + 1.55
2.57
7.0**
* significant at 10%
** significant at 1%
+ Price data begin in 1990, except for rice, which begins in 2000
1.16
0.95
0.86
1.37
1.4
1.77
1.16
1.33
1.4
2.47
2.0*
1.7*
4.2**
0.2
6.9**
0.54
1.00
1.06
1.15
2.42
3.59
1.29
1.49
1.84
1.95
2.4*
13.0**
3.7**
5.4**
2.6**
Department of Agricultural Economics
Purdue University

Since 2005 U.S. energy legislation ethanol has become a substitute for gasoline , capacity built in response
Crude oil also subject to LOP/Trade and Macro linkage effects from exchange rate
Ethanol link passes ex-impacts on crude oil to corn
Energy linkage didn’t matter until plant capacity built
RFS minimum, capacity constraints and “blending wall all limit/ break linkage
Crude oil price changes go to rents when constraints bind
Department of Agricultural Economics
Purdue University

5
4
3
2
1
0
0
10
9
8
7
6
RFS - Minimum ethanol production
Corn price determined by gasoline/ crude oil price
Ethanol plant capacity constraining
2 4 6
Stocks demand (carry-out)
Feed demand
8 10 12
Ethanol demand for corn
@ Higher oil price
14 16 18
Food demand
Total domestic demand
20

1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
crude/corn gas/corn ethanol/corn
“Gold rush”
Capacity
Constraints
RFS binds

Crude oil
Corn
Soybeans
Wheat
Rice +
1990-2010
Ԑ Pd t-stat
1.62
6.8**
1.11
11.6**
1.21
13.5**
0.74
25.4**
0.66
20.8**
Ethanol era
90-06 06-08
0.74
0.73
3.61
t-stat on difference
9.8**
1.95
10.7**
0.94
0.93
1.82
7.4**
2.45
13.0**
1.96
2.45
2.9**
* significant at 10%
** significant at 1%
+ Price data begin in 1990, except for rice, which begins in 2000
Department of Agricultural Economics
Purdue University

Significant, strong linkages between exchange rates and agricultural commodity prices observed
Larger than predicted by law of one price
Correlations of endogeous variables
Variations in quantitative magnitude of effect according to economic conditions
Low stocks and recession both bring much larger effects
Macro and energy links relevant to food crisis impacts
Overlapping events not sorted
Overshooting seems evident but downward sticky prices (for manufacturing & services) seem to matter more than inflationary expectations (or loose monetary policy)
Trade effects will depend on poorly measured net trade elasticities
Department of Agricultural Economics
Purdue University