Valuing State Level Funding for Agricultural Research: Results for the Southeastern United States and the Cornbelt
Gülcan Önel and Charles B. Moss *
* Food and Resource Economics Department, University of Florida, Gainesville, FL 32611
Selected Poster prepared for presentation at the Agricultural & Applied Economics Association’s
2013 AAEA & CAES Joint Annual Meeting, Washington, DC, August 4-6, 2013.
Copyright 2013 by Gülcan Önel and Charles B. Moss. All rights reserved. Readers may make
verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.
IFAS
Food and Resource Economics Department
Valuing State Level Funding for Agricultural Research: Results forthe Southeastern United States and the Cornbelt
Gulcan Onel and Charles B. MossFood and Resource Economics Department, University of Florida
1. Motivation
• The current debate on the Farm Bill has brought the continuation of several ”safe” pro-grams into question including crop insurance and the funding for agricultural research.•Research into agriculture has historically been supported on a variety of grounds.
– Funding agricultural research reduced food prices which provided significant benefitsfor poor and lower middle class households.
– Funding agricultural research through state and federal funding of each state’s agri-cultural experiment station provided a mechanism to benefit small and family farms.
– Federal and state funding could be focused on basic research with long-term payoffsoutside the scope of private research interest.
2. Economic Model
•Moss (2006) presents a decomposition of the change in profit which provides insightinto question of investment in agricultural research. Specifically, Moss decomposes thechange in profit into total factor productivity and changes in relative prices
D (Πt) = D (Ft) + D (Ψt) (1)– D (Πt) is the overall change in agricultural profit.– D (Ft) is the change in total factor productivity – the ratio of the value of total outputs
to the total value of inputs.– D (Ψt) is the weighted change in input and output prices.•Hence, as depicted in Figure 1, most studies agree that research and development
shifts the agricultural supply function to the right (from S0 (p) to S1 (p)).
oD p
oS p
1S p
0p
1p
a
b
c
Price
Quantity1Q0Q
d
Figure 1: Effect of Research and Development
• The primary question is the division of the gains between consumers who benefit fromlower prices and producers whose costs have declined.•Change in Total Factor Productivity measures the change between the values of outputs
produced divided by the value of inputs used.• This productivity change provides information about the change in societal welfare.
– As depicted in Figure 1, the gain in consumer surplus is p0abp1.– The net gain to producers is cbed− p0acp1� 0.– The net societal gain is abf .• Thus, while the change in Total Factor Productity provides a measure of societal gain
(i.e., abf ∝ ∆TFP ), the change in productivity provides little evidience on how the gainis divided between produces and consumers.•Moss (2006) concludes that increases in the stock of Agricultural Research and De-
velopment are associated with increases in productity measured as the level of TotalFactor Productivity.
•However, Moss also concludes that the increases in Total Factor Productivity are notassociated with long run increases in either Net Cash Income or Farmland Values.•Hence, Moss concludes that the increases in Total Factor Productivity largely accrue to
consumers (i.e., p0abp1 is significantly larger than cbed− p0acp1).
3. Data and Methods
• This study extends the analysis of Moss by considering the panel of Cornbelt (i.e.,Illinios, Indiana, Iowa, Missouri, and Ohio) and Southeastern (i.e., Alabama, Florida,Georgia, and South Carolina) states.– Following the Moss, we use the Total Factor Productivity computed at the state level
for 1960-2004 (updated based on Ball, Butault, and Nehring 2002).– Research and Development stocks at the state level for 1960-1999 are take from
Huffman, McCunn and Xu (2001).– The Net Cash Income and Farmland Values are taken from the Economic Research
Service’s Farm Income and Balance Sheet data for each state for 1960-2003.• In order to provide a common level of measurement, we depart from Moss by dividing
the Research and Development stocks, Net Cash Income and Farmland Values by thenumber of acres in each state.
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1960 1970 1980 1990 2000
Nat
ura
l L
og
arit
hm
Year
ln(R & D) ln(TFP)
Figure 2: Panel Average Total Factor Productivity and R & D Stock
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
4.5
4.6
4.7
4.8
4.9
5.0
5.1
5.2
5.3
5.4
5.5
1960 1970 1980 1990 2000
Nat
ura
l L
og
arit
hm
Nat
ura
l L
og
arit
hm
(N
et I
nco
me)
Year
ln(Return per Acre) ln(R & D) ln(TFP)
Figure 3: Panel Average Total Factor Productivity, R & D Stock and Net Cash Income
• To analyze the effect relationship between investment in Agricultural Research and De-velopment, Total Factor Productivity, and the benefts to the farmers, we will use cointe-gration analysis to estimate whether a long-run equilibrium exists between each variable(a cointegrating vector).
• This study extends the analysis of Moss (2006) by using a panel approach to cointegra-tion.• Following Moss we use a cointegration approach that allows for multiple cointegrating
relationships.
4. Empirical Results
Panel Unit Root Tetsts, Null: Unit RootIm, Perasan, Shin Maddala-Wu BreitungTest Stat. p-value Test Stat. p-value Test Stat. p-value
Log(TFP) 4.161 0.999 2.356 0.999 -0.929 0.177Log(R&D) -1.274 0.101 34.788 0.01* 6.158 0.999
log(NCI) -1.331 0.092 28.587 0.054* -1.972 0.024*
Single Equation Cointegration Tests,Null: No Cointegration
Test Stat. p-valuePedroni 10.474 0.000*
Kao -0.861 0.195Larsson et. al. Multiple Eq. Cointegration TestTest Stat. p-value
Null1: No Cointegration 13.685 0.000*Null2: At most 1 Coint. Relations 8.264 0.000*Null3: At most 2 Coint. Relations 4.947 0.000*
Table 3: Cointegration Results
Ln(TFP) Ln(NCI) Ln(R&D) Ln(TFP) Ln(NCI) Ln(R&D) Ln(TFP) Ln(NCI) Ln(R&D) Ln(TFP) Ln(NCI) Ln(R&D)Alabama Iowa
1 -1.391 0.567 1 0 -0.416 1 0.098 -0.428 1 0 -0.4640 1 -0.706 0 1 -0.706 0 1 0.365 0 1 0.365
Florida Missouri1 -0.388 -0.116 1 0 -0.364 1 0.169 -0.316 1 0 -2.2690 1 -0.639 0 1 -0.639 0 1 11.556 0 1 11.556
Georgia Ohio1 -0.517 -0.046 1 0 -0.261 1 -1.380 -1.719 1 0 -0.6390 1 -0.415 0 1 -0.415 0 1 0.783 0 1 0.783
Illinois South Carolina1 0.137 -0.711 1 0 -0.947 1 -0.650 -0.233 1 0 -0.3830 1 1.724 0 1 1.724 0 1 -0.231 0 1 -0.231
Indiana Panel1 -0.668 -1.390 1 0 -0.787 1 0.123 -0.386 1 0 1.2130 1 0.904 0 1 0.904 0 1 -12.992 0 1 -12.992
5. Discussion
• The state level results indicate that increases in the stock of agricultural research anddevelopment are associated with higher levels of productivity.• In the southeastern states, increases in research and development stock are also as-
sociated with higher levels of profit (i.e., net cash income). However, in cornbelt statesincreased levels of research and development are associated with lower levels of profit.• The panel results indicate that increased investment in research and development are
associated with increased agricultural profitability. However, the panel results do notsupport a positive relationship between research and development and productivity.
6. Contact Information
Charles Moss – [email protected] (http://ricardo.ifas.ufl.edu/)