Econometric Estimates of the Contribution of GM to Yield Potential and Damage Control: Estimates from State Average Corn Yields

Transcription

1 Symposium August 1, 2014 Econometric Estimates of the Contribution of GM to Yield Potential and Damage Control: Estimates from State Average Corn Yields by W.E. Huffman, Y. Jin and Z. Xu Iowa State University, The Shanghai University of Business and Economic, University of North Carolina at Chapel Hill 1

2 Introduction Understanding crop yields is important to feeding the world. The Midwest is the center of non-irrigated crop production. State average corn yields there have a long-term strong upward trend, but year-to-year variation in weather (and pest outbreaks) have introduced some sharp breaks. Nitrogen rates rose steadily from the mid-50 to 1980 and leveled off. Recent studies Studies in (Lobell and Asner; Schlenker and Roberts; Roberts, Schlenker and Eyer; and Lobell et al.) have estimated the impact of weather on corn yields using relatively disaggregate data, but ignore the impacts of N. Studies in (Nolan and Santos; Shi, Chavas and Lauer; and Xu et al) have shown that average corn yields at the plot and county level are related to GM technology, while controlling for N use. These studies have chosen unusually simplistic corn yield functions, e.g., no N, weather, or no diminishing marginal product of N, i.e., simple additive effects. 2

3 Motivations The objectives of the project Estimate the contribution of GM technology to potential state average corn yields and abatement of downside yield risk caused by adverse weather and pest events Better identify the transmission mechanism by which adverse weather impacts state average corn yield Hypothesis to test Higher N rates significant increase state average corn yields Productivity of N is reduced when corn plant is exposed to extreme heat during growing season Extreme deficit or surplus of water cause plant stress and yield reductions GM hybrid corn adoption shift upward yield potential and abate downside yield risk GM-damage control is larger on the fringe than in the Central Corn Belt Public corn research has shifted upward corn yield frontier 3

4 Outline Background. Some facts and observations. Model and data Frontier state average corn yield function. Cobb-Douglas production function between state average corn yields and nitrogen fertilizer application provides major advantages over simpler forms Yield damage control function. GM corn adoption abates asymmetric effects of adverse weather and pest events. GM adoption may also abate disadvantages of a state being on the fringe of the Central Corn Belt The observations are state level data for the 8 major non-irrigated Midwestern States, Technology indicators in this study are GM corn hybrid adoption, public corn research and trend. Weather indicators are accumulated growing degree days, excessheat-degree days, and Palmer s Z moisture stress index. The N elasticity of corn yields is made a function of weather extreme heating degree days (Huffman 1974, Westgate et al. 2004) Results and findings. 4

5 ln(yields) Figure 1. State Average Corn Yields (bu/ac) Panel A. IA, IL, IN, OH, IA IL IN OH

6 ln(yields) Figure 1: Panel B. MI, MN, MS, and WI MI MN MS WI

7 Figure 2. State Average Nitrogen Fertilizer Rate Applied To Corn: 8 Midwestern States (lb/ac) IA IL IN MI MN MS OH WI

8 Figure 3. GM Corn Adoption Rates: IA, IL, IN, MI, MN, MS, OH and WI, (Xu et al) IA IL IN MI MN MS OH WI

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16 Fig. 4. Proximity of Corn Yields to Stochastic Frontier, Panel A: IA, IL, IN, and OH IA IL IN OH

17 Fig 4: Panel B. MI, MN, MS and WI MI MN MS WI

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20 Yields Figure 5. Frontier State Average Corn Yield (bu/ac/yr) as a Function of N (lb/ac), Real Price of Nitrogen, and Optimal N N 20

21 Findings and Conclusions I Paper provides empirical evidence that the generalized C-D production function provides a good model of the production frontier for state average corn yields. The econometric evidence favors estimating the production frontier as a stochastic frontier C-D production function. Evidence has been presented that supports six hypotheses Higher N significantly increases state average corn yield; near optimal use given price of N and corn Productivity of N applied to corn significantly decreases with larger number of extreme heat degree days and net effect of additional excess heat degree days is negative on state average corn yields 21

22 Findings and Conclusions II Evidence (continued) Extremes (-.+) in water availability, summarized in Palmer Z-sq-ed, reduce state average corn yields significantly GM hybrid adoption significantly increases the yield potential and reduces downside yield risk due to moisture stress but not to excess heat due to moisture stress but not to excess heat Marginal net benefits of adoption of GM hybrids decays over post-gm era Evidence supports other studies that found non-linear benefits from larger number of GM traits GM hybrids have delivered larger damage control on the fringe than Central Corn Belt State Public corn research has significantly increased the yield potential of corn in the Midwest. Impact of public spilling corn research on state average corn yields is larger than within-state corn research, but both of these impacts have been declining over time due to change in emphasis of public corn research 22

23 Findings and Conclusions III With global warming expected in the future, the environment in the Midwest may become more harsh for growing corn Public and private research can be marshalled to develop new management strategies and new corn varieties that can better resist excess heat, extremes in moisture availability and common pests With adaptation, future prospects for corn production seem to be good 23

24 Thank you We thank David Hennessy and GianCarlo Moschini for sharing the data set used in Xu et al (2014). We thank David Zilberman, Kendall Lamkey, and Wayne Fuller for suggestions and helpful comments. We acknowledge financial assistance from a USDA- ERS cooperative agreement and USDA-NIFA support through the Iowa Agricultural Experiment Station. 24