Performing Department
Agri Economics & Rural Sociol
Non Technical Summary
Ever since the elimination of marketing quotas in 2002, the U.S. peanut production sector has been undergoing significant structural changes including significant locational shifts in the production with a considerable amount of peanut planting relocating from the Southwest and the Virginia/North Carolina regions to the Southeast, which is emerging as the dominant peanut base. This is particularly relevant to Alabama agriculture, given that peanuts are among the top four crops (by value) in the state. At the same time, owing to no longer subsidized and thus lower prices of food-use peanuts, the peanut acreage has declined substantially since the elimination of quotas; but the yields are up. USDA heuristically attributes these yield improvements to a systemic shift in the peanut production to more efficient farmers and more productive lands, which is however not self-evident and requires formal scientific examination. The gap in our knowledge on drivers of these better-than-ever yield improvements is important to address because the knowledge of primary contributors to increases in peanut yields has a significant potential to benefit both the peanut producers and regulators. Since the yield, which effectively measures the overall productivity of land, has a direct intensive-margin-type link to farmers' profitability, the understanding of underlying yield-enhancing factors can help peanut growers in Alabama and, more generally, in the Southeast to better adapt to post-quota-system realities and remain economically viable in the new market environment.The project will utilize high-quality farm-level data from USDA Economic Research Service Agricultural Resource Management Survey, which is to be merged with the data on climate and soil conditions. The statistical/econometric analysis of the data will rely on novel and robust methods including the recently developed tests of stochastic dominance for the estimated data with dependence as well as state-of-the-art moment-based and distributional decomposition techniques. This research project will ultimately result in an increase in our knowledge of the U.S. peanut production sector and its structure.
Animal Health Component
0%
Research Effort Categories
Basic
100%
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
The goal of this project is tounderstand temporal changes (and to investigate potential causes thereof)in the peanut yields between 2004 and 2013 following the elimination of quota system. More specifically, the objective of my research is to determine the following: (1)Does the observed improvement in peanut yields hold across the entire distribution of farms or is it an illusionary "on-average"phenomenon driven by few exceptionally productive outliers? (2) Has the technological efficiency of peanut producers improved over time in the post-quota period? (3) To what extent can the increase in peanut yields be attributed to improvements in the efficiency of producers and the relocation to (naturally) more productive land?
Project Methods
The project will begin by constructing a dataset usinghigh-quality raw farm-level data on peanut producers from the USDA ERS ARMS survey.The ARMS include both the production-side and financial information which is essential for the proposed research. Peanut producers were surveyed three times: in 1999, 2004 and 2013. The 1999 survey was partial, andI will therefore use the data for 2004 and 2013 only, thereby confining my analysis to the period afterthe elimination of quotas. These data will then merge (at the county or, when feasible, ZIP-code level) with the data on climate and soil conditions. The geographical soil data will come from the extensive SSURGO database created by the USDA NRCSwhich includes information about soil collected via the National Cooperative Soil Survey. The climate data will come from the Parameter-Elevation Regressions on Independent Slopes Model developed by the Spatial Climate Analysis Service at the Oregon State University.(1) To analyze if gains in peanut yields are shared byall farms and are not merely an illusionary "on-average"phenomenon driven by few exceptionally productive outliers, I will test for a rightward shift in the entire yield distribution over time.I will test if the distribution of farm-level peanut yield in 2013 stochastically dominates that in 2004. To do so, I will use the recently developedrobust extension of the nonparametric Kolmogorov-Smirnov test, whichlets the underlying variables share dependence and be the estimated quantities.(2) To examine ifthe technological efficiency of peanut producers has improved since the elimination of quotas, I will first estimate the unobserved farm efficiency (capturinglatent management quality) by employing a stochastic frontier model which is capable of recovering farm-specific efficiency under some distributional assumptions.To mitigate potential sensitivity of the results to distributional assumptions, I will use a recently proposed model-averaging estimator.I will then formally test if the technological efficiency of peanut growers has improved over time.(3) To investigate towhat extent the increase in peanut yields in the post-quota period can be attributed to efficiency gains and the relocation to (naturally) more productive land, I willdecompose changes in peanut yields over timevia several Blinder-Oaxaca-type decomposition techniques. The traditional decomposition is performed at the mean. In this project, I will take two steps further. First, I will also decompose the change in the variance of peanut yield, which will shed light on what drives changes in the variability of yields across individual farmers. Second, I will also perform a state-of-the-artdistributional decomposition of peanut yields across time, which will facilitatethe decomposition across different quantiles of the yield distribution.