Steven Wallander
United States Department of Agriculture
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Steven Wallander.
Economic Information Bulletin - USDA Economic Research Service | 2011
Steven Wallander; Roger Claassen; Cynthia J. Nickerson
The recent 9-billion-gallon increase in corn-based ethanol production, which resulted from a combination of rising gasoline prices and a suite of Federal bioenergy policies, provides evidence of how farmers altered their land-use decisions in response to increased demand for corn. As some forecasts had suggested, corn acreage increased mostly on farms that previously specialized in soybeans. Other farms, however, offset this shift by expanding soybean production. Farm-level data reveal that the simultaneous net expansion of corn and soybean acreage resulted from a reduction in cotton acreage, a shift from uncultivated hay to cropland, and the expansion of double cropping (consecutively producing two crops of either like or unlike commodities on the same land within the same year).
American Journal of Agricultural Economics | 2016
Joseph C. Cooper; A. Nam Tran; Steven Wallander
Abstract The literature on climate risk and crop yields is currently focused on the potential for highly non‐linear marginal effects, essentially modeling the threshold effects with a yield function that maps weather inputs into crop yields. Implicit in this line of research is the assertion that the traditional quadratic model of crop yield suffers from specification bias. This article examines this assumption by using the Flexible Fourier Transforms (FFT) to allow for global flexibility in the weather effects while also maintaining the traditional quadratic model as a nested model specification. In order to speak to the global flexibility of FFT, as well as to provide both robustness to outliers and information on the scale effects of weather variables, this article compares FFT with restricted cubic spline (RCS) and quadratic models in a quantile regression framework. Using U.S. county‐level data on corn, soybeans, and winter wheat from 1975 to 2013, we find that while the threshold effects are largely captured by the traditional quadratic model, we statistically reject the hypothesis that the quadratic model is sufficiently flexible. We find that, under the more flexible FFT functional forms, at lower temperatures there is a greater positive impact of marginal increases in temperature on yield than with the quadratic model, which suggests a different yield‐temperature relationship than found in much of the literature on threshold effects of temperature on crop yields, and is more consistent with the positive effects of minor temperature increases found in some of the Ricardian climate effect literature.
Economic Information Bulletin - USDA Economic Research Service | 2014
Allison Borchers; Elizabeth Truex-Powell; Steven Wallander; Cynthia J. Nickerson
Archive | 2015
Tara Wade; Roger Claassen; Steven Wallander
Archive | 2013
Steven Wallander; Marcel P. Aillery; Daniel Hellerstein; Michael S. Hand
Amber Waves | 2013
Steven Wallander
Archive | 2011
Steven Wallander; Roger Claassen; Cynthia J. Nickerson
2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania | 2011
Steven Wallander; Michael S. Hand
Archive | 2018
Steven Wallander; Daniel Hellerstein; Reid Johnsen
Archive | 2017
Steven Wallander; Maria Bowman; Roger Claassen