Crop Supply Dynamics and the Illusion of Partial Adjustment

Abstract

We use field-level data to estimate the response of corn and soybean acreage to price shocks. Our sample contains more than eight million observations derived from satellite imagery and includes every field in Iowa, Illinois, and Indiana. We estimate that aggregate crop acreage responds more to price shocks in the short run than in the long run, and we show theoretically how the benefits of crop rotation generate this response pattern. In essence, farmers who change crops due to a price shock have an incentive to switch back to the previous crop to capture the benefits of crop rotation. Our result contradicts the long-held belief that agricultural supply responds gradually to price shocks through partial adjustment. We would not have obtained this result had we used county-level panel data. Standard econometric methods applied to county-level data produce estimates consistent with partial adjustment. We show that this apparent partial adjustment is illusory, and we demonstrate how it arises from the fact that fields in the same county are more similar to each other than to fields in other counties. This result underscores the importance of using models with appropriate micro-foundations and cautions against inferring micro-level rigidities from inertia in aggregate panel data. Our preferred estimate of the own-price long-run elasticity of corn acreage is 0.29 and the cross-price elasticity is -0.22. The corresponding elasticities for soybean acreage are 0.26 and -0.33. Our estimated short-run elasticities are 37 percent larger than their long-run counterparts. 2 How much more land gets allocated to a crop when relative prices change? The answer to this question is the central parameter for understanding world food prospects, the impacts of farm subsidies, and the environmental consequences from land use change, among other public and policy issues (e.g., Roberts and Schlenker 2013;Lichtenberg and Zilberman 1986;Searchinger et al. 2008;Donner and Kucharik 2008). We provide a new and better answer for an important set of commodities in the world food system. We use a conceptual approach that accounts for crop rotations, a massive sample of individual fields, and econometric methods that account for heterogeneous incentives to rotate crops and heterogeneous responses to prices. Moreover, we show that supply response is seriously misestimated when standard econometric methods are applied to county-level panel data. One consequence of this bias is a mistaken understanding of supply dynamics and, in particular, the relationship between short-run and long-run supply response.A typical agricultural field in the United States Corn Belt tends to alternate between growing corn in one year and soybeans the next. This pattern reflects a common agronomic feature of crop production: planting a crop on the same field in consecutive years decreases the productivity of the soil for growing that crop and increases pest populations. These features generate dynamic complementarity in crop production because the marginal valu...

Evidence of climate change impacts on crop comparative advantage and land use

“…Second, crop rotations are not explicitly modeled. Rotations matter when studying responses to shocks (Hendricks, Smith, & Sumner, 2014;Kim & Moschini, 2018) although their omission in county-level analysis is inevitable due to aggregation. Third, the crop-specific production costs data are spatially invariant, which is unrealistic.…”

The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era

“…Some of these studies also differentiate between short-and long-run behavior, an element of interest in this setting at least since Nerlove (1956) (e.g., Arnberg and Hansen 2012;Hausman 2012;de Menezes and Piketty 2012). The dynamics of supply can be complex once one explicitly accounts for crop rotational effects (Eckstein 1984(Eckstein , 1985, with results that depart form the canonical findings of traditional Nerlovian models (Hendricks, Smith, and Sumner 2014).…”

“…When these considerations outweigh those associated with possible adjustment costs, the short-run response to price can exceed the long-run response. Hendricks, Smith, and Sumner (2014) find empirical support for the underlying role of crop rotation by estimating a Markov transition probability model for field-level crop data from satellite imagery-the Cropland Data Layer (CDL) made available by the U.S. Department of Agriculture (USDA) -for three central Midwest states.…”

The Critical Role of Conversion Cost and Comparative Advantage in Modeling Agricultural Land Use Change

“…Note that previous econometric estimations focused on a particular region. For example, Hendricks et al (2014) estimated long-run own-and cross-price acreage elasticity to be 0.29 and À0.22 for corn and 0.26 and À0.33 for soybeans, using data from three US corn belt states (Iowa, Illinois, and Indiana). The own-price acreage elasticity for corn and soybeans estimated in Miao et al (2015) for the U.S. was 0.45 for corn and 0.63 for soybeans.…”