Agricultural payments and land concentration" a semiparametric spatial regression analysis.

Over the last twenty years, agricultural production has become increasingly concentrated on larger farms. According to Census of Agriculture data, farms from 1,000 to 10,000 acres increased in number by 14.3% between 1982 and 2002 and total farmland controlled by these large operations increased by 20.6%. (1) In contrast, over this period farms with fewer than 1,000 acres declined in number and amount of farmland controlled. Increasing concentration of agricultural production has coincided with an increasing share of government payments going to large farms: between 1982 and 2002 the share of all payments going to farms from 1,000 to 10,000 acres increased from 41.1% to 49.5%.

In recent years interest groups, politicians, and newspaper editorials have expressed concern that payments unfairly advantage large operations and have argued that government payments are a key factor contributing to the growth in concentration and farm sizes (e.g., Williams-Derry and Cook 2000; Becker 2001; Nelson 2002). Concerns about the link between agricultural payments and farm size have helped motivate congressional efforts to tighten payment caps on large-scale producers (U.S. Department of Agriculture 2003). (2)

Claims that government payments unfairly advantage large farms are usually supported with statistics showing a steady growth in farm size and the strong association between farm size and payment levels. However, while government payments and production have both become increasingly concentrated, this concurrence of trends does not necessarily imply a causal link between payments and farm size. The design of government agricultural programs is such that payment levels are tied to the amount of land farmed and the land's production history. Thus, regardless of what caused farms to increase in size, payments would have become more concentrated on larger farms (MacDonald, Hoppe, and Banker 2005).

To what extent are government agricultural programs and their associated payments contributing to the concentration of production? Most studies that have attempted to explain changes in the size and survival of individual farms have focused on characteristics of the farm operator or farm, not on the role of government payments (Sumner and Leiby 1987; Hallam 1993; Zepeda 1995; Kimhi and Bollman 1999; Weiss 1999). Exceptions are two recent studies by Key and Roberts (2006; 2007) that found government payments positively and significantly associated with the survival rate and duration of individual farm businesses, as well as farm size conditional upon survival. These studies, however, consider effects of payments on the growth or survival of individual farms, which cannot predict the effects of an increase in payments on aggregate farm structure. This is because studies of individual farms cannot account for how induced changes on one farm affect other, neighboring farms, or how payments influence the size and number of entering farms. For example, consider a hypothetical case where payments cause consolidation of two neighboring farms of equal size and equal payment levels. At the level of an individual farm, the average payment effect on size may appear to equal zero: one farm increased in size by 100% while the other declined in size by 100%. Nevertheless, the aggregate effect on land concentration is substantial.

Some past studies have estimated the effect of agricultural payments on aggregate measures of farm structure, including the national agricultural bankruptcy rate (Shepard and Collins 1982), the total number of farms (Tweeten 1993), and average farm size (Huffman and Evenson 2001). While taking very different approaches, these studies treat government payments as exogenous and have used current payments to explain current indicators of farm structure. A problem with this approach is that it is difficult to attribute a causal mechanism to an observed cross-sectional association between payments and farm size. To do so requires confidence that determinants of farm structure, other than agricultural payments, are adequately accounted for. A particular concern is the heterogeneity of land and farms across regions in the United States. A finding that farms are larger in areas with higher payments might be explained by the fact that government programs target field crops (e.g., corn, soybeans, and wheat), which require more land to be profitably farmed. Another concern is the endogeneity of payments: farm acreage decisions influence payment levels, so causation may go in the opposite direction.

This study compares zip codes with different per-acre payment levels to subsequent percentage changes in land concentration. That is, it examines whether concentration growth rates are higher in areas with higher historical payments per acre relative to areas with lower payments per acre. Even if programs happen to target regions where farms are larger because of the crops grown, we see no obvious reason to expect programs to target regions inclined to subsequently experience faster growth in concentration over time--by examining growth rates we control for time-invariant factors associated with concentration. In other words, a correlation between payments and the subsequent change in land concentration is less likely to result from reverse causality.

The study supplements the simple comparisons described above with a semiparametric generalized additive model (GAM) to control for location, historical concentration, historical sales per acre, and the share of land in agriculture in a flexible way. These variables control for time-varying factors that may create a spurious relationship between payments and concentration growth.

Concentration is measured at the zip code level. Farmland concentration is defined as the acre-weighted median farm size: the farm size such that half the farmland within each zip code resides on larger farms and half resides on smaller farms (cropland concentration is analogously defined). We focus on this measure, rather than the more commonly used mean or median farm size, because these measures are extremely sensitive to the definition of a farm, which has changed implicitly or explicitly over time, and are heavily influenced by a growing number of small "hobby" farms. In table 1, notice the growth in the number of smallest farms (0-50 acres) and larger farms (1,000-10,000 and 10,000 + acres) and the marked decline in the number of middle-sized farms (150-500 and 500-1000 acres).

The analysis uses microdata from the 1987, 1992, 1997, and 2002 agricultural censuses and includes all U.S. zip codes with at least three farms in all four censuses. The zip code analysis improves upon national, state, or county-level analyses by providing more observations and more variation across observations in both concentration and payment levels. Sufficient variation at a local level is important when using an empirical technique that controls for factors that vary geographically. The census data are the only data available for such a fine-scale analysis: the census attempts to collect information on every U.S. farm business with expected sales of at least $1,000.

Determinants of Concentration: Farm Size and Survival

As the amount of U.S. farmland and cropland has remained relatively stable, changes in concentration from one period to the next depend on the size distribution and growth rate of surviving farms, and on the sizes of entering farms (Vesterby et al. 2006). The literature on firm size and survival therefore provides some insight into the determinants of farm structure. In this literature, the relationship between firm size and survival is often modeled as a dynamic process wherein firms (or entrepreneurs) are uncertain about their own competitiveness at startup (Jovanovic 1982; Ericson and Pakes 1992; and Pakes and Ericson 1998). In these models, firms gradually learn about their abilities over time and the longer they operate, the more they learn about their competitiveness. As managers revise their perceptions of their firm's ability upward, they tend to expand, while those revising downward tend to contract or exit. Thus, the longer a firm has existed, the bigger it will become and the less likely it will be to fail. Empirical studies generally confirm these theoretical predictions (Dunne, Roberts, and Samuelson 1988; Baldwin and Gorecki 1991; Audretsch 1991; Audretsch and Mahmood 1995; among others).

Theory does not provide unambiguous predictions as to how a change in government payments would influence farm growth and survival. Consider, for example, a model of a representative farm where the quantity of agricultural land is fixed, but labor and capital are mobile between agricultural and nonagricultural sectors (Kislev and Peterson 1982). In this model, farm size is a function of the ratio of wages to the cost of capital. An increase in government payments increases returns to farming, but these additional profits are capitalized into the price of land. Hence, a change in government payments has no clear direct effect on the cost of labor relative to capital, and therefore has no effect on farm size.