This article explores whether income underreporting for tax purposes can explain why the majority of U.S. farmers earn low or negative net farm income. Using 10 years of U.S. Department of Agriculture farm-level data, the extent of underreporting is estimated by exploiting the fact that farm households face an incentive to underreport farm income that varies with their reported off-farm income. Results indicate that 39% of total farm income is underreported. For large farms, the results imply a substantial discrepancy between reported and earned farm income. For small-scale operations, underreporting reduces but does not eliminate the gap between farm and off-farm wages.

Entrepreneurs innovate their individual business organizations not only to deal with production and price risks, but also to cope with the risk of sanctions or penalties imposed by society's laws and regulations. More specifically, labor-intensive agricultural firms, faced with potentially large fines for violation of immigration and labor laws, increasingly modify the organization of their firms by shifting the management of routine seasonal labor jobs to independent farm labor contractors. The use of labor contracting is further intensified because of the effectiveness of labor contractors in the recruitment of illegal aliens.

Local labor market characteristics are theoretically relevant to the determination of off-farm earnings of farm operators, but the empirical analysis of these effects has been hindered by a lack of appropriate data. This study employs the new census public use micro-data sample, PUMS-D, to investigate the effect of local labor market characteristics on off-farm earnings of farm operators. The PUMS-D data allow local characteristics to be defined on a labor market area basis, rather than on a political boundary basis. For a sample of Georgia farm operators, local labor market size, unemployment rates, and industrial structure were found to have significant impacts on off-farm employment and earnings.

Regular hired farm workers, performing 150 days or more of farm work annually, became increasingly important in the 1970's. The number of regular hired workers in the United States increased by almost 50 percent during the decade, while the number of seasonal workers, operators, and unpaid family workers declined. Pricing of regular hired labor is investigated through estimation of three nested wage determination models in a case study analysis for Georgia. Micro-level data on individual workers were used to analyze the effects of general human capital, farm worker duties, local labor market conditions, and farm characteristics on wage rates.

Producers' preferences for cottonseed with respect to price, seed type, yield, and fiber quality are examined by a willingness-to-pay approach via mail surveys. Results indicate a positive willingness to pay (WTP) for technology relative to conventional cottonseed, and WTP increases with the level of technology. Yield and quality also show a positive WTP. Larger farms have a higher WTP for technology, and farms with more farm labor have a lower WTP for technology. These results suggest economies of size in technology adoption (biotechnology is not size-neutral) and that labor and biotechnology are direct substitutes.

The substitution of capital for labor and new labor-saving technologies has reduced the labor required for farming, yet many farms today depend on hired labor in some form. Common in the literature is the assumption of perfectly substitutable farm labor. This has implications for the operator's off-farm labor decision. Intuitively, different forms of farm labor have different impacts on production. We use the Agricultural and Resource Management Survey to estimate the elasticity of substitution between hired and family labor. The results provide little evidence to support the popular homogeneity assumption and find labor can be unitary and complimentary under certain scenarios.

A case study of the nopal-vegetable agroecosystem in metropolitan Mexico City was conducted to evaluate the crop's economic productivity and sustainability using economic, social, and environmental indicators. Economic indicators were based on a gross margin analysis, commercialization strategies, and provision of employment. Social indicators were education level, family size, origin of laborers, plot size providing a measure of equity, and social self-organization. Environmental indicators were soil nutrient content and fertilizer application, technological management, and crop and natural biodiversity. Information on relevant social, technological, and economic elements was obtained through structured interviews with 100 producers of the city's nopalproducing zone of Milpa Alta in the hills southeast of Mexico City. Analysis of soil samples from cropped fields at three different depths was conducted, along with a study of nopal-associated weed species used by the community. Net income per ha was equivalent to 4 minimum wages. Estimated scores of 89, 74, and 64 (on a scale of 0 to 100) were obtained for social, economic, and environmental sustainability indicators, respectfully, for this unique cropping system. Discussion focuses on trade-offs between indicators, the cost of achieving sustainability in the metropolitan zone of Mexico City, and appropriate policy responses.