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AbstractNumerous studies have evaluated the impact of Extension on farm productivity and related outcomes. Here we use annual data from 1983 to 2010 covering the 50 U.S. states to examine the impact of Extension on net changes in the number of farmers. The historical transition of farmers out of U.S. agriculture raises the question of whether Cooperative Extension and underlying Hatch‐funded research spending keeps farmers in agriculture or accelerates their exit. On balance, nearly 500,000 more farmers left than entered agriculture over the period studied. We estimate that without Extension, as many as 137,700 (or 28%) additional farmers would have disappeared on net. Overall, Extension programs are a remarkably cost effective way of keeping farmers in agriculture. Alternatively, shifting just 1.5% of federal farm program payments to Extension would have reduced net exits over this period by an estimated 11%, or 55,000 farmers.

Objectives. This study seeks to identify the independent effect of Wal‐Mart stores on changes in U.S. family‐poverty rates at the county level. We draw on the contributions of a number of disciplines to enhance our understanding of the broader forces that influence poverty.Methods. A key innovation is that we estimate a two‐stage regression model, in which an instrument is created for new Wal‐Mart stores from a location equation; this reduces any potential endogeneity bias in the poverty‐change equation. In addition, we use spatial econometric methods to correct for spatial dependence bias.Results. After controlling for other factors determining changes in the poverty rate over time, we find that counties with more initial (1987) Wal‐Mart stores and counties with more additions of stores between 1987 and 1998 experienced greater increases (or smaller decreases) in family‐poverty rates during the 1990s economic boom period.Conclusions. Wal‐Mart creates both benefits and costs to communities in which the chain locates. These benefits and costs need to be weighed carefully by community decisionmakers in deciding whether to provide public subsidies to the chain.

Objectives: This study seeks to identify the independent effect of Wal-Mart stores on changes in U.S. family-poverty rates at the county level. We draw on the contributions of a number of disciplines to enhance our understanding of the broader forces that influence poverty. Methods: A key innovation is that we estimate a two-stage regression model, in which an instrument is created for new Wal-Mart stores from a location equation; this reduces any potential endogeneity bias in the poverty-change equation. In addition, we use spatial econometric methods to correct for spatial dependence bias. Results: After controlling for other factors determining changes in the poverty rate over time, we find that counties with more initial (1987) Wal-Mart stores and counties with more additions of stores between 1987 and 1998 experienced greater increases (or smaller decreases) in family-poverty rates during the 1990s economic boom period. Conclusions: Wal-Mart creates both benefits and costs to communities in which the chain locates. These benefits and costs need to be weighed carefully by community decision-makers in deciding whether to provide public subsidies to the chain. Tables, 1, References. Adapted from the source document.

Objectives.Two powerful socioeconomic innovations are sweeping the nation, led by Wal‐Mart Stores, Inc. and Starbucks Corp. These innovations both affect and are driven by profound labor market changes, but exactly how they affect self‐employment or entrepreneurship has not been investigated. We examine the independent effects of these phenomena on the returns to self‐employment, which is itself an underresearched topic in labor economics.Methods.We apply spatial econometric analysis to data from more than 3,000 U.S. counties to analyze how big‐boxes and drinking places that facilitate social networking affect self‐employment earnings.Findings.The presence of Wal‐Mart stores is associated with higher returns to self‐employment, whereas the results for coffee shops and drinking places are mixed. A negative interaction effect on earnings emerges when Wal‐Mart stores and drinking places exist in the same county.Conclusions.We confirm both Schumpeter's and Putnam's assertions about the importance of creative destruction and social networking in raising the productivity of entrepreneurs, although the latter effect is not as clear‐cut as the former.