The paper analyzes the relationship between off-farm labor allocation and on-farm enterprise diversification as farm household income stabilization strategies with census data from the federal state of Upper Austria, Austria. The results suggest that both on-farm diversification and off-farm labor allocation are related to farm and household characteristics. Larger farms tend to be more diversified. Younger farmers are more likely to work off-farm. Larger farm households tend to allocate more labor to off-farm income activities.

This study provides an analysis of nonindustrial private forest (NIPF) landowners' participation in forestry assistance programs. A probit model was used for data collected from a random sample of 329 Indiana landowners. The analysis revealed that total land owned, commercial reasons for ownership, government sources of information, and membership in forestry organizations influenced NIPF landowners' program participation. Age, fear of loss of property rights, and duration since the first wooded tract was acquired also influenced program participation. Location of landowners' residence on their wooded land and landowners' knowledge of and willingness to participate in a conservation easement influenced the participation in cost-share programs.

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Infrastructure, agglomeration, product and input markets, fiscal attributes, and labor markets of local communities influenced food manufacturing location decisions in the lower 48 United States, 2000-2004. Negative binomial regression and spatial clustering methods forecast food processor location patterns at the county level. Noncore counties are at a comparative disadvantage with respect to attracting most food processors, but nonmetropolitan counties adjacent to urban areas may be attractive investment sites for footloose, supply, and demand-oriented food manufacturers. Copyright (c) 2009 International Association of Agricultural Economists.

This paper examines local and regional attributes associated with growth in the food processing industry. The paper uses industrial location studies to develop a model of food processing plants’growth. Ordinary least squares (OLS) models are estimated to analyze which local, regional and state attributes are associated with county level growth, measured by a change in the number of establishments. The results suggest that food processing growth is associated with factors similar to those influencing the location of footloose manufacturing plants. However, growth in food processing sectors is associated with different local attributes depending on a firm's industry type (demand‐oriented, supply‐oriented, footloose).