Detecting Technological Heterogeneity in New York Dairy Farms

Abstract

Agricultural studies have often differentiated and estimated different technologies within a sample of farms. The common approach is to use observable farm characteristics to split the sample into several groups and subsequently estimate different functions for each group. Alternatively, unique technologies can be determined by econometric procedures such as latent class models. This paper compares the results of a latent class model with the use of a priori information to split the sample using dairy farm data in the application. Latent class separation appears to be a superior method of separating heterogeneous technologies.