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Abstract
Data Envelopment Analysis (DEA) techniques are applied to a state-level data set to measure the total factor productivity in US agriculture over 1960–1996. Total factor productivity is decomposed into input and output biased technological change, efficiency change, and scale change, under both constant return to scale (CRS) and variable return to scale (VRS). Assumption of Hick neutral technological change is discussed. Technological change is found to be the result of efficient use of inputs much more than the effects of output capability increase.
Notes
1 Ray and Desli (1997) argue that TFP index is equivalent to the ratio of the CRS distance function even if the technology is not characterized by CRS. Productivity is a long run problem thus it is measured relative to the CRS technology. In other words, TFP index under CRS equals the TFP index under VRS.
2 The GAMS is used for these computations (e.g., see Olesen and Petersen (Citation1996) for more details).
