In a competitive market dairy production will shift to that region which is the most productive. Thus, this paper reports the measurement of productivity of dairy production in the various states of the U.S using recent Census data and non-parametric Malmquist index techniques. These are total factor productivity measures that do not require the assumption of cost or profit maximization behavior for aggregation. The Malmquist approach utilizes distance functions and can be used to measure technical and efficiency differences over time and between regions at a point in time. Using two output and six input variables, the distance functions were calculated via linear programming methods. The scalar values from those distance functions were used to calculate indexes for efficiency, technical, and productivity changes across the time periods. Individual state estimates of changes in efficiency, technology, and productivity from 1987 to 1992 were computed, divided by 1987 values. Over these states the average increase in productivity was 3.6 percent, or about 0.7 percent per year. Almost all of the productivity increase occurred from technological change, since the average increase in efficiency was only 0.1 percent. Technological change averaged 3.5 percent over the five year period, or about 0.7 percent each year. Ifthere is a significant decrease in the number of farms in a state, it might be expected that the remaining farms are more efficient, under the assumption that the least efficient farms are those that exit the industry. This was tested by regressing the percent change in efficiency on the percent change in farm numbers. The results were statistically insignificant. Likewise, if the output of the average farm increased it might be expected that efficiency might fall. This was tested by regressing the percent change in efficiency on the percent change in output per farm. Again the results were statistically insignificant. It was further expected that states that increased output per farm might have done so by using new technology. This was tested by regressing percent technological change on the percent change in output per farm. These results were also statistically insignificant.


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