This project examines three topics in production analysis. These are: returns-to-scale and technical progress, the effects of imposing regularity conditions, and direct estimation of production functions from data on inputs and output. Empirical estimation of the returns-to-scale and changes in technical proficiency have long been central questions in the analysis of production. Past work has typically specified constant returns and technical progress due to the inherent econometric tractability. This project extends that work by incorporating production functions which are non-homothetic in returns and technology, and are more realistic, general, and flexible. Investigation of the imposition of regularity conditions at every point in the sample data addresses an important but often neglected issue in empirical production analysis. The theory underlying the economics of production assumes that the conditions of monotonicity and convexity apply to every combination of inputs and output. Empirical data often do not meet those conditions, and this project systematically examines the effects of violating the regularity assumptions. The comparison of direct estimation of production functions with the indirect method makes a fundamental contribution in empirical econometrics. Estimating functions directly has the advantage of not requiring data on factor prices nor does it assume cost minimization. Estimating input demand systems with factor price data is often econometrically intractable. This project addresses some important problems in the economic analysis of production. Economic theory in regard to production is quite well developed; indeed analyzing the interaction of production and consumption has been a fundamental endeavor for many years. From an empirical standpoint, however, the analytical techniques are much less straightforward. Transferring the conditions imposed by economic theory into empirical econometric analysis has proven to be quite difficult, and often restricting assumptions about the data must be made to render empirical analysis tractable. These distinctions between the theoretical models and the more tractable but simpler empirical models are very important in that most decisions made by production managers and policy makers are based on empirical analysis. This work promises to provide insight into the importance of some often-used empirical assumptions. By using various empirical specifications this project examines the effects of some fundamental assumptions in production theory. These are: 1) returns-to-scale, which is the manner in which product output changes with respect to changes in inputs. Of particular importance is the assumption that output will expand or contract in exact proportion to changes in input, 2) regularity conditions, which imply that the theoretical properties of the production function are met by all sample data values, 3) direct versus indirect specification of the production function, the former specification incorporating data on input and output quantities, the latter using only data on the prices of inputs.
