Using Second-Order Polynomials as Production Functions.
Abstract
This research attempted to show that an Air Force unit can be modeled as an industry with its output determined through a production function. A second-order polynomial was used as the production function in this research. A resource-allocation simulation was used to generate the data for analysis. Only two input factors were analyzed--support kits and maintenance crews. In this way, these two inputs could be compared to the microeconomic factors of production--capital and labor. Basic Response Surface Methodology (RSM) techniques were used to estimate the second-order polynomial. Experimental designs in the form of central composite designs (CCD) were used to determine the input factor combinations. A complete statistical analysis of the pure linear model and the second-order model, complete with statistical tests and ANOVA, was performed. Basic microeconomic definitions of first-and second-order conditions were discussed and the conditions for least-cost combinations of the inputs for the second-order polynomial were derived. The problems associated with using simulated data to estimate production functions were outlined. Some benefits of using a second-order polynomial as a production function in comparison with the commonly used Cobb-Douglas and Constant Elasticity of Substitution (CES) production functions were discussed.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1987
- Accession Number
- ADA189497
Entities
People
- James J. Revetta Jr
Organizations
- Air Force Institute of Technology