More Realistic Single Equation Models Through Specification of Random Coefficients*

Max R. Langham and Michael Mara

Journal of Agricultural and Applied Economics, 1973, vol. 5, issue 1, 161-166

Abstract: Regression analysis with its many modifications and extensions plays a dominant role as an analytical tool in economic research. The linear regression model with random coefficients (hereafter RCR for random coefficient regression) provides a generalization of the classical linear regression model and permits a more realistic specification of the real world than does the classical model. As a consequence RCR will probably play an increasingly important role in econometric analysis of a wide class of problems-particularly as probabilistic micro-economic theory develops.

Date: 1973
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