By George G. Judge, Richard H. Day, S. R. Johnson, Gordon C. Rausser, Lee R. Martin
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Extra info for Survey of Agriculture Economics Literature: Quantitative Methods in Agricultural Economics, 1940'S-1970's
Sample text
Xj, the statistical model Y = X)3 + u, with usual definitions for the variables and the least squares estimator, then Given this result, Theil [1954] raised the question of whether we should abolish the macro models and estimates. Alternatively, Klein [1953] showed that when the macro and micro relations are derived so that they are consistent, then the macro variables are weighted averages of the micro coefficients. If the weights are stable over time, then no aggregation bias results. The usual case, however, is for the weights to change over time.
Anderson and Rubin [1949] developed the "limited information" maximum likelihood estimators for estimating the parameters of an equation in a system of equations and derived corresponding large sample properties and statistical tests. Koopmans [1949] faced up to the problem first raised by Working [1926] and developed, with the aid of zero linear restrictions on F, B, and 2, necessary and sufficient conditions for identifying each mathematical equation as a definite economic relation and discriminating between alternative competing structures.
Work continued on how to detect and mitigate such specification errors as autocorrelation and heteroscedasticity and even the old multicollinearity problem took on new interest. In particular, Lancaster [1968] , Goldfeld and Quandt [1965], Glejser [1969], and Rutemiller and Bowers [1968] advanced the topic of estimation in a heteroscedastic regression model; Koerts [1967], Theil [1965, 1968], Kadiyala [1968], Durbin [1970a, 1970b], Tiao and Zellner [1964], and Rao and Griliches [1969] contributed procedures and tests for autocorrelation; Farrar and Glauber [1967], Silvey [1969] , andToroVizcarrondo and Wallace [1968] contributed procedures and tests for handling multicollinearity.