I N 1956 Gale [4] considered a general model of balanced growth and asserted the existence of price vectors which equate the economic growth with the technological growth rate. This model of Gale was an extension of fundamental results earlier proven by von Neumann for the case in which the production space was polyhedral. Recently Hulsmann and Steinmetz [6] demonstrated that Gale's theorem was not true by constructing a counterexample. In this paper we shall prove that Gale's theorem in a modified form is true and with a certain regularization the original theorem of Gale is valid. This regularization will be automatically satisfied by polyhedral production spaces so that as a corollary the proof for the polyhedral version of Gale's theorem will be attained. Finally we show that the counterexample of Hulsmann and Steinmetz [6] does not satisfy this regularization.

This paper presents a comparison of three distributed lag estimators: OLS, the Almon procedure, and the Hannan inefficient method. Each method is compared for sample sizes of 50 and 100 for several alternative distributed lag shapes and residual process structures. The results not only reveal the relative performance of these estimators, but also provide evidence on each method's performance under misspecification with respect to lag length and the residual process.

Aman Ullah, A. L. Nagar, The Exact Mean of the Two-Stage Least Squares Estimator of the Structural Parameters in an Equation Having Three Endogenous Variables, Econometrica, Vol. 42, No. 4 (Jul., 1974), pp. 749-758

The distribution of personal income is approximated by a two-parameter gamma density function (Pearson Type III). The two parameters may be considered as indicators of scale and of inequality, respectively. Maximum likelihood estimates of the parameters are derived from a random sample using graphical techniques, and a likelihood ratio test for the hypothesis that the inequality parameter is the same for different distributions is presented. The derivation of both the estimates and the test statistic requires computing the arithmetic and geometric means from the sample. An empirical application, including a comparison of the gamma and lognormal distributions to demonstrate the better fit of the gamma, is made to personal income data in the United States for the years 1960 to 1969. Using the gamma density, inequality is shown to decrease when unemployment or inflation decreases, or when the real national product increases.