[This article presents the first and second moments of an estimator which might be used when two subsamples are characterized by the same regression coefficients, but possibly different error variances. The estimator is the OLS estimator if the hypothesis of equal variances is accepted and the two-step Aitken estimator otherwise. The estimator is similar to one suggested by Goldfeld and Quandt and is applicable to a reparameterized version of the error components model.]

Firms' investment in plant and equipment is explained by a stock-adjustment model in which the coefficient of adjustment is allowed to vary. It is assumed that firms partially close the gap between desired and actual capital stock, but that the speed of adjustment depends on the firm's ability to procure funds at reasonable cost. A panel of individual firm responses to the McGraw-Hill plant and equipment survey is the principal data source, supplemented by financial statement information for the firms and two indices representing costs of debt and equity financing. The predictions generated by the regressions are aggregated for comparison with the observed aggregates. 1. A STOCK-ADJUSTMENT INVESTMENT MODEL THE PURPOSE of this paper is to develop and test a model to explain firms' investment in plant and equipment. The model incorporates features which recent research on the investment decision suggests are significant. The basic framework is a stock-adjustment model, in which each year the firm moves partially toward its desired position, with the coefficient of adjustment (reaction coefficient) allowed to vary by firm and year. The model has the form

T HE main purpose of this paper is to investigate the relationships between the state distribution of military prime contract awards for experimental and developmental, tests, and research work (hereafter EDTR) and the state distribution of total military prime contract awards. It has been argued that the acquisition of research contracts in a particular state is desirable because such contracts lead to large procurement awards in the future, and these awards are important for the state's economic growth. Consider, for example, the remark of Senator Hubert H. Humphrey:

This paper is concerned with the problem of price regulation when demand is uncertain. Uncertainty gives rise to substantial difficulties in determining both the return a firm's owners should be provided and a set of prices capable of producing that return. We argue that conventional approaches to price regulation are incapable of attaining the economically desirable objectives of efficiency and an equitable return to investors. The deficiencies in current practices are attributable to the separation of the risk measurement‐return determination and price setting activities in the conventional approach. We present a model of the regulated firm that synthesizes contemporary financial market theory and the theory of the firm under uncertainty. 1 In our approach, the income stream produced by the firm is valued ex ante in the financial market according to investors' perceptions and preferences over riskreturn characteristics. We portray the firm as producing risk and return by choosing among available production technologies to maximize its market value, given the prices set by regulators. Within this framework, it is shown that regulators can choose the lowest prices consistent with an equitable return to investors. We also show that prices so chosen induce the choice of the optimal technology by the firm.