This paper develops an economic theory of replacement investment that can provide a basis for specifying an econometric model of investment behavior. The long-run and short-run effects of changes in the interest rate and in tax laws are examined. The paper also investigates several reasons why the common assumption of a technologically constant rate of replacement is incorrect even as an asymptotic limit. LARGE VARIATIONS in capital spending continue to motivate econometric studies of investment behavior. The past decade has seen the development of attempts to model net investment as the adjustment of the capital stock to a desirable level. Building on earlier work by Lutz [35], Haavelmo [21], and others, Jorgenson and his collaborators (e.g. [24, 28, 31, and 33]) have provided an operational model of net capital accumulation that relates desired capital to the cost of capital services. Although serious objections have been raised about the specification of the optimal capital stock (including [5, 9, 13, and 15]) and about the arbitrary nature of the adjustment dynamics [37], it is likely that some form of this general model will continue to provide a framework for future investment studies. In contrast to these developments of a theory of capital expansion, replacement investment continues to be analyzed in terms of a non-economic model of technical necessity. Jorgenson and others have adopted the simplifying assumption that replacement investment is a constant proportion of the capital stock.2 This assumption has been challenged and contrary evidence has been offered by Feldstein and Foot [14] and Eisner [10]. The purpose of the current paper is to examine several aspects of a theory of replacement investment. We hope not only to show that a model with a constant replacement rate is implausible and unsatisfactory but also to provide a basis for better empirical work in the future. The magnitude of replacement investment (the annual rate of replacement investment generally exceeds expansion investment) makes this issue a matter of substantial importance.

THE CLASSIC PAPER by Grunfeld and Griliches [3] contains many instructive insights into question of circumstances under which an aggregate dependent variable may be forecasted more precisely with a model based on aggregate variables as opposed to an aggregate of forecasts from individual equations. The statistical model they employ is standard regression framework, a single at macro level and a set of seemingly unrelated regressions (to use Zellner's term) at level. Under assumptions of perfect model specification and nonstochastic regressors, a result of Theil's supports superiority of equations. It is Grunfeld and Griliches' main contention, however, that equations are likely to be more poorly specified than is macro equation. Perhaps, therefore, an aggregation will be realized in prediction of aggregate dependent variable by use of macro equation. While intuitively appealing, one soon finds that to articulate notion that micro equations are likely to be more poorly specified than is macro equation is difficult. Grunfeld and Griliches provide an illustration [3, pp. 7-9] that more than anything else points up elusive character of this notion. Recently, Orcutt, Watts, and Edwards [7] and Edwards and Orcutt [2] published papers that ostensibly support prediction from disaggregated data. Edwards and Orcutt note that a more basic difficulty with equations is that suitable data are scarce. Grunfeld and Griliches had earlier observed in passing that the poor quality of data may be another source of aggregation gain [3, p. 10]. It is precisely this consideration which we propose to examine in present paper. More particularly, we examine virtues of estimating or macro equations when independent variables in equations are observed with error, but corresponding aggregate variables have a smaller (or possibly no) observation error. There are many economic applications in which such offsetting errors may be plausibly hypothesized. For example, there may be some arbitrariness in classification of products (or industrial breakdown), so that while total sales figures for a given firm may be well established, their components may be subject to error. Alternatively, we may have common situation in which an aggregate figure is collected on a regular basis from a relatively complete sample, but components are calculated from benchmarks provided from a smaller or an older sample.

[The paper presents maximum likelihood methods for estimating four types of disequilibrium models. In each case the model includes three equations: the demand equation, the supply equation, and the condition that quantity observed is the minimum of quantity demanded and quantity supplied. The first model consists of just these equations. In the second model one knows whether one is on the demand function or the supply function by looking at the direction of the change in price. In the third model the price change is assumed to be proportional to excess demand. In the fourth model the price change is a stochastic function of excess demand and possibly other exogenous variables. Some illustrative calculations are presented using the housing starts model considered by Fair and Jaffee in an earlier issue of this journal.]

Abstract The article reports that in a situation of decentralized decision making, the Multiple Objective Linear Programming (MOLP) approach provides the decision makers with an appropriate multidimensional scheme of transfer prices. Once again these prices exactly balance the accounts associated with basic products and show opportunity losses for nonbasic products. The transfer prices derived from the MOLP allow central management to calculate the actual divisional contributions to each of the measures of corporate performance, adjusted for the opportunity costs associated with transferred goods. It follows that the divisional targets derived from an MOLP solution are logical and "fair." Operationally and assuming a state of certainty for planning purposes the task of the corporate planner would be to review the various alternative efficient solutions and pick out the "best" or "most desirable." In a situation of decentralized decision making it is already known that the transfer pricing mechanism does not necessarily lead to optimal divisional decisions. This drawback applies equally to MOLP in general and the example in particular.

John S. McCallum, The Expected Holding Period Return, The Term Structure of Interest Rates and Investment in the Government of Canada Bond Market, The Journal of Finance, Vol. 29, No. 1 (Mar., 1974), p. 276