Knowledge that Transforms

The theory of the firm under uncertainty has been discussed by P. A. Diamond and H. Leland in an elaboration of the expected utility maximization hypothesis. Leland's approach emphasizes the connection between the theory of the firm and inventory theory, with the price of the output being a stochastic variable. Diamond deals with technological uncertainty in a general equilibrium context; his theory explains, in part, the supply of financial assets by firms. Both approaches clearly have their origins in earlier literature on the theory of the firm under uncertainty, though Leland's seems to be much more closely related to the earlier quantitative literature. In inventory theory (see K. J. Arrow, S. Karlin, and H. Scarf), the firm minimizes the expected cost of holding inventories of the product it sells subject to stochastic demand, while in Leland's paper the firm produces output under what may be known and fixed production costs but sells output at a stochastic price. Diamond's paper can, with reinterpretation, be treated as the production function analogue of the theory of the demand for money under uncertainty, the stochastic input playing the role of the bond or asset with uncertain rate of return. Diamond's approach sharpens Jack Hirshleifer's hypothesis that the theory of investment under uncertainty involves an application of the expected utility maximization by presenting a specific source of uncertainty, the stochastic input in the neoclassical production function. In Diamond's paper, output by thejth firm is, in general,

According to a new approach to demand theory, households produce the commodities that enter their utility functions with inputs of market goods and their own time (see Gary Becker, Becker and Robert T. Michael, Kelvin Lancaster, Richard Muth). Provided time and goods were not employed in fixed proportions in the production of commodities, consumers would have an incentive to substitute the former for the latter if the price of their time, measured, say, by their potential real wage rate, declined. Since the incidence of unemployment causes the price of time to fall, one would expect unemployed workers to substitute their own time for market goods in the production of commodities. In this note, I use the notion of substitution in production between goods and time to interpret data on detailed family consumption expenditures before and during unemployment. The information is contained in a survey of the insured unemployed. In particular, I focus on differences in the pattern of expenditure reductions that emerge when primary market workers are unemployed, compared to when secondary market workers are unemployed. I also examine differences in the estimated income elasticity of total consumption for claimants in low unemployment areas compared to that for claimants in high unemployment areas. A tentative part of this analysis is a computation of the reduction in total consumption due to substitution of time for goods that would occur if unemployment were fully anticipated and, hence, not accompanied by a reduction in permanent income.

This Committee the Association's Committee on Economic Education is charged to help improve the teaching of economics. This is obviously a many-faceted problem, and at most a committee like this can expect to play only a modest role in prodding, stimulating innovation, encouraging, and providing help on some fronts. During the past decade the Committee has attempted especially to stimulate research on the effectiveness of alternative teaching approaches, to stimulate attention to the teaching process, and to raise the prestige of teaching at the college level. These attempts are documented elsewhere.1 Building on them, we now suggest some next steps.

Ronald Grieson comments on two aspects of our paper: the plausibility of its results, and the interpretation of its empirical findings. On empirical findings, we have no strong preference for our interpretation over Grieson's. He shows, in essence, that if the general price level enters the supply function as well as the demand function, then our regression coefficients may imply elasticities of supply somewhat higher than the ones we presented. The elasticities we presented ranged from .3 to .7; the ones he presents range from .4 to 2.2. Both Grieson's interpretation and ours lead to the same principal conclusion; namely, that . . . the long-run supply of housing services is less than perfectly elastic (see de Leeuw and Ekanem, p. 812). Both sets of elasticity estimates suffer from the problems of measurement error which our article discussed. An advantage of Grieson's interpretation is that it implies higher reduced-form coefficients for the price level than for income per household, which fits the data better than our specification. One disadvantage of his interpretation is that there is no clear theoretical basis for including the general price level in the supply function; if the supply function is the result of profit maximization subject to a production function for converting capital and operating inputs into housing services, then the only relevant prices would seem to be those of housing services, capital inputs, and operating inputs (all of which were already included in our specification). Possibly the general price level serves as a proxy for prices of inputs not covered by our measures. But surely the general price level does not belong in the supply function simply because it appears in the demand function, as Grieson seems to argue. On the plausibility of results, we have reservations about Grieson's position. He finds a long-run rising supply price for housing services plausible because of the inelastic supply of land. Both our elasticity estimates and his, however, refer to the elasticity of supply holding constant the price of land as well as prices of other inputs. (See de Leeuw and Ekanem, pp. 808, 810.) Hence, the explanation of our findings cannot be the tendency for the price of land to rise as housing demand shifts upward. We suspect that the explanation of our findings lies in diseconomies of scale in the maintenance, improvement, and conversion of existing housing capital. To understand the connection between these activities and our study it is useful to distinguish between two meanings of in the housing market. The first is a time period long enough for the total quantity of housing capital in a housing market to respond fully to changes in underlying conditions-a period whose length has been estimated to be of the order of magnitude of six years. (See Richard Muth, p. 76.) The second is a time period long enough for not just the quantity, but theform of existing housing capital number of units per building, architectural style, location pattern within a housing market area, and so forth-to respond fully to changes in underlying conditions. The second long run is surely a great deal longer than six years. We believe that the results of our study apply to the first rather than the second of these long runs. In the second long run, at least under competitive conditions, prices per unit of housing service presumably approach new construction prices (plus local land rents) for all types of housing. Since the construction of new housing is a replicable process, we might expect (input prices aside) constant returns to scale to characterize, at least approximately, this long run. In the first long run, however, there could be important quasi rents-positive or nega* The Urban Institute.