HIS paper develops and applies a model for analyzing regulatory change in the freight transportation industry. The model incorporates multiple product markets, multiple transport modes and imperfect competition between the modes. An application of the model to consider some of the consequences of extending the Interstate Commerce Commission's agricultural exemption to the railroads, for the movement of corn in the Midwest, is provided. The analysis has three significant elements. First, we extend the work in Daughety and Inaba (1978a,b) to obtain transport demands that are based on the theory of the firm. The shipper chooses markets to ship to, mode to ship by, as well as output level and amounts to ship. He faces transport modes that are differentiated by service characteristics which are generally stochastic in nature. Analyses of demand for freight transport that have been especially attentive to transport service characteristics and other micro-parameters include Allen (1970), Boyer (1977), Daughety and Inaba (1978a,b) and Levin (1978). While varying in some degree as to form and technique, these studies have all attempted to estimate disaggregate models of shipper behavior. In some cases this behavior was eventually aggregated to some form of market (or industry) demand functions. While such analyses are generally time-consuming and expensive the results have (at least sometimes) been worth the effort, paying off in models of demand that are responsive to important market parameters. Second, we propose a mechanism for constructing equilibria in imperfectly competitive transport markets. The underlying approach is to introduce a coniectural variations narameter that reflects different assumptions about how carriers will react to the actions of competitors. Third, we apply our methods to examine some of the consequences of extending the agricultural exemption (see, e.g., Locklin (1972)) to the railroads. Three market equilibria are computed: A base case wherein rail is regulated and trucks are unregulated and two polar deregulation cases wherein railroads act either competitively or in a coordinated fashion. Data to estimate transport demands were obtained from a survey of country grain elevator operators on shipments of corn originating in the Midwest (Iowa, Illinois and Indiana) and destined for interior, East Coast and Gulf Coast markets. ICC data were used to estimate rail cost functions, while survey data were used to provide truck rate functions, surrogates for truck supply functions. Our computations indicate that while transport rates will generally nrse after deregulation, rail rates will increase relatively more in markets characterized by low-volume or, short-haul activity. This will encourage a redistribution of freight patterns between rail and truck. Essentially, we argue that trucks will dominate in low-volume or short-haul markets so that just about all shipments made by country grain elevators will be by truck. On the other hand, rail will predominate over shipments made from inland terminal elevators to coast export markets, even in the face of barge competition. It is particularly interesting that these conclusions are implied by either of the two polar deregulation cases. That is, our conclusions are the same whether railroads price competitively or coordinate their actions. Of course, there is one difference: rates will tend to be slightly higher under coordination

T HE purpose of this paper is to evaluate the policy option of controlling cyclicality in housing and briefly review its policy-related implications. This subject has recently returned to the forefront of public concern,' because it is feared that housing cyclicality contributes to the high cost of housing (HUD, 1979) and has a detrimental effect on the continuity of urban change (as patterns of neighborhood development are affected (HUD, 1978)). The importance of housing derives from its dual role in the economy (Federal Home Loan Bank Board, 1969; Goldsmith and Lipsey, 1963). At the micro level it is a large component of both the consumer budget and asset portfolio (Artle and Varaiya, 1978). It also affects the quality of urban neighborhoods spatially. At the macro level, it accounts for 25% to 30% of gross domestic investment. Since the marked cycles in housing construction lead the business cycle, countercyclical monetary policy has relied on housing as a policy instrument (Harberger, 1970). Two arguments plead in favor of greater control of housing cyclicality: (i) the high and rising cost of housing causes housing unaffordability,2 raising questions of consumer welfare and equity: which socio-economic groups suffer most and deserve compensation; (ii) cyclicality destabilizes the macro economy, generating unemployment (hence the loss of urban jobs) while at the same time compounding the high cost of housing by creating inefficiency in the housing construction industry. These combined effects limit the redevelopment of urban neighborhoods called for under the 1974 Housing and Community Development Act and thus conflict with the aims of this Act. In section II we investigate the existence of significant cyclicality and characterize it. Problems of statistical methodology are discussed in section III. We conclude in section IV with an outline of the policy-related implications of our analysis, leaving the details of the statistical formulae and data sources to appendices A and B. The main highlights of the paper are (i) New Housing construction exhibits significant cyclicality. The length of the dominant cycle varies depending on which estimate of the spectral density is used. The smoothed periodogram shows a powerful cycle around 128 months' length. The unaveraged periodogram, on the other hand, is dominated by a shorter cycle of 70 to 80 months' length. These estimates of the spectral density are shown diagramatically. The difference in the length of the dominant cycles is attributed to the well-known problem of resolution when two peaks are near each other, the smoothed periodogram will be unable to distinguish between the two. The KolmoReceived for publication October 15, 1979. Revision accepted for publication December 9, 1980. * Cornell University and Boston College, respectively. This paper was developed while the first author was a Visiting Research Scholar with the Division of Policy and Research Development at the U.S. Department of Housing and Urban Development (HUD), Washington, D.C. A preliminary version of this paper was presented at the Annual Allied Social Sciences Meeting of the American Real Estate and Urban Economics Association, Atlanta, December 1979. The authors are grateful to Craig Swan and an anonymous referee for useful comments. Ibrahim Levent helped with the calculations. 1 The U.S. Department of Housing and Urban Development (HUD), the White House, the Council on Wage and Price Control, various Congressional committees, the Office of Budget Management, etc., are all now interested in housing cyclicality and its policy implications. 2 Housing costs increased faster than most components of the consumer price index (U.S. Department of Labor, 1978), and threaten to make housing unaffordable (Data Resources, Inc., 1978; Jacobe and Parliment, 1979; Weicher, 1977). Some studies deny this, pointing to several important elements which offset the cost of housing, especially during periods of high inflation. These include tax advantages accruing to homeowners and capital gains on houses (Diamond, 1979; Hendershott and Hu, 1979; Van Order, 1979; Villani, 1978). These studies, however, neglect the equity problem resulting from the income distribution welfare effect. In a recent study using a production function analysis, Clemhout (1979) found that fluctuations in residential housing starts (or expenditures) create a range of inefficiencies in production, thereby increasing costs. Additional increases can be attributed to government regulation (Seidel, 1978), but many costs could be reduced if fluctuations in construction were moderated