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Regional model of multi family housing starts : an inventory adjustment approach Fountain, Judy A.

Abstract

The decline in multi family housing starts in Urban Canada during the 1970's and the attendant low vacancy rates has generated comment on the efficiency of housing markets and the possibity of a housing crisis. Traditionally, existing vacant units are cited as a buffer between the demand and supply. This paper proposes that the inventory of new units offers a more direct buffer. Therefore the use of an inventory adjustment model to estimate and predict multi family housing starts is suggested. The theoretical model suggests that there is some desired inventory level which builders or investors will try to maintain depending on expected profitability, the relative yield on other investments and the cost of maintaining vacant units. Demand for new rental units will depend upon the deomographic structure of the population, unemployment, income, and the relationship between rents ownership costs and the cost of other goods and services. Starts will be set to satisfy the expected demand and adjust actual inventory levels to the desired inventory level. Quarterly data for the Vancouver CMA, from 1963 to 1982 are used to test this model. The empirical analysis consists of three parts: a structural- model based on the inventory adjustment process, a time series model to provide a measure for evaluating the success of the structural model, and an analysis of the forecasting capabilities of these two models. Data from 1963 to 1980 are used to estimate the models and 1981 to 1982 data are maintained to test the forecasts. The results suffer from inadequacies of the available data, immeasurable impacts of government policy and programs and possible idiosyncracies of the Vancouver housing market. In general, the results indicate that inventories do provide a buffer between the demand and supply of multi family housing units. As such, the vacancy rate of existing units, in isolation, is an insufficient indicator of market activity and response. Similar analysis for other urban centres in Canada is needed to determine the uniqueness of these results. Also, it may be possible to develop an improved forecasting model by incorporating the time series coefficients with the structural model.

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