6

# **4. Motorization**

What have analysts discovered about the determinants of motor vehicle ownership? Because vehicles are mainly privately produced and purchased, vehicle ownership is usually analyzed in the traditional economic demand framework. Knowledge about the effects of income, prices, demographic trends, and transport policy on car ownership is needed to predict the effect that specific policies might have on vehicle ownership patterns.

During the last four decades, many empirical studies have modeled and forecast the trends of motor vehicle ownership and use in various countries.<sup>7</sup> These studies fall into three categories, based on the type of data used. In the first category are models that analyze motorization using time series data (trends over time in a city or country) or attempt to extrapolate national or regional motor vehicle ownership trends to future years under the explicit assumption of a saturation level.8 The second category of models uses cross-section data (data from a single point in time where variations are analyzed across households, cities, or countries). Some of these studies use aggregate data to produce longrun income elasticity estimates while others use disaggregate household level data to explain household car ownership behavior.<sup>9</sup> The third category of models uses panel data, 7For a concise survey of the commonly used methodologies, see Juan de Dios Ortuzar and Luis G. Willumsen, _Modeling Transport_ (New York: John Wiley & Sons, 1994), pp. 405-13. For more thorough discussions of the econometric techniques, see Stephen Glaister, _Fundamentals of Transport Economics_ (New York: St. Martin's Press, 1981); Kenneth Button, A. D. Pearnan, and A. S. Fowkes, _Car Ownership Modeling and Forecasting_ (London: Gower Publishing Company Ltd., 1982); M. J. H. Mogridge, _The Car Market: A Study of the Statics and Dynamics of Supply-Demand Equilibrium_ (London: Pion, 1983); and Kenneth E. Train, _Qualitative Choice Analysis: Theory, Econometrics and An Application to Automobile Demand_ (Cambridge, Mass.: MIT Press, 1986).

_8_ See, for example, S. Wildhom and others, _How to Save Gasoline_ (Santa Monica, Calif.: Rand Corporation, 1974); J. L. Sweeney, _Energy Policy and Automobile Use of Gasoline_ (Palo Alto, Calif.: Stanford University Press, 1978); Anthony Chin and Peter Smith, "Automobile Ownership and Govermnent Policy: the Economics of Singapore's Vehicle Quota Scheme," _Transportation Research A,_ Vol. 31, No. 2, pp. 129-40. The time series models that extrapolate motor vehicle ownership trends assume that the number of vehicles per person has an upper limit, beyond which changes in income or other attributes will have no effect on vehicle ownership. This upper limit is termed a saturation level. For examples of these models, see J. C. Tanner, "Forecasts of Future Numbers of Vehicles in Great Britain," _Roads and Road Construction,_ vol. 40 (1962), pp. 236-74; J. C. Tanner, "Long Term Forecasting of Vehicle Ownership and Road Traffic," _Journal of the Royal Statistical Society,_ vol. 141A, no. 1 (1978), pp. 14-63; M. J. H. Mogridge, "The Prediction of Car Ownership," _Journal of Transport Economics and Policy,_ vol. I (January 1967), pp. 52-74; and M. J. H. .Mogridge, "The Prediction of Car Ownership and Use Revisited," _Journal of Transport Economics and Policy,_ vol. 23 (January 1989), pp. 55-74.

For studies using aggregate data, see Michael E. Beesley and John F. Kain, "Urban Form, Car Ownership and Public Policy: An Appraisal of Traffic in Towns," _Urban Studies, vol._ 1, no. 2 (November 1964), pp. 174-203; Aubrey Silberston, "Automobile Use and the Standard of Living in East and West." _Journal of Transport Economics and Policy,_ vol. 4 (January 1970), pp. 3-14; William C. Wheaton, "The Long-Run Structure of Transportation and Gasoline Demand." _The Bell Journal of Economics,_ vol. 13 (Autumn 1982), pp. 439-54; and John F. Kain and Zhi Liu, "Efficiency and Locational Consequences of Government Transport Policies and Spending in Chile," Harvard Project on Urbanization in Chile (Harvard University, 1994). Studies using disaggregate household level data include D. A. Quarmby and J. J. Bates, "An