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Theory and Estimation in the Economics of Housing Demand

Theory and Estimation in the Economics of Housing Demand. By Stephen K. Mayo From Journal of Urban Economics, 1981, p95-116 Presented by Yong Li December.4, 2002. Introduction and Purpose.

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Theory and Estimation in the Economics of Housing Demand

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  1. Theory and Estimation in the Economics of Housing Demand By Stephen K. Mayo From Journal of Urban Economics, 1981, p95-116 Presented by Yong Li December.4, 2002

  2. Introduction and Purpose • A review of theoretical and empirical developments made prior to 1980 on the subject of housing demand. • Four main topics: • Income elasticity of demand for housing • Price elasticity of demand for housing • Demographic variation in housing demand • Dynamic aspects of housing demand

  3. Basic Model • A log-linear demand equation: lnH = a + blny + clnpH , Where H is housing; y is income; pH is the relative price of housing a, b and c are parameters

  4. Income Elasticity • Key issues: • How sensitive is demand to changes in income? • Empirical work uses current income rather than an appropriate measure of permanent, or expected income, to estimate the model. • As a result, to what degree are the estimates of elasticity likely to be biased?

  5. The Bias • Current income elasticity will be biased downward in proportion to the ratio of variances of permanent income to current income asymptotic E(êy) = eyVy Where Vy=Var(yp)/Var(y)=Var(yp)/[Var(yp)+Var(yt))]<1 yp is permanent income; yt is transitory income

  6. The Bias • The smaller the variance of transitory income, the smaller the bias of estimated current income elasticity. • Efforts made to deal with the problem of estimating permanent income elasticity. • Grouping • Averaging • IV

  7. Some Discussions

  8. Demographic Effects • What’s the impact of inclusion of demographic variables on estimated demand elasticity? • Difficult to compare the results of previous work. • Some general conclusions from analyses using additive specifications of demographic variables. • Race • Sex • Age and household size • Alternative methods dealing with demographic variables

  9. Extension • Stone-Geary utility function with three goods—housing quality, Q; housing quantity, S; and other goods, Z: U=(Q-θQ)a(S-θS)b(Z-θZ)c (1) Where a+b+c=1. Maximize equation (1) with respect to the budget constraint: y=pzZ+R, (2) And, let R=QSm, where 0<m<1 (3) So, budget constraint is y=pzZ+QSm (4)

  10. Conclusions • For a wide range of analyses employing different data bases and methodologies, the permanent income elasticity of demand for housing is estimated to be well below one on average. • It’s been shown that not only are aggregation biases serious in affecting demand elasticity estimates, but, fortunately, they are largely avoidable if proper precautions are taken.

  11. Conclusions • Demographic variables, which have so far been only poorly integrated into theories of housing demand appear to have significant impacts on demand. • It’s been suggested that demand equations explicitly based on appropriate utility functions deserve more attention.

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