An econometric model of housing price, permanent income, tenure choice, and housing demand

Goodman, Allen C.

doi:10.1016/0094-1190(88)90022-8

Cited by 263 publications

(173 citation statements)

References 13 publications

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“…, must not be collinear with the other regressors in equation (11). One way of achieving identification is by ensuring that one or more variables in the neighborhood choice model be excluded from the housing structure demand equation.…”

Section: Parameter and N(h) Denotes The Neighborhood Cluster Of Indimentioning

confidence: 99%

“…We report here the specific form of the sample selection bias correction terms that are included in the housing structure demand equation (11). The mean of skh , conditional on alternative s h being chosen according to the MNL model, is given by:…”

Section: Appendix B: Selection Correction Termsmentioning

confidence: 99%

“…When a full complement of 74 explanatory variables are included, the pseudo-R 2 rises to 0.1934, and the additional variables included compared to those in the model reported in column 3 of Table 4 are jointly statistically significant. Table 5 reports the estimation results for the housing structure demand equation (11). As discussed in Section 4, we correct for (non-random) neighborhood choice by including an estimate of the expectation of the disturbance term conditional on census tract choice.…”

Section: Estimation Of Neighborhood Choicementioning

confidence: 99%

“…This is the familiar process for correcting for sample selection bias. Using the results in Dubin and McFadden [8], we derive the specific form of the sample selection bias correction terms that are included in equation (11). This requires eleven terms, one for each of the eleven census tracts in the neighborhood choice model.…”

Section: Parameter and N(h) Denotes The Neighborhood Cluster Of Indimentioning

confidence: 99%

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Interactions, neighborhood selection and housing demand

Ioannides

Zabel

2008

Journal of Urban Economics

163

148

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This paper contributes to the growing literature that aims at identifying and measuring the impact of social context on individual economic behavior. We develop a model of housing structure demand with neighborhood effects and neighborhood choice. Modeling neighborhood choice is of fundamental importance in estimating and understanding endogenous and contextual neighborhood effects. Controlling for non-random sorting into neighborhoods allows for unbiased estimates and provides a means for identifying endogenous neighborhood effects.Estimation of the model exploits a household-level data set that has been augmented with contextual information at two different levels ("scales") of aggregation. One is at the neighborhood level, consisting of about ten neighbors, with the data coming from the neighborhood clusters sub-sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. These data were geocoded by means of privileged access to confidential US Census data. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. Our estimates of the housing structure demand equation confirm that neighborhood effects are important. In particular, one's demand for housing depends on the mean of neighbors' demand for housing. JEL Classification Codes: R21, C31.

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Section: Parameter and N(h) Denotes The Neighborhood Cluster Of Indimentioning

confidence: 99%

Section: Appendix B: Selection Correction Termsmentioning

confidence: 99%

Section: Estimation Of Neighborhood Choicementioning

confidence: 99%

Section: Parameter and N(h) Denotes The Neighborhood Cluster Of Indimentioning

confidence: 99%

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Interactions, neighborhood selection and housing demand

Ioannides

Zabel

2008

Journal of Urban Economics

163

148

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“…For example, see Rosen (1979), Goodman (1988), Kan (2000), or Campbell and Cocco (2007). This literature studies how observable and unobservable household factors affect selection into and welfare from homeownership.…”

Section: Relation To the Literaturementioning

confidence: 99%

The housing stock, housing prices, and user costs: the roles of location, structure and unobserved quality

Halket¹,

Nesheim²,

Oswald³

2015

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Using the English Housing Survey, we estimate a supply side selection model of the allocation of properties to the owner-occupied and rental sectors. We find that location, structure and unobserved quality are important for understanding housing prices, rents and selection. Structural characteristics and unobserved quality are important for selection. Location is not. Accounting for selection is important for estimates of rent-to-price ratios and can explain some puzzling correlations between rent-to-price ratios and homeownership rates. We interpret this as strong evidence in favor of contracting frictions in the rental market likely related to housing maintenance.

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Cities After Socialism

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An econometric model of housing price, permanent income, tenure choice, and housing demand

Cited by 263 publications

References 13 publications

Interactions, neighborhood selection and housing demand

Interactions, neighborhood selection and housing demand

The housing stock, housing prices, and user costs: the roles of location, structure and unobserved quality

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