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Keeping up with the Joneses: Neighborhood effects in housing renovation

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  • Helms, Andrew C.
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    Abstract

    Despite widespread recognition that housing renovation is influenced by “neighborhood effects”, virtually all empirical studies have failed to identify a positive feedback effect between renovation activity and neighborhood quality. By explicitly modeling the spatial interdependence of households' renovation decisions and analyzing a detailed block-level data set, this study finds strong empirical evidence that endogenous neighborhood effects exist as expected. Moreover, by considering four different parameterizations of a “neighborhood set” and comparing the results of these spatial econometric models with a standard OLS estimation, this paper provides insight into some common methodological issues encountered when modeling neighborhood effects.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0166046211001001
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    Article provided by Elsevier in its journal Regional Science and Urban Economics.

    Volume (Year): 42 (2012)
    Issue (Month): 1-2 ()
    Pages: 303-313

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    Handle: RePEc:eee:regeco:v:42:y:2012:i:1:p:303-313
    Contact details of provider: Web page: http://www.elsevier.com/locate/regec

    Keywords: Neighborhood effects; Housing renovation; Spatial econometrics;

    Find related papers by JEL classification:

    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

    References listed on IDEAS
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    Cited by:

    1. Munneke, Henry J. & Womack, Kiplan S., 2015. "Neighborhood renewal: The decision to renovate or tear down," Regional Science and Urban Economics, Elsevier, vol. 54(C), pages 99-115.
    2. Simlai, Prodosh, 2014. "Estimation of variance of housing prices using spatial conditional heteroskedasticity (SARCH) model with an application to Boston housing price data," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 17-30.
    3. Jin, Fei & Lee, Lung-fei, 2012. "Approximated likelihood and root estimators for spatial interaction in spatial autoregressive models," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 446-458.

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