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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
    DOI: 10.1016/j.regsciurbeco.2011.07.005
    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

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    1. Mark Grinblatt & Matti Keloharju & Seppo Ikäheimo, 2008. "Social Influence and Consumption: Evidence from the Automobile Purchases of Neighbors," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 735-753, November.
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    3. Stoker, Thomas M, 1993. "Empirical Approaches to the Problem of Aggregation Over Individuals," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1827-1874, December.
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    7. Daniel Aaronson, 1998. "Using Sibling Data to Estimate the Impact of Neighborhoods on Children's Educational Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 33(4), pages 915-946.
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    12. Masayoshi Hayashi & Robin Boadway, 2001. "An empirical analysis of intergovernmental tax interaction: the case of business income taxes in Canada," Canadian Journal of Economics, Canadian Economics Association, vol. 34(2), pages 481-503, May.
    13. Ioannides, Yannis M. & Zabel, Jeffrey E., 2008. "Interactions, neighborhood selection and housing demand," Journal of Urban Economics, Elsevier, vol. 63(1), pages 229-252, January.
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    17. Evans, William N & Oates, Wallace E & Schwab, Robert M, 1992. "Measuring Peer Group Effects: A Study of Teenage Behavior," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 966-991, October.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.

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