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On Hedonic Valuation of Urban Amenities Using Unbalanced Data

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  • Valerie Mueller
  • Glenn Sheriff

Abstract

Hedonic valuation of urban amenities often requires estimating housing and labor market regressions. It is difficult to get both types of data for all survey respondents. We show that the common practice of conducting two separate regressions with unbalanced data causes inconsistent covariance matrix estimation and improper inference regarding amenity values. We demonstrate how two easily implementable yet consistent techniques can be used for hedonic valuation with an application in valuing temperature increases in urban Brazil.

Suggested Citation

  • Valerie Mueller & Glenn Sheriff, 2010. "On Hedonic Valuation of Urban Amenities Using Unbalanced Data," Land Economics, University of Wisconsin Press, vol. 86(3).
    • Handle: RePEc:uwp:landec:v:86:y:2010:iii:1:p545-551
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    References listed on IDEAS

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    1. Badi H. Baltagi & Susan Garvin & Stephen Kerman, 1989. "Further Monte Carlo Evidence on Seemingly Unrelated Regressions with Unequal Number of Observations," Annals of Economics and Statistics, GENES, issue 14, pages 103-115.
    2. Bayer, Patrick & Keohane, Nathaniel & Timmins, Christopher, 2009. "Migration and hedonic valuation: The case of air quality," Journal of Environmental Economics and Management, Elsevier, vol. 58(1), pages 1-14, July.
    3. Schmidt, Peter, 1977. "Estimation of seemingly unrelated regressions with unequal numbers of observations," Journal of Econometrics, Elsevier, vol. 5(3), pages 365-377, May.
    4. repec:adr:anecst:y:1989:i:14:p:05 is not listed on IDEAS
    5. Hwang, Hae-shin, 1990. "Estimation of a Linear SUR Model with Unequal Numbers of Observations," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 510-515, August.
    6. Allen McDowell, 2004. "From the help desk: Seemingly unrelated regression with unbalanced equations," Stata Journal, StataCorp LP, vol. 4(4), pages 442-448, December.
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    Cited by:

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    2. Waldemar Beimer & Wolfgang Maennig, 2017. "Fallende Preise für Einfamilienhäuser: Struktur oder Lage? Der Fall Berlins," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 24(02), pages 21-25, April.

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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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