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A mean squared error estimator of market size in hedonic price analysis

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  • Camilo Sarmiento

Abstract

This paper presents a spatial kernel estimator that allows coefficients and market size to be estimated at the observation of interest. In economic terms, the bandwidth length of the spatial kernel estimator captures the size of the market incorporated in estimation at the location of interest, and this optimal size of the market included in regression minimizes mean square error (MSE).

Suggested Citation

  • Camilo Sarmiento, 2005. "A mean squared error estimator of market size in hedonic price analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 12(6), pages 355-359.
    • Handle: RePEc:taf:apeclt:v:12:y:2005:i:6:p:355-359
    DOI: 10.1080/13504850500044187
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    References listed on IDEAS

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    1. C. Sarmiento, 2004. "Modelling firm heterogeneity with spatial 'trends'," Applied Economics Letters, Taylor & Francis Journals, vol. 11(5), pages 271-274.
    2. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-965, July.
    3. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    4. Z. Wang, 2003. "Hedonic prices for crude oil," Applied Economics Letters, Taylor & Francis Journals, vol. 10(13), pages 857-861.
    5. Richard Schmalensee & Thomas M. Stoker, 1999. "Household Gasoline Demand in the United States," Econometrica, Econometric Society, vol. 67(3), pages 645-662, May.
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    Cited by:

    1. Camilo Sarmiento & William Wilson, 2007. "Spatially correlated exit strategies in the baking industry," Applied Economics, Taylor & Francis Journals, vol. 39(4), pages 441-448.

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