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Hedonic regressions: mis-specification and neural networks

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  • Bruce Curry
  • Peter Morgan
  • Mick Silver

Abstract

There is an emerging literature in the field of hedonic regressions which successfully applies flexible functional forms. In contrast, numerous authors report hedonic regressions with relatively simple functions, often with little or no attempt to consider interaction terms and higher level powers. Such simple functions perform relatively well in spite of good a priori grounds for quite complex interaction effects. Indeed, the studies are characterised by a general indifference to testing these more flexible models, even when degrees of freedom permit. Using detailed scanner data, hedonic functions for the UK TV market are estimated and tested for interaction effects. For a case study of the market, higher level interaction effects are tested for and compare the results with those from a neural network, with its property of 'universal approximation'. The use of neural networks is particularly novel in this context and some general findings on their suitability emerge.

Suggested Citation

  • Bruce Curry & Peter Morgan & Mick Silver, 2001. "Hedonic regressions: mis-specification and neural networks," Applied Economics, Taylor & Francis Journals, vol. 33(5), pages 659-671.
  • Handle: RePEc:taf:applec:v:33:y:2001:i:5:p:659-671
    DOI: 10.1080/00036840122335
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    References listed on IDEAS

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    1. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
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    1. repec:spr:alstar:v:102:y:2018:i:1:d:10.1007_s10182-017-0293-4 is not listed on IDEAS
    2. Brachinger, Hans Wolfgang & Beer, Michael, 2009. "The Econometric Foundations of Hedonic Elementary Price Indices," DQE Working Papers 12, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland.
    3. Hoffmann, Johannes & Kurz, Claudia, 2002. "Rent indices for housing in West Germany 1985 to 1998," Working Paper Series 0116, European Central Bank.
    4. Manuel Landajo & Celia Bilbao & Amelia Bilbao, 2012. "Nonparametric neural network modeling of hedonic prices in the housing market," Empirical Economics, Springer, vol. 42(3), pages 987-1009, June.
    5. Michael Beer, 2007. "Bootstrapping a hedonic price index: experience from used cars data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(1), pages 77-92, March.

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