Modelling Scale Effect in Crosssection Data:The Case of Hedonic Price Regression
AbstractAn innovative and simple experiment with cross-section data ordering is carried out to exploit a basic and common feature between many economic variablesâ€“nonlinear scale dependence. The experiment is tried on hedonic price regression models using two data sets, one for automobiles and the other computers. The key findings are: (a) Hedonic price indices can be significantly biased if they are constructed using models which disregard possible nonlinear scale effects latent in random data samples; (b) Scale-based data ordering offers considerable potential to filter such scale-dependent information from cross-section samples; (c) The filtering can be easily carried out by systematic adoption of dynamic modelling methods.
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Bibliographic InfoPaper provided by Department of Economics, SOAS, University of London, UK in its series Working Papers with number 184.
Length: 20 pages
Date of creation: Sep 2013
Date of revision:
cross-section data ordering; scale effects; hedonic price; COMFAC model;
Find related papers by 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
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- D40 - Microeconomics - - Market Structure and Pricing - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-10-18 (All new papers)
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