Estimation in Large and Disaggregated Demand Systems: An Estimator for Conditionally Linear Systems
AbstractEmpirical demand systems that do not impose unreasonable restrictions on preferences are typically non-linear. We show, however, that all popular systems possess the property of conditional linearity. A computationally attractive iterated linear least squares estimator (ILLE) is proposed for large non-linear simultaneous equation systems which are conditionally linear in unknown parameters. The estimator is shown to be consistent and its asymptotic efficiency properties are derived. An application is given for a 22-commodity quadratic demand system using household-level data from a time series of repeated cross-sections.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.
Volume (Year): 14 (1999)
Issue (Month): 3 (May-June)
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Web page: http://www.interscience.wiley.com/jpages/0883-7252/
Other versions of this item:
- Richard Blundell & Jean-Marc Robin, 1999. "Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems," Working Papers 249982, Institut National de la Recherche Agronomique, France.
- R, Blundell & Jean-Marc Robin, 1997. "Estimation in Large and Dissagregated Demand Systems : An Estimator for Conditionally Linear Systems," Working Papers 97-08, Centre de Recherche en Economie et Statistique.
- Blundell & Robin, 1999. "Estimation in large and disaggregated demand systems : an estimator for conditionally linear systems," Working Papers 156380, Institut National de la Recherche Agronomique, France.
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