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Estimation in Large and Disaggregated Demand Systems: An Estimator for Conditionally Linear Systems

Richard Blundell and Jean Marc Robin
Journal of Applied Econometrics
Vol. 14, No. 3 (May - Jun., 1999), pp. 209-232
Published by: Wiley
Stable URL: http://www.jstor.org/stable/223176
Page Count: 24
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Estimation in Large and Disaggregated Demand Systems: An Estimator for Conditionally Linear Systems
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Abstract

Empirical 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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