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

Richard Blundell () and Jean-Marc Robin

Journal of Applied Econometrics, 1999, vol. 14, issue 3, 209-32

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.

Date: 1999
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Related works:
Journal Article: Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems (1999)
Working Paper: Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems (1999)
Working Paper: Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems (1999)
Working Paper: Estimation in large and disaggregated demand systems: An estimator for conditionally linear systems (1999)
Working Paper: Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems (1999)
Working Paper: Estimation in Large and Dissagregated Demand Systems: An Estimator for Conditionally Linear Systems (1997)
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