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, 209-232

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. Copyright © 1999 John Wiley & Sons, Ltd.

Date: 1999
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https://doi.org/10.1002/(SICI)1099-1255(199905/06)14:33.0.CO;2-X

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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