Richard Blundell
;
Jean-Marc Robin
You're currently viewing an old version of this dataset. To see the current version, click here.

estimation in large and disaggregated demand systems: an estimator for conditionally linear systems (replication data)

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.

Data and Resources

This dataset has no data

Suggested Citation

Blundell, Richard; Robin, Jean-Marc (1999): Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems (replication data). Version: 1. Journal of Applied Econometrics. Dataset. https://journaldata.zbw.eu/dataset/estimation-in-large-and-disaggregated-demand-systems-an-estimator-for-conditionally-linear-systems?activity_id=f124b45f-85d3-4971-9970-8824635626f7