Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems
提出一种迭代线性最小二乘估计量，用于估计条件线性的非线性需求系统，并证明其一致性和渐近有效性，以22种商品的需求系统为例进行应用。
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.