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Excerpt from Nonlinear Three Stage Least Squares Pooling of Cross Section and Average Time Series DataThe purpose of this paper is to discuss the estimation of exact aggregation models by the nonlinear three stage least squares method (nlbsls) of Amemiya Gallant Gallant and Jorgenson Jorgenson and Laffont (1974) and others. In exact aggregation models there is a unique correspondence between individual behavior and aggregate behavior. This property, known as recoverability, makes exact aggregation models appropriate for the analysis of individual data, average data or both in combination. In this paper we consider estima tion using both cross section data on individuals and average time series data. We present the estimator, discuss its properties, demon strate its similarity to linear pooling estimators, and indicate its computational advantages over other nonlinear estimators.About the PublisherForgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.comThis book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works
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Nonlinear Three Stage Least Squares Pooling of Cross Section and Average Time Series Data
Bokrecensioner » Nonlinear Three Stage Least Squares Pooling of Cross Section and Average Time Series Data (Classic Reprint)
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