Working Paper No. 62

Missing Variables and Two-Stage Least-Squares Estimation from More than One Data Set

Published: April, 1982Pages: 19Keywords: Missing data, Pooling data, Statistical matching, TSLS estimation

Missing Variables and Two-Stage Least-Squares Estimation from More than One Data Set Anders Klevmarken


In a situation when no single sample inc1udes all the endogenous variables of a simultaneous equation model but there are two (or more) non-overlapping samples and each variable is included in at least one, then it is possible to pool the data and estimate the model consistently by a two-stage least-squares procedure. The asymptotic variances of the estimates are not always larger than those which would have been obtained with TSLS from one complete sample. It is also shown that under certain assumptions the same approach can be applied to an ordinary regression model.

Integrating Immigrants into the Nordic Labour Markets

An Overall Perspective

Pages-from-2019-Calmfors-Gassen---Integrating-Immigrants-into-the-Nordic-Labour-Markets.gif

Denmark, Finland, Norway and Sweden face similar problems of integrating large groups of immigrants, especially low-educated ones from outside the EU, into their labour markets. In this volume, edited by Lars Calmfors, IFN, and Nora Sánchez Gassen in cooperation with researchers from across the Nordic Region analyse how labour market integration of immigrants can be promoted. 

About the book

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