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.

Global index of the sharing economy

Timbro SEI

2018 Bergh Funcke Wernberg - Timbro Sharing Economy Index-1fHemsidan.jpg

Andreas Bergh, IFN and Lund University, is one of the authors of this book. The Timbro Sharing Economy Index is the first global index of the sharing economy. The index has been compiled using traffic volume data and scraped data, and provides a unique insight into the driving factors behind the peer-to-peer economy.

About the book

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