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Linear Regressions, Shorts to Long

Toru Kitagawa and Masayuki Sawada

No 747, Discussion Paper Series from Institute of Economic Research, Hitotsubashi University

Abstract: We study the identification problem of the linear long regression coefficients by data combination. Unlike the usual data combination problem, we consider combining multiple short regressions of the same outcome with different regressors. For this conceptually novel problem, we provide partial identification results for the long regression coefficients under a restriction on the unknown correlation structure. Specifically, we employ an elliptic constraint from the relations among the explained variations of the regressions to induce the bounds.

Keywords: Data combination; Linear regression; Elliptic constraint (search for similar items in EconPapers)
Pages: 23 pages
Date: 2023-08
New Economics Papers: this item is included in nep-ecm
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