Arbeitspapier

Testing the correlated random coefficient model

The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baselinepretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing economist. Such models are called correlated random coefficient models. Sorting on unobserved components of gains complicates the interpretation of what IV estimates. This paper examines testable implications of the hypothesis that agents do not sort into treatment based on gains. In it, we develop new tests to gauge the empirical relevance of the correlated random coefficient model to examine whether the additional complications associated with it are required. We examine the power of the proposed tests. We derive a new representation of the variance of the instrumental variable estimator for the correlated random coefficient model. We apply the methods in this paper to the prototypical empirical problem of estimating the return to schooling and find evidence of sorting into schooling based on unobserved components of games.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP10/10

Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Thema
correlated random coefficient
testing
instrumental variables
power of tests based on IV
Instrumentalvariablen-Schätzmethode
Korrelation
Statistischer Test
Theorie
Bildungsertrag
Schätzung
USA

Ereignis
Geistige Schöpfung
(wer)
Heckman, James J.
Schmierer, Daniel
Urzua, Sergio
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2010

DOI
doi:10.1920/wp.cem.2010.1010
Handle
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Heckman, James J.
  • Schmierer, Daniel
  • Urzua, Sergio
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2010

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