Arbeitspapier

Identification and Inference in a Simultaneous Equation under Alternative Information Sets and Sampling Schemes

In simple static linear simultaneous equation models the empirical distributions of IV and OLS are examined under alternative sampling schemes and compared with their first-order asymptotic approximations. We demonstrate that the limiting distribution of consistent IV is not affected by conditioning on exogenous regressors, whereas that of inconsistent OLS is. The OLS asymptotic and simulated actual variances are shown to diminish by extending the set of exogenous variables kept fixed in sampling, whereas such an extension disrupts the distribution of IV and deteriorates the accuracy of its standard asymptotic approximation, not only when instruments are weak. Against this background the consequences for the identification of parameters of interest are examined for a setting in which (in practice often incredible) assumptions regarding the zero correlation between instruments and disturbances are replaced by (generally more credible) interval assumptions on the correlation between endogenous regressor and disturbance. This yields OLS-based modified confidence intervals, which are usually conservative. Often they compare favorably with IV-based intervals and accentuate their frailty.

Sprache
Englisch

Erschienen in
Series: Tinbergen Institute Discussion Paper ; No. 12-128/III

Klassifikation
Wirtschaft
Hypothesis Testing: General
Estimation: General
Statistical Simulation Methods: General
Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
Wage Level and Structure; Wage Differentials
Thema
partial identification
weak instruments
(un)restrained repeated sampling
(un)conditional (limiting) distributions
credible robust inference

Ereignis
Geistige Schöpfung
(wer)
Kiviet, Jan F.
Ereignis
Veröffentlichung
(wer)
Tinbergen Institute
(wo)
Amsterdam and Rotterdam
(wann)
2012

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Kiviet, Jan F.
  • Tinbergen Institute

Entstanden

  • 2012

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