Specification and estimation of simultaneous equation models

By Jerry A. Hausman. 1983

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Citations in the corpus

The Econometrics of Randomized Experiments (2016, background): “A formal comparison of the two estimates, in a linear model setting, would be a Hausman test (Hausman, 1983).”
Aid and Performance: A Reassessment (2001, methodology): “A way to check that the instruments are not correlated with the growth residual is to perform an over-identification test12 (Hausman, 1983).”
Estimation with Weak Instruments: Accuracy of Higher-order Bias and MSE Approximations (2004, unknown): “A partial list of such research activities is Nelson and Startz (1990), Maddala and Jeong (1992), Staiger and Stock (1997) and Hahn and Hausman (2002a).”
Testing the trade credit and trade link: evidence from data on export credit insurance (2014, unknown): “3.2 Dealing with the reverse causality issue Testing for endogeneity as proposed by Hausman (1978, 1983) we find insured trade credits to be endogenous at the 1 % significance level using pooled ordinary least squares (OLS), 5 % significance level for random effect and close to 10 % significance…”
Special Issue on Design and Development: Sourcing By Design: Product Complexity and the Supply Chain (2001, methodology): “See Hausman (1983).”
Estimation with Valid and Invalid Instruments (2003, unknown): “The OID test can be quite important since it tests the economic theory embodied in the model as discuss by e.g. Hausman (1983).”
Bayesian Model Averaging in the Instrumental Variable Regression Model (2012, unknown): “In practice, researchers typically try different specifications until a set of restrictions (i.e. a particular choice of instruments, exogenous and endogenous regressors) passes a battery of misspecification tests (e.g. Anderson and Rubin, 1949, 1950; Hausman, 1983; Sargan, 1958).”