This paper shows a convenient way to test whether instrumental variables are correlated with individual effects in a panel data set. It shows that the correlated fixed effects specification tests developed by Hausman and Taylor (1981) extend in an analogous way to panel data sets with endogenous right hand side variables. In the panel data context, different sets of instrumental variables can be used to construct the test. Asymptotically, I show that the test in many cases is more efficient if an incomplete set of instruments is used. However, in small samples one is likely to do better using the complete set of instruments. Monte Carlo results demonstrate the likely gains for different assumptions about the degree of variance in the data across observations relative to variation across time.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number
0123.
Length: Date of creation: Jun 1996 Date of revision: Handle: RePEc:nbr:nberte:0123
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Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Breusch, Trevor S & Mizon, Grayham E & Schmidt, Peter, 1989.
"Efficient Estimation Using Panel Data,"
Econometrica,
Econometric Society, vol. 57(3), pages 695-700, May.
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