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A Note on Missing Data Effects on the Hausman (1978) Simultaneity Test: Some Monte Carlo Results

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Author Info
Dikaios Tserkezos () (Department of Economics, University of Crete, Greece)
Konstantinos Tsagarakis () (Department of Environmental Engineering, Democritus University of Thrace)

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Abstract

This short paper demonstrates the effects of using missing data on the power of the well-known Hausman (1978) test for simultaneity in structural econometric models. This test is a reliable test and is widely used for testing simultaneity in linear and nonlinear structural models. Using Monte Carlo techniques, we find that the existence of missing data could affect seriously the power of the test. As their number is getting larger, the probability of rejecting simultaneity with Hausman test is increasing significantly especially in small samples. A Full Information Maximum Likelihood Missing Data correction technique is used to overcome the problem and then we find out that that the test is more effective when we retrieve these data and include them in the sample.

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Publisher Info
Paper provided by University of Crete, Department of Economics in its series Working Papers with number 0821.

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Length: 10 pages
Date of creation: 03 Jun 2008
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Handle: RePEc:crt:wpaper:0821

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Related research
Keywords: Hausman (1978) simultaneity test; structural econometric models; FIML; missing data; simulation;

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Find related papers by JEL classification:
C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
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

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References listed on IDEAS
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  1. Dimitris Georgoutsos & George Kouretas & Dikaios Tserkezos, . "Temporal Aggregation In Structural Var Models," Working Papers 9505, University of Crete, Department of Economics.
  2. Gilbert, Christopher L., 1977. "Regression using mixed annual and quarterly data," Journal of Econometrics, Elsevier, vol. 5(2), pages 221-239, March. [Downloadable!] (restricted)
  3. Oguchi, Noriyoshi & Fukuchi, Takao, 1990. "On Temporal Aggregation of Linear Dynamic Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 31(1), pages 187-93, February. [Downloadable!] (restricted)
  4. Drettakis, E G, 1973. "Missing Data in Econometric Estimation," Review of Economic Studies, Blackwell Publishing, vol. 40(4), pages 537-52, October. [Downloadable!] (restricted)
  5. Sargan, J D & Drettakis, E G, 1974. "Missing Data in an Autoregressive Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 39-58, February. [Downloadable!] (restricted)
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