Assessing Instrumental Variable Relevance:An Alternative Measure and Some Exact Finite Sample Theory
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- Forchini, Giovanni & Hillier, Grant, 2003.
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- Woglom, Geoffrey, 2001. "More Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 69(5), pages 1381-1389, September.
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Citations
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Cited by:
- Grant Hillier & Giovanni Forchini, 2004. "Ill-posed Problems and Instruments' Weakness," Econometric Society 2004 Australasian Meetings 357, Econometric Society.
- Joseph, Agnes S. & Kiviet, Jan F., 2005.
"Viewing the relative efficiency of IV estimators in models with lagged and instantaneous feedbacks,"
Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 417-444, April.
- Agnes S. Joseph & Jan F. Kiviet, 2004. "Viewing the Relative Efficiency of IV Estimators in Models with Lagged and Instantaneous Feedbacks," Tinbergen Institute Discussion Papers 04-056/4, Tinbergen Institute.
- Kapetanios, George & Marcellino, Massimiliano, 2010.
"Cross-sectional averaging and instrumental variable estimation with many weak instruments,"
Economics Letters, Elsevier, vol. 108(1), pages 36-39, July.
- George Kapetanios & Massimiliano Marcellino, 2008. "Cross-sectional Averaging and Instrumental Variable Estimation with Many Weak Instruments," Working Papers 627, Queen Mary University of London, School of Economics and Finance.
- Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/generalized method of moments estimation and testing," Stata Journal, StataCorp LP, vol. 7(4), pages 465-506, December.
- Kapetanios, George & Marcellino, Massimiliano, 2010.
"Cross-sectional averaging and instrumental variable estimation with many weak instruments,"
Economics Letters, Elsevier, vol. 108(1), pages 36-39, July.
- George Kapetanios & Massimiliano Marcellino, 2008. "Cross-sectional Averaging and Instrumental Variable Estimation with Many Weak Instruments," Working Papers 627, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios & Massimiliano Marcellino, 2008. "Cross-sectional Averaging and Instrumental Variable Estimation with Many Weak Instruments," Working Papers 627, Queen Mary University of London, School of Economics and Finance.
- D. S. Poskitt & C. L. Skeels, 2004. "Approximating the Distribution of the Instrumental Variables Estimator when the Concentration Parameter is Small," Monash Econometrics and Business Statistics Working Papers 19/04, Monash University, Department of Econometrics and Business Statistics.
- Gönül Çolak, 2010. "Diversification, Refocusing and Firm Value," European Financial Management, European Financial Management Association, vol. 16(3), pages 422-448, June.
- Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007.
"Enhanced routines for instrumental variables/GMM estimation and testing,"
CERT Discussion Papers
0706, Centre for Economic Reform and Transformation, Heriot Watt University.
- Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," Boston College Working Papers in Economics 667, Boston College Department of Economics, revised 05 Sep 2007.
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More about this item
Keywords
Instrumental variables; weak instruments; relevance; alienation; Wilks’ Lambda.;All these keywords.
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
Statistics
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