Sensitivity analysis of the unconfoundedness assumption in observational studies
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- Guildo W. Imbens, 2003. "Sensitivity to Exogeneity Assumptions in Program Evaluation," American Economic Review, American Economic Association, vol. 93(2), pages 126-132, May.
- John Copas & Shinto Eguchi, 2001. "Local sensitivity approximations for selectivity bias," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 871-895.
- LaLonde, Robert J, 1986.
"Evaluating the Econometric Evaluations of Training Programs with Experimental Data,"
American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
- Robert J. LaLonde, 1984. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," Working Papers 563, Princeton University, Department of Economics, Industrial Relations Section..
- Sander Greenland, 2005. "Multiple‐bias modelling for analysis of observational data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 267-306, March.
- John Copas & Shinto Eguchi, 2005. "Local model uncertainty and incomplete‐data bias (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(4), pages 459-513, September.
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- Patrik Gustavsson Tingvall & Josefin Videnord, 2020. "Regional differences in effects of publicly sponsored R&D grants on SME performance," Small Business Economics, Springer, vol. 54(4), pages 951-969, April.
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More about this item
Keywords
Causal inference; effects of college choice; propensity score; register data;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2009-07-03 (Econometrics)
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