Jackknife instrumental variables estimation in Stata

Stata Journal

Volumn 6, Issue 3, 2006, Pages 364-376

  Poi, Brian P ^a  

^a StataCorp   (United States)

Author keywords

2SLS; Endogeneity; Instrumental variables; Jive; JIVE; LIML; St0108; Weak instruments

Indexed keywords

EID: 33749378620     PISSN: 1536867X     EISSN: None     Source Type: Journal    
DOI: 10.1177/1536867x0600600305     Document Type: Article

References (14)

1. Angrist, J. D., G. W. Imbens, and A. B. Krueger. 1999. Jackknife instrumental variables estimation. Journal of Applied Econometrics 14: 57-67.
2. Angrist, J. D., and A. B. Krueger. 1991. Does compulsory school attendance affect schooling and earnings? Quarterly Journal of Economics 106: 979-1014.
3. Baum, C. F., M. E. Schaffer, and S. Stillman. 2003. Instrumental variables and GMM: Estimation and testing. Stata Journal 3: 1-31.
4. _. 2004. Software updates: Instrumental variables and GMM: Estimation and testing. Stata Journal 4: 224.
5. _. 2005. Software updates: Instrumental variables and GMM: Estimation and testing. Stata Journal 5: 607.
6. Blomquist, S., and M. Dahlberg. 1999. Small sample properties of LIML and Jackknife IV estimators: Experiments with weak instruments. Journal of Applied Econometrics 14: 69-88.
7. Bound, J., D. Jaeger, and R. Baker. 1995. Problems with instrumental variable estimation when the correlation between the instruments and the endogenous explanatory variables is weak. Journal of the American Statistical Association 90: 443-450.
8. Chao, J. C., and N. R. Swanson. 2004. Asymptotic distribution of JIVE in a heteroskedastic IV regression with many weak instruments. http://www.econ.vt. edu/Seminars/Seminarpapers/Chao_B_jive2.pdf.
9. Mikusheva, A., and B. P. Poi. 2006. Tests and confidence sets with correct size when instruments are potentially weak. Stata Journal 6. 51-63.
10. Moreira, M. J., and B. P. Poi. 2003. Implementing tests with correct size in the simultaneous equations model. Stata Journal 3: 57-70.
11. Nagar, A. L. 1959. The bias and moment matrix of the general k-class estimators of the parameters in simultaneous equations. Econometrica 27: 575-595.
12. Nelson, C. R., and R. Startz. 1990. The distribution of the instrumental variables estimator arid its t-ratio when the instrument is a poor one. Journal of Business 63: 5125-5140.
13. Phillips, G. D. A., and C. Hale. 1977. The bias of instrumental variable estimators of simultaneous equation systems. International Economic Review 18: 219-228.
14. Stock, J. H., J. H. Wright, and M. Yogo. 2002. A survey of weak instruments and weak identification in generalized method of moments. Journal of Business and Economic Statistics 20: 518-529.