Oracle efficient variable selection in random and fixed effects panel data models

Econometric Theory

Volumn 29, Issue 1, 2013, Pages 115-152

  Kock, Anders Bredahl ^a  

^a AARHUS UNIVERSITY   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84873628920     PISSN: 02664666     EISSN: 14694360     Source Type: Journal    
DOI: 10.1017/S0266466612000230     Document Type: Article

References (12)

1. Arellano, M. (2003) Panel Data Econometrics. Oxford University Press.
2. Candes, E. & T. Tao (2007) The Dantzig selector: Statistical estimation when p is much larger than n. Annals of Statistics 35, 2313-2351.
3. Fan, J. & J. Lv (2008) Sure independence screening for ultrahigh dimensional feature space. Journal of the Royal Statistical Society, Series B 70, 849-911.
4. Hoffmann-Jørgensen, J. (1994) Probability with a View Toward Statistics, vol. 1. Chapman & Hall/CRC.
5. Huang, J., J. Horowitz, & S. Ma (2008) Asymptotic properties of bridge estimators in sparse highdimensional regression models. Annals of Statistics 36, 587-613.
6. Hunter, D. & R. Li (2005) Variable selection using MM algorithms. Annals of Statistics 33, 1617-1642. (Pubitemid 41423982)
7. Knight, K. &W. Fu (2000) Asymptotics for lasso-type estimators. Annals of Statistics 28, 1356-1378. (Pubitemid 33244917)
8. Meinshausen, N. & B. Yu (2009) Lasso-type recovery of sparse representations for high-dimensional data. Annals of Statistics 37, 246-270.
9. Stoyanov, J. (1997) Counterexamples in Probability, 2nd ed. Wiley.
10. Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society, Series B 73, 267-288.
11. Van der Vaart, A. & J. Wellner (1996) Weak Convergence and Empirical Processes. Springer-Verlag.
12. Zou, H. (2006) The adaptive lasso and its oracle properties. Journal of the American Statistical Association 101, 1418-1429.