Bayesian geoadditive sample selection models

Journal of the Royal Statistical Society. Series C: Applied Statistics

Volumn 59, Issue 3, 2010, Pages 381-404

  Wiesenfarth, Manuel ^a   Kneib, Thomas ^b  

^a UNIVERSITY OF GÖTTINGEN   (Germany)

^b UNIVERSITY OF OLDENBURG   (Germany)

Author keywords

Heckman regression; Markov chain Monte Carlo methods; Markov random fields; Penalized splines; Selection bias; Varying coefficients

Indexed keywords

EID: 77956009036     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/j.1467-9876.2009.00698.x     Document Type: Article

References (22)

1. Albert J H, Chib S. Bayesian analysis of binary and polychotomous response data. J. Am. Statist. Ass. 1993, 88:669-679.
2. Benini A, Conley C, Dittemore B, Waksman Z. Survivor Needs or Logistical Convenience?: factors shaping decisions to deliver relief to earthquake-affected communities, Pakistan 2005-06. Navigating Post-conflict Environments Series 2006, Washington DC, Vietnam Veterans of America Foundation-Information Management and Mine Action Programs
3. Benini A, Conley C, Dittemore B, Waksman Z. Survivor needs or logistical convenience?: factors shaping decisions to deliver relief to earthquake-affected communities Pakistan 2005-06. Disasters 2009, 33:110-131.
4. Chib S, Greenberg E, Jeliazkov I. Estimation of semiparametric models in the presence of endogeneity and sample selection. J. Computnl Graph. Statist. 2009, 18:321-348.
5. Das M, Newey W, Vella F. Estimation of sample selection models. Rev. Econ. Stud. 2003, 70:33-58.
6. Eilers P H C, Marx B D. Flexible smoothing using B-splines and penalties (with comments and rejoinder). Statist. Sci. 1996, 11:89-121.
7. Fahrmeir L, Kneib T, Lang S. Penalized structured additive regression: a Bayesian perspective. Statist. Sin. 2004, 14:731-761.
8. van Hasselt M. Bayesian sampling algorithms for the sample selection and two-part models. Computing in Economics and Finance 2005 2005, Society for Computational Economics
9. Hastie T, Tibshirani R. Varying-coefficient models (with discussion). J. R. Statist. Soc. B 1993, 55:757-796.
10. Heckman J. Sample selection bias as a specification error. Econometrica 1979, 47:153-161.
11. Henningsen A, Toomet O. sampleSelection: sample selection models. 2008, (Available from.)
12. Kai L. Bayesian inference in a simultaneous equation model with limited dependent variables. J. Econometr. 1998, 85:387-400.
13. Lang S, Adebayo S, Fahrmeir L, Steiner W J. Bayesian geoadditive seemingly unrelated regression. Computnl Statist. 2003, 18:263-292.
14. Lang S, Brezger A. Bayesian P-splines. J. Computnl Graph. Statist. 2004, 13:183-212.
15. Lee L. Self Selection. A Companion to Theoretical Econometrics 2000, Baltagi B. ed, Oxford, Blackwell
16. Min Y, Agresti A. Modeling nonnegative data with clumping at zero: a survey. J. Iran. Statist. Soc. 2002, 1:7-33.
17. Omori Y. Efficient Gibbs sampler for Bayesian analysis of a sample selection model. Statist. Probab. Lett. 2007, 77:1300-1311.
18. Robert C P. Simulation of truncated normal variables. Statist. Comput. 1995, 5:121-125.
19. Rue H, Held L. Gaussian Markov Random Fields: Theory and Applications 2005, London, CRC-Chapman and Hall
20. Sigelman L, Zeng L. Analyzing censored and sample-selected data with Tobit and Heckit models. Polit. Anal. 1999, 8:167-182.
21. Vella F. Estimating models with sample selection bias: a survey. J. Hum. Resour. 1998, 33:127-169.
22. Winship C, Mare R D. Models for sample selection bias. A. Rev. Sociol. 1992, 18:327-350.