The incidental parameter problem since 1948

Journal of Econometrics

Volumn 95, Issue 2, 2000, Pages 391-413

  Lancaster, Tony ^a  

^a BROWN UNIVERSITY   (United States)

Author keywords

Bayes; Incidental parameters; Maximum likelihood; Nuisance parameters

Indexed keywords

EID: 0001099021     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-4076(99)00044-5     Document Type: Article

References (55)

1. Ahn, S., Schmidt, P., 1995. Efficient estimation of models for dynamic panel data. Journal of Econometrics 68, 5-27.
2. Aigner, D., Hsiao, C., Kapteyn, A., Wansbeek, T., 1984. Latent variables. In: Engle, R.F., McFadden, D. (Eds.), Handbook of Econometrics, Vol 3. Elsevier, Amsterdam.
3. Amemiya, T., 1985. Advanced Econometrics. Harvard University Press, Harvard.
4. Andersen, E.B., 1970. Asymptotic properties of conditional maximum likelihood estimators. Journal of the Royal Statistical Society B 32, 283-301.
5. Anderson, T.W., Hsiao, C., 1981. Estimation of dynamic models with error components. Journal of the American Statistical Association 76, 598-606.
6. Anscombe, F.J., 1964. Normal likelihoods. Annals of the Institute of Statistical Mathematics 26, 1-19.
7. Arellano, M., Bover, O., 1995. Another look at the instrumental variable estimation of error components models. Journal of Econometrics 68, 29-51.
8. Baltagi, B.H., 1995. Econometric Analysis of Panel Data. Wiley, New York.
9. Barndorff-Nielsen, O.E., 1978. Information and Exponential Families in Statistical Theory. Wiley, New York.
10. Barro, R.J., Xavier Sala-i-Martin, 1994. Economic Growth. McGraw-Hill, New York.
11. Basu, D., 1977. On the elimination of nuisance parameters. Journal of the American Statistical Association 72 (358), 355-366.
12. Berger, J.O., Liseo, B., Wolpert, R.L., 1997. Integrated likelihood methods for eliminating nuisance parameters. Working paper 97-01. Institute of Statistics and Decision Sciences, Duke University.
13. Bickel, P.J., Klaassen, C.A.J., Ritov, Y., Wellner, J.A., 1993. Efficient and Adaptive Estimation for Semiparametric Models. Johns Hopkins, Baltimore, MD.
14. Chamberlain, G., 1984. Panel data. In: Griliches, Z., Intriligator, M.D. (Eds.), Handbook of Econometrics, Vol. 2. North-Holland, Amsterdam.
15. Chamberlain, G., 1985. Heterogeneity, omitted variable bias, and duration dependence. In: Heckman, J.J., Singer, B. (Eds.), Longitudinal Analysis of Labor Market Data. Cambridge University Press, Cambridge.
16. Chamberlain, G., 1992. Comment: sequential moment restrictions in panel data. Journal of Business and Economic Statistics 10, 20-26.
17. Cox, D.R., 1972. Regression models and life tables. Journal of the Royal Statistical Society B 34, 187-220.
18. Cox, D.R., Hinkley, D.V., 1974. Theoretical Statistics. Chapman & Hall, London.
19. Cox, D.R., Reid, N., 1987. Parameter orthogonality and approximate conditional inference (with discussion). Journal of the Royal Statistical Society B 49 (1), 1-39.
20. David, H.A., 1995. First(?) occurence of common terms in mathematical statistics. The American Statistician 49 (2), 121-133.
21. Diaconis, P., Freedman, D., 1986. On the consistency of Bayes estimates. Annals of Statistics 14, 1-67.
22. Ferguson, H., Reid N., Cox, D.R., 1991. Estimating equations from modified profile likelihood. In: Godambe, V.P. (Ed.), Estimating Functions. Oxford University Press, Oxford.
23. Fisher, R.A., 1923. Statistical tests of agreement between observation and hypothesis. Economica 3, 139-147.
24. Fisher, R.A., 1935. The mathematical distributions used in the common tests of significance. Econometrica 3, 353-365.
25. Godambe, V.P., 1960. An optimum property of regular maximum likelihood estimation. Annals of Mathematical Statistics 31, 1208-11.
26. Hahn, J., 1994. The efficiency bound of the mixed proportional hazard model. Review of Economic Studies 61 (4), 607-629.
27. Hausman, J., Hall, B.H., Griliches, Z., 1984. Econometric models for count data with an application to the patents - R&D Relationship. Econometrica 52 (4), 909-938.
28. Heckman, J.J., 1981. The incidental parameters problem and the problem of initial conditions in estimating a discrete time-discrete data stochastic process. In: Manski, C.F., McFadden, D. (Eds.), Structural Analysis of Discrete Data with Econometric Applications. MIT Press, Cambridge, MA.
29. Honoré, B.E., 1992. Trimmed LAD and least squares estimation of truncated and censored regression models with fixed effects. Econometrica 60 (3), 533-567.
30. Honoré, B.E., Kyriazidou, E., 1997. Panel data discrete choice models with lagged dependent variables. Mimeo, Department of Economics, Princeton University.
31. Hsiao, C., 1986. Analysis of Panel Data. Cambridge University Press, Cambridge.
32. Jeffreys, H., 1960. Theory of Probability, 3rd Edition, Oxford University Press, Oxford.
33. Johnston, J., 1964. Econometric Methods, McGraw-Hill, New York.
34. Johnston, J., DiNardo, J., 1997. Econometric Methods. McGraw-Hill, New York.
35. Kalbfleisch, J., 1978. Non-parametric Bayesian analysis of survival time data. Journal of the Royal Statistical Society B 40, 214-220.
36. Lancaster, T., 1990. The econometric analysis of transition data. Cambridge University Press, Cambridge.
37. Lancaster, T., 1997. Orthogonal parameters and panel data. Brown University Working paper, pp. 97-32.
38. Leamer, E.E., 1978. Specification Searches. Wiley, New York.
39. Liang, K.-Y., 1987. Estimating functions and approximate conditional likelihood. Biometrika 74 (4), 695-702.
40. Liang, K.-Y., Zeger, S.L., 1995. Inference based on estimating functions in the presence of nuisance parameters. Statistical Science 10 (2), 158-172.
41. Lindsey, J., 1996. Parametric Statistical Inference. Oxford University Press, Oxford.
42. Manski, C., 1987. Semiparametric analysis of random effects linear models from binary panel data. Econometrica 55, 357-362.
43. Morgan, M.S., 1990. The history of econometric ideas. Cambridge University Press, Cambridge.
44. Mundlak, Y., 1961. Empirical production function free of management bias. Journal of Farm Economics 43, 44-56.
45. Newey, W.K., McFadden, D., 1994. Large sample estimation and hypothesis testing. (Chapter 36) In: Engle, R.F., McFadden, D. (Eds.), Handbook of Econometrics, Vol. 4. Elsevier, Amsterdam.
46. Neyman, J., Pearson, E.S., 1928. On the use and interpretation of certain test criteria for the purposes of statistical inference. Biometrika 20A, 175; 263.
47. Neyman, J., Scott, E.L., 1948. Consistent estimation from partially consistent observations. Econometrica 16, 1-32.
48. Poirier, D.J. (1995). Intermediate Statistics and Econometrics. MIT Press, Cambridge, MA.
49. Powell, J.L. (1994). Estimation of semiparametric models. Chapter 41. In: Engle, R.F., McFadden, D. (Eds.), Handbook of Econometrics, Vol. 4. Elsevier, Amsterdam.
50. Reid, N., 1995. The roles of conditioning in inference. Statistical Science 10 (2), 138-157.
51. Reid, N., 1996. Likelihood and Bayesian approximation methods. In: Bernardo, J.M., Berger, Jo.O., Dawid, A.P., Smith, A.F.M. (Eds.), Bayesian Statistics, Vol. 5. Oxford Science Publications, Oxford.
52. Ridder, G., Tunali, I., 1989. Analysis of related durations: a semi-parametric approach with an application to a study of child mortality in Malysia. Population Research Center Discussion Paper 90-1, NORC and the University of Chicago.
53. Stuart, A., Ord, J.K., 1991. Kendall's Advanced Theory of Statistics. Oxford University Press, Oxford.
54. Sweeting, T., 1987. Discussion of Cox and Reid, 1987.
55. Theil, H. 1971. Principles of Econometrics. Wiley, New York.