Hostname: page-component-cb9f654ff-fg9bn Total loading time: 0 Render date: 2025-08-09T14:56:49.362Z Has data issue: false hasContentIssue false
  • English
  • Français

NONNESTED TESTING IN MODELS ESTIMATED VIAGENERALIZED METHOD OF MOMENTS

Published online by Cambridge University Press:  13 September 2010

Alastair R. Hall  and
Denis Pelletier
Get access Rights & Permissions [Opens in a new window]

Abstract

We analyze the limiting distribution of the Rivers andVuong (2002, Econometrics Journal5, 1–39) statistic for choosing between twocompeting dynamic models based on a comparison ofgeneralized method of moments minimands. It is shownthat (i) if both models are misspecified then thestatistic has a standard normal distribution underthe null hypothesis of equal fit but the rankingcould be determined by the choice of the weightingmatrix; (ii) if both models are correctly specifiedor locally misspecified then the limitingdistribution of the test statistic is nonstandardunder the null.

Information

Type
Brief Report
Information
Econometric Theory , Volume 27 , Issue 2 , April 2011 , pp. 443 - 456
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

We thank Atsushi Inoue, Eric Renault, QuangVuong, Ken West, a coeditor, and two anonymousreferees for helpful comments.

References

REFERENCES

Dridi, R., Guay, A., & Renault, E. (2007) Indirect inference and calibration of dynamic general equilibrium models. Journal of Econometrics 136, 397–430.CrossRefGoogle Scholar
Hall, A.R. (2005) Generalized Method of Moments. Oxford University Press.Google Scholar
Hall, A.R. & Inoue, A. (2003) The large sample behaviour of the generalized method of moments estimator in misspecified models. Journal of Econometrics 114, 361–394.CrossRefGoogle Scholar
Hall, A.R. & Pelletier, D. (2007) Non-Nested Testing in Models Estimated via Generalized Method of Moments. Economics Working Paper 11, Department of Economics, North Carolina State University.Google Scholar
Hansen, L.P. & Jagannathan, R. (1997) Assessing specification errors in stochastic discount factor models. Journal of Finance 52, 557–590.CrossRefGoogle Scholar
Kitamura, Y. (2000) Comparing Misspecified Dynamic Econometric Models Using Nonparametric Likelihood. Mimeo, University of Pennsylvania.Google Scholar
Kitamura, Y. (2002) A Likelihood-Based Approach to the Analysis of a Class of Nested and Non-nested Models. Discussion paper, Department of Economics, University of Pennsylvania.Google Scholar
Marcellino, M. & Rossi, B. (2008) Model selection for nested and overlapping nonlinear dynamic and possibly mis-specified models. Oxford Bulletin of Economics and Statistics 70, 867–893.CrossRefGoogle Scholar
Newey, W.K. (1985) Generalized method of moments specification testing. Journal of Econometrics 29, 229–256.CrossRefGoogle Scholar
Potscher, B.M. (1983) Order estimation in ARMA models by Lagrangian multiplier tests. Annals of Statistics 11, 872–885.CrossRefGoogle Scholar
Rivers, D. & Vuong, Q. (2002) Model selection tests for nonlinear dynamic models. Econometrics Journal 5, 1–39.CrossRefGoogle Scholar
Shi, X. (2010) Model Selection Tests for Nonnested Moment Inequality Models. Mimeo, Yale University.Google Scholar
Smith, R.J. (1997) Alternative semi-parametric likelihood approaches to generalized method of moments estimation. Economics Journal 107, 503–519.CrossRefGoogle Scholar
Vuong, Q. (1989) Likelihood ratio tests for model selection and non–nested hypotheses. Econometrica 57, 307–334.CrossRefGoogle Scholar