Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-27T17:53:32.606Z Has data issue: false hasContentIssue false

NONNESTED TESTING IN MODELS ESTIMATED VIA GENERALIZED METHOD OF MOMENTS

Published online by Cambridge University Press:  13 September 2010

Abstract

We analyze the limiting distribution of the Rivers and Vuong (2002, Econometrics Journal 5, 1–39) statistic for choosing between two competing dynamic models based on a comparison of generalized method of moments minimands. It is shown that (i) if both models are misspecified then the statistic has a standard normal distribution under the null hypothesis of equal fit but the ranking could be determined by the choice of the weighting matrix; (ii) if both models are correctly specified or locally misspecified then the limiting distribution of the test statistic is nonstandard under the null.

Type
Brief Report
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.)

Footnotes

We thank Atsushi Inoue, Eric Renault, Quang Vuong, Ken West, a coeditor, and two anonymous referees 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, 397430.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, 361394.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, 557590.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, 867893.CrossRefGoogle Scholar
Newey, W.K. (1985) Generalized method of moments specification testing. Journal of Econometrics 29, 229256.CrossRefGoogle Scholar
Potscher, B.M. (1983) Order estimation in ARMA models by Lagrangian multiplier tests. Annals of Statistics 11, 872885.CrossRefGoogle Scholar
Rivers, D. & Vuong, Q. (2002) Model selection tests for nonlinear dynamic models. Econometrics Journal 5, 139.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, 503519.CrossRefGoogle Scholar
Vuong, Q. (1989) Likelihood ratio tests for model selection and non–nested hypotheses. Econometrica 57, 307334.CrossRefGoogle Scholar