Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-27T21:42:52.488Z Has data issue: false hasContentIssue false
  • English
  • Français

TESTING FOR EXOGENEITY IN THRESHOLD MODELS

Published online by Cambridge University Press:  13 August 2009

George Kapetanios
George Kapetanios*
Affiliation:
Queen Mary, University of London
*
*Address correspondence to George Kapetanios, Department of Economics, Queen Mary, University of London, Mile End Road, London E1 4NS; email: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Most work in the area of nonlinear econometric modeling is based on a single equation and assumes exogeneity of the explanatory variables. Recently, work by Caner and Hansen (2004) and Psaradakis, Sola, and Spagnolo (2005) has considered the possibility of estimating nonlinear models by methods that take into account endogeneity but provide no tests for exogeneity. This paper examines the problem of testing for exogeneity in nonlinear threshold models. We suggest new Hausman-type tests and discuss the use of the bootstrap to improve the properties of asymptotic tests. The theoretical properties of the tests are discussed and an extensive Monte Carlo study is undertaken.

Type
ARTICLES
Information
Econometric Theory , Volume 26 , Issue 1 , February 2010 , pp. 231 - 259
Copyright
Copyright © Cambridge University Press 2009

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.)

References

REFERENCES

Bickel, P.J., Gotze, F., & van Zwet, W.R. (1997) Resampling fewer than n observations: Gains, losses and remedies for losses. Statistica Sinica 7(1), 1–31.Google Scholar
Blundell, R., & Powell, J.L. (2004) Endogeneity in semiparametric binary response models. Review of Economic Studies 71, 581–913.CrossRefGoogle Scholar
Caner, M., & Hansen, B. (2004) Instrumental variables estimation of a threshold model. Econometric Theory 20, 813–843.Google Scholar
Chan, K.S. (1993) Consistency and limiting distribution of the least squares estimator of a threshold autoregressive model. Annals of Statistics 21(1), 520–533.Google Scholar
Freedman, D. (1981) Bootstrapping regression models. Annals of Statistics 9, 1218–1228.CrossRefGoogle Scholar
Gonzalo, J., & Wolf, M. (2005) Subsampling inference in threshold autoregressive models. Journal of Econometrics 127, 201–224.CrossRefGoogle Scholar
Hansen, B.E. (1996) Inference when a nuisance parameter is not identified under the null hypothesis. Econometrica 64, 413–430.Google Scholar
Hansen, B.E. (2000) Sample splitting and threshold estimation. Econometrica 68, 575–603.CrossRefGoogle Scholar
Hausman, J.A. (1978) Specification tests in econometrics. Econometrica 46, 1251–1271.Google Scholar
Inoue, A., & Kilian, L. (2003) The continuity of the limit distribution in the parameter of interest is not essential for the validity of the bootstrap. Econometric Theory 19, 944–961.Google Scholar
Kapetanios, G. (2000) Small sample properties of the conditional least squares estimator in SETAR models. Economics Letters 69(3), 267–276.Google Scholar
Kim, C.J. (2004) Markov-switching models with endogenous explanatory variables. Journal of Econometrics 122.CrossRefGoogle Scholar
Peligrad, M. (1982) Invariance principles for mixing sequences of random variables. Annals of Probability 10, 968–981.Google Scholar
Politis, D.N., & Romano, J.P. (1994a) Large sample confidence regions based on subsamples under minimal assumptions. Annals of Statistics 22(4), 2031–2050.CrossRefGoogle Scholar
Politis, D.N., & Romano, J.P. (1994b) The stationary bootstrap. Journal of the American Statistical Association 89, 1303–1313.CrossRefGoogle Scholar
Psaradakis, Z., Sola, M., & Spagnolo, F. (2005) Testing the unbiased forward exchange rate hypothesis using a Markov-switching model and instrumental variables. Journal of Applied Econometrics 20, 423–437.Google Scholar
Tibshirani, R. (1988) Variance stabilization and the bootstrap. Biometrika 75(3), 433–444.Google Scholar