Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-19T08:35:32.529Z Has data issue: false hasContentIssue false
  • English
  • Français

NONPARAMETRIC INFERENCE FOR UNBALANCED TIME SERIES DATA

Published online by Cambridge University Press:  08 February 2005

Oliver Linton
Oliver Linton
Affiliation:
London School of Economics
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper is concerned with the practical problem of conducting inference in a vector time series setting when the data are unbalanced or incomplete. In this case, one can work with only the common sample, to which a standard HAC/bootstrap theory applies, but at the expense of throwing away data and perhaps losing efficiency. An alternative is to use some sort of imputation method, but this requires additional modeling assumptions, which we would rather avoid. We show how the sampling theory changes and how to modify the resampling algorithms to accommodate the problem of missing data. We also discuss efficiency and power. Unbalanced data of the type we consider are quite common in financial panel data; see, for example, Connor and Korajczyk (1993, Journal of Finance 48, 1263–1291). These data also occur in cross-country studies.I thank Greg Connor, Esfandiar Maasoumi, Peter Phillips, Peter Robinson, Yoon Whang, and two referees for helpful comments.

Type
Research Article
Information
Econometric Theory , Volume 21 , Issue 1 , February 2005 , pp. 143 - 157
Copyright
© 2005 Cambridge University Press

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

Amemiya, T. (1985) Advanced Econometrics. Harvard University Press.
Andrews, D.W.K. (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59, 817–858.Google Scholar
Bickel, P., C.A.J. Klaassen, Y. Ritov, & J. Wellner (1993) Efficient and Adaptive Estimation for Semiparametric Models. Springer-Verlag.
Bickel, P., Y. Ritov, & J. Wellner (1991) Efficient estimation of linear functionals. Annals of Statistics 19, 1316–1346.Google Scholar
Connor, G. & R.A. Korajczyk (1993) A test for the number of factors in an approximate factor model. Journal of Finance 48, 1263–1291.Google Scholar
Grenander, U. (1954) On the estimation of regression coefficients in the case of an autocorrelated disturbance. Annals of Mathematical Statistics 25, 252–272.Google Scholar
Hannan, E.J. (1957) The variance of the mean of a stationary process. Journal of the Royal Statistical Society, Series B 19, 282–285.Google Scholar
Hansen, B.E. (1992) Consistent covariance matrix estimation for dependent heterogenous processes. Econometrica 60, 967–972.Google Scholar
de Jong, R.M. & J. Davidson (2000) Consistency of kernel estimators of heteroskedastic and autocorrelated covariance matrices. Econometrica 68, 407–423.Google Scholar
Jowett, G.H. (1955) The comparison of means of sets of observations from sections of independent stochastic series. Journal of the Royal Statistical Society, Series B 17, 208–227.Google Scholar
Lahiri, S.N. (2003) Resampling Methods for Dependent Data. Springer-Verlag.
Linton, O., E. Maasoumi, & Y.J. Whang (2003) Consistent Testing for Stochastic Dominance under General Sampling Schemes. Cowles Foundation Discussion paper, Yale University.
Little, R.J.A. & D.B. Rubin (1987) Statistical Analysis with Missing Data. Wiley.
Newey, W.K. & K. West (1987) A simple positive semi-definite heteroscedasticity and autocorrelation consistent covariance matrix. Econometrica 55, 703–708.Google Scholar
Phillips, P.C.B. (2005) HAC estimation by automated regression. Econometric Theory (this issue).Google Scholar
Politis, D.N., J.P. Romano, & M. Wolf (1999) Subsampling. Springer-Verlag.
Robinson, P.M. (2005) Robust covariance matrix estimation: “HAC” estimates with long memory/antipersistence correction. Econometric Theory (this issue).Google Scholar
Xiao, Z. & O. Linton (2002) A nonparametric prewhitened covariance estimator. Journal of Time Series Analysis 23, 215–250.Google Scholar