Hostname: page-component-76fb5796d-dfsvx Total loading time: 0 Render date: 2024-04-26T21:33:40.440Z Has data issue: false hasContentIssue false
  • English
  • Français

Stochastic Limit Theory: An Introduction for EconometriciansJames Davidson, Oxford University Press, 1994

Published online by Cambridge University Press:  11 February 2009

Stéphane Gregoir
Stéphane Gregoir
Affiliation:
INSEE-Paris
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Book Review
Information
Econometric Theory , Volume 12 , Issue 5 , December 1996 , pp. 859 - 865
Copyright
Copyright © Cambridge University Press 1996

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

Andrews, D.W.K. (1984) Non-strong mixing autoregressive processes. Journal of Applied Probability 21, 930–934.CrossRefGoogle Scholar
Andrews, D.W.K. (1987) Consistency in nonlinear econometric models: A generic uniform law of large numbers. Econometrica 55, 1465–1471.CrossRefGoogle Scholar
Andrews, D.W.K. (1992) Generic uniform convergence. Econometric Theory 8, 241–257.CrossRefGoogle Scholar
Billingsley, P. (1968) Convergence of Probability Measures. New York: John Wiley.Google Scholar
Davis, R.A. & Resnick, S.I. (1985) Limit theory for moving averages of random variables with regularly varying tail probabilities. Annals of Probability 13, 179–195.CrossRefGoogle Scholar
DeJong, R.M. (1995) Laws of large numbers for dependent heterogeneous process. Econometric Theory 11, 347–358.CrossRefGoogle Scholar
Gaposhkin, V.F. (1977) Criteria for the strong law of large numbers for some classes of secondorder stationary processes and homogeneous random fields. Theory of Probability and Its Application 23 (2), 286–309.Google Scholar
Hall, P. & Heyde, C.C. (1980) Martingale Limit Theory and Its Application. New York: Academic Press.Google Scholar
Houdre, C. (1992) On the spectral SLLN and a pointwise ergodic theorem in L. Annals of Probability 20 (4), 1731–1753.CrossRefGoogle Scholar
McLeish, D.L. (1974) Dependent central limit theorems and invariance principles. Annals of Probability 2 (4), 620–628.CrossRefGoogle Scholar
McLeish, D.L. (1975) A maximal inequality and dependent strong laws. Annals of Probability 3 (5), 329–339.CrossRefGoogle Scholar
Phillips, P.C.B. (1986) Understanding spurious regressions in econometrics. Journal of Econometrics 33, 311–340.CrossRefGoogle Scholar
Phillips, P.C.B. (1987) Time series regression with a unit root. Econometrica 55, 277–301.CrossRefGoogle Scholar
Phillips, P.C.B. (1988) Weak convergence to the matrix stochastic integral. Journal of Multivariate Analysis 24, 252–264.CrossRefGoogle Scholar
Phillips, P.C.B. & Durlauf, S.N. (1986) Multiple time series regression with integrated processes. Review of Economic Studies 53, 473–495.CrossRefGoogle Scholar
Phillips, P.C.B. & Solo, V. (1992) Asymptotics for linear processes. Annals of Statistics 20 (2), 971–1001.CrossRefGoogle Scholar
Potscher, B.M. & Prucha, I.R. (1989) A uniform law of large numbers for dependent and heterogeneous data processes. Econometrica 57, 675–684.CrossRefGoogle Scholar
Potscher, B.M. & Prucha, I.R. (1991) Basic structure of the asymptotic theory in dynamic nonlinear econometric models, part I: Consistency and approximation concepts. Econometric Reviews 10, 125–216.CrossRefGoogle Scholar
Potscher, B.M. & Prucha, I.R. (1994) Generic uniform convergence and equicontinuity concepts for random functions: An exploration of the basic structure. Journal of Econometrics 60, 23–63.CrossRefGoogle Scholar