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학술저널

Log Periodogram Estimation with Nonstationary Process

Log Periodogram Estimation with Nonstationary Process

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This paper studies a new semiparametric estimation procedure of the memory parameter (d) in models of fractional integration. The procedure is called modified log periodogram regression and it is especially useful for nonstationary time series where d≥½. The modified estimator is shown to be consistent and asymptotically normally distributed with variance π²/24 under mild regularity conditions. Simulations reveal that the estimator performs well for all d≥½.

Abstract

1. Introduction

2. The DFT of Fractionally Integrated Processes

3. Modified Log-Periodogram Regression

4. Finite Sample Performance of the Modified Log Periodogram Regression

5. Concluding Remarks

6. Appendix

References

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