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Nonparametric estimation equations for time series data

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  • Cai, Zongwu

Abstract

In this article, the nonparametric version of estimation equations is investigated, which unifies various statistical methodologies, for both nonlinear discrete and continuous time series data. The weak consistency and asymptotic normality of the resulting estimators are established. Under this general framework, a nonparametric regression estimator can be obtained easily and the asymptotic theory can be derived without going through case-by-case.

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  • Cai, Zongwu, 2003. "Nonparametric estimation equations for time series data," Statistics & Probability Letters, Elsevier, vol. 62(4), pages 379-390, May.
    • Handle: RePEc:eee:stapro:v:62:y:2003:i:4:p:379-390
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    References listed on IDEAS

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    1. repec:wyi:journl:002108 is not listed on IDEAS
    2. Rongning Wu & Yunwei Cui, 2014. "A Parameter-Driven Logit Regression Model For Binary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 462-477, August.
    3. Cai, Zongwu & Li, Qi, 2008. "Nonparametric Estimation Of Varying Coefficient Dynamic Panel Data Models," Econometric Theory, Cambridge University Press, vol. 24(5), pages 1321-1342, October.
    4. Zongwu Cai & Yongmiao Hong, 2013. "Some Recent Developments in Nonparametric Finance," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    5. Cai, Zongwu & Ould-Saïd, Elias, 2003. "Local M-estimator for nonparametric time series," Statistics & Probability Letters, Elsevier, vol. 65(4), pages 433-449, December.
    6. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2017. "Extreme M-quantiles as risk measures: From L1 to Lp optimization," TSE Working Papers 17-841, Toulouse School of Economics (TSE).
    7. Bravo, Francesco, 2023. "Local polynomial estimation of nonparametric general estimating equations," Statistics & Probability Letters, Elsevier, vol. 197(C).
    8. Francesco Bravo, 2016. "Local Information Theoretic Methods for smooth Coefficients Dynamic Panel Data Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(5), pages 690-708, September.

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