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Optimal Bandwidth Selection in Heteroskedasticity-Autocorrelation Robust Testing
Sun, Yixiao; Phillips, Peter C. B.; Jin, Sainan - Cowles Foundation for Research in Economics, Yale University - 2006
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirical practice to use kernel-based robust standard errors that involve some smoothing function over the sample autocorrelations. The underlying smoothing parameter b, which can be defined as the ratio...
Persistent link: https://www.econbiz.de/10005093965
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Tilted Nonparametric Estimation of Volatility Functions with Empirical Applications, 2nd Version
Xu, Ke-Li - 2010
This paper proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local level nonparametric regression applied to squared mean...
Persistent link: https://www.econbiz.de/10012716626
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Threshold Regression with Endogeneity
Yu, Ping - 2014
This paper studies estimation and specification testing in threshold regression with endogeneity. Three key results differ from those in regular models. First, both the threshold point and the threshold effect parameters are shown to be identified without the need for instrumentation. Second, in...
Persistent link: https://www.econbiz.de/10013043164
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Optimal Bandwidth Selection in Heteroskedasticity-Autocorrelation Robust Testing
Sun, Yixiao - 2006
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirical practice to use kernel-based robust standard errors that involve some smoothing function over the sample autocorrelations. The underlying smoothing parameter b, which can be defined as the ratio...
Persistent link: https://www.econbiz.de/10012783449
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Optimal Bandwidth Choice for Interval Estimation in GMM Regression
Sun, Yixiao - 2008
In time series regression with nonparametrically autocorrelated errors, it is now standard empirical practice to construct confidence intervals for regression coefficients on the basis of nonparametrically studentized t-statistics. The standard error used in the studentization is typically...
Persistent link: https://www.econbiz.de/10012771849
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Improved Har Inference Using Power Kernels Without Truncation
Phillips, Peter C. B.; Sun, Yixiao; Jin, Sainan - 2005
Employing power kernels suggested in earlier work by the authors (2003), this paper shows how to refine methods of robust inference on the mean in a time series that rely on families of untruncated kernel estimates of the long-run parameters. The new methods improve the size properties of...
Persistent link: https://www.econbiz.de/10014064311
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Regression Asymptotics Using Martingale Convergence Methods
Ibragimov, Rustam; Phillips, Peter C. B. - 2004
relies on the fact that the econometric quantities of interest involve discrete time martingales or semimartingales and shows … how in the limit these quantities become continuous martingales and semimartingales. The limit theory itself uses very … general convergence results for semimartingales that were obtained in work by Jacod and Shiryaev (2003). The theory that is …
Persistent link: https://www.econbiz.de/10014070490
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Tilted Nonparametric Estimation of Volatility Functions with Empirical Applications
Phillips, Peter C. B.; Xu, Ke-Li - 2010
This paper proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local level nonparametric regression applied to squared mean...
Persistent link: https://www.econbiz.de/10014049786
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Consistent Hac Estimation and Robust Regression Testing Using Sharp Origin Kernels with No Truncation
Phillips, Peter C. B.; Sun, Yixiao; Jin, Sainan - 2003
A new family of kernels is suggested for use in heteroskedasticity and autocorrelation consistent (HAC) and long run variance (LRV) estimation and robust regression testing. The kernels are constructed by taking powers of the Bartlett kernel and are intended to be used with no truncation (or...
Persistent link: https://www.econbiz.de/10014088395
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Nonlinear Log-Periodogram Regression for Perturbed Fractional Processes
Sun, Yixiao; Phillips, Peter C. B. - 2003
This paper studies fractional processes that may be perturbed by weakly dependent time series. The model for a perturbed fractional process has a components framework in which there may be components of both long and short memory. All commonly used estimates of the long memory parameter (such as...
Persistent link: https://www.econbiz.de/10014116703