Open AccessPosted Content
Automatic Lag Selection in Covariance Matrix Estimation
Reads0
Chats0
TLDR
A nonparametric method for automatically selecting the number of autocovariances to use in computing a heteroskedasticity and autocorrelation consistent covariance matrix is proposed and proved to be asymptotically equivalent to one that is optimal under a mean squared error loss function.Abstract:
We propose a nonparametric method for automatically selecting the number of autocovariances to use in computing a heteroskedasticity and autocorrelation consistent covariance matrix. For a given kernel for weighting the autocovariances, we prove that our procedure is asymptotically equivalent to one that is optimal under a mean squared error loss function. Monte Carlo simulations suggest that our procedure performs tolerably well, although it does result in size distortions.read more
Citations
More filters
Journal ArticleDOI
Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors
TL;DR: In this paper, a method for testing the null of no cointegration in dynamic panels with multiple regressors and computing approximate critical values for these tests is presented. But the method is limited to simple bivariate examples, in large part due to the lack of critical values available for more complex multivariate regressions.
Journal ArticleDOI
Testing for error correction in panel data
TL;DR: This article proposed new error correction-based cointegration tests for panel data, which have good small-sample properties with small size distortions and high power relative to other popular residual-based panel coIntegration tests.
Book ChapterDOI
Fully modified OLS for heterogeneous cointegrated panels
TL;DR: In this paper, the authors used fully modified OLS principles to develop new methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels in a manner that is consistent with the degree of cross sectional heterogeneity that has been permitted in recent panel unit root and panel cointegration studies.
Journal ArticleDOI
Robust standard errors for panel regressions with cross–sectional dependence
TL;DR: In this article, the authors present a new Stata program, xtscc, that estimates pooled or dual least squares/weighted least squares regression and xed-eects (within) regression models with Driscoll and Kraay (Review of Economics and Statistics 80: 549{560) standard errors.
References
More filters
ReportDOI
A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix
Whitney K. Newey,Kenneth D. West +1 more
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
BookDOI
Density estimation for statistics and data analysis
TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Journal ArticleDOI
Large sample properties of generalized method of moments estimators
Journal Article
Spectral Analysis and Time Series
TL;DR: In this article, the authors introduce the concept of Stationary Random Processes and Spectral Analysis in the Time Domain and Frequency Domain, and present an analysis of Processes with Mixed Spectra.
Journal ArticleDOI
Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
TL;DR: Using these results, data-dependent automatic bandwidth/lag truncation parameters are introduced and asymptotically optimal kernel/weighting scheme and bandwidth/agreement parameters are obtained.
Related Papers (5)
A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix
Whitney K. Newey,Kenneth D. West +1 more