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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 管中閔 | |
| dc.contributor.author | Yu-Wei Hsieh | en |
| dc.contributor.author | 謝鈺偉 | zh_TW |
| dc.date.accessioned | 2021-06-13T06:06:42Z | - |
| dc.date.available | 2008-07-07 | |
| dc.date.copyright | 2006-07-07 | |
| dc.date.issued | 2006 | |
| dc.date.submitted | 2006-06-12 | |
| dc.identifier.citation | Andrews, D. W. K. (1991), Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation,
Econometrica ,59, 817-854. Andrews, D. W. K. and Monahan, J. C. (1992), An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimatior, Econometrica ,60, 953-966. Bai, J. (2003), Testing Parametric Conditional Distributions of Dynamic Models, Review of Economics and Statistics ,85, 531-549. Brown, R.L., Durbin, J. and Evans, J.M. (1975), Techniques for Testing the Constancy of Regression Relationships over Time, Journal of the Royal Statistical Society B,37, 149-192. Bunzel, H., Kiefer, N.M. and Vogelsang, T.J. (2001), Simple Robust Testing of Hypotheses in Non-linear Models, Journal of American Statistical Association ,96, 1088-1098. de Jong, R.M. and Davidson, J. (2000), Consistency of Kernel Estimators of Heteroskedastic and Autocorrelated Covariance Matrices, Econometrica ,68, 407-424. Gallant, A. (1987), Nonlinear Statistical Models, Wiley, New York. Hansen, B.E. (1992), Consistent Covariance Matrix Estimation for Dependent Heterogenous Processes, Econometrica ,60, 967-972. Hong, Y and Lee, J. (1999) Wavelet-based Estimation of Heteroskedasticity and Autocorrelation Consistent Covariance Matrices, Working Paper Jansson, M. (2004), The Error in Rejection Probability of Simple Autocorrelation Robust Tests, Econometrica ,72,937-946. Khmaladze, E.V. (1981), Martingale Approach in the Theory of Goodness-Of-Fit Tests, Theory of Probability and Its Applications ,26,240-265. Kiefer, N.M., Vogelsang, T.J. and Bunzel, H. (2000), Simple Robust Testing of Regression Hypotheses, Econometrica ,68, 695-714. Kiefer, N.M. and Vogelsang, T.J. (2002)a, Heteroskedasticity-Autocorrelation Robust Standard Errors Using the Bartlett Kernel Without Truncation, Econometrica ,70, 2093-2095. Kiefer, N.M. and Vogelsang, T.J. (2002)b, Heteroskedasticity-Autocorrelation Robust Testing Using Bandwidth Equal to Sample Size, Econometric Theory ,18, 1350-1366. Kiefer, N.M. and Vogelsang, T.J. (2005), A New Asymptotic Theory for Heteroskedasticity-Autocorrelation Robust Tests, Econometric Theory ,21, 1130-1164. Kuan, C.M. and Lee, W.M. (2006), Robust M Tests without Consistent Estimation of Asymptotic Covariance Matrix, Working Paper. Lin, C.C. and Sakata, S (2005), Consistent Estimation of Long-Run Covariance Matrices with Truncated Flat Kernel, Working Paper. Lobato, I.N., Nankervis, J.C., and Savin, N.E. (2001), Testing for Autocorrelation using a modified Box-Pierce Q test, International Economic Review ,42, 187-205. Lobato, I.N. (2001), Testing that A Dependent Processes is Uncorrelated, Journal of the American Statistical Association ,96, 1066-1076. Lumley, T. and Heagerty, P. (1999), Weighted Empirical Adaptive Variance Estimators for Correlated Data Regression, Journal of the Royal Statistical Society B,61, 459-477. McLeish, D.L. (1975), A Maximal Inequality and Dependent Strong Laws, The Annals of Probability ,5,829-839. Newey, W.K. and West, K.D. (1987), A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix, Econometrica ,55, 703-708. Newey, W.K. and West, K.D. (1994), Automatic Lag Selection in Covariance Estimation, Review of Economic Studies ,61, 631-654. Ng, S. and Perron, P. (1996), The Exact Error in Estimating the Spectral Density at the Origin, Journal of Time Series Analysis ,17, 379-408. Phillips, P.C.B., Sun, Y. and Jin, S. (2003), Consistent HAC Estimation and Robust Regression Testing Using Sharp Origin Kernels with No Truncation, Working Paper, Department of Economics , Yale University. Phillips, P.C.B. (2005), HAC Estimation by Automated Regression, Econometric Theory ,21, 116-142. Ploberger, W., Kramer, W. and Kontrus, K. (1989), A New Test for Structural Stability in the Linear Regression Model, Journal of Econometrics ,40, 307-318. Politis, D.N. and Romano, J.P. (1995), Bias-corrected nonparametric spectral estimation, Journal of Time Series Analysis ,16, 67-103 Politis, D.N. (2005), Higher-order Accurate, Positive Semi-definite Estimation of Large-sample Covariance and Spectral Density Matrices, Working Paper. Priestley, M.B. (1981), Spectral Analysis and Time Series, Vol. 1, Academic Press, New York. Robinson, P.M. (1991), Automatic Frequency Domain Inference on Semiparametric and Nonparametric Models, Econometrica ,59, 1329-1363. Simonoff, J. (1993), The Relative Importance of Bias and Variability in the Estimation of the Variance of a Statistic, The Statistician ,42, 3-7. Sul, D., Phillips, P.C.B. and Choi, C.Y. (2003), Prewhitening Bias in HAC Estimation, Working Paper. Vogelsang, T.J. (2002), Testing in GMM Models Without Truncation, Working Paper. White, H. (1984), Asymptotic Theory for Econometricians, Academic Press, New York. Xiao, Z. and Linton, O. (2002), A Nonparametric Prewhitened Covariance Estimator, Journal of Time Series Analysis ,23, 215-250. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34400 | - |
| dc.description.abstract | We propose using recursive residuals to compute HAC estimators.
Simulations show that the recursive residuals-based HAC estimator has smaller bias than the conventional HAC estimator, and the tests based on this estimator performs very well in terms of size and power. In contrast to the KVB robust test, it pays a slight price of power loss but delivers accurate finite sample size. In some cases, the tests based on the proposed HAC estimator even has more accurate finite sample size than that of KVB. In contrast to the prewhitened HAC estimator, the tests based on the proposed HAC estimator still works well when nonlinear dependency or heteroskedasticity is present. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T06:06:42Z (GMT). No. of bitstreams: 1 ntu-95-R93323003-1.pdf: 525072 bytes, checksum: c3914d0725f0cef6d6d022b43d58ef61 (MD5) Previous issue date: 2006 | en |
| dc.description.tableofcontents | 1. Introduction...............................1
2. Preliminary................................5 3. HAC Estimation Using Recursive Residuals...9 4. Monte Carlo Simulation....................13 5. Conclusions...............................19 Appendix: Technical Proofs...................21 Reference....................................24 | |
| dc.language.iso | en | |
| dc.title | HAC變異數矩陣的新估計方法 | zh_TW |
| dc.title | HAC Covariance Matrix Estimation : An Improved Method with Recursive Residual | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 94-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林金龍,銀慶剛 | |
| dc.subject.keyword | 迴歸參數的檢定,長期變異數, | zh_TW |
| dc.subject.keyword | spectral density,Newey-West estimator,kernel,prewhiten,long run variance, | en |
| dc.relation.page | 42 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2006-06-12 | |
| dc.contributor.author-college | 社會科學院 | zh_TW |
| dc.contributor.author-dept | 經濟學研究所 | zh_TW |
| Appears in Collections: | 經濟學系 | |
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| File | Size | Format | |
|---|---|---|---|
| ntu-95-1.pdf Restricted Access | 512.77 kB | Adobe PDF |
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