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Xiaofeng Shao

Personal Details

First Name:Xiaofeng
Middle Name:
Last Name:Shao
Suffix:
RePEc Short-ID:psh274
http://www.stat.uiuc.edu/~xshao

Research output

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Articles

  1. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
  2. Xianyang Zhang & Bo Li & Xiaofeng Shao, 2014. "Self-normalization for Spatial Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 311-324, June.
  3. Xiaofeng Shao & Jingsi Zhang, 2014. "Martingale Difference Correlation and Its Use in High-Dimensional Variable Screening," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1302-1318, September.
  4. Zhang, Jingsi & Jiang, Wenxin & Shao, Xiaofeng, 2013. "Bayesian model selection based on parameter estimates from subsamples," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 979-986.
  5. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.
  6. Zhou Zhou & Xiaofeng Shao, 2013. "Inference for linear models with dependent errors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(2), pages 323-343, March.
  7. Xiaofeng Shao & Dimitris N. Politis, 2013. "Fixed b subsampling and the block bootstrap: improved confidence sets based on p-value calibration," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(1), pages 161-184, January.
  8. Xiaofeng Shao, 2012. "Parametric Inference in Stationary Time Series Models with Dependent Errors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(4), pages 772-783, December.
  9. Xiaofeng Shao, 2011. "A simple test of changes in mean in the possible presence of long‐range dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(6), pages 598-606, November.
  10. Shao, Xiaofeng, 2011. "Testing For White Noise Under Unknown Dependence And Its Applications To Diagnostic Checking For Time Series Models," Econometric Theory, Cambridge University Press, vol. 27(02), pages 312-343, April.
  11. Shao, Xiaofeng, 2011. "A bootstrap-assisted spectral test of white noise under unknown dependence," Journal of Econometrics, Elsevier, vol. 162(2), pages 213-224, June.
  12. Shao, Xiaofeng & Zhang, Xianyang, 2010. "Testing for Change Points in Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1228-1240.
  13. Shao, Xiaofeng, 2010. "Nonstationarity-Extended Whittle Estimation," Econometric Theory, Cambridge University Press, vol. 26(04), pages 1060-1087, August.
  14. Shao, Xiaofeng, 2010. "The Dependent Wild Bootstrap," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 218-235.
  15. Xiaofeng Shao, 2010. "A self-normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 343-366.
  16. Xiaofeng Shao, 2010. "Corrigendum: A self-normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 695-696.
  17. Shao, Xiaofeng, 2009. "A Generalized Portmanteau Test For Independence Between Two Stationary Time Series," Econometric Theory, Cambridge University Press, vol. 25(01), pages 195-210, February.
  18. Xiaofeng Shao, 2009. "Confidence intervals for spectral mean and ratio statistics," Biometrika, Biometrika Trust, vol. 96(1), pages 107-117.
  19. Shao, Xiaofeng & Wu, Wei Biao, 2007. "Local asymptotic powers of nonparametric and semiparametric tests for fractional integration," Stochastic Processes and their Applications, Elsevier, vol. 117(2), pages 251-261, February.
  20. Shao, Xiaofeng & Wu, Wei Biao, 2007. "Local Whittle Estimation Of Fractional Integration For Nonlinear Processes," Econometric Theory, Cambridge University Press, vol. 23(05), pages 899-929, October.
  21. Wu, Wei Biao & Shao, Xiaofeng, 2007. "A Limit Theorem For Quadratic Forms And Its Applications," Econometric Theory, Cambridge University Press, vol. 23(05), pages 930-951, October.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Xianyang Zhang & Bo Li & Xiaofeng Shao, 2014. "Self-normalization for Spatial Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 311-324, June.

    Cited by:

    1. Mackenbach, Johan P. & McKee, Martin, 2015. "Government, politics and health policy: A quantitative analysis of 30 European countries," Health Policy, Elsevier, vol. 119(10), pages 1298-1308.

  2. Xiaofeng Shao & Jingsi Zhang, 2014. "Martingale Difference Correlation and Its Use in High-Dimensional Variable Screening," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1302-1318, September.

    Cited by:

    1. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Cross-Spectral Measures of Dependence between Economic Variables," Papers 1510.06946, arXiv.org.
    2. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    3. Chen, Xiaolin & Chen, Xiaojing & Wang, Hong, 2018. "Robust feature screening for ultra-high dimensional right censored data via distance correlation," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 118-138.

  3. Zhou Zhou & Xiaofeng Shao, 2013. "Inference for linear models with dependent errors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(2), pages 323-343, March.

    Cited by:

    1. Yinxiao Huang & Stanislav Volgushev & Xiaofeng Shao, 2015. "On Self-Normalization For Censored Dependent Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 109-124, January.
    2. Johan Blomquist & Joakim Westerlund, 2016. "Panel bootstrap tests of slope homogeneity," Empirical Economics, Springer, vol. 50(4), pages 1359-1381, June.
    3. Porshnev, Alexander V. & Lakshina, Valeriya V. & Redkin, Ilya E., 2016. "Using Emotional Markers' Frequencies in Stock Market ARMAX-GARCH Model," MPRA Paper 82875, University Library of Munich, Germany.
    4. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
    5. Bai, Shuyang & Taqqu, Murad S. & Zhang, Ting, 2016. "A unified approach to self-normalized block sampling," Stochastic Processes and their Applications, Elsevier, vol. 126(8), pages 2465-2493.
    6. Yamada, Hiroshi & Yoon, Gawon, 2014. "When Grilli and Yang meet Prebisch and Singer: Piecewise linear trends in primary commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 193-207.
    7. Alexander Porshnev & Valeria Lakshina & Ilya Redkin, 2016. "Could Emotional Markers in Twitter Posts Add Information to the Stock Market Armax-Garch Model," HSE Working papers WP BRP 54/FE/2016, National Research University Higher School of Economics.

  4. Xiaofeng Shao & Dimitris N. Politis, 2013. "Fixed b subsampling and the block bootstrap: improved confidence sets based on p-value calibration," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(1), pages 161-184, January.

    Cited by:

    1. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Srijan Sengupta & Xiaofeng Shao & Yingchuan Wang, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 315-326, May.

  5. Xiaofeng Shao, 2012. "Parametric Inference in Stationary Time Series Models with Dependent Errors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(4), pages 772-783, December.

    Cited by:

    1. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.

  6. Xiaofeng Shao, 2011. "A simple test of changes in mean in the possible presence of long‐range dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(6), pages 598-606, November.

    Cited by:

    1. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "A Simple Test on Structural Change in Long-Memory Time Series," Hannover Economic Papers (HEP) dp-592, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Fabrizio Iacone & Stephen J. Leybourne & A. M. Robert Taylor, 2014. "A FIXED- b TEST FOR A BREAK IN LEVEL AT AN UNKNOWN TIME UNDER FRACTIONAL INTEGRATION," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 40-54, January.
    3. Papailias, Fotis & Fruet Dias, Gustavo, 2015. "Forecasting long memory series subject to structural change: A two-stage approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1056-1066.
    4. Seong Yeon Chang & Pierre Perron, 2014. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Boston University - Department of Economics - Working Papers Series wp2015-011, Boston University - Department of Economics, revised 20 Sep 2015.
    5. Annika Betken, 2016. "Testing for Change-Points in Long-Range Dependent Time Series by Means of a Self-Normalized Wilcoxon Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 785-809, November.
    6. Chatzikonstanti, Vasiliki & Venetis, Ioannis A., 2015. "Long memory in log-range series: Do structural breaks matter?," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 104-113.
    7. Javier Hualde & Fabrizio Iacone, 2015. "Autocorrelation robust inference using the Daniell kernel with fixed bandwidth," Discussion Papers 15/14, Department of Economics, University of York.
    8. Bai, Shuyang & Taqqu, Murad S. & Zhang, Ting, 2016. "A unified approach to self-normalized block sampling," Stochastic Processes and their Applications, Elsevier, vol. 126(8), pages 2465-2493.
    9. Luis Alberiko & OlaOluwa S. Yaya & Olarenwaju I. Shittu, 2015. "Fractional integration and asymmetric volatility in european, asian and american bull and bear markets. Applications to high frequency stock data," NCID Working Papers 07/2015, Navarra Center for International Development, University of Navarra.
    10. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Change-in-Mean Tests in Long-memory Time Series: A Review of Recent Developments," Hannover Economic Papers (HEP) dp-598, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  7. Shao, Xiaofeng, 2011. "Testing For White Noise Under Unknown Dependence And Its Applications To Diagnostic Checking For Time Series Models," Econometric Theory, Cambridge University Press, vol. 27(02), pages 312-343, April.

    Cited by:

    1. Ke Zhu, 2016. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 463-485, March.
    2. Zhang, Xianyang, 2016. "White noise testing and model diagnostic checking for functional time series," Journal of Econometrics, Elsevier, vol. 194(1), pages 76-95.
    3. Li, Linyuan & Yao, Shan & Duchesne, Pierre, 2014. "On wavelet-based testing for serial correlation of unknown form using Fan’s adaptive Neyman method," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 308-327.
    4. Ke. Zhu, 2013. "A mixed portmanteau test for ARMA-GARCH models by the quasi-maximum exponential likelihood estimation approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(2), pages 230-237, March.
    5. Colin M. Gallagher & Thomas J. Fisher, 2015. "On Weighted Portmanteau Tests For Time-Series Goodness-Of-Fit," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 67-83, January.
    6. Zhu, Ke & Li, Wai Keung, 2015. "A bootstrapped spectral test for adequacy in weak ARMA models," Journal of Econometrics, Elsevier, vol. 187(1), pages 113-130.
    7. Chen, Min & Zhu, Ke, 2014. "Sign-based specification tests for martingale difference with conditional heteroscedasity," MPRA Paper 56347, University Library of Munich, Germany.

  8. Shao, Xiaofeng, 2011. "A bootstrap-assisted spectral test of white noise under unknown dependence," Journal of Econometrics, Elsevier, vol. 162(2), pages 213-224, June.

    Cited by:

    1. Ke Zhu, 2016. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 463-485, March.
    2. Brüggemann, Ralf & Jentsch, Carsten & Trenkler, Carsten, 2014. "Inference in VARs with Conditional Heteroskedasticity of Unknown Form," Working Papers 14-21, University of Mannheim, Department of Economics.
    3. Zhang, Xianyang, 2016. "White noise testing and model diagnostic checking for functional time series," Journal of Econometrics, Elsevier, vol. 194(1), pages 76-95.
    4. Antoine Djogbenou & Sílvia Gonçalves & Benoit Perron, 2015. "Bootstrap inference in regressions with estimated factors and serial correlation," CIRANO Working Papers 2015s-20, CIRANO.
    5. Ulrich Hounyo, 2014. "The wild tapered block bootstrap," CREATES Research Papers 2014-32, Department of Economics and Business Economics, Aarhus University.
    6. Smeekes S. & Urbain J.R.Y.J., 2014. "A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing," Research Memorandum 008, Maastricht University, Graduate School of Business and Economics (GSBE).
    7. Doukhan, Paul & Lang, Gabriel & Leucht, Anne & Neumann, Michael H., 2014. "Dependent wild bootstrap for the empirical process," Working Papers 35246, University of Mannheim, Department of Economics.
    8. Skrobotov Anton & Cavaliere Giuseppe & Taylor Robert, 2016. "Wild Bootstrap Seasonal Unit Root Tests for Time Series with Periodic Non-Stationary Volatility," Working Papers wpaper-2016-269, Gaidar Institute for Economic Policy, revised 2016.
    9. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Antoine Djogbenou & Sílvia Gonçalves & Benoit Perron, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 481-502, May.
    10. Zhu, Ke & Li, Wai Keung, 2015. "A bootstrapped spectral test for adequacy in weak ARMA models," Journal of Econometrics, Elsevier, vol. 187(1), pages 113-130.
    11. Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.
    12. Chen, Min & Zhu, Ke, 2014. "Sign-based specification tests for martingale difference with conditional heteroscedasity," MPRA Paper 56347, University Library of Munich, Germany.

  9. Shao, Xiaofeng & Zhang, Xianyang, 2010. "Testing for Change Points in Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1228-1240.

    Cited by:

    1. Hoga, Yannick, 2017. "Monitoring multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 105-121.
    2. Fabrizio Iacone & Stephen J. Leybourne & A. M. Robert Taylor, 2014. "A FIXED- b TEST FOR A BREAK IN LEVEL AT AN UNKNOWN TIME UNDER FRACTIONAL INTEGRATION," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 40-54, January.
    3. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. YAMAZAKI, Daisuke & KUROZUMI, Eiji, 2014. "Improving the Finite Sample Performance of Tests for a Shift in Mean," Discussion Papers 2014-16, Graduate School of Economics, Hitotsubashi University.
    5. Annika Betken, 2016. "Testing for Change-Points in Long-Range Dependent Time Series by Means of a Self-Normalized Wilcoxon Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 785-809, November.
    6. JIANG, Peiyun & KUROZUMI, Eiji, 2017. "Power Properties of the Modified CUSUM Tests," Discussion Papers 2017-05, Graduate School of Economics, Hitotsubashi University.
    7. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
    8. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Change-in-Mean Tests in Long-memory Time Series: A Review of Recent Developments," Hannover Economic Papers (HEP) dp-598, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Ivan Kojadinovic & Jean-François Quessy & Tom Rohmer, 2016. "Testing the constancy of Spearman’s rho in multivariate time series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(5), pages 929-954, October.

  10. Shao, Xiaofeng, 2010. "Nonstationarity-Extended Whittle Estimation," Econometric Theory, Cambridge University Press, vol. 26(04), pages 1060-1087, August.

    Cited by:

    1. Gilles De Truchis, 2013. "Approximate whittle analysis of fractional cointegration and the stock market synchronization issue," Post-Print hal-01410658, HAL.
    2. Morten Ørregaard Nielsen, 2014. "Asymptotics for the conditional-sum-of-squares estimator in multivariate fractional time series models," CREATES Research Papers 2014-34, Department of Economics and Business Economics, Aarhus University.

  11. Shao, Xiaofeng, 2010. "The Dependent Wild Bootstrap," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 218-235.

    Cited by:

    1. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 0509. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    2. Hounyo, Ulrich & Varneskov, Rasmus T., 2017. "A local stable bootstrap for power variations of pure-jump semimartingales and activity index estimation," Journal of Econometrics, Elsevier, vol. 198(1), pages 10-28.
    3. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 269-271, May.
    4. Chen, Bin, 2015. "Modeling and testing smooth structural changes with endogenous regressors," Journal of Econometrics, Elsevier, vol. 185(1), pages 196-215.
    5. Christoph Bergmeir & Rob J Hyndman & Jose M Benitez, 2014. "Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation," Monash Econometrics and Business Statistics Working Papers 11/14, Monash University, Department of Econometrics and Business Statistics.
    6. Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," IDEI Working Papers 870, Institut d'Économie Industrielle (IDEI), Toulouse.
    7. Yeonwoo Rho & Xiaofeng Shao, 2018. "Bootstrap-Assisted Unit Root Testing With Piecewise Locally Stationary Errors," Papers 1802.05333, arXiv.org.
    8. Pang Du & Christopher F. Parmeter & Jeffrey S. Racine, 2012. "Nonparametric Kernel Regression with Multiple Predictors and Multiple Shape Constraints," Department of Economics Working Papers 2012-08, McMaster University.
    9. Friedrich, Marina & Smeekes, Stephan & Urbain, Jean-Pierre, 2017. "Autoregressive Wild Bootstrap Inference for Nonparametric Trends," Research Memorandum 010, Maastricht University, Graduate School of Business and Economics (GSBE).
    10. Ulrich Hounyo, 2014. "The wild tapered block bootstrap," CREATES Research Papers 2014-32, Department of Economics and Business Economics, Aarhus University.
    11. Leucht, Anne & Neumann, Michael H., 2013. "Dependent wild bootstrap for degenerate U- and V-statistics," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 257-280.
    12. Bucchia, Béatrice & Wendler, Martin, 2017. "Change-point detection and bootstrap for Hilbert space valued random fields," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 344-368.
    13. Gu, Jingping & Liang, Zhongwen, 2014. "Testing cointegration relationship in a semiparametric varying coefficient model," Journal of Econometrics, Elsevier, vol. 178(P1), pages 57-70.
    14. Smeekes S. & Urbain J.R.Y.J., 2014. "A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing," Research Memorandum 008, Maastricht University, Graduate School of Business and Economics (GSBE).
    15. Doukhan, Paul & Lang, Gabriel & Leucht, Anne & Neumann, Michael H., 2014. "Dependent wild bootstrap for the empirical process," Working Papers 35246, University of Mannheim, Department of Economics.
    16. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Antoine Djogbenou & Sílvia Gonçalves & Benoit Perron, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 481-502, May.
    17. Ulrich Hounyo & Rasmus T. Varneskov, 2015. "A Local Stable Bootstrap for Power Variations of Pure-Jump Semimartingales and Activity Index Estimation," CREATES Research Papers 2015-26, Department of Economics and Business Economics, Aarhus University.
    18. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Paul Doukhan & Gabriel Lang & Anne Leucht & Michael H. Neumann, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 290-314, May.
    19. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Srijan Sengupta & Xiaofeng Shao & Yingchuan Wang, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 315-326, May.
    20. Ivan Kojadinovic & Jean-François Quessy & Tom Rohmer, 2016. "Testing the constancy of Spearman’s rho in multivariate time series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(5), pages 929-954, October.
    21. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.

  12. Xiaofeng Shao, 2010. "A self-normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 343-366.

    Cited by:

    1. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.
    2. Hoga, Yannick, 2017. "Monitoring multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 105-121.
    3. Fabrizio Iacone & Stephen J. Leybourne & A. M. Robert Taylor, 2014. "A FIXED- b TEST FOR A BREAK IN LEVEL AT AN UNKNOWN TIME UNDER FRACTIONAL INTEGRATION," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 40-54, January.
    4. Zhongjun Qu & Yi-Ting Chen, 2010. "M Tests with a New Normalization Matrix," Boston University - Department of Economics - Working Papers Series WP2010-050, Boston University - Department of Economics.
    5. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series," Cambridge Working Papers in Economics 1452, Faculty of Economics, University of Cambridge.
    6. Yinxiao Huang & Stanislav Volgushev & Xiaofeng Shao, 2015. "On Self-Normalization For Censored Dependent Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 109-124, January.
    7. RMI staff article, 2016. "NUS-RMI Credit Research Initiative Technical Report Version: 2016 Update 1," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 49-132.
    8. Seong Yeon Chang & Pierre Perron, 2014. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Boston University - Department of Economics - Working Papers Series wp2015-011, Boston University - Department of Economics, revised 20 Sep 2015.
    9. Sun, Yixiao, 2013. "Fixed-smoothing Asymptotics in a Two-step GMM Framework," University of California at San Diego, Economics Working Paper Series qt64x4z265, Department of Economics, UC San Diego.
    10. Daniel J. Nordman & Helle Bunzel & Soumendra N. Lahiri, 2012. "A Non-standard Empirical Likelihood for Time Series," CREATES Research Papers 2012-55, Department of Economics and Business Economics, Aarhus University.
    11. Xianyang Zhang & Bo Li & Xiaofeng Shao, 2014. "Self-normalization for Spatial Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 311-324, June.
    12. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
    13. Zhang, Xianyang, 2016. "Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework," Journal of Econometrics, Elsevier, vol. 193(1), pages 123-146.
    14. Bai, Shuyang & Taqqu, Murad S. & Zhang, Ting, 2016. "A unified approach to self-normalized block sampling," Stochastic Processes and their Applications, Elsevier, vol. 126(8), pages 2465-2493.
    15. Zhang, Jingsi & Jiang, Wenxin & Shao, Xiaofeng, 2013. "Bayesian model selection based on parameter estimates from subsamples," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 979-986.
    16. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Change-in-Mean Tests in Long-memory Time Series: A Review of Recent Developments," Hannover Economic Papers (HEP) dp-598, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    17. Hwang, Jungbin & Sun, Yixiao, 2015. "Should We Go One Step Further? Â An Accurate Comparison of One-step and Two-step Procedures in a Generalized Method of Moments Framework," University of California at San Diego, Economics Working Paper Series qt58r2z98m, Department of Economics, UC San Diego.
    18. Xianyang Zhang & Xiaofeng Shao, 2016. "On the coverage bound problem of empirical likelihood methods for time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 395-421, March.

  13. Xiaofeng Shao, 2010. "Corrigendum: A self-normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 695-696.

    Cited by:

    1. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.
    2. Hoga, Yannick, 2017. "Monitoring multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 105-121.
    3. Fabrizio Iacone & Stephen J. Leybourne & A. M. Robert Taylor, 2014. "A FIXED- b TEST FOR A BREAK IN LEVEL AT AN UNKNOWN TIME UNDER FRACTIONAL INTEGRATION," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 40-54, January.
    4. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series," Cambridge Working Papers in Economics 1452, Faculty of Economics, University of Cambridge.
    5. Yinxiao Huang & Stanislav Volgushev & Xiaofeng Shao, 2015. "On Self-Normalization For Censored Dependent Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 109-124, January.
    6. RMI staff article, 2016. "NUS-RMI Credit Research Initiative Technical Report Version: 2016 Update 1," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 49-132.
    7. Seong Yeon Chang & Pierre Perron, 2014. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Boston University - Department of Economics - Working Papers Series wp2015-011, Boston University - Department of Economics, revised 20 Sep 2015.
    8. Xianyang Zhang & Bo Li & Xiaofeng Shao, 2014. "Self-normalization for Spatial Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 311-324, June.
    9. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
    10. Zhang, Xianyang, 2016. "Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework," Journal of Econometrics, Elsevier, vol. 193(1), pages 123-146.
    11. Bai, Shuyang & Taqqu, Murad S. & Zhang, Ting, 2016. "A unified approach to self-normalized block sampling," Stochastic Processes and their Applications, Elsevier, vol. 126(8), pages 2465-2493.
    12. Zhang, Jingsi & Jiang, Wenxin & Shao, Xiaofeng, 2013. "Bayesian model selection based on parameter estimates from subsamples," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 979-986.
    13. Xianyang Zhang & Xiaofeng Shao, 2016. "On the coverage bound problem of empirical likelihood methods for time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 395-421, March.

  14. Shao, Xiaofeng, 2009. "A Generalized Portmanteau Test For Independence Between Two Stationary Time Series," Econometric Theory, Cambridge University Press, vol. 25(01), pages 195-210, February.

    Cited by:

    1. Torben G. Andersen & Rasmus T. Varneskov, 2702. "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers 2018-09, Department of Economics and Business Economics, Aarhus University.

  15. Xiaofeng Shao, 2009. "Confidence intervals for spectral mean and ratio statistics," Biometrika, Biometrika Trust, vol. 96(1), pages 107-117.

    Cited by:

    1. Xiaofeng Shao, 2010. "A self-normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 343-366.

  16. Shao, Xiaofeng & Wu, Wei Biao, 2007. "Local Whittle Estimation Of Fractional Integration For Nonlinear Processes," Econometric Theory, Cambridge University Press, vol. 23(05), pages 899-929, October.

    Cited by:

    1. Hailin Sang & Yongli Sang, 2017. "Memory properties of transformations of linear processes," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 79-103, April.
    2. Zhongjun Qu, 2010. "A Test Against Spurious Long Memory," Boston University - Department of Economics - Working Papers Series WP2010-051, Boston University - Department of Economics.
    3. Luis Alberiko Gil-Alaña & Juan C. Cuestas & Estefania Mourelle, 2011. "Is there asymmetric behaviour in African inflation? A non-linear approach," NCID Working Papers 03/2011, Navarra Center for International Development, University of Navarra.
    4. Arteche, Josu & Orbe, Jesus, 2016. "A bootstrap approximation for the distribution of the Local Whittle estimator," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 645-660.
    5. La Spada Gabriele & Lillo Fabrizio, 2014. "The effect of round-off error on long memory processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(4), pages 1-38, September.
    6. Arteche, Josu & Orbe, Jesus, 2017. "A strategy for optimal bandwidth selection in Local Whittle estimation," Econometrics and Statistics, Elsevier, vol. 4(C), pages 3-17.
    7. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2011. "Fractional Integration and Cointegration in US Financial Time Series Data," Discussion Papers of DIW Berlin 1116, DIW Berlin, German Institute for Economic Research.
    8. de Menezes, Lilian M. & Houllier, Melanie A., 2015. "Germany's nuclear power plant closures and the integration of electricity markets in Europe," Energy Policy, Elsevier, vol. 85(C), pages 357-368.
    9. Shimotsu, Katsumi, 2010. "Exact Local Whittle Estimation of Fractionally Cointegrated Systems," Discussion Papers 2010-11, Graduate School of Economics, Hitotsubashi University.
    10. Lilian de Menezes & Melanie A. Houllier, 2013. "Modelling Germany´s Energy Transition and its Potential Effect on European Electricity Spot Markets," EcoMod2013 5395, EcoMod.

  17. Wu, Wei Biao & Shao, Xiaofeng, 2007. "A Limit Theorem For Quadratic Forms And Its Applications," Econometric Theory, Cambridge University Press, vol. 23(05), pages 930-951, October.

    Cited by:

    1. Zhongjun Qu, 2010. "A Test Against Spurious Long Memory," Boston University - Department of Economics - Working Papers Series WP2010-051, Boston University - Department of Economics.
    2. Atchadé, Yves F. & Cattaneo, Matias D., 2014. "A martingale decomposition for quadratic forms of Markov chains (with applications)," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 646-677.
    3. Jirak, Moritz, 2012. "Change-point analysis in increasing dimension," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 136-159.
    4. Chan, Ngai Hang & Zhang, Rong-Mao, 2013. "Limit theory of quadratic forms of long-memory linear processes with heavy-tailed GARCH innovations," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 18-33.
    5. Jirak, Moritz, 2013. "A Darling–Erdös type result for stationary ellipsoids," Stochastic Processes and their Applications, Elsevier, vol. 123(6), pages 1922-1946.
    6. Zhang, Rong-Mao & Sin, Chor-yiu (CY) & Ling, Shiqing, 2015. "On functional limits of short- and long-memory linear processes with GARCH(1,1) noises," Stochastic Processes and their Applications, Elsevier, vol. 125(2), pages 482-512.
    7. Kin Wai Chan & Chun Yip Yau, 2017. "High-order Corrected Estimator of Asymptotic Variance with Optimal Bandwidth," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 866-898, December.

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