An Alternative Bootstrap to Moving Blocks for Time Series Regression Models
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Paulo M. D. C. Parente & Richard J. Smith, 2021.
"Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
- Paulo M.D.C. Parente & Richard J. Smith, 2018. "Quasi-Maximum Likelihood and the Kernel Block Bootstrap for Nonlinear Dynamic Models," Working Papers REM 2018/59, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
- Paulo Parente & Richard J. Smith, 2019. "Quasi-maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," CeMMAP working papers CWP60/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Hidalgo, J., 2008. "Specification testing for regression models with dependent data," Journal of Econometrics, Elsevier, vol. 143(1), pages 143-165, March.
- Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
- George Kapetanios & Fotis Papailias, 2011. "Block Bootstrap and Long Memory," Working Papers 679, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios & Zacharias Psaradakis, 2006. "Sieve Bootstrap for Strongly Dependent Stationary Processes," Working Papers 552, Queen Mary University of London, School of Economics and Finance.
- Javier Hidalgo, 2007. "Specification Testing Forregression Models Withdependent Data," STICERD - Econometrics Paper Series 518, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- J. Hidalgo & M. Schafgans, 2020. "Inference without smoothing for large panels with cross-sectional and temporal dependence," Papers 2006.14409, arXiv.org.
- Javier Hidalgo & Marcia M Schafgans, 2015. "Inference and Testing Breaks in Large Dynamic Panels with Strong Cross Sectional Dependence," STICERD - Econometrics Paper Series /2015/583, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Hinich Melvin J & Mendes Eduardo M & Stone Lewi, 2005. "Detecting Nonlinearity in Time Series: Surrogate and Bootstrap Approaches," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-15, December.
- Hidalgo, Javier, 2007. "Specification testing for regression models with dependent data," LSE Research Online Documents on Economics 6799, London School of Economics and Political Science, LSE Library.
- 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.
- Hidalgo, Javier, 2009. "Goodness of fit for lattice processes," Journal of Econometrics, Elsevier, vol. 151(2), pages 113-128, August.
- Dalla, Violetta & Hidalgo, Javier, 2005. "A parametric bootstrap test for cycles," LSE Research Online Documents on Economics 6829, London School of Economics and Political Science, LSE Library.
- Johan Blomquist & Joakim Westerlund, 2016. "Panel bootstrap tests of slope homogeneity," Empirical Economics, Springer, vol. 50(4), pages 1359-1381, June.
- Lazarova, Stepana, 2005. "Testing for structural change in regression with long memory processes," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 329-372.
- Hidalgo, Javier & Schafgans, Marcia, 2021. "Inference without smoothing for large panels with cross-sectional and temporal dependence," LSE Research Online Documents on Economics 107426, London School of Economics and Political Science, LSE Library.
- George Kapetanios, 2004. "A Bootstrap Invariance Principle for Highly Nonstationary Long Memory Processes," Working Papers 507, Queen Mary University of London, School of Economics and Finance.
- Kirch Claudia, 2007. "Resampling in the frequency domain of time series to determine critical values for change-point tests," Statistics & Risk Modeling, De Gruyter, vol. 25(3), pages 237-261, July.
- Dalla, Violetta & Hidalgo, Javier, 2005. "A parametric bootstrap test for cycles," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 219-261.
- Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," LSE Research Online Documents on Economics 68839, London School of Economics and Political Science, LSE Library.
- repec:ehu:biltok:48980 is not listed on IDEAS
- Arteche, Josu & Orbe, Jesus, 2009. "Using the bootstrap for finite sample confidence intervals of the log periodogram regression," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1940-1953, April.
- Arteche, Josu, 2024. "Bootstrapping long memory time series: Application in low frequency estimators," Econometrics and Statistics, Elsevier, vol. 29(C), pages 1-15.
- George Kapetanios & Zacharias Psaradakis, 2006.
"Sieve Bootstrap for Strongly Dependent Stationary Processes,"
Working Papers
552, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios & Zacharias Psaradakis, 2006. "Sieve Bootstrap for Strongly Dependent Stationary Processes," Working Papers 552, Queen Mary University of London, School of Economics and Finance.
- Violetta Dalla & Javier Hidalgo, 2005. "A Parametric Bootstrap Test for Cycles," STICERD - Econometrics Paper Series 486, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- George Kapetanios & Fotis Papailias, 2011.
"Block Bootstrap and Long Memory,"
Working Papers
679, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios & Fotis Papailias, 2011. "Block Bootstrap and Long Memory," Working Papers 679, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios, 2004.
"A Bootstrap Invariance Principle for Highly Nonstationary Long Memory Processes,"
Working Papers
507, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios, 2004. "A Bootstrap Invariance Principle for Highly Nonstationary Long Memory Processes," Working Papers 507, Queen Mary University of London, School of Economics and Finance.
- Hidalgo, Javier & Schafgans, Marcia M. A., 2017. "Inference without smoothing for large panels with cross-sectional and temporal dependence," LSE Research Online Documents on Economics 87748, London School of Economics and Political Science, LSE Library.
- Gerolimetto, Margherita, 2006. "Frequency domain bootstrap for the fractional cointegration regression," Economics Letters, Elsevier, vol. 91(3), pages 389-394, June.
- Murphy, A. & Izzeldin, M., 2009.
"Bootstrapping long memory tests: Some Monte Carlo results,"
Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2325-2334, April.
- Anthony Murphy & M Izzeldin, 2006. "Bootstrapping long memory tests: some Monte Carlo results," Working Papers 574547, Lancaster University Management School, Economics Department.
- Javier Hidalgo & Marcia M Schafgans, 2017. "Inference Without Smoothing for Large Panels with Cross- Sectional and Temporal Dependence," STICERD - Econometrics Paper Series 597, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Hidalgo, Javier & Schafgans, Marcia, 2021. "Inference without smoothing for large panels with cross-sectional and temporal dependence," Journal of Econometrics, Elsevier, vol. 223(1), pages 125-160.
- Kim, Young Min & Nordman, Daniel J., 2013. "A frequency domain bootstrap for Whittle estimation under long-range dependence," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 405-420.
- Peter C. B. Phillips, 2021. "Pitfalls in Bootstrapping Spurious Regression," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 163-217, December.
- Guillermo Ferreira & Jorge Mateu & Jose A. Vilar & Joel Muñoz, 2021. "Bootstrapping regression models with locally stationary disturbances," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 341-363, June.
Printed from https://ideas.repec.org/r/cep/stiecm/452.html