• Less, V. and Sibbertsen, P. (2022): Estimation and Testing in a Perturbed Multivariate Long Memory Framework | File |
  • Mboya, M. and Sibbertsen, P. (2022): Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory | File |
  • Sibbertsen, P., Lampert, T., Müller, K. and Taktikos, M. (2021): Do algebraic numbers follow Khinchin's Law?Hannover Economic Paper 686 | File |
  • Stöver, B. and Sibbertsen, P. (2020): The similarities in efficiency of universities and universities of applied sciences in Lower SaxonyHannover Economic Papers, Nr. 673 | File |
  • Stöver, B. (2020): Gleich oder nicht gleich - Unterschiede und Gemeinsamkeiten von Fachhochschulen und UniversitätenHannover Economic Papers, Nr. 674 | File |
  • Dräger, L., Nguyen, D. B. B., Prokopczuk, M. and Sibbertsen, P. (2020): The Long Memory of Equity Volatility and the Macroeconomy: International Evidence | File |
  • Rodrigues, P. M. M., Sibbertsen, P. and Voges, M. (2019): Testing for breaks in the cointegrating relationship: On the stability of government bond markets' equilibriumHannover Economic Papers, Nr. 656. | File |
  • Stöver, B. (2019): Estimating the transition time from school to university using a stochastic mortality modelHannover Economic Papers, Nr. 657 | File |
  • Becker, J., Leschinski, C. and Sibbertsen, P. (2019): Robust Multivariate Local Whittle Estimation and Spurious Fractional CointegrationHannover Economic Papers, Nr. 660 | File |

Referierte Fachzeitschriften

  • Dissanayake, P., Brown, J., Sibbertsen, P., Winter, C. (2021): Using a two-step framework for the investigation of storm impacted beach/dune erosion, Coastal EngineeringCoastal Engineering, Volume 168
  • Kampers, J., Gerhardt, E., Sibbertsen, P., Flock, T., Klapdor, R., Hertel, H., Jentschke, M. and Hillemanns, P. (2021): Protective operative techniques in radical hysterectomy in early cervical carcinoma and their influence on disease-free and overall survival: a systematic review and meta-analysis of risk groupsArchives of Gynecology and Obstetrics, 304, 577–587
  • Afzal, A. and Sibbertsen, P. (2021): Modeling fractional cointegration between high and low stock prices in Asian countriesEmpirical Economics, 60 (2), 661 – 682 More Info
    DOI: 10.1007/s00181-019-01784-4
  • Bertram, P., Flock, T., Ma, J. and Sibbertsen, P. (2021): Real Exchange Rates and Fundamentals in a new Markov-STAR Modelforthcoming in Oxford Bulletin of Economics and Statistics | File | More Info
  • Dissanayake, P., Flock, T., Meier, J. und Sibbertsen, P. (2021): Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave HeightsMathematics 2021, 9(21), 2817 More Info
  • Voges, M. and Sibbertsen, P. (2021): Cyclical fractional cointegrationEconometrics and Statistics, Volume 19, 114-129 More Info
  • Voges, M. and Sibbertsen, P. (2021): Cyclical fractional cointegrationEconometrics and Statistics, Volume 19, 114-129 More Info
  • Leschinski, C., Voges, M. and Sibbertsen, P. (2021): A Comparison of Semiparametric Tests for Fractional CointegrationStatistical Papers 62, 1997–2030
  • Leschinski, C., Voges, M. and Sibbertsen, P. (2021): Integration and Disintegration of EMU Government Bond MarketsEconometrics 2021, 9(1), 13 More Info
    DOI: 10.3390/econometrics9010013
  • Jentschke, M., Kampers, J., Becker, J., Sibbertsen, P. and Hillemanns, P. (2020): Prophylactic HPV vaccination after conization: A systematic review and meta-analysisVaccine, Volume 38, Issue 41 | File |
    DOI: 10.1016/j.vaccine.2020.07.055
  • Wingert, S., Mboya, M. and Sibbertsen, P. (2020): Distinguishing between Breaks in the Mean and Breaks in Persistence under Long MemoryEconomics Letters, Volume 193, 109338 More Info
    DOI: 10.1016/j.econlet.2020.109338
  • Stöver, B. (2020): The regional significance of university locations in Lower SaxonyRaumforschung und Raumordnung / Spatial Research and Planning (published online ahead of print). More Info
  • Wenger, K. and Less, V. (2020): A Modified Wilcoxon Test for Change Points in Long-Range Dependent Time SeriesEconomics Letters, Volume 192, 109237
  • Wenger, K. and Leschinski, C. (2019): Fixed-Bandwidth CUSUM Tests Under Long MemoryEconometrics and Statistics
    DOI: 10.1016/j.ecosta.2019.08.001
  • Wegener, C., Basse, T., Sibbertsen, P. and Nguyen, D. K. (2019): Liquidity Risk and the Covered Bond Market in Times of Crisis: Empirical Evidence from GermanyAnnals of Operations Research 282, 407–426
  • Leschinski, C., Sibbertsen, P. (2019): Model Order Selection in Seasonal/Cyclical Long Memory ModelsEconometrics and Statistics, 1, 78-94
  • Wenger, K., Fritzsch, B., Sibbertsen, P. and Ullmann, G. (2019): Can Google Trends improve Sales Forecasts on a Product Level?Applied Economics Letters, Volume 27, Issue 17
    DOI: 10.1080/13504851.2019.1686110
  • Stöver, B. (2019): The impact of a shortened schooling time on the transition from school to studies – empirical evidence from a natural experimentEducational Research and Evaluation, 25:3-4, 179-202
    DOI: 10.1080/13803611.2019.1683043
  • Wenger, K., Leschinski, C. and Sibbertsen, P. (2019): Change-in-Mean Tests in Long-memory Time Series: A Review of Recent DevelopmentsAdvances in Statistical Analysis, 103, 02/2019, 237-256. More Info
  • Wenger, K. and Becker, J. (2019): An R package for estimation procedures and tests for persistent time seriesJournal of Open Source Software, 4(43), 1820
    DOI: 10.21105/joss.01820
  • Becker, J., Hollstein, F., Prokopczuk, M. and Sibbertsen, P. (2019): The Memory of BetaJournal of Banking and Finance, Volume 124, 106026
  • Kruse, R., Leschinski, C. and Will, M. (2018): Comparing predictive accuracy under long memory - with an application to volatility forecastingJournal of Financial Econometrics, Volume 17, Issue 2, Spring 2019, 180-228
  • Bodnar, T., Parolya, N., Schmid, W. (2018): Estimation of the global minimum variance portfolio in high dimensionsEuropean Journal of Operational Research, 1, 04/2018, 371-390 More Info
  • Nguyen, D. B. B., Prokopczuk, M. and Sibbertsen, P. (2020) (2018): The Memory of Stock Return Volatility: Asset Pricing ImplicationsJournal of Financial Markets, Volume 47, 100487 More Info
    DOI: 10.1016/j.finmar.2019.01.002
  • Stöver, B. and Sibbertsen, P. (2018): Die räumliche Flexibilität von Studierenden - Gründe für das Wanderungsverhalten von Studienanfänger/-innen zwischen den BundesländernBeiträge zur Hochschulforschung, 03/2018, Heft 3, 8-33 More Info
  • Busch, M. and Sibbertsen, P. (2018): An Overview of Modified Semiparametric Memory Estimation MethodsEconometrics, 6(1), 13 More Info
    DOI: 10.3390/econometrics6010013
  • Wenger, K., Leschinski, C. and Sibbertsen, P. (2018): The Memory of VolatilityQuantitative Finance and Economics, 2(1), 137-159 More Info
  • Sibbertsen, P., Leschinski, C., Busch, M. (2018): A Multivariate Test Against Spurious Long MemoryJournal of Econometrics | File | More Info
  • Wenger, K., Leschinski, C. and Sibbertsen, P. (2018): A Simple Test on Structural Change in Long-Memory Time SeriesEconomics Letters, 163, 02/2018, 90-94 More Info
  • Golosnoy, V., Parolya, N. (2017): "To have what they are having": portfolio choice for mimicking mean-variance saversQuantitative Finance, 04/2017, 1645-1653 More Info
  • Leschinski, C. (2017): On the memory of products of long range dependent time seriesEconomics Letters, 153, 04/2017, 72-76 More Info
  • Leschinski, C. and Bertram, P. (2017): Time varying contagion in EMU government bond spreadsJournal of Financial Stability, 29, 04/2017, 72-91 More Info
  • Demetrescu, M., Sibbertsen, P. (2016): Inference on the Long-Memory Properties of Time Series with Non-Stationary VolatilityEconomics Letters, 144, 07/2016, 80-84 More Info
  • Bodnar, T., Dette, H., Parolya, N. (2016): Spectral analysis of the Moore-Penrose inverse of a large dimensional sample covariance matrixJournal of Multivariate Analysis 148, 06/2016, 160-172 More Info
  • Bodnar, T., Gupta, A.K., Parolya, N. (2016): Direct Shrinkage Estimation of Large Dimensional Precision MatrixJournal of Multivariate Analysis 146, 04/2016, 223-236 More Info
  • Rinke, S. and Sibbertsen, P. (2016): Information Criteria for Nonlinear Time Series ModelsStudies of Nonlinear Dynamics and Econometrics, 20(3), 325–341 More Info
  • Bertram, P., Sibbertsen, P., Stahl, G. (2015): About the impact of Model Risk on Capital Reserves: A Quantitative AnalysisJournal of Risk, 17, 69-97 More Info
  • Bodnar, T., Parolya, N., Schmid, W. (2015): On the Exact Solution of the Multi-Period Portfolio Choice Problem for an Exponential Utility under Return PredictabilityEuropean Journal of Operational Research 246, 528-542 More Info
  • Bodnar, T., Parolya, N., Schmid, W. (2015): A Closed-Form Solution of the Multi-Period Portfolio Choice Problem for a Quadratic Utility FunctionAnnals of Operations Research 229, 121-158 More Info
  • Rohde, J. (2015): Downside Risk Measure Performance in the Presence of Breaks in VolatilityJournal of Risk Model Validation, 9(4)
  • Bodnar, T., Gupta, A.K., Parolya, N. (2014): On the Strong Convergence of the Optimal Linear Shrinkage Estimator for the Large Dimensional Covariance MatrixJournal of Multivariate Analysis, 132, 215-228 More Info
  • Kaufmann, H., Heinen, F., Sibbertsen, P. (2014): The dynamics of real exchange rates - A reconsiderationJournal of Applied Econometrics, 29, 758 - 773 More Info
  • Sibbertsen, P., Wegener, C. and Basse, T. (2014): Testing for a Break in the Persistence in Yield Spreads of EMU Government BondsJournal of Banking and Finance, 41, 109 - 118 More Info
  • Bertram, P., Kruse, R. and Sibbertsen, P. (2013): Fractional integration versus level shifts: the case of realized correlationsStatistical Papers, 54, 977 - 991 More Info
  • Breitung, J., Kruse, R. (2013): When bubbles burst: Econometric tests based on structural breaksStatistical Papers, 54, 911 - 930 More Info
  • Demetrescu, M. and R. Kruse (2013): The Power of Unit Root Tests Against Nonlinear Local AlternativesJournal of Time Series Analysis, 34, 40 - 61 More Info
  • Haldrup, N., Kruse, R., Teräsvirta, T. and R.T. Varneskov (2013): Unit roots, structural breaks, and non-linearitiesIn N. Hashimzade and M. Thornton, Eds., Handbook on Empirical Macroeconomics. Handbook of Research Methods and Applications series, Edward Elgar Publishing Ltd., 61 - 94 | File |
  • Heinen, F., Michael, S. and Sibbertsen, P. (2013): Weak identification in the ESTAR model and a new modelJournal of Time Series Analysis, 34, 238 - 261 More Info
  • Bodnar, T., Parolya, N., Schmid, W. (2013): On the Equivalence of Quadratic Optimization Problems Commonly Used in Portfolio TheoryEuropean Journal of Operational Research, 229, 637-644 More Info
  • Kaufmann H., Kruse R. and Sibbertsen P. (2012): On tests for linearity against STAR models with deterministic trendsEconomics Letters, 117, 268 - 271 More Info
  • Kruse, R., Frömmel, M. (2012): Testing for a rational bubble under long memoryQuantitative Finance, 12, 1723 - 1732 More Info
  • Kruse, R., Frömmel, M., Menkhoff, L., Sibbertsen, P. (2012): What do we know about real exchange rate non-linearities?Empirical Economics, 43, 457 - 474 More Info
  • Kruse, R., Sibbertsen, P. (2012): Long memory and changing persistenceEconomics Letters, 114, 268 - 272 More Info
  • Sibbertsen, P., Willert, J. (2012): Testing for a break in persistence under long-range dependencies and mean shiftsStatistical Papers, 53, 357 - 370 More Info
  • Davidson, J., Sibbertsen, P. (2009): Tests of Bias in Log-Periodogram RegressionEconomics Letters 102, 83-86 More Info
  • Sibbertsen, P., Kruse, R. (2009): Testing for a break in persistence under long-range dependenciesJournal of Time Series Analysis 30, 263 - 285 More Info
  • Sibbertsen, P., Stahl, G., Luedtke, C. (2008): Measuring model riskJournal of Risk Model Validation 2, 65 - 81 More Info
  • Nordman, D., Sibbertsen, P., Lahiri, S. N. (2007): Empirical likelihood confidence intervals for the mean of a long-range dependent processJournal of Time Series Analysis 28, 576 - 599 More Info
  • Rothe, C., Sibbertsen, P. (2006): Phillips - Perron - type unit root tests in the nonlinear ESTAR frameworkAllgemeines Statistisches Archiv 90, 439 - 456 More Info
  • Sibbertsen, P., Krämer, W. (2006): The Power of the KPSS - Test for Cointegration when Residuals are Fractionally IntegratedEconomics Letters 91, 321 - 324 More Info
  • Davidson, J., Sibbertsen, P. (2005): Generating schemes for long memory processesGenerating schemes for long memory processes More Info
  • Halverscheid, S., Hiltawsky, K., Sibbertsen, P. (2004): SamstagsUni: Ein Konzept zwischen Schule, Lehrerbildung und HochschuleZeitschrift für Hochschuldidaktik September 2004, 1 - 12 More Info
  • Sibbertsen, P. (2004): Long memory in volatilities of German stock returnsEmpirical Economics 29, 477 - 488 More Info
  • Sibbertsen, P. (2004): Long-memory versus structural change: An overviewStatistical Papers 45, 465 - 515 More Info
  • Beran, J., Ghosh, S., Sibbertsen, P. (2003): Nonparametric M-estimation with long-memory errorsJournal of Statistical Planning and Inference 117, 199 - 206 More Info
  • Lohre, M., Sibbertsen, P., Könning, T. (2003): Modelling Water Flow of the Rhine River Using Seasonal Long MemoryWater Resources Research 39, 1132 - 1138 More Info
  • Sibbertsen, P. (2003): Log-Periodogram estimation of the memory parameter of a long-memory process under trendStatistics and Probability Letters 61, 261 - 268 More Info
  • Beran, J., Feng, Y., Ghosh, S., Sibbertsen, P. (2002): On robust local polynomial estimation with long-memory errorsInternational Journal of Forecasting 18, 227 - 241 More Info
  • Lohre, M., Sibbertsen, P. (2002): Persistenz und saisonale Abhängigkeiten in Abflüssen des RheinsHydrology and Water Resources Management 46, 166 - 174
  • Krämer, W., Sibbertsen, P. (2002): Testing for structural change in the presence of long-memoryInternational Journal of Business and Economics 1, 235 - 243
  • Krämer, W., Sibbertsen, P., Kleiber, C. (2002): Long Memory versus Structural Change in Financial Time SeriesAllgemeines Statistisches Archiv 86, 83 - 96
  • Sibbertsen, P. (2001): S-estimation in the linear regression model with long- memory error terms under trendJournal of Time Series Analysis 22, 353 - 363 More Info

Veröffentlichte Bücher und referierte Buchbeiträge

  • Voges, M., Leschinski, C. and Sibbertsen, P. (2018): Seasonal long memory in intraday volatility and trading volume of Dow Jones stocksAdvances in Applied Financial Econometrics More Info
  • Bartelheimer, P., Drosdowski, T., Stöver, B., Tyrell, M. & Wolter, M. I. (2017): Das Potenzial für Teilhabe - Spielräume und RisikenForschungsverbund Sozioökonomische Berichterstattung, (Hg.): Berichterstattung zur sozioökonomischen Entwicklung in Deutschland, wbv Open Access More Info
    DOI: 10.3278/6004498w001
  • Bieritz, L., Drosdowski, T., Stöver, B., Thobe, I. & Wolter, M. I. (2017): Konsumentwicklung bis 2030 nach Haushaltstypen und SzenarienForschungsverbund Sozioökonomische Berichterstattung, (Hg.): Berichterstattung zur sozioökonomischen Entwicklung in Deutschland, wbv Open Acces More Info
    DOI: 10.3278/6004498w017
  • Drosdowski, T., Mönnig, A., Stöver, B., Ulrich, P. & Wolter, M. I., Hänisch, C., Kalinowski, M. (2017): Gesamtwirtschaftliche Entwicklung 1991 bis 2030Forschungsverbund Sozioökonomische Berichterstattung, (Hg.): Berichterstattung zur sozioökonomischen Entwicklung in Deutschland, wbv Open Access
    DOI: 10.3278/6004498w004
  • Stöver, B. & Wolter, M. I. (2015): Demographic Change and Consumption - How Ageing Affects the Level and Structure of Private ConsumptionMeade, D.S. (ed): In Quest of the Craft - Economic Modeling for the 21st Century, Firenze University Press, 195-209
  • Grote, C., Sibbertsen, P. (2014): Testing for Cointegration in a Double-LSTR FrameworkBeran, Jan, Feng, Yuanhua and Hebbel, Hartmut: Empirical Economic and Financial Research - Theory, Methods and Practice, Springer, New York More Info
  • Kaufmann, H., Kruse, R., Sibbertsen, P. (2014): A Simple procedures for specifying transition functions in persistent nonlinear time series modelsRecent Advances in Estimating Nonlinear Models, Springer, New York, 2014, XVI, 169 - 191. More Info
  • Kruse, R., Sandberg, R. (2013): Linearity testing for trending data with an application of the wild bootstrapEssays in Nonlinear Time Series Econometrics: A Festschrift for Timo Teräsvirta, edited by Mika Meitz, Pentti Saikkonen and Niels Haldrup, Oxford University Press. More Info
  • Luedtke, C. , Sibbertsen, P. (2010): Model Risk in GARCH-Type Financial Time SeriesIn: Model Risk, Identification, Measurement and Management, D. Rösch and H. Schedule (editors), Risk books, 75 – 89.
  • Stahl, G., Sibbertsen, P., Bertram, P. (2010): Modellrisiko = Spezifikation + ValidierungIn: Handbuch Solvency II, C. Bennemann, L. Oehlenberg, and G. Stahl (editors), Schäffer-Poeschel-Verlag.
  • Peters, A., Sibbertsen, P. (2002): Tests on Fractional Cointegration. Comparison of a finite M- and ML-test on fractional cointegrationIn: Developments in Robust Statistics. Editors: R. Dutter, U. Gather, P. J. Rousseeuw and P. Filzmoser, 306 - 315.
  • Sibbertsen, P. (1999): Robuste Parameterschätzung im linearen Regressionsmodell.Verlag für Wissenschaft und Forschung, Berlin.
    ISBN: 978-3897000926