Publications

del Barrio Castro, T., Escribano, A., Sibbertsen, P. (2024): Modeling and Forecasting the Long Memory of Cyclical Trends in Poleoclimate Data | File |

Dierkes, M., Fitter, K., Sibbertsen, P. (2024): Monitoring Breaks in Fractional Cointegration | File |

Kreye, T. J., Sibbertsen, P. (2024): Testing for a Forecast Accuracy Breakdown under Long Memory | File |

Toumping Fotso, C., Sibbertsen, P. (2024): Block Whittle Estimation of Time Varying Stochastic Regression Models with Long Memory | File |

Less, V. and Sibbertsen, P. (2022): Estimation and Testing in a Perturbed Multivariate Long Memory Framework | File |

Dissanayake, P., Amft, J., Sibbertsen, P. (2024): Defining an exposure index along the Schleswig-Holstein Baltic Sea coast, Marine Geology, Volume 476, 107382
DOI: https://doi.org/10.1016/j.margeo.2024.107382

Rodrigues, P. M. M., Sibbertsen, P. and Voges, M. (2024): The stability of government bond markets’ equilibrium and the interdependence of lending rates, Empirical Economics,  Empirical Economics, Volume 67, 2503–2538 More info
DOI: https://doi.org/10.1007/s00181-024-02623-x

Dräger, L., Kolaiti, T. and Sibbertsen, P. (2023): Measuring Macroeconomic Convergence and Divergence within EMU Using Long Memory,  Empirical Economics
DOI: https://doi.org/10.1007/s00181-023-02426-6

Niu, Z., Meier, J. and Briol, F.-X. (2023): Discrepancy-based inference for intractable generative models using Quasi-Monte Carlo,  Electronic Journal of Statistics, Vol. 17 (1), 1411-1456
DOI: https://doi.org/10.1214/23-EJS2131

Dierkes, M., Krupski, J., Schroen, S., Sibbertsen, P. (2023): Volatility-Dependent Probability Weighting and the Dynamics of the Pricing Kernel Puzzle,  Review of Derivatives Research
DOI: https://doi.org/10.1007/s11147-023-09197-3

Mboya, M. and Sibbertsen, P. (2023): Optimal Forecasts in the Presence of Discrete Structural Breaks under Long Memory,  Journal of Forecasting, Volume 42, Issue 7, 1889-1908
DOI: http://doi.org/10.1002/for.2988

Dissanayake, P., Brown, J., Sibbertsen, P., Winter, C. (2021): Using a two-step framework for the investigation of storm impacted beach/dune erosion, Coastal Engineering,  Coastal Engineering, Volume 168
DOI: https://doi.org/10.1016/j.coastaleng.2021.103939

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 groups,  Archives of Gynecology and Obstetrics, 304, 577–587
DOI: https://doi.org/10.1007/s00404-021-06082-y

Afzal, A. and Sibbertsen, P. (2021): Modeling fractional cointegration between high and low stock prices in Asian countries,  Empirical 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 Model,  forthcoming in Oxford Bulletin of Economics and Statistics | File | More info

Dissanayake, P., Flock, T., Meier, J. and Sibbertsen, P. (2021): Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights,  Mathematics 2021, 9(21), 2817 More info

Voges, M. and Sibbertsen, P. (2021): Cyclical fractional cointegration,  Econometrics and Statistics, Volume 19, 114-129 More info
DOI: https://doi.org/10.1016/j.ecosta.2020.05.004

Voges, M. and Sibbertsen, P. (2021): Cyclical fractional cointegration,  Econometrics and Statistics, Volume 19, 114-129 More info
DOI: https://doi.org/10.1016/j.ecosta.2020.05.004

Leschinski, C., Voges, M. and Sibbertsen, P. (2021): A Comparison of Semiparametric Tests for Fractional Cointegration,  Statistical Papers 62, 1997–2030
DOI: https://doi.org/10.1007/s00362-020-01169-1

Leschinski, C., Voges, M. and Sibbertsen, P. (2021): Integration and Disintegration of EMU Government Bond Markets,  Econometrics 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-analysis,  Vaccine, Volume 38, Issue 41 | File |

Wingert, S., Mboya, M. and Sibbertsen, P. (2020): Distinguishing between Breaks in the Mean and Breaks in Persistence under Long Memory,  Economics Letters (forthcoming)

Stöver, B. (2020): The regional significance of university locations in Lower Saxony,  Raumforschung 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 Series,  Economics Letters, Volume 192, 109237
DOI: https://doi.org/10.1016/j.econlet.2020.109237

Wenger, K. and Leschinski, C. (2019): Fixed-Bandwidth CUSUM Tests Under Long Memory,  Econometrics and Statistics
DOI: 10.1016/j.ecosta.2019.08.001

Becker, J., Hollstein, F., Prokopczuk, M. and Sibbertsen, P. (2019): The Memory of Beta,  Journal of Banking and Finance, Volume 124, 106026
DOI: https://doi.org/10.2139/ssrn.3492931

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 Germany,  Annals of Operations Research 282, 407–426
DOI: https://doi.org/10.1007/s10479-019-03326-8

Leschinski, C., Sibbertsen, P. (2019): Model Order Selection in Seasonal/Cyclical Long Memory Models,  Econometrics and Statistics, 1, 78-94
DOI: https://doi.org/10.1016/j.ecosta.2017.11.002

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 experiment,  Educational 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 Developments,  Advances 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 series,  Journal of Open Source Software, 4(43), 1820
DOI: 10.21105/joss.01820

Kruse, R., Leschinski, C. and Will, M. (2018): Comparing predictive accuracy under long memory - with an application to volatility forecasting,  Journal of Financial Econometrics, Volume 17, Issue 2, Spring 2019, 180-228
DOI: https://doi.org/10.1093/jjfinec/nby011

Bodnar, T., Parolya, N., Schmid, W. (2018): Estimation of the global minimum variance portfolio in high dimensions,  European Journal of Operational Research, 1, 04/2018, 371-390 More info

Nguyen, D. B. B., Prokopczuk, M. and Sibbertsen, P. (2018): The Memory of Stock Return Volatility: Asset Pricing Implications,  Journal of Financial Markets (forthcoming)

Stöver, B. and Sibbertsen, P. (2018): Die räumliche Flexibilität von Studierenden - Gründe für das Wanderungsverhalten von Studienanfänger/-innen zwischen den Bundesländern,  Beiträge zur Hochschulforschung, 03/2018, Heft 3, 8-33 More info

Busch, M. and Sibbertsen, P. (2018): An Overview of Modified Semiparametric Memory Estimation Methods,  Econometrics, 6(1), 13 More info

Wenger, K., Leschinski, C. and Sibbertsen, P. (2018): The Memory of Volatility,  Quantitative Finance and Economics, 2(1), 137-159 More info

Sibbertsen, P., Leschinski, C., Busch, M. (2018): A Multivariate Test Against Spurious Long Memory,  Journal of Econometrics | File | More info

Wenger, K., Leschinski, C. and Sibbertsen, P. (2018): A Simple Test on Structural Change in Long-Memory Time Series,  Economics 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 savers,  Quantitative Finance, 04/2017, 1645-1653 More info

Leschinski, C. (2017): On the memory of products of long range dependent time series,  Economics Letters, 153, 04/2017, 72-76 More info

Leschinski, C. and Bertram, P. (2017): Time varying contagion in EMU government bond spreads,  Journal 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 Volatility,  Economics 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 matrix,  Journal 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 Matrix,  Journal of Multivariate Analysis 146, 04/2016, 223-236 More info

Rinke, S. and Sibbertsen, P. (2016): Information Criteria for Nonlinear Time Series Models,  Studies 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 Analysis,  Journal 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 Predictability,  European 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 Function,  Annals of Operations Research 229, 121-158 More info

Rohde, J. (2015): Downside Risk Measure Performance in the Presence of Breaks in Volatility,  Journal 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 Matrix,  Journal of Multivariate Analysis, 132, 215-228 More info

Kaufmann, H., Heinen, F., Sibbertsen, P. (2014): The dynamics of real exchange rates - A reconsideration,  Journal 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 Bonds,  Journal 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 correlations,  Statistical Papers, 54, 977 - 991 More info

Breitung, J., Kruse, R. (2013): When bubbles burst: Econometric tests based on structural breaks,  Statistical Papers, 54, 911 - 930 More info

Demetrescu, M. and R. Kruse (2013): The Power of Unit Root Tests Against Nonlinear Local Alternatives,  Journal 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-linearities,  In 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 model,  Journal 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 Theory,  European 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 trends,  Economics Letters, 117, 268 - 271 More info

Kruse, R., Frömmel, M. (2012): Testing for a rational bubble under long memory,  Quantitative 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 persistence,  Economics Letters, 114, 268 - 272 More info

Sibbertsen, P., Willert, J. (2012): Testing for a break in persistence under long-range dependencies and mean shifts,  Statistical Papers, 53, 357 - 370 More info

Davidson, J., Sibbertsen, P. (2009): Tests of Bias in Log-Periodogram Regression,  Economics Letters 102, 83-86 More info

Sibbertsen, P., Kruse, R. (2009): Testing for a break in persistence under long-range dependencies,  Journal of Time Series Analysis 30, 263 - 285 More info

Sibbertsen, P., Stahl, G., Luedtke, C. (2008): Measuring model risk,  Journal 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 process,  Journal of Time Series Analysis 28, 576 - 599 More info

Rothe, C., Sibbertsen, P. (2006): Phillips - Perron - type unit root tests in the nonlinear ESTAR framework,  Allgemeines Statistisches Archiv 90, 439 - 456 More info

Sibbertsen, P., Krämer, W. (2006): The Power of the KPSS - Test for Cointegration when Residuals are Fractionally Integrated,  Economics Letters 91, 321 - 324 More info

Davidson, J., Sibbertsen, P. (2005): Generating schemes for long memory processes,  Generating schemes for long memory processes More info

Halverscheid, S., Hiltawsky, K., Sibbertsen, P. (2004): SamstagsUni: Ein Konzept zwischen Schule, Lehrerbildung und Hochschule,  Zeitschrift für Hochschuldidaktik September 2004, 1 - 12 More info

Sibbertsen, P. (2004): Long memory in volatilities of German stock returns,  Empirical Economics 29, 477 - 488 More info

Sibbertsen, P. (2004): Long-memory versus structural change: An overview,  Statistical Papers 45, 465 - 515 More info

Beran, J., Ghosh, S., Sibbertsen, P. (2003): Nonparametric M-estimation with long-memory errors,  Journal 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 Memory,  Water Resources Research 39, 1132 - 1138 More info

Sibbertsen, P. (2003): Log-Periodogram estimation of the memory parameter of a long-memory process under trend,  Statistics 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 errors,  International Journal of Forecasting 18, 227 - 241 More info

Lohre, M., Sibbertsen, P. (2002): Persistenz und saisonale Abhängigkeiten in Abflüssen des Rheins,  Hydrology and Water Resources Management 46, 166 - 174

Krämer, W., Sibbertsen, P. (2002): Testing for structural change in the presence of long-memory,  International Journal of Business and Economics 1, 235 - 243

Krämer, W., Sibbertsen, P., Kleiber, C. (2002): Long Memory versus Structural Change in Financial Time Series,  Allgemeines Statistisches Archiv 86, 83 - 96

Sibbertsen, P. (2001): S-estimation in the linear regression model with long- memory error terms under trend,  Journal of Time Series Analysis 22, 353 - 363 More info

Otto, P. and Sibbertsen, P. (2024): Spatial Autoregressive Fractionally Integrated Moving Average Model,  Knoth, Okhrim, Otto: Advanced Statistical Methods in Process Monitoring, Finance and Environmental Science, Springer, New York, 449 – 466
DOI: 10.1007/978-3-031-69111-9_22

Voges, M., Leschinski, C. and Sibbertsen, P. (2018): Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks,  Advances in Applied Financial Econometrics More info

Bartelheimer, P., Drosdowski, T., Stöver, B., Tyrell, M. & Wolter, M. I. (2017): Das Potenzial für Teilhabe - Spielräume und Risiken,  Forschungsverbund 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 Szenarien,  Forschungsverbund 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 2030,  Forschungsverbund 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 Consumption,  Meade, 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 Framework,  Beran, Jan, Feng, Yuanhua and Hebbel, Hartmut: Empirical Economic and Financial Research - Theory, Methods and Practice, Springer, New York

Kaufmann, H., Kruse, R., Sibbertsen, P. (2014): A Simple procedures for specifying transition functions in persistent nonlinear time series models,  Recent 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 bootstrap,  Essays 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 Series,  In: 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 + Validierung,  In: 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 cointegration,  In: 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