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Rolf Tschernig

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Harry Haupt & Joachim Schnurbus & Rolf Tschernig, 2010. "On nonparametric estimation of a hedonic price function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 894-901.

    Mentioned in:

    1. On nonparametric estimation of a hedonic price function (Journal of Applied Econometrics 2010) in ReplicationWiki ()

Working papers

  1. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.

    Cited by:

    1. Tobias Hartl, 2021. "Monitoring the pandemic: A fractional filter for the COVID-19 contact rate," Papers 2102.10067, arXiv.org.
    2. Hartl, Tobias, 2021. "Monitoring the pandemic: A fractional filter for the COVID-19 contact rate," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242380, Verein für Socialpolitik / German Economic Association.

  2. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2013. "Fractionally Integrated VAR Models with a Fractional Lag Operator and Deterministic Trends: Finite Sample Identification and Two-step Estimation," University of Regensburg Working Papers in Business, Economics and Management Information Systems 471, University of Regensburg, Department of Economics.

    Cited by:

    1. Federico Carlini & Paolo Santucci de Magistris, 2013. "On the identification of fractionally cointegrated VAR models with the F(d) condition," CREATES Research Papers 2013-44, Department of Economics and Business Economics, Aarhus University.
    2. Mishra, Tapas & Park, Donghyun & Parhi, Mamata & Uddin, Gazi Salah & Tian, Shu, 2023. "A memory in the bond: Green bond and sectoral investment interdependence in a fractionally cointegrated VAR framework," Energy Economics, Elsevier, vol. 121(C).
    3. Tobias Hartl, 2021. "Monitoring the pandemic: A fractional filter for the COVID-19 contact rate," Papers 2102.10067, arXiv.org.
    4. Hartl, Tobias, 2021. "Monitoring the pandemic: A fractional filter for the COVID-19 contact rate," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242380, Verein für Socialpolitik / German Economic Association.

  3. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2013. "Long- versus medium-run identification in fractionally integrated VAR models," University of Regensburg Working Papers in Business, Economics and Management Information Systems 476, University of Regensburg, Department of Economics.

    Cited by:

    1. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2014. "Long- versus medium-run identification in fractionally integrated VAR models," University of Regensburg Working Papers in Business, Economics and Management Information Systems 122, University of Regensburg, Department of Economics.
    2. Contreras-Reyes, Javier E., 2022. "Rényi entropy and divergence for VARFIMA processes based on characteristic and impulse response functions," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    3. Salisu, Afees A. & Ndako, Umar B. & Adediran, Idris A. & Swaray, Raymond, 2020. "A fractional cointegration VAR analysis of Islamic stocks: A global perspective," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

  4. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2010. "Long-run Identification in a Fractionally Integrated System," University of Regensburg Working Papers in Business, Economics and Management Information Systems 447, University of Regensburg, Department of Economics.

    Cited by:

    1. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
    2. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends in unobserved components models," Papers 2005.03988, arXiv.org, revised May 2020.
    3. Søren Johansen & Morten Ørregaard Nielsen, 2012. "The role of initial values in nonstationary fractional time series models," Discussion Papers 12-18, University of Copenhagen. Department of Economics.
    4. Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
    5. Lovcha, Yuliya & Pérez Laborda, Àlex, 2013. "Hours worked - Productivity puzzle: identification in fractional integration settings," Working Papers 2072/211796, Universitat Rovira i Virgili, Department of Economics.
    6. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2014. "Long- versus medium-run identification in fractionally integrated VAR models," University of Regensburg Working Papers in Business, Economics and Management Information Systems 122, University of Regensburg, Department of Economics.
    7. Ross Doppelt & Keith O'Hara, 2018. "Bayesian Estimation of Fractionally Integrated Vector Autoregressions and an Application to Identified Technology Shocks," 2018 Meeting Papers 1212, Society for Economic Dynamics.
    8. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    9. Morten Ø. Nielsen & S Johansen, 2012. "The Role Of Initial Values In Conditional Sum-of-squares Estimation Of Nonstationary Fractional Time Series Models," Working Paper 1300, Economics Department, Queen's University.
    10. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "Structural shocks and dinamic elasticities in a long memory model of the US gasoline retail market," Working Papers 2072/261538, Universitat Rovira i Virgili, Department of Economics.
    11. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," Discussion Papers 19/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    12. Tobias Hartl, 2020. "Macroeconomic Forecasting with Fractional Factor Models," Papers 2005.04897, arXiv.org.
    13. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," CREATES Research Papers 2019-02, Department of Economics and Business Economics, Aarhus University.

  5. Schotman, Peter & Tschernig, Rolf & Budek, Jan, 2008. "Long Memory and the Term Structure of Risk," University of Regensburg Working Papers in Business, Economics and Management Information Systems 427, University of Regensburg, Department of Economics.

    Cited by:

    1. Gil-Alana, Luis A. & Moreno, Antonio, 2012. "Uncovering the US term premium: An alternative route," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1181-1193.
    2. Daniela Osterrieder, 2013. "Interest Rates with Long Memory: A Generalized Affine Term-Structure Model," CREATES Research Papers 2013-17, Department of Economics and Business Economics, Aarhus University.
    3. Guglielmo Maria Caporale & Luis A. Gil-Alana & Carlos Poza, 2021. "The Covid-19 Pandemic and the Degree of Persistence of US Stock Prices and Bond Yields," CESifo Working Paper Series 8976, CESifo.
    4. Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
    5. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2014. "Long- versus medium-run identification in fractionally integrated VAR models," University of Regensburg Working Papers in Business, Economics and Management Information Systems 122, University of Regensburg, Department of Economics.
    6. Daniela Osterrieder & Peter C. Schotman, 2012. "The Volatility of Long-term Bond Returns: Persistent Interest Shocks and Time-varying Risk Premiums," CREATES Research Papers 2012-35, Department of Economics and Business Economics, Aarhus University.
    7. Ľuboš Pástor & Robert F. Stambaugh, 2012. "Are Stocks Really Less Volatile in the Long Run?," Journal of Finance, American Finance Association, vol. 67(2), pages 431-478, April.
    8. Carlo A. Favero & Andrea Tamoni, 2010. "Demographics and the Econometrics of the Term Structure of Stock Market Risk," Working Papers 367, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Todea, Alexandru, 2016. "Cross-correlations between volatility, volatility persistence and stock market integration: the case of emergent stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 208-215.
    10. Chevillon, Guillaume & Mavroeidis, Sophocles, 2018. "Perpetual learning and apparent long memory," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 343-365.
    11. Gündüz, Yalin & Kaya, Orcun, 2014. "Impacts of the financial crisis on eurozone sovereign CDS spreads," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 425-442.

  6. Haupt, Harry & Schnurbus, Joachim & Tschernig, Rolf, 2008. "On Nonparametric Estimation of a Hedonic Price Function," University of Regensburg Working Papers in Business, Economics and Management Information Systems 429, University of Regensburg, Department of Economics.

    Cited by:

    1. Fritsch, Markus & Haupt, Harry & Ng, Pin T., 2016. "Urban house price surfaces near a World Heritage Site: Modeling conditional price and spatial heterogeneity," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 260-275.
    2. Gaetano Lisi, 2013. "On the Functional Form of the Hedonic Price Function: A Matching-theoretic Model and Empirical Evidence," International Real Estate Review, Global Social Science Institute, vol. 16(2), pages 189-207.
    3. Schulz, Rainer & Wersing, Martin & Werwatz, Axel, 2013. "Automated valuation modelling: A specification exercise," SFB 649 Discussion Papers 2013-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Simlai, Prodosh, 2014. "Estimation of variance of housing prices using spatial conditional heteroskedasticity (SARCH) model with an application to Boston housing price data," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 17-30.
    5. Jens Kolbe & Rainer Schulz & Martin Wersing & Axel Werwatz, 2021. "Real estate listings and their usefulness for hedonic regressions," Empirical Economics, Springer, vol. 61(6), pages 3239-3269, December.
    6. Hyung-Gun Kim & Kwong-Chin Hung & Sung Park, 2015. "Determinants of Housing Prices in Hong Kong: A Box-Cox Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(2), pages 270-287, February.
    7. Mauro Iacobini & Gaetano Lisi, 2016. "Prezzi edonici delle caratteristiche abitative e analisi di regressione multipla: suggerimenti pratici per la stima," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(2), pages 5-42.
    8. Alice Barreca & Rocco Curto & Diana Rolando, 2020. "Urban Vibrancy: An Emerging Factor that Spatially Influences the Real Estate Market," Sustainability, MDPI, vol. 12(1), pages 1-23, January.
    9. Gaetano Lisi & Mauro Iacobini, 2013. "Real estate appraisals, hedonic models and the measurement of house price dispersion," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(1), pages 61-73.
    10. Yu, Peiyong, 2015. "The Effect of Eminent Domain on Private and Mixed Development on Property Values," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 45(2).
    11. Lerbs, Oliver & Sebastian, Steffen P., . "Mietspiegel aus ökonomischer Sicht – Vorschläge für eine Neuregulierung," Beiträge zur Immobilienwirtschaft, University of Regensburg, Department of Economics, number 10, August.
    12. Gaetano Lisi, 2019. "Hedonic pricing models and residual house price volatility," Letters in Spatial and Resource Sciences, Springer, vol. 12(2), pages 133-142, August.
    13. Sebastian Steffen & Lerbs Oliver, 2016. "Mietspiegel aus ökonomischer Sicht – Vorschläge für eine Neuregulierung," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 17(4), pages 347-363, December.
    14. Lisi, Gaetano, 2012. "On the theoretical derivation of a functional form for the hedonic price function," MPRA Paper 37066, University Library of Munich, Germany.
    15. Jeffrey S. Racine & Christopher F. Parmeter, 2012. "Data-Driven Model Evaluation: A Test for Revealed Performance," Department of Economics Working Papers 2012-13, McMaster University.
    16. Vijverberg, Wim P. & Hasebe, Takuya, 2015. "GTL Regression: A Linear Model with Skewed and Thick-Tailed Disturbances," IZA Discussion Papers 8898, Institute of Labor Economics (IZA).

  7. Rolf Tschernig & Lijian Yang, 2000. "Nonparametric Estimation of Generalized Impulse Response Functions," Econometric Society World Congress 2000 Contributed Papers 1417, Econometric Society.

    Cited by:

    1. Mototsugu Shintani, 2006. "A nonparametric measure of convergence towards purchasing power parity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 589-604.
    2. Mototsugu Shintani, 2006. "A nonparametric measure of convergence towards purchasing power parity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 589-604, July.
    3. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.

  8. Härdle, Wolfgang & Tschernig, Rolf, 2000. "Flexible time series analysis," SFB 373 Discussion Papers 2000,51, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Härdle, Wolfgang Karl & Chen, Ying & Schulz, Rainer, 2004. "Prognose mit nichtparametrischen Verfahren," Papers 2004,07, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

  9. Härdle, Wolfgang & Kleinow, Torsten & Tschernig, Rolf, 2000. "Web quantlets for time series analysis," SFB 373 Discussion Papers 2000,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Aydınlı, Gökhan & Härdle, Wolfgang Karl & Neuwirth, E., 2003. "Computational Statistics with Spreadsheets Towards Efficiency, Reproducibility and Security," SFB 373 Discussion Papers 2003,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Aydınlı, Gökhan & Härdle, Wolfgang Karl & Rönz, Bernd, 2003. "E-learning, e-teaching of statistics: A new challenge," SFB 373 Discussion Papers 2003,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Rönz, Bernd, 2001. "MM*Stat - a multimedia tool for teaching of statistics," SFB 373 Discussion Papers 2001,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.
    5. Kleinow, Torsten & Lehmann, Heiko, 2002. "Client/server based statistical computing," SFB 373 Discussion Papers 2002,49, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Härdle, Wolfgang & Rönz, Bernd, 2002. "E-learning / e-teaching of statistics: Students' and teachers' views," SFB 373 Discussion Papers 2002,84, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Härdle, Wolfgang & Lehmann, Heiko & Rönz, Bernd, 2001. "MM*STAT: Eine interaktive Einführung in die Welt der Statistik," SFB 373 Discussion Papers 2001,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  10. Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 296, Stockholm School of Economics, revised 06 Apr 2000.

    Cited by:

    1. Marcelo C. Medeiros & Alvaro Veiga, 2003. "Diagnostic Checking in a Flexible Nonlinear Time Series Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 461-482, July.
    2. Marcelo Cunha Medeiros & Álvaro Veiga & Carlos Eduardo Pedreira, 2000. "Modelling exchange rates: smooth transitions, neural networks, and linear models," Textos para discussão 432, Department of Economics PUC-Rio (Brazil).
    3. Marie Lebreton & Katia Melnik, 2009. "Voluntary Participation as a Determinant of Social Capital in France : Allowing for Parameter Heterogeneity," Working Papers halshs-00410530, HAL.
    4. Eduardo Mendes & Alvaro Veiga & MArcelo Cunha Medeiros, 2007. "Estimation And Asymptotic Theory For A New Class Of Mixture Models," Textos para discussão 538, Department of Economics PUC-Rio (Brazil).
    5. Henrik Amilon, 2003. "A neural network versus Black-Scholes: a comparison of pricing and hedging performances," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 317-335.
    6. Barrera, Carlos R., 2010. "Redes neuronales para predecir el tipo de cambio diario," Working Papers 2010-001, Banco Central de Reserva del Perú.
    7. Lebreton, Marie, 2005. "The NCSTAR model as an alternative to the GWR model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 77-84.
    8. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
    9. Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
    10. Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
    11. Anne Péguin-Feissolle & Birgit Strikholm & Timo Teräsvirta, 2008. "Testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form," CREATES Research Papers 2008-19, Department of Economics and Business Economics, Aarhus University.
    12. Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003. "Local-global neural networks: a new approach for nonlinear time series modelling," Textos para discussão 470, Department of Economics PUC-Rio (Brazil).
    13. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
    14. Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 29 Apr 2004.
    15. Marcelo C. Medeiros & Eduardo F. Mendes, 2012. "Estimating High-Dimensional Time Series Models," CREATES Research Papers 2012-37, Department of Economics and Business Economics, Aarhus University.
    16. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    17. Leila Ali & Marie Lebreton, 2013. "The Fall of Bretton Woods: Which Geography Matters?," Economics Bulletin, AccessEcon, vol. 33(2), pages 1396-1419.

  11. Yang, L. & Tschernig, R., 1998. "Non- and Semiparametric Identification of Seasonal Nonlinear Autoregression Models," SFB 373 Discussion Papers 1998,114, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom [A nonparametric prediction test of the France Telecom stock proces]," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.
    2. Yang, Lijian & Park, Byeong U. & Xue, Lan & Hardle, Wolfgang, 2006. "Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1212-1227, September.
    3. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    4. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    5. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    6. CHIKHI, Mohamed, 2009. "Identification non paramétrique d’un processus non linéaire hétéroscédastique [Nonparametric identification of heteroscedastic nonlinear process]," MPRA Paper 82108, University Library of Munich, Germany, revised 2009.
    7. Tang, Ling & Yu, Lean & He, Kaijian, 2014. "A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 128(C), pages 1-14.
    8. Mohamed Chikhi & Ali Bendob, 2018. "Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 105-120.

  12. Profit, Stefan & Tschernig, Rolf, 1998. "Germany's labor market problems: What to do and what not to do? A survey among experts," SFB 373 Discussion Papers 1998,94, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Michael Reutter, 2000. "Hysteresis in West German Unemployment Reconsidered," CESifo Working Paper Series 240, CESifo.

  13. Tschernig, Rolf & Yang, Lijian, 1997. "Nonparametric lag selection for time series," SFB 373 Discussion Papers 1997,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Su, Liangjun & White, Halbert, 2003. "A Consistent Characteristic-Function-Based Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt4dv0837f, Department of Economics, UC San Diego.
    2. Yang, Lijian & Härdle, Wolfgang & Nielsen, Jens P., 1998. "Nonparametric autoregression with multiplicative volatility and additive mean," SFB 373 Discussion Papers 1998,107, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom [A nonparametric prediction test of the France Telecom stock proces]," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.
    4. Rolf Tschernig & Lijian Yang, 2000. "Nonparametric Estimation of Generalized Impulse Response Functions," Econometric Society World Congress 2000 Contributed Papers 1417, Econometric Society.
    5. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.
    6. Mohamed Chikhi & Claude Diebolt, 2006. "Nonparametric Analysis of Financial Time Series by the Kernel Methodology," Working Papers 06-11, Association Française de Cliométrie (AFC).
    7. Stanislav Anatolyev, 2009. "Nonparametric regression (in Russian)," Quantile, Quantile, issue 7, pages 37-52, September.
    8. Diks, C.G.H. & Manzan, S., 2001. "Tests for serial independence and linearity based on correlation integrals," CeNDEF Working Papers 01-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    9. Stanislav Anatolyev, 2005. "Optimal Instruments in Time Series: A Survey," Working Papers w0069, Center for Economic and Financial Research (CEFIR).
    10. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    11. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    12. Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
    13. Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Levine's Bibliography 122247000000000621, UCLA Department of Economics.
    14. Inés Barbeito & Ricardo Cao & Stefan Sperlich, 2023. "Bandwidth selection for statistical matching and prediction," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 418-446, March.
    15. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    16. Cai, Zongwu, 2003. "Trending Time-Varying Coefficient Models With Serially Correlated Errors," SFB 373 Discussion Papers 2003,7, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    17. Giancarlo Bruno, 2008. "Forecasting Using Functional Coefficients Autoregressive Models," ISAE Working Papers 98, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    18. Shafik, Nivien & Tutz, Gerhard, 2009. "Boosting nonlinear additive autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2453-2464, May.
    19. Sami MESTIRI, 2022. "Modeling the volatility of Bitcoin returns using Nonparametric GARCH models," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 13(1), pages 2-16, June.
    20. Manzan, S., 2002. "Model Selection for Nonlinear Time Series," CeNDEF Working Papers 02-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    21. Cees Diks & Sebastiano Manzan, 2001. "Tests for Serial Independence and Linearity based on Correlation Integrals," Tinbergen Institute Discussion Papers 01-085/1, Tinbergen Institute.
    22. Nikolay Robinzonov & Gerhard Tutz & Torsten Hothorn, 2012. "Boosting techniques for nonlinear time series models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 99-122, January.
    23. Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 296, Stockholm School of Economics, revised 06 Apr 2000.
    24. Guo, Zheng-Feng & Shintani, Mototsugu, 2011. "Nonparametric lag selection for nonlinear additive autoregressive models," Economics Letters, Elsevier, vol. 111(2), pages 131-134, May.
    25. Chevallier, Julien, 2011. "Nonparametric modeling of carbon prices," Energy Economics, Elsevier, vol. 33(6), pages 1267-1282.
    26. Mohamed Chikhi & Ali Bendob, 2018. "Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 105-120.
    27. Miao Yang & Lan Xue & Lijian Yang, 2016. "Variable selection for additive model via cumulative ratios of empirical strengths total," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 595-616, September.
    28. Zhou, Yunzhe & Shi, Chengchun & Li, Lexin & Yao, Qiwei, 2023. "Testing for the Markov property in time series via deep conditional generative learning," LSE Research Online Documents on Economics 119352, London School of Economics and Political Science, LSE Library.
    29. Yang, Lijian & Tschernig, Rolf, 1997. "Multivariate plug-in bandwidth for local linear regression," SFB 373 Discussion Papers 1997,99, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  14. Tschernig, R., 1996. "Nonlinearities in German Unemployment Rates: A Nonparametric Analysis," SFB 373 Discussion Papers 1996,45, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom [A nonparametric prediction test of the France Telecom stock proces]," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.
    2. Skalin, Joakim & Teräsvirta, Timo, 1998. "Modelling asymmetries and moving equilibria in unemployment rates," SSE/EFI Working Paper Series in Economics and Finance 262, Stockholm School of Economics, revised Jul 1999.
    3. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    4. CHIKHI, Mohamed, 2009. "Identification non paramétrique d’un processus non linéaire hétéroscédastique [Nonparametric identification of heteroscedastic nonlinear process]," MPRA Paper 82108, University Library of Munich, Germany, revised 2009.

  15. Schmidt, C. M. & Tschernig, R., 1995. "The Identification of Fractional ARIMA Models," SFB 373 Discussion Papers 1995,8, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Mark J. Jensen, 1997. "Using Wavelets to Obtain a Consistent Ordinary Least Squares Estimator of the Long Memory Parameter," Econometrics 9710002, University Library of Munich, Germany.
    2. Olan Henry, 2002. "Long memory in stock returns: some international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 725-729.
    3. Jensen, Mark J., 2000. "An alternative maximum likelihood estimator of long-memory processes using compactly supported wavelets," Journal of Economic Dynamics and Control, Elsevier, vol. 24(3), pages 361-387, March.

  16. Pfann, G. & Schotman, P. & Tschernig, R., 1994. "Nonlinear Interest Rate Dynamics and Implications for the Term Structure," SFB 373 Discussion Papers 1994,43, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Muhammad Yasir & Sitara Afzal & Khalid Latif & Ghulam Mujtaba Chaudhary & Nazish Yameen Malik & Farhan Shahzad & Oh-young Song, 2020. "An Efficient Deep Learning Based Model to Predict Interest Rate Using Twitter Sentiment," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    2. Dankenbring, Henning, 1998. "Volatility estimates of the short term interest rate with an application to German data," SFB 373 Discussion Papers 1998,96, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Markus Leippold & Liuren Wu, 2002. "Asset Pricing Under The Quadratic Class," Finance 0207015, University Library of Munich, Germany.
    4. Wolfgang Lemke & Theofanis Archontakis, 2008. "Bond pricing when the short-term interest rate follows a threshold process," Quantitative Finance, Taylor & Francis Journals, vol. 8(8), pages 811-822.
    5. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.
    6. LUBRANO, Michel, 2000. "Bayesian non-linear modellings of the short term US interest rate: the help of non-parametric tools," LIDAM Discussion Papers CORE 2000038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    8. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," PSE-Ecole d'économie de Paris (Postprint) halshs-00185373, HAL.
    9. Xiaoyang Zhuo & Olivier Menoukeu-Pamen, 2017. "Efficient Piecewise Trees For The Generalized Skew Vasicek Model With Discontinuous Drift," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
    10. Lubrano, Michel, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499, Juin-Sept.
    11. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
    12. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
    13. Tauchen, George E., 1995. "New Minimum Chi-Square Methods in Empirical Finance," Working Papers 95-42, Duke University, Department of Economics.
    14. Greg Tkacz, 2000. "Estimating the Fractional Order of Integration of Interest Rates Using a Wavelet OLS Estimator," Staff Working Papers 00-5, Bank of Canada.
    15. Benjamin M. Tabak, 2007. "Estimating the Fractional Order of Integration of Yields in the Brazilian Fixed Income Market," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 36(3), pages 231-246, November.
    16. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    17. John Barkoulas & Christopher F. Baum & Joseph Onochie, 1996. "Nonlinear Nonparametric Prediction of the 90-Day T-Bill Rate," Boston College Working Papers in Economics 320., Boston College Department of Economics.
    18. Breitung, Jörg, 1998. "Rank tests for nonlinear cointegration," SFB 373 Discussion Papers 1998,65, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    19. Michael Dueker & Martin Sola & Fabio Spagnolo, 2007. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Discussion Papers 5_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    20. Dominique Guegan, 2011. "Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison," Post-Print halshs-00185373, HAL.
    21. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
    22. Høg, Espen P. & Frederiksen, Per H., 2006. "The Fractional Ornstein-Uhlenbeck Process: Term Structure Theory and Application," Finance Research Group Working Papers F-2006-01, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    23. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    24. Goldman Elena & Nam Jouahn & Tsurumi Hiroki & Wang Jun, 2013. "Regimes and long memory in realized volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 521-549, December.
    25. Gil-Alana, Luis A., 2004. "Long memory in the U.S. interest rate," International Review of Financial Analysis, Elsevier, vol. 13(3), pages 265-276.
    26. Jin-Chuan Duan & Kris Jacobs, 2001. "Short and Long Memory in Equilibrium Interest Rate Dynamics," CIRANO Working Papers 2001s-22, CIRANO.
    27. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modeling Multivariate Interest Rates using Time-Varying Copulas and Reducible Stochastic Differential Equations," Working Papers halshs-00408014, HAL.
    28. Teresa Corzo Santamaría & Javier Gómez Biscarri, 2005. "Nonparametric estimation of convergence of interest rates: Effects on bond pricing," Spanish Economic Review, Springer;Spanish Economic Association, vol. 7(3), pages 167-190, September.
    29. Christopher S. Jones, 2003. "Nonlinear Mean Reversion in the Short-Term Interest Rate," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 793-843, July.
    30. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    31. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Economics Working Paper Archive at Hunter College 406, Hunter College Department of Economics, revised 2005.
    32. Barkoulas, John T. & Baum, Christopher F. & Onochie, Joseph, 1997. "A nonparametric investigation of the 90-day t-bill rate," Review of Financial Economics, Elsevier, vol. 6(2), pages 187-198.
    33. Yizhou Bai & Yongjin Wang & Haoyan Zhang & Xiaoyang Zhuo, 2022. "Bayesian Estimation of the Skew Ornstein-Uhlenbeck Process," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 479-527, August.
    34. Clements, Michael P. & Galvao, Ana Beatriz, 2004. "A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure," International Journal of Forecasting, Elsevier, vol. 20(2), pages 219-236.
    35. Petros Dellaportas & David G. T. Denison & Chris Holmes, 2007. "Flexible Threshold Models for Modelling Interest Rate Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 419-437.
    36. Singh, Tarlok, 2014. "On the regime-switching and asymmetric dynamics of economic growth in the OECD countries," Research in Economics, Elsevier, vol. 68(2), pages 169-192.
    37. Episcopos, Athanasios, 2000. "Further evidence on alternative continuous time models of the short-term interest rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(2), pages 199-212, June.
    38. Peter Martey Addo, 2014. "Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input," Papers 1407.7738, arXiv.org.
    39. Fabrizio Iacone, 2009. "A Semiparametric Analysis of the Term Structure of the US Interest Rates," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 475-490, August.
    40. Duan, Jin-Chuan & Jacobs, Kris, 2008. "Is long memory necessary? An empirical investigation of nonnegative interest rate processes," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 567-581, June.
    41. Jack Strauss & Mark E. Wohar, 2007. "Domestic‐Foreign Interest Rate Differentials: Near Unit Roots and Symmetric Threshold Models," Southern Economic Journal, John Wiley & Sons, vol. 73(3), pages 814-829, January.
    42. Shively, Philip A., 2005. "Threshold nonlinear interest rates," Economics Letters, Elsevier, vol. 88(3), pages 313-317, September.
    43. John Hatgioannides & Menelaos Karanasos & Marika Karanassou, 2004. "Modelling the Yield Curve: A Two Components Approach," Working Papers 519, Queen Mary University of London, School of Economics and Finance.
    44. Barry E. Jones & Travis D. Nesmith, 2006. "Linear cointegration of nonlinear time series with an application to interest rate dynamics," Finance and Economics Discussion Series 2007-03, Board of Governors of the Federal Reserve System (U.S.).
    45. Esben Hoeg & Per Frederiksen, 2006. "The Fractional OU Process: Term Structure Theory and Application," Computing in Economics and Finance 2006 194, Society for Computational Economics.
    46. Hans Dewachter, 1996. "Modelling interest rate volatility: Regime switches and level links," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 132(2), pages 236-258, September.
    47. Gil-Alana, Luis A., 2004. "Modelling the U.S. interest rate in terms of I(d) statistical models," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(4), pages 475-486, September.
    48. Zhu, Junjun & Xie, Shiyu, 2010. "Bayesian Analysis of a Triple-Threshold GARCH Model with Application in Chinese Stock Market," MPRA Paper 28235, University Library of Munich, Germany.
    49. Kenneth R. Szulczyk & Changyong Zhang, 2020. "Switching-regime regression for modeling and predicting a stock market return," Empirical Economics, Springer, vol. 59(5), pages 2385-2403, November.
    50. Luis Gil-Alana, 2003. "Strong dependence in the real interest rates," Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 119-124.
    51. Al-Sulami, Dawlah & Jiang, Zhenyu & Lu, Zudi & Zhu, Jun, 2017. "Estimation for semiparametric nonlinear regression of irregularly located spatial time-series data," Econometrics and Statistics, Elsevier, vol. 2(C), pages 22-35.
    52. Clements, Michael P. & Galvão, Ana Beatriz C., 2003. "Testing The Expectations Theory Of The Term Structure Of Interest Rates In Threshold Models," Macroeconomic Dynamics, Cambridge University Press, vol. 7(4), pages 567-585, September.
    53. Yacine Ait-Sahalia, 1995. "Testing Continuous-Time Models of the Spot Interest Rate," NBER Working Papers 5346, National Bureau of Economic Research, Inc.
    54. Ang, Andrew & Bekaert, Geert, 2002. "Short rate nonlinearities and regime switches," Journal of Economic Dynamics and Control, Elsevier, vol. 26(7-8), pages 1243-1274, July.
    55. Gu, Rongbao & Chen, Xi & Li, Xinjie, 2014. "Chaos recognition and fractal analysis in the term structure of Shanghai Interbank Offered Rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 101-112.
    56. Adrian Cantemir Calin & Tiberiu Diaconescu & Oana – Cristina Popovici, 2014. "Nonlinear Models for Economic Forecasting Applications: An Evolutionary Discussion," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 2(1), pages 42-47, June.
    57. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
    58. Schotman, Peter C., 2001. "When units roots matter: excess volatility and excess smoothness of long-term interest rates," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 669-694, December.
    59. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    60. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modelling Multivariate Interest Rates using Time-Varying Copulas and Reducible Non-Linear Stochastic Differential," Economics Working Papers 09-02, Queen's Management School, Queen's University Belfast.
    61. Sandy Suardi, 2010. "Nonstationarity, cointegration and structural breaks in the Australian term structure of interest rates," Applied Economics, Taylor & Francis Journals, vol. 42(22), pages 2865-2879.

  17. Tschernig, R., 1994. "Long Memory in Foreign Exchange Rates Revisited," SFB 373 Discussion Papers 1994,46, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Man, K.S. & Tiao, G.C., 2006. "Aggregation effect and forecasting temporal aggregates of long memory processes," International Journal of Forecasting, Elsevier, vol. 22(2), pages 267-281.
    2. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2013. "Econometric modeling of exchange rate volatility and jumps," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 16, pages 373-427, Edward Elgar Publishing.
    3. Christelle Lecourt, 1999. "Dépendance de court et de long terme des rendements de taux de change," Christelle Lecourt Working Papers 990609, Université de Lille 2 (France) Faculté des Sciences juridiques, politiques et sociales de Lille.
    4. Souza, Leonardo Rocha & Smith, Jeremy & Souza, Reinaldo Castro, 2003. "Convex combinations of long memory estimates from different sampling rates," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 489, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    5. Aouad Hadjer, Soumia & Taouli, Mustapha Kamel & Benbouziane, Mohamed, 2012. "Modélisation du Comportement du Taux de Change du Dinar Algérien: Une Investigation Empirique par la Méthode ARFIMA [Modeling of the Algerian Dinar Exchange Rate: An empirical investigation using t," MPRA Paper 38605, University Library of Munich, Germany.
    6. Uwe Hassler, 2011. "Estimation of fractional integration under temporal aggregation," Post-Print hal-00815563, HAL.
    7. Souza, Leonardo R. & Smith, Jeremy, 2004. "Effects of temporal aggregation on estimates and forecasts of fractionally integrated processes: a Monte-Carlo study," International Journal of Forecasting, Elsevier, vol. 20(3), pages 487-502.
    8. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.

  18. Tschernig, Rolf J.V. & Zimmermann, Klaus F, 1992. "Illusive Persistence in German Unemployment," CEPR Discussion Papers 739, C.E.P.R. Discussion Papers.

    Cited by:

    1. Laurence Ball & Joern Onken, 2022. "Hysteresis in unemployment: Evidence from OECD estimates of the natural rate," International Finance, Wiley Blackwell, vol. 25(3), pages 268-284, December.
    2. Imene Mootamri & Mohamed Boutahar & Anne Peguin-Feissolle, 2008. "A fractionally integrated exponential STAR model applied to the US real effective exchange rate," Post-Print halshs-00390134, HAL.
    3. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    4. Guglielmo Maria Caporale & Luis A. Gil-Alana & Yuliya Lovcha, 2016. "Testing unemployment theories: A multivariate long memory approach," Journal of Applied Economics, Universidad del CEMA, vol. 19, pages 95-112, May.
    5. Diego Romero‐Ávila & Carlos Usabiaga, 2007. "Unit Root Tests, Persistence, and the Unemployment Rate of the U.S. States," Southern Economic Journal, John Wiley & Sons, vol. 73(3), pages 698-716, January.
    6. T. D. Stanley, 2004. "Does unemployment hysteresis falsify the natural rate hypothesis? a meta‐regression analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 18(4), pages 589-612, September.
    7. Dilem Yıldırım & Dilan Aydın, 2021. "One Crisis After Another: A Dynamic Unemployment Persistence Analysis For The Gips Countries," ERC Working Papers 2102, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
    8. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2006. "Modelling Structural Breaks in the US, UK and Japanese Unemployment Rates," CESifo Working Paper Series 1734, CESifo.
    9. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2008. "Modelling the US, UK and Japanese unemployment rates: Fractional integration and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4998-5013, July.
    10. Luis Alberiko Gil-Alana & Pedro Garcia-del-Barrio, 2006. "New Revelations about Unemployment Persistence in Spain," Faculty Working Papers 10/06, School of Economics and Business Administration, University of Navarra.
    11. Monge, Manuel, 2021. "U.S. historical initial jobless claims. Is it different with the coronavirus crisis? A fractional integration analysis," International Economics, Elsevier, vol. 167(C), pages 88-95.
    12. Peijie Wang, 2003. "Cycles and Common Cycles in Property and Related Sectors," International Real Estate Review, Global Social Science Institute, vol. 6(1), pages 22-42.
    13. Mohamed Boutahar & Imene Mootamri & Anne Peguin-Feissolle, 2007. "An exponential FISTAR model applied to the US real effective exchange rate," Working Papers halshs-00353836, HAL.

Articles

  1. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2014. "Long- versus medium-run identification in fractionally integrated VAR models," Economics Letters, Elsevier, vol. 122(2), pages 299-302.
    See citations under working paper version above.
  2. Rolf Tschernig & Enzo Weber & Roland Weigand, 2013. "Long-Run Identification in a Fractionally Integrated System," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 438-450, October.
    See citations under working paper version above.
  3. Harry Haupt & Joachim Schnurbus & Rolf Tschernig, 2010. "On nonparametric estimation of a hedonic price function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 894-901.
    See citations under working paper version above.
  4. Peter C. Schotman & Rolf Tschernig & Jan Budek, 2008. "Long Memory and the Term Structure of Risk," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 459-495, Fall.
    See citations under working paper version above.
  5. Yang, Lijian & Tschernig, Rolf, 2002. "Non- And Semiparametric Identification Of Seasonal Nonlinear Autoregression Models," Econometric Theory, Cambridge University Press, vol. 18(6), pages 1408-1448, December.
    See citations under working paper version above.
  6. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.
    See citations under working paper version above.
  7. Rolf Tschernig & Lijian Yang, 2000. "Nonparametric Lag Selection for Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(4), pages 457-487, July.
    See citations under working paper version above.
  8. L. Yang & R. Tschernig, 1999. "Multivariate bandwidth selection for local linear regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 793-815.

    Cited by:

    1. Gilboa, Itzhak & Lieberman, Offer & Schmeidler, David, 2011. "A similarity-based approach to prediction," Journal of Econometrics, Elsevier, vol. 162(1), pages 124-131, May.
    2. Rong Liu & Lijian Yang, 2008. "Kernel estimation of multivariate cumulative distribution function," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(8), pages 661-677.
    3. Yingcun Xia & Howell Tong & W. K. Li & Li‐Xing Zhu, 2002. "An adaptive estimation of dimension reduction space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 363-410, August.
    4. Jan Koláček & Ivana Horová, 2017. "Bandwidth matrix selectors for kernel regression," Computational Statistics, Springer, vol. 32(3), pages 1027-1046, September.
    5. Giordano, Francesco & Parrella, Maria Lucia, 2016. "Bias-corrected inference for multivariate nonparametric regression: Model selection and oracle property," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 71-93.
    6. Yang, Lijian, 2006. "A semiparametric GARCH model for foreign exchange volatility," Journal of Econometrics, Elsevier, vol. 130(2), pages 365-384, February.
    7. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom [A nonparametric prediction test of the France Telecom stock proces]," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.
    8. Francesco Giordano & Maria Lucia Parrella, 2014. "Bias-corrected inference for multivariate nonparametric regression: model selection and oracle property," Working Papers 3_232, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    9. Rolf Tschernig & Lijian Yang, 2000. "Nonparametric Estimation of Generalized Impulse Response Functions," Econometric Society World Congress 2000 Contributed Papers 1417, Econometric Society.
    10. Andrea Meilán-Vila & Mario Francisco-Fernández & Rosa M. Crujeiras & Agnese Panzera, 2021. "Nonparametric multiple regression estimation for circular response," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 650-672, September.
    11. Donald W.K. Andrews & Xiaoxia Shi, 2011. "Nonparametric Inference Based on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1840R, Cowles Foundation for Research in Economics, Yale University, revised Feb 2013.
    12. Naito, Kanta & Yoshizaki, Masahiro, 2009. "Bandwidth selection for a data sharpening estimator in nonparametric regression," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1465-1486, August.
    13. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.
    14. Mohamed Chikhi & Claude Diebolt, 2006. "Nonparametric Analysis of Financial Time Series by the Kernel Methodology," Working Papers 06-11, Association Française de Cliométrie (AFC).
    15. Jean-Pierre Urbain & Sébastien Laurent, 2005. "Bridging the gap between Ox and Gauss using OxGauss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 131-139.
    16. Hupfeld, Stefan, 2009. "Rich and healthy--better than poor and sick?: An empirical analysis of income, health, and the duration of the pension benefit spell," Journal of Health Economics, Elsevier, vol. 28(2), pages 427-443, March.
    17. Jochen Einbeck, 2003. "Multivariate Local Fitting with General Basis Functions," Computational Statistics, Springer, vol. 18(2), pages 185-203, July.
    18. Max Köhler & Anja Schindler & Stefan Sperlich, 2011. "A Review and Comparison of Bandwidth Selection Methods for Kernel Regression," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 95, Courant Research Centre PEG.
    19. Gonzalez Manteiga, W. & Martinez Miranda, M. D. & Perez Gonzalez, A., 2004. "The choice of smoothing parameter in nonparametric regression through Wild Bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 47(3), pages 487-515, October.
    20. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    21. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    22. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    23. CHIKHI, Mohamed, 2009. "Identification non paramétrique d’un processus non linéaire hétéroscédastique [Nonparametric identification of heteroscedastic nonlinear process]," MPRA Paper 82108, University Library of Munich, Germany, revised 2009.
    24. Cheng, Ming-Yen & Peng, Liang, 2006. "Simple and efficient improvements of multivariate local linear regression," Journal of Multivariate Analysis, Elsevier, vol. 97(7), pages 1501-1524, August.
    25. Vidaurre, Diego & Bielza, Concha & Larrañaga, Pedro, 2013. "Sparse regularized local regression," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 122-135.
    26. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, vol. 3(2), pages 1-24, April.
    27. Qiu, D. & Shao, Q. & Yang, L., 2013. "Efficient inference for autoregressive coefficients in the presence of trends," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 40-53.
    28. Chevallier, Julien, 2011. "Nonparametric modeling of carbon prices," Energy Economics, Elsevier, vol. 33(6), pages 1267-1282.
    29. Bastian Schäfer, 2021. "Bandwidth selection for the Local Polynomial Double Conditional Smoothing under Spatial ARMA Errors," Working Papers CIE 146, Paderborn University, CIE Center for International Economics.

  9. Pfann, Gerard A. & Schotman, Peter C. & Tschernig, Rolf, 1996. "Nonlinear interest rate dynamics and implications for the term structure," Journal of Econometrics, Elsevier, vol. 74(1), pages 149-176, September.
    See citations under working paper version above.
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