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Charles Bos

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. Charles S. Bos & Ronald J. Mahieu & Herman K. Van Dijk, 2000. "Daily exchange rate behaviour and hedging of currency risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 671-696.

    Mentioned in:

    1. Daily exchange rate behaviour and hedging of currency risk (Journal of Applied Econometrics 2000) in ReplicationWiki ()

Working papers

  1. Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüß, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Menac, 2024. "Nonstandard errors," LSE Research Online Documents on Economics 123002, London School of Economics and Political Science, LSE Library.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad‐Díaz & Menachem (Meni) Abudy , 2024. "Nonstandard Errors," Journal of Finance, American Finance Association, vol. 79(3), pages 2339-2390, June.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian Brownlees & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
    • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Frömmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
    • Francesco Franzoni & Roxana Mihet & Markus Leippold & Per Ostberg & Olivier Scaillet & Norman Schürhoff & Oksana Bashchenko & Nicola Mano & Michele Pelli, 2022. "Non-Standard Errors," Swiss Finance Institute Research Paper Series 22-09, Swiss Finance Institute.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Hasse, Jean-Baptiste & e.a.,, 2023. "Non-Standard Errors," LIDAM Reprints LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
    • Moinas, Sophie & Declerck, Fany & Menkveld, Albert J. & Dreber, Anna, 2023. "Non-Standard Errors," TSE Working Papers 23-1451, Toulouse School of Economics (TSE).
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-04676112, HAL.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
    • Ferrara, Gerardo & Jurkatis, Simon, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500882, HAL.
    • Ciril Bosch-Rosa & Bernhard Kassner, 2023. "Non-Standard Errors," Rationality and Competition Discussion Paper Series 385, CRC TRR 190 Rationality and Competition.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Janeway Institute Working Papers 2112, Faculty of Economics, University of Cambridge.
    • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
    • Albert J. Menkveld & Anna Dreber & Félix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard, 2021. "Non-Standard Errors," Documents de travail du Centre d'Economie de la Sorbonne 21033, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    Cited by:

    1. Nate Breznau & Eike Mark Rinke & Alexander Wuttke & Hung H. V. Nguyen & Muna Adem & Jule Adriaans & Amalia Alvarez-Benjumea & Henrik K. Andersen & Daniel Auer & Flavio Azevedo & Oke Bahnsen & Dave Bal, 2022. "Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(44), pages 2203150119-, November.
    2. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    3. Dreber, Anna & Johannesson, Magnus, 2023. "A framework for evaluating reproducibility and replicability in economics," I4R Discussion Paper Series 38, The Institute for Replication (I4R).
    4. Fišar, Miloš & Greiner, Ben & Huber, Christoph & Katok, Elena & Ozkes, Ali & Collaboration, Management Science Reproducibility, 2023. "Reproducibility in Management Science," OSF Preprints mydzv, Center for Open Science.
    5. Christoph Huber & Christian König-Kersting & Matteo M. Marini, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck, revised Jun 2024.
    6. Stephen A. Gorman & Frank J. Fabozzi, 2023. "Alternative risk premium: specification noise," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 459-473, October.
    7. Christophe Pérignon & Olivier Akmansoy & Christophe Hurlin & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johanneson & Michael Kirchler & Albert Menkveld & Michael Razen & Utz Weitzel, 2022. "Reproducibility of Empirical Results: Evidence from 1,000 Tests in Finance," Working Papers hal-03810013, HAL.

  2. Tomori, Françeska & Ansink, Erik & Houba, Harold & Hagerty, Nick & Bos, Charles, 2021. "Market power in California’s water market," Working Papers 2072/534854, Universitat Rovira i Virgili, Department of Economics.

    Cited by:

    1. Harold Houba & Françeska Tomori, 2023. "Stackelberg Social Equilibrium in Water Markets," Games, MDPI, vol. 14(4), pages 1-9, July.

  3. Françeska Tomori & Erik Ansink & Harold Houba & Nick Hagerty & Charles Bos, 2021. "Market power in California's water market," Tinbergen Institute Discussion Papers 21-011/VIII, Tinbergen Institute.

    Cited by:

    1. Harold Houba & Françeska Tomori, 2023. "Stackelberg Social Equilibrium in Water Markets," Games, MDPI, vol. 14(4), pages 1-9, July.

  4. Charles S. Bos & Pawel Janus, 2013. "A Quantile-based Realized Measure of Variation: New Tests for Outlying Observations in Financial Data," Tinbergen Institute Discussion Papers 13-155/III, Tinbergen Institute.

    Cited by:

    1. Marcel, Bräutigam & Marie, Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," ESSEC Working Papers WP1807, ESSEC Research Center, ESSEC Business School.
    2. Marcel Bräutigam & Marie Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," Working Papers hal-02296832, HAL.

  5. Charles S. Bos, 2011. "A Bayesian Analysis of Unobserved Component Models using Ox," Tinbergen Institute Discussion Papers 11-048/4, Tinbergen Institute.

    Cited by:

    1. Nonejad Nima, 2016. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," Journal of Time Series Econometrics, De Gruyter, vol. 8(1), pages 55-90, January.
    2. Nonejad, Nima, 2014. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," MPRA Paper 55662, University Library of Munich, Germany.
    3. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    4. Nima Nonejad, 2013. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," CREATES Research Papers 2013-27, Department of Economics and Business Economics, Aarhus University.

  6. Charles S. Bos, 2011. "Relating Stochastic Volatility Estimation Methods," Tinbergen Institute Discussion Papers 11-049/4, Tinbergen Institute.

    Cited by:

    1. Trojan, Sebastian, 2013. "Regime Switching Stochastic Volatility with Skew, Fat Tails and Leverage using Returns and Realized Volatility Contemporaneously," Economics Working Paper Series 1341, University of St. Gallen, School of Economics and Political Science, revised Aug 2014.
    2. Sergey Egiev, 2016. "On Persistence of Uncertainty Shocks," HSE Working papers WP BRP 144/EC/2016, National Research University Higher School of Economics.

  7. Charles S. Bos & Pawel Janus & Siem Jan Koopman, 2009. "Spot Variance Path Estimation and its Application to High Frequency Jump Testing," Tinbergen Institute Discussion Papers 09-110/4, Tinbergen Institute.

    Cited by:

    1. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2014. "Estimating the spot covariation of asset prices: Statistical theory and empirical evidence," SFB 649 Discussion Papers 2014-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    4. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    5. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," Journal of Financial Markets, Elsevier, vol. 17(C), pages 121-149.
    6. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
    7. Charles S. Bos & Pawel Janus, 2013. "A Quantile-based Realized Measure of Variation: New Tests for Outlying Observations in Financial Data," Tinbergen Institute Discussion Papers 13-155/III, Tinbergen Institute.
    8. Lahaye, Jerome & Shaw, Philip, 2014. "Can we reject linearity in an HAR-RV model for the S&P 500? Insights from a nonparametric HAR-RV," Economics Letters, Elsevier, vol. 125(1), pages 43-46.
    9. Lee, Suzanne S. & Mykland, Per A., 2012. "Jumps in equilibrium prices and market microstructure noise," Journal of Econometrics, Elsevier, vol. 168(2), pages 396-406.
    10. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040, arXiv.org.
    11. Katahira, Kei & Chen, Yu & Hashimoto, Gaku & Okuda, Hiroshi, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 503-518.
    12. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.

  8. Michel Beine & Charles Bos & Serge Coulombe, 2009. "Does the Canadian economy suffer from Dutch Disease?," DEM Discussion Paper Series 09-06, Department of Economics at the University of Luxembourg.

    Cited by:

    1. Bayari, Celal, 2015. "Economic Geography of the Australian Mining Industry," MPRA Paper 102831, University Library of Munich, Germany, revised 25 Jul 2015.
    2. Mardi Dungey & Renee Fry‐Mckibbin & Vladimir Volkov, 2020. "Transmission of a Resource Boom: The Case of Australia," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 503-525, June.
    3. Evan Capeluck, 2014. "Convergence Across Provincial Economies in Canada: Trends, Drivers, and Implications," CSLS Research Reports 2014-03, Centre for the Study of Living Standards.
    4. Brian R. Copeland & M. Scott Taylor, 2017. "Environmental and resource economics: A Canadian retrospective," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1381-1413, December.
    5. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Volatility spillovers between strategic commodity futures and stock markets and portfolio implications: Evidence from developed and emerging economies," Resources Policy, Elsevier, vol. 71(C).
    6. Timothy W. Kelsey & Mark D. Partridge & Nancy E. White, 2016. "Unconventional Gas and Oil Development in the United States: Economic Experience and Policy Issues," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 38(2), pages 191-214.
    7. Jason Brown, 2014. "Production of natural gas from shale in local economies: a resource blessing or curse?," Economic Review, Federal Reserve Bank of Kansas City, issue Q I, pages 1-29.
    8. Arsham Reisinezhad, 2020. "The Dutch Disease Revisited: Theory and Evidence," PSE Working Papers halshs-03012647, HAL.
    9. Kang-Soek Lee, 2017. "Safe-haven currency: An empirical identification," Review of International Economics, Wiley Blackwell, vol. 25(4), pages 924-947, September.
    10. Shao, Shuai & Zhang, Yan & Tian, Zhihua & Li, Ding & Yang, Lili, 2020. "The regional Dutch disease effect within China: A spatial econometric investigation," Energy Economics, Elsevier, vol. 88(C).
    11. Pilar Poncela & Eva Senra & Lya Paola Sierra, 2017. "Long-term links between raw materials prices, real exchange rate and relative de-industrialization in a commodity-dependent economy: empirical evidence of “Dutch disease” in Colombia," Empirical Economics, Springer, vol. 52(2), pages 777-798, March.
    12. Liming Chen & Jesus Felipe & Andrew J.Y. Kam & Aashish Mehta, 2018. "Is Employment Globalizing?," Working Papers id:12912, eSocialSciences.
    13. Dungey, Mardi & Fry-McKibbin, Renée & Linehan, Verity, 2013. "Chinese resource demand and the natural resource supplier," Working Papers 17027, University of Tasmania, Tasmanian School of Business and Economics, revised 01 Jul 2013.
    14. Arsham Reisinezhad, 2024. "The Dutch disease revisited: consistency of theory and evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(3), pages 553-603, March.
    15. Elissaios Papyrakis & Ohad Raveh, 2013. "An Empirical Analysis of a Regional Dutch Disease: The Case of Canada," OxCarre Working Papers 106, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    16. Allah Morad Seif & Hossein Panahi & Davoud Hamidi Razi, 2017. "An Estimation of The Impact of Economic Sanctions and Oil Price Shocks on Iran-Russian Trade: Evidence from a Gravity- VEC Approach," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 21(3), pages 469-497, Summer.
    17. Berisha, Edmond & Chisadza, Carolyn & Clance, Matthew & Gupta, Rangan, 2021. "Income inequality and oil resources: Panel evidence from the United States," Energy Policy, Elsevier, vol. 159(C).
    18. Mr. Itai Agur, 2016. "Products and Provinces: A Disaggregated Panel Analysis of Canada’s Manufacturing Exports," IMF Working Papers 2016/193, International Monetary Fund.
    19. Gerelmaa, Lkhagva & Kotani, Koji, 2016. "Further investigation of natural resources and economic growth: Do natural resources depress economic growth?," Resources Policy, Elsevier, vol. 50(C), pages 312-321.
    20. Michel Beine & Serge Coulombe & Wessel N. Vermeulen, 2015. "Dutch Disease and the Mitigation Effect of Migration: Evidence from Canadian Provinces," Economic Journal, Royal Economic Society, vol. 125(589), pages 1574-1615, December.
    21. Marek Szturo & Bogdan Włodarczyk & Alberto Burchi & Ireneusz Miciuła & Karolina Szturo, 2021. "Improving Relations between a State and a Business Enterprise in the Context of Counteracting Adverse Effects of the Resource Curse," Sustainability, MDPI, vol. 13(3), pages 1-14, January.
    22. Anthony Venables & Torfinn Harding, 2013. "The Implications of Natural Resource Exports for Non-Resource Trade," OxCarre Working Papers 103, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    23. International Monetary Fund, 2013. "Canada: Selected Issues," IMF Staff Country Reports 2013/041, International Monetary Fund.
    24. Honorata Nyga-Łukaszewska & Tomasz M. Napiórkowski, 2022. "Does Energy Demand Security Affect International Competitiveness? Case of Selected Energy-Exporting OECD Countries," Energies, MDPI, vol. 15(6), pages 1-19, March.
    25. Wessel N. Vermeulen, 2011. "External income, De-industrialisation and Labour Mobility," DEM Discussion Paper Series 11-20, Department of Economics at the University of Luxembourg.
    26. Osama D. Sweidan, 2013. "The Effect of Exchange Rate on Exports and Imports: The Case of Jordan," The International Trade Journal, Taylor & Francis Journals, vol. 27(2), pages 156-172, June.
    27. Weber, Jeremy G., 2014. "A decade of natural gas development: The makings of a resource curse?," Resource and Energy Economics, Elsevier, vol. 37(C), pages 168-183.
    28. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    29. Chi-Swian Wong, 2021. "Science Mapping: A Scientometric Review on Resource Curses, Dutch Diseases, and Conflict Resources during 1993–2020," Energies, MDPI, vol. 14(15), pages 1-48, July.
    30. Jared C. Carbone & Kenneth J. McKenzie, 2015. "Going Dutch? The Impact of Oil Price Shocks on the Canadian Economy," Working Papers 2015-07, Colorado School of Mines, Division of Economics and Business.
    31. Moshiri, Saeed & Bakhshi Moghaddam, Mohsen, 2018. "The effects of oil price shocks in a federation; The case of interregional trade and labour migration," Energy Economics, Elsevier, vol. 75(C), pages 206-221.
    32. Wessel N. Vermeulen, 2013. "Resource Income and the Effect on Domestic Neighbours: A case study on Canadian Provinces," DEM Discussion Paper Series 13-05, Department of Economics at the University of Luxembourg.
    33. Liu, Tong & Lan, Bo, 2024. "On the conflict of natural resources abundance and export upgrading in upper-middle and high-income countries," Resources Policy, Elsevier, vol. 89(C).
    34. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillovers and connectedness between crude oil and currency markets using high-frequency data," Resources Policy, Elsevier, vol. 77(C).
    35. Sabna Ali & Syed Mansoob Murshed & Elissaios Papyrakis, 2020. "Happiness and the Resource Curse," Journal of Happiness Studies, Springer, vol. 21(2), pages 437-464, February.
    36. Khezri, Mohsen & Heshmati, Almas & Ghazal, Reza & Khodaei, Mehdi, 2022. "Non-resource revenues and the resource curse in different institutional structures: The DIGNAR-MTFF model," Resources Policy, Elsevier, vol. 79(C).
    37. Ådne Cappelen & Torbjørn Eika, 2020. "Immigration and the Dutch disease A counterfactual analysis of the Norwegian resource boom 2004-2013," Open Economies Review, Springer, vol. 31(3), pages 669-690, July.
    38. Oliver Loertscher & Pau S. Pujolas, 2023. "Canadian Productivity Growth: Stuck in the Oil Sands," Department of Economics Working Papers 2023-01, McMaster University.
    39. João Sousa Andrade & António Portugal Duarte, 2013. "The Dutch Disease in the Portuguese Economy," GEMF Working Papers 2013-05, GEMF, Faculty of Economics, University of Coimbra.
    40. Serge Coulombe & Robin Boadway & Michel Beine, 2016. "Moving Parts: Immigration Policy, Internal Migration and Natural Resource Shocks," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 446, March.
    41. Michel Beine & Serge Coulombe & Wessel Vermeulen, 2015. "Dutch Disease and the Mitigation: Evidence from Canadian Provinces," OxCarre Working Papers 151, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    42. Brian R. Copeland & M. Scott Taylor, 2017. "Environmental and resource economics: A Canadian retrospective," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1381-1413, December.
    43. Osiris Jorge Parcero & Elissaios Papyrakis, 2024. "Income inequality and the oil resource curse," Papers 2401.04046, arXiv.org.
    44. Jean Dubé & Mario Polèse, 2015. "Resource Curse and Regional Development: Does Dutch Disease Apply to Local Economies? Evidence from Canada," Growth and Change, Wiley Blackwell, vol. 46(1), pages 38-57, March.
    45. Parcero, Osiris J. & Papyrakis, Elissaios, 2016. "Income inequality and the oil resource curse," Resource and Energy Economics, Elsevier, vol. 45(C), pages 159-177.
    46. Vatsa, Puneet & Hu, Baiding, 2021. "Intra-federal effects of oil prices: Evidence from Canada," Resources Policy, Elsevier, vol. 74(C).
    47. Alssadek, Marwan & Benhin, James, 2021. "Oil boom, exchange rate and sectoral output: An empirical analysis of Dutch disease in oil-rich countries," Resources Policy, Elsevier, vol. 74(C).
    48. Talan İşcan, 2015. "Windfall Resource Income, Productivity Growth, and Manufacturing Employment," Open Economies Review, Springer, vol. 26(2), pages 279-311, April.
    49. Chang, Kuei-Feng & Lin, Jin-Xu & Lin, Shih-Mo, 2021. "Revisiting the Dutch disease thesis from the perspective of value-added trade," Resources Policy, Elsevier, vol. 72(C).
    50. Takatsuka, Hajime & Zeng, Dao-Zhi & Zhao, Laixun, 2015. "Resource-based cities and the Dutch disease," Resource and Energy Economics, Elsevier, vol. 40(C), pages 57-84.
    51. Mahmood, Haider & Alkhateeb, Tarek Tawfik Yousef & Ahmed, Nawaz, 2017. "Impact of Devaluation on Industrial Exports in Saudi Arabia: J-Curve Hypothesis," MPRA Paper 109455, University Library of Munich, Germany.
    52. Xuan Xie & Ke Li & Zhiqiang Liu & Hongshan Ai, 2021. "Curse or blessing: how does natural resource dependence affect city‐level economic development in China?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(2), pages 413-448, April.

  9. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.

    Cited by:

    1. Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012. "Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
    2. BOUDT, Kris & CROUX, Christophe & LAURENT, Sabéastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," LIDAM Reprints CORE 2411, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Eric Jondeau & Jérôme Lahaye & Michael Rockinger, 2013. "Estimating the Price Impact of Trades in an High-Frequency Microstructure Model with Jumps," Swiss Finance Institute Research Paper Series 13-47, Swiss Finance Institute, revised Feb 2016.
    4. Istvan Barra & Siem Jan Koopman & Agnieszka Borowska, 2016. "Bayesian Dynamic Modeling of High-Frequency Integer Price Changes," Tinbergen Institute Discussion Papers 16-028/III, Tinbergen Institute, revised 16 Feb 2018.

  10. Charles S. Bos & Phillip Gould, 2007. "Dynamic Correlations and Optimal Hedge Ratios," Tinbergen Institute Discussion Papers 07-025/4, Tinbergen Institute.

    Cited by:

    1. Charles S. Bos, 2011. "Relating Stochastic Volatility Estimation Methods," Tinbergen Institute Discussion Papers 11-049/4, Tinbergen Institute.
    2. Alshammari, Saad & Obeid, Hassan, 2023. "Analyzing commodity futures and stock market indices: Hedging strategies using asymmetric dynamic conditional correlation models," Finance Research Letters, Elsevier, vol. 56(C).
    3. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
    4. Chun, Dohyun & Cho, Hoon & Kim, Jihun, 2019. "Crude oil price shocks and hedging performance: A comparison of volatility models," Energy Economics, Elsevier, vol. 81(C), pages 1132-1147.

  11. Charles S. Bos & Siem Jan Koopman & Marius Ooms, 2007. "Long memory modelling of inflation with stochastic variance and structural breaks," CREATES Research Papers 2007-44, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Josu Arteche, 2012. "Standard and seasonal long memory in volatility: an application to Spanish inflation," Empirical Economics, Springer, vol. 42(3), pages 693-712, June.
    2. Grassi, Stefano & Proietti, Tommaso, 2008. "Has the Volatility of U.S. Inflation Changed and How?," MPRA Paper 11453, University Library of Munich, Germany.
    3. Luis A. Gil-Alana & Yadollah Dadgar & Rouhollah Nazari, 2019. "Iranian inflation: peristence and structural breaks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(2), pages 398-408, April.

  12. BEINE, Michel & BOS, Charles S. & LAURENT, Sébastien, 2006. "The impact of Central Bank FX interventions on currency components," LIDAM Reprints CORE 1980, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Michel Beine & Charles Bos & Serge Coulombe, 2009. "Does the Canadian economy suffer from Dutch Disease?," DEM Discussion Paper Series 09-06, Department of Economics at the University of Luxembourg.
    2. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 176, WU Vienna University of Economics and Business.
    3. Christopher J. Neely, 2005. "An analysis of recent studies of the effect of foreign exchange intervention," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 685-718.
    4. Holmes, Mark J. & Iregui, Ana María & Otero, Jesús, 2021. "The effects of FX-interventions on forecasters disagreement: A mixed data sampling view," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    5. Christopher J. Neely, 2007. "Central bank authorities’ beliefs about foreign exchange intervention," Working Papers 2006-045, Federal Reserve Bank of St. Louis.
    6. Kazım Berk Küçüklerli & Veysel Ulusoy, 2024. "Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(3), pages 1-4.
    7. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    8. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
    9. Georgios Chortareas & Ying Jiang & John C. Nankervis, 2013. "Volatility and Spillover Effects of Yen Interventions," Review of International Economics, Wiley Blackwell, vol. 21(4), pages 671-689, September.
    10. Ferhan SALMAN & Tolga CASKURLU & Mustafa PINAR & Aslihan SALIH, 2008. "Can Central Bank Interventions Affect the Exchange Rate Volatility? Multivariate GARCH Approach Using Constrained Nonlinear Programming," EcoMod2008 23800121, EcoMod.
    11. Kunze, Frederik, 2017. "Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts," University of Göttingen Working Papers in Economics 326, University of Goettingen, Department of Economics.

  13. BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," LIDAM Reprints CORE 1731, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. L. Bauwens & J.V.K. Rombouts, 2007. "Bayesian inference for the mixed conditional heteroskedasticity model," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 408-425, July.
    2. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    3. HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & van DIJK, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," LIDAM Reprints CORE 1922, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Waggoner, Daniel F. & Wu, Hongwei & Zha, Tao, 2016. "Striated Metropolis–Hastings sampler for high-dimensional models," Journal of Econometrics, Elsevier, vol. 192(2), pages 406-420.
    5. McCausland, William J., 2008. "On Bayesian analysis and computation for functions with monotonicity and curvature restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 484-507, January.
    6. Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012. "A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.
    7. Tsionas, Mike G., 2019. "Multi-objective optimization using statistical models," European Journal of Operational Research, Elsevier, vol. 276(1), pages 364-378.
    8. Rodney Strachan & Herman K. van Dijk, "undated". "Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan," MRG Discussion Paper Series 1407, School of Economics, University of Queensland, Australia.
    9. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    10. Hoogerheide, L.F. & van Dijk, H.K., 2007. "Note on neural network sampling for Bayesian inference of mixture processes," Econometric Institute Research Papers EI 2007-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2004. "Neural network based approximations to posterior densities: a class of flexible sampling methods with applications to reduced rank models," Econometric Institute Research Papers EI 2004-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2003. "Explaining Adaptive Radial-Based Direction Sampling," Econometric Institute Research Papers EI 2003-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. HOOGERHEIDE, Lennart F. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2007. "Simulation based Bayesian econometric inference: principles and some recent computational advances," LIDAM Discussion Papers CORE 2007015, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. David Ardia & Lennart Hoogerheide & Herman K. van Dijk, 2009. "To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods," Tinbergen Institute Discussion Papers 09-017/4, Tinbergen Institute.
    15. Martin Burda & John Maheu, 2011. "Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Papers tecipa-438, University of Toronto, Department of Economics.

  14. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Economics Papers 2004-W02, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Charles S. Bos, 2011. "Relating Stochastic Volatility Estimation Methods," Tinbergen Institute Discussion Papers 11-049/4, Tinbergen Institute.
    2. Michel Beine & Charles Bos & Serge Coulombe, 2009. "Does the Canadian economy suffer from Dutch Disease?," DEM Discussion Paper Series 09-06, Department of Economics at the University of Luxembourg.
    3. Christophe Chesneau & Salima El Kolei & Fabien Navarro, 2022. "Parametric estimation of hidden Markov models by least squares type estimation and deconvolution," Statistical Papers, Springer, vol. 63(5), pages 1615-1648, October.
    4. Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    5. Carmen Broto & Esther Ruiz, 2008. "Testing for conditional heteroscedasticity in the components of inflation," Working Papers 0812, Banco de España.
    6. Michel Beine & Charles S. Bos & Sébastien Laurent, 2007. "The Impact of Central Bank FX Interventions on Currency Components," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 154-183.
    7. Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
    8. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
    9. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
    10. Grassi, Stefano & Proietti, Tommaso, 2008. "Has the Volatility of U.S. Inflation Changed and How?," MPRA Paper 11453, University Library of Munich, Germany.
    11. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.
    12. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    13. Huang Yu-Fan, 2021. "An effcient exact Bayesian method For state space models with stochastic volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-10, April.
    14. Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.
    15. Kjartan Kloster Osmundsen & Tore Selland Kleppe & Roman Liesenfeld & Atle Oglend, 2021. "Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices," Econometrics, MDPI, vol. 9(4), pages 1-24, November.

  15. Charles S. Bos, 2003. "Time Series Modelling using TSMod 3.24," Tinbergen Institute Discussion Papers 03-091/4, Tinbergen Institute.

    Cited by:

    1. Marwan Izzeldin & Ana-Maria Fuertes & Anthony Murphy, 2005. "A guided tour of TSMod 4.03," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 691-698.
    2. Dima, Bogdan & Dima, Ştefana Maria, 2017. "Mutual information and persistence in the stochastic volatility of market returns: An emergent market example," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 36-59.

  16. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2002. "Adaptive polar sampling, a class of flexibel and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2002-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    2. Andrzej Kociêcki, 2003. "On Priors for Impulse Responses in Bayesian Structural VAR Models," Econometrics 0307006, University Library of Munich, Germany.
    3. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.

  17. Charles S. Bos, 2002. "A Comparison of Marginal Likelihood Computation Methods," Tinbergen Institute Discussion Papers 02-084/4, Tinbergen Institute.

    Cited by:

    1. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Economics Papers 2004-W02, Economics Group, Nuffield College, University of Oxford.
    2. Li, Gong & Shi, Jing, 2010. "Application of Bayesian model averaging in modeling long-term wind speed distributions," Renewable Energy, Elsevier, vol. 35(6), pages 1192-1202.
    3. Zhenyu Zhao & Thomas A. Severini, 2017. "Integrated likelihood computation methods," Computational Statistics, Springer, vol. 32(1), pages 281-313, March.
    4. Jochen Ranger & Jorg-Tobias Kuhn, 2012. "A flexible latent trait model for response times in tests," Psychometrika, Springer;The Psychometric Society, vol. 77(1), pages 31-47, January.
    5. Pierangelo De Pace, 2005. "Grid-Bootstrap Methods vs. Bayesian Analysis. Testing for Structural Breaks in the Conditional Variance of Nominal Interest Rate Spreads - Four Cases in Europe," Econometrics 0509011, University Library of Munich, Germany, revised 14 Feb 2006.

  18. Luc Bauwens & Charles S. Bos & Herman K. van Dijk & Rutger D. van Oest, 2002. "Adaptive Polar Sampling," Computing in Economics and Finance 2002 307, Society for Computational Economics.

    Cited by:

    1. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    2. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    3. Andrzej Kociêcki, 2003. "On Priors for Impulse Responses in Bayesian Structural VAR Models," Econometrics 0307006, University Library of Munich, Germany.
    4. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    5. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.

  19. Charles S. Bos & Philip Hans Franses & Marius Ooms, 2001. "Inflation, Forecast Intervals and Long Memory Regression Models," Tinbergen Institute Discussion Papers 01-029/4, Tinbergen Institute.

    Cited by:

    1. J. Cuñado & L. Gil-Alana & F. Gracia, 2009. "US stock market volatility persistence: evidence before and after the burst of the IT bubble," Review of Quantitative Finance and Accounting, Springer, vol. 33(3), pages 233-252, October.
    2. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    3. Luis A Gil-Alana & Christophe André & Rangan Gupta & Tsangyao Chang & Omid Ranjbar, 2015. "The Feldstein-Horioka Puzzle in South Africa: A Fractional Cointegration Approach," Working Papers 201501, University of Pretoria, Department of Economics.
    4. Luis Gil-Alana, 2008. "Real GDP growth rates across countries: long memory and mean shifts," Applied Economics Letters, Taylor & Francis Journals, vol. 15(6), pages 449-455.
    5. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    6. Heinen, Florian & Sibbertsen, Philipp & Kruse, Robinson, 2009. "Forecasting long memory time series under a break in persistence," Hannover Economic Papers (HEP) dp-433, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Claudio Morana & Fabio Cesare Bagliano, 2007. "Inflation and monetary dynamics in the USA: a quantity-theory approach," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 229-244.
    8. Siem Jan Koopman & Borus Jungbacker & Eugenie Hol, 2004. "Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements," Tinbergen Institute Discussion Papers 04-016/4, Tinbergen Institute.
    9. Lovcha, Yuliya & Pérez Laborda, Àlex, 2013. "A fractionally integrated approach to monetary policy and inflation dynamics," Working Papers 2072/211795, Universitat Rovira i Virgili, Department of Economics.
    10. Georgios KOURETAS & Mark E. WOHAR, 2010. "The Dynamics of Inflation: A Study of a Large Number of Countries," EcoMod2010 259600096, EcoMod.
    11. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    12. Hyung, Namwon & Franses, Philip Hans & Penm, Jack, 2006. "Structural breaks and long memory in US inflation rates: Do they matter for forecasting?," Research in International Business and Finance, Elsevier, vol. 20(1), pages 95-110, March.
    13. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    14. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    15. Manmohan S. Kumar & Tatsuyoshi Okimoto, 2007. "Dynamics of Persistence in International Inflation Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1457-1479, September.
    16. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    17. Franses, Ph.H.B.F., 2018. "Model-based forecast adjustment; with an illustration to inflation," Econometric Institute Research Papers EI2018-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    18. Luis A. Gil-Alana & Antonio Moreno & Seonghoon Cho, 2009. "The Deaton paradox in a long memory context with structural breaks," Faculty Working Papers 03/09, School of Economics and Business Administration, University of Navarra.
    19. Gil-Alana, Luis A. & Mudida, Robert, 2017. "CPI and inflation in Kenya. Structural breaks, non-linearities and dependence," International Economics, Elsevier, vol. 150(C), pages 72-79.
    20. Eugenie Hol & Siem Jan Koopman, 2002. "Stock Index Volatility Forecasting with High Frequency Data," Tinbergen Institute Discussion Papers 02-068/4, Tinbergen Institute.
    21. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Economics Working Papers ECO2006/3, European University Institute.
    22. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    23. Luis A. Gil-Alana, 2006. "Fractional integration and structural breaks at unknown periods of time," Faculty Working Papers 16/06, School of Economics and Business Administration, University of Navarra.
    24. Juncal Cunado & Luis A. Gil-Alana & Fernando Pérez de Gracia, 2006. "Additional Empirical Evidence on Real Convergence: A Fractionally Integrated Approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 142(1), pages 67-91, April.
    25. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    26. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-21, University of Connecticut, Department of Economics.
    27. Chevillon, Guillaume, 2009. "Multi-step forecasting in emerging economies: An investigation of the South African GDP," International Journal of Forecasting, Elsevier, vol. 25(3), pages 602-628, July.
    28. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    29. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    30. Chien-Chiang Lee & Chun-Ping Chang, 2007. "Mean reversion of inflation rates in 19 OECD countries: Evidence from panel Lm unit root tests with structural breaks," Economics Bulletin, AccessEcon, vol. 3(23), pages 1-15.
    31. J. Cunado & L.A. Gil-Alana & F. P Erez de Gracia, 2008. "Fractional Integration and Structural Breaks: Evidence from International Monthly Arrivals in the USA," Tourism Economics, , vol. 14(1), pages 13-23, March.
    32. Juncal Cunado & Luis Alberiko Gil-Alana & Fernando Perez de Gracia, 2008. "New Evidence on US Current Account Sustainability," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 1-21, April.
    33. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    34. Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
    35. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    36. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2018. "Long-Memory Modeling and Forecasting: Evidence from the U.S. Historical Series of Inflation," Working Papers 201869, University of Pretoria, Department of Economics.
    37. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    38. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    39. Chu Shiou-Yen & Shane Christopher, 2017. "Using the hybrid Phillips curve with memory to forecast US inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-16, September.
    40. Dmytro Krukovets & Olesia Verchenko, 2019. "Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 248, pages 11-20.
    41. Cunado, J. & Gil-Alana, L. A. & Perez de Gracia, F., 2004. "Is the US fiscal deficit sustainable?: A fractionally integrated approach," Journal of Economics and Business, Elsevier, vol. 56(6), pages 501-526.
    42. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    43. Luis A. Gil-Alana & Yadollah Dadgar & Rouhollah Nazari, 2019. "Iranian inflation: peristence and structural breaks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(2), pages 398-408, April.

  20. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 2000. "On the variation of hedging decisions in daily currency risk management," Econometric Institute Research Papers EI 2000-20/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Broto, Carmen, 2003. "Unobserved component models with asymmetric conditional variances," DES - Working Papers. Statistics and Econometrics. WS ws032003, Universidad Carlos III de Madrid. Departamento de Estadística.

  21. Charles S. Bos & Ronald J. Mahieu & Herman K. van Dijk, 2000. "Daily Exchange Rate Behaviour and Hedging of Currency Risk," Econometric Society World Congress 2000 Contributed Papers 0504, Econometric Society.

    Cited by:

    1. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 2000. "On the variation of hedging decisions in daily currency risk management," Econometric Institute Research Papers EI 2000-20/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Thomas M. Trimbur, 2006. "Detrending economic time series: a Bayesian generalization of the Hodrick-Prescott filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 247-273.
    3. Vasco Curdia & Marco Del Negro & Daniel L. Greenwald, 2012. "Rare shocks, great recessions," Staff Reports 585, Federal Reserve Bank of New York.
    4. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Economics Papers 2004-W02, Economics Group, Nuffield College, University of Oxford.
    5. HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & van DIJK, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," LIDAM Reprints CORE 1922, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Jacek Osiewalski & Mateusz Pipien, 2004. "Bayesian Comparison of Bivariate GARCH Processes in the Presence of an Exogenous Variable," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 6, pages 25-36.
    7. Siem Jan Koopman & Charles S. Bos, 2002. "Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series," Tinbergen Institute Discussion Papers 02-113/4, Tinbergen Institute.
    8. Baştürk, N. & Grassi, S. & Hoogerheide, L. & Opschoor, A. & van Dijk, H.K., 2015. "The R package MitISEM : efficient and robust simulation procedures for Bayesian inference," Research Memorandum 011, Maastricht University, Graduate School of Business and Economics (GSBE).
    9. Kin-Yip Ho & Albert K Tsui, 2008. "Volatility Dynamics in Foreign Exchange Rates : Further Evidence from the Malaysian Ringgit and Singapore Dollar," Finance Working Papers 22571, East Asian Bureau of Economic Research.
    10. Michel Beine & Charles S. Bos & Sébastien Laurent, 2007. "The Impact of Central Bank FX Interventions on Currency Components," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 154-183.
    11. Koop, G. & van Dijk, H.K., 1999. "Testing for integration using evolving trend and seasonal models: A Bayesian approach," Econometric Institute Research Papers EI 9934/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Nalan Basturk & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2012. "The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation," Tinbergen Institute Discussion Papers 12-096/III, Tinbergen Institute.
    13. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
    14. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    15. Lennart Hoogerheide & Herman K. van Dijk, 2008. "Possibly Ill-behaved Posteriors in Econometric Models," Tinbergen Institute Discussion Papers 08-036/4, Tinbergen Institute, revised 18 Apr 2008.
    16. Jacek Kwiatkowski, 2008. "Bayesian Analysis of Polish Inflation Rates Using RCA and GLL Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 8, pages 129-138.
    17. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    18. Charles S. Bos & Siem Jan Koopman, 2010. "Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production," Tinbergen Institute Discussion Papers 10-017/4, Tinbergen Institute.
    19. Osiewalski, Jacek & Pipien, Mateusz, 2004. "Bayesian comparison of bivariate ARCH-type models for the main exchange rates in Poland," Journal of Econometrics, Elsevier, vol. 123(2), pages 371-391, December.

  22. BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K., 1999. "Adaptive polar sampling with an application to a Bayes measure of value-at-risk," LIDAM Discussion Papers CORE 1999057, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 2000. "On the variation of hedging decisions in daily currency risk management," Econometric Institute Research Papers EI 2000-20/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    3. Badescu Alex & Kulperger Reg & Lazar Emese, 2008. "Option Valuation with Normal Mixture GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-42, May.
    4. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics.
    5. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
    6. Ausin, Maria Concepcion & Galeano, Pedro, 2007. "Bayesian estimation of the Gaussian mixture GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2636-2652, February.
    7. Mohamed Saidane & Christian Lavergne, 2009. "Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 323-364, November.
    8. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
    9. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    10. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    11. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
    12. Qiang Xia & Heung Wong & Jinshan Liu & Rubing Liang, 2017. "Bayesian Analysis of Power-Transformed and Threshold GARCH Models: A Griddy-Gibbs Sampler Approach," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 353-372, October.

  23. Franses, Ph.H.B.F. & Ooms, M. & Bos, C.S., 1998. "Long memory and level shifts: re-analysing inflation rates," Econometric Institute Research Papers EI 9811, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
    2. Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Zeynel Abidin Ozdemir & Mehmet Balcilar & Aysit Tansel, 2014. "Are Labor Force Participation Rates Really Non-Stationary? Evidence from Three OECD Countries," Working Papers 15-25, Eastern Mediterranean University, Department of Economics.
    4. Nobay, A. Robert & Paya, Ivan & Peel, David A., 2007. "Inflation dynamics in the US - a nonlinear perspective," LSE Research Online Documents on Economics 24499, London School of Economics and Political Science, LSE Library.
    5. Gabriel Rodríguez & Dennis Alvaro & Ángel Guillén, 2016. "Modelling the Volatility of Commodities Prices using a Stochastic Volatility Model with Random Level Shifts," Documentos de Trabajo / Working Papers 2016-414, Departamento de Economía - Pontificia Universidad Católica del Perú.
    6. Claudio Morana, 2007. "A structural common factor approach to core inflation estimation and forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 14(3), pages 163-169.
    7. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    8. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    9. Claudio Morana & Fabio Cesare Bagliano, 2007. "Inflation and monetary dynamics in the USA: a quantity-theory approach," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 229-244.
    10. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 225-241, April.
    11. Bos, Charles S. & Koopman, Siem Jan & Ooms, Marius, 2014. "Long memory with stochastic variance model: A recursive analysis for US inflation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 144-157.
    12. Gil-Alana, Luis A. & Shittu, Olanrewaju I. & Yaya, OlaOluwa S., 2014. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 149-162.
    13. McMillan, David G. & Wohar, Mark E., 2010. "Persistence and time-varying coefficients," Economics Letters, Elsevier, vol. 108(1), pages 85-88, July.
    14. Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
    15. Haldrup, Niels & Nielsen, Morten Orregaard, 2007. "Estimation of fractional integration in the presence of data noise," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3100-3114, March.
    16. 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.
    17. Choi, Kyongwook & Zivot, Eric, 2007. "Long memory and structural changes in the forward discount: An empirical investigation," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 342-363, April.
    18. Giorgio Canarella & Luis A. Gil-Alana & Rangan Gupta & Stephen M. Miller, 2020. "Modeling US historical time-series prices and inflation using alternative long-memory approaches," Empirical Economics, Springer, vol. 58(4), pages 1491-1511, April.
    19. Georgios KOURETAS & Mark E. WOHAR, 2010. "The Dynamics of Inflation: A Study of a Large Number of Countries," EcoMod2010 259600096, EcoMod.
    20. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    21. 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.
    22. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    23. Baillie Richard T. & Kapetanios George, 2016. "On the estimation of short memory components in long memory time series models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 365-375, September.
    24. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    25. Narayan, Paresh Kumar & Popp, Stephan, 2011. "An application of a new seasonal unit root test to inflation," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 707-716, October.
    26. Bos, Charles S, 2004. "Time Series Modelling using TSMod 3.24," International Journal of Forecasting, Elsevier, vol. 20(3), pages 515-522.
    27. Jesús Clemente & María Dolores Gadea & Antonio Montañés & Marcelo Reyes, 2017. "Structural Breaks, Inflation and Interest Rates: Evidence from the G7 Countries," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    28. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    29. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, September.
    30. Massimiliano Caporin & Rangan Gupta, 2017. "Time-varying persistence in US inflation," Empirical Economics, Springer, vol. 53(2), pages 423-439, September.
    31. L.A. Gil-Alana & G.M. caporale, 2004. "Long-run and Cyclical Dynamics in the US Stock Market," Econometric Society 2004 Latin American Meetings 344, Econometric Society.
    32. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Long-memory dynamics in a SETAR model - applications to stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(5), pages 391-406, December.
    33. Rinke, Saskia & Busch, Marie & Leschinski, Christian, 2017. "Long Memory, Breaks, and Trends: On the Sources of Persistence in Inflation Rates," Hannover Economic Papers (HEP) dp-584, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    34. Zeynel Abidin Ozdemir & Mehmet Balcilar & Aysit Tansel, 2011. "International Labour Force Participation Rates by Gender: Unit Root or Structural Breaks?," ERC Working Papers 1105, ERC - Economic Research Center, Middle East Technical University, revised Oct 2011.
    35. Hyung, N. & Franses, Ph.H.B.F., 2002. "Inflation rates; long-memoray, level shifts, or both?," Econometric Institute Research Papers EI 2002-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    36. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    37. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    38. Richard Paap & Philip Hans Franses & Marco Van Der Leij, 2002. "Modelling and forecasting level shifts in absolute returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 601-616.
    39. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-21, University of Connecticut, Department of Economics.
    40. Haldrup; Niels & Morten Oerregaard Nielsen, 2005. "Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices," Economics Working Papers 2005-18, Department of Economics and Business Economics, Aarhus University.
    41. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    42. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    43. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    44. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    45. Morana, Claudio, 2000. "Measuring core inflation in the euro area," Working Paper Series 36, European Central Bank.
    46. Juncal Cunado & Luis Alberiko Gil-Alana & Fernando Perez de Gracia, 2008. "New Evidence on US Current Account Sustainability," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 1-21, April.
    47. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    48. Sibbertsen, Philipp & Wenger, Kai & Wingert, Simon, 2020. "Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series," Hannover Economic Papers (HEP) dp-676, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    49. Hwang, Eunju & Shin, Dong Wan, 2013. "A CUSUM test for a long memory heterogeneous autoregressive model," Economics Letters, Elsevier, vol. 121(3), pages 379-383.
    50. Philip Hans Franses & Namwon Hyung, 2005. "Forecasting time series with long memory and level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 1-16.
    51. Guglielmo M. Caporale & Luis A. Gil‐Alana, 2004. "Testing for Seasonal Fractional Roots in German Real Output," German Economic Review, Verein für Socialpolitik, vol. 5(3), pages 319-333, August.
    52. de Figueiredo, Erik Alencar, 2010. "Dynamics of regional unemployment rates in Brazil: Fractional behavior, structural breaks, and Markov switching," Economic Modelling, Elsevier, vol. 27(5), pages 900-908, September.
    53. Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
    54. Chih-Chiang Hsu, 2000. "Long Memory or Structural Change: Testing Method and Empirical Examination," Econometric Society World Congress 2000 Contributed Papers 0867, Econometric Society.
    55. Luis A. Gil-Alana & Andrea Mervar & James E. Payne, 2017. "The stationarity of inflation in Croatia: anti-inflation stabilization program and the change in persistence," Economic Change and Restructuring, Springer, vol. 50(1), pages 45-58, February.
    56. Hwang, Eunju & Shin, Dong Wan, 2015. "A CUSUMSQ test for structural breaks in error variance for a long memory heterogeneous autoregressive model," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 167-176.
    57. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
    58. Franses, Philip Hans & Janssens, Eva, 2018. "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 261-292.
    59. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "The effects of sovereign rating drifts on financial return distributions: Evidence from the European Union," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 5-20.
    60. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2018. "Long-Memory Modeling and Forecasting: Evidence from the U.S. Historical Series of Inflation," Working Papers 201869, University of Pretoria, Department of Economics.
    61. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    62. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    63. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    64. Heni Boubaker, 2016. "A Comparative Study of the Performance of Estimating Long-Memory Parameter Using Wavelet-Based Entropies," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 693-731, December.
    65. Reisen, Valdério Anselmo & Monte, Edson Zambon & da Conceição Franco, Glaura & Sgrancio, Adriano Marcio & Molinares, Fábio Alexander Fajardo & Bondon, Pascal & Ziegelmann, Flávio Augusto & Abraham, Bo, 2018. "Robust estimation of fractional seasonal processes: Modeling and forecasting daily average SO2 concentrations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 146(C), pages 27-43.
    66. Cleomar Gomes da Silva & Maria Carolina da Silva Leme, 2008. "Inflation and Interest Rate: Which one is more persistent in Brazil?," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807181224190, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
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  3. Bos, Charles S. & Koopman, Siem Jan & Ooms, Marius, 2014. "Long memory with stochastic variance model: A recursive analysis for US inflation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 144-157.

    Cited by:

    1. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "A Simple Test on Structural Change in Long-Memory Time Series," Hannover Economic Papers (HEP) dp-592, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Goliński, Adam & Zaffaroni, Paolo, 2016. "Long memory affine term structure models," Journal of Econometrics, Elsevier, vol. 191(1), pages 33-56.
    3. M. Shelton Peiris & Manabu Asai, 2016. "Generalized Fractional Processes with Long Memory and Time Dependent Volatility Revisited," Econometrics, MDPI, vol. 4(3), pages 1-21, September.
    4. Phillip, Andrew & Chan, Jennifer & Peiris, Shelton, 2020. "On generalized bivariate student-t Gegenbauer long memory stochastic volatility models with leverage: Bayesian forecasting of cryptocurrencies with a focus on Bitcoin," Econometrics and Statistics, Elsevier, vol. 16(C), pages 69-90.
    5. Rinke, Saskia & Busch, Marie & Leschinski, Christian, 2017. "Long Memory, Breaks, and Trends: On the Sources of Persistence in Inflation Rates," Hannover Economic Papers (HEP) dp-584, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    7. Richard Hunt & Shelton Peiris & Neville Weber, 2022. "Estimation methods for stationary Gegenbauer processes," Statistical Papers, Springer, vol. 63(6), pages 1707-1741, December.
    8. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    9. Granville, Brigitte & Zeng, Ning, 2019. "Time variation in inflation persistence: New evidence from modelling US inflation," Economic Modelling, Elsevier, vol. 81(C), pages 30-39.
    10. Chu Shiou-Yen & Shane Christopher, 2017. "Using the hybrid Phillips curve with memory to forecast US inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-16, September.
    11. 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.
    12. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    13. Nima Nonejad, 2019. "Has the 2008 financial crisis and its aftermath changed the impact of inflation on inflation uncertainty in member states of the european monetary union?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 246-276, May.

  4. Beine, Michel & Bos, Charles S. & Coulombe, Serge, 2012. "Does the Canadian economy suffer from Dutch disease?," Resource and Energy Economics, Elsevier, vol. 34(4), pages 468-492.
    See citations under working paper version above.
  5. Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012. "Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
    See citations under working paper version above.
  6. Bos, Charles S., 2011. "A Bayesian Analysis of Unobserved Component Models Using Ox," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i13).
    See citations under working paper version above.
  7. Michel Beine & Charles S. Bos & Sébastien Laurent, 2007. "The Impact of Central Bank FX Interventions on Currency Components," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 154-183.
    See citations under working paper version above.
  8. Charles Bos & Neil Shephard, 2006. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 219-244.
    See citations under working paper version above.
  9. Bos, Charles S, 2004. "Time Series Modelling using TSMod 3.24," International Journal of Forecasting, Elsevier, vol. 20(3), pages 515-522.
    See citations under working paper version above.
  10. Koopman S.J. & Bos C.S., 2004. "State Space Models With a Common Stochastic Variance," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 346-357, July.

    Cited by:

    1. Broto, Carmen, 2003. "Unobserved component models with asymmetric conditional variances," DES - Working Papers. Statistics and Econometrics. WS ws032003, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Bos, Charles S. & Koopman, Siem Jan & Ooms, Marius, 2014. "Long memory with stochastic variance model: A recursive analysis for US inflation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 144-157.
    3. Hui ‘Fox’ Ling & Douglas B. Stone, 2016. "Time-varying forecasts by variational approximation of sequential Bayesian inference," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 43-67, January.
    4. Charles S. Bos & Neil Shephard, 2004. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Economics Papers 2004-W02, Economics Group, Nuffield College, University of Oxford.
    5. Carmen Broto & Esther Ruiz, 2008. "Testing for conditional heteroscedasticity in the components of inflation," Working Papers 0812, Banco de España.
    6. Rodríguez, Alejandro, 2010. "Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters," DES - Working Papers. Statistics and Econometrics. WS ws100301, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
    8. Broto, Carmen, 2006. "Using auxiliary residuals to detect conditional heteroscedasticity in inflation," DES - Working Papers. Statistics and Econometrics. WS ws060402, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    10. Charles S. Bos & Siem Jan Koopman, 2010. "Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production," Tinbergen Institute Discussion Papers 10-017/4, Tinbergen Institute.

  11. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    See citations under working paper version above.
  12. Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
    See citations under working paper version above.
  13. Charles S. Bos & Ronald J. Mahieu & Herman K. Van Dijk, 2000. "Daily exchange rate behaviour and hedging of currency risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 671-696.
    See citations under working paper version above.
  14. Philip Hans Franses & Marius Ooms & Charles S. Bos, 1999. "Long memory and level shifts: Re-analyzing inflation rates," Empirical Economics, Springer, vol. 24(3), pages 427-449.
    See citations under working paper version above.
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