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Guillaume Chevillon

Personal Details

First Name:Guillaume
Middle Name:
Last Name:Chevillon
Suffix:
RePEc Short-ID:pch128
http://guillaume-chevillon.faculty.essec.edu/
ESSEC Business School Avenue Bernard Hirsch BP 50105 F-95021 Cergy-Pontoise cedex FRANCE
Terminal Degree:2004 Department of Economics; Oxford University (from RePEc Genealogy)

Affiliation

(99%) ESSEC Business School

Cergy-Pontoise, France
http://www.essec.fr/

:

BP 50105, 95021 Cergy-Pontoise
RePEc:edi:essecfr (more details at EDIRC)

(1%) Centre de Recherche en Économie et Statistique (CREST)

France
http://crest.science/

: 01 41 17 60 81

Bâtiment ENSAE, 5 rue Henry LE Chatelier, 91120 Palaiseau
RePEc:edi:crestfr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Chevillon, Guillaume & Hecq , Alain & Laurent, Sébastien, 2015. "Long Memory Through Marginalization of Large Systems and Hidden Cross-Section Dependence," ESSEC Working Papers WP1507, ESSEC Research Center, ESSEC Business School.
  2. Banerjee, Anurag N. & Chevillon, Guillaume & Kratz, Marie, 2013. "Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Coefficient Model," ESSEC Working Papers WP1314, ESSEC Research Center, ESSEC Business School.
  3. Guillaume Chevillon & Sophocles Mavroeidis, 2013. "Learning generates Long Memory," Post-Print hal-00661012, HAL.
  4. Chevillon, Guillaume, 2013. "Robust Cointegration Testing in the Presence of Weak Trends, with an Application to the Human Origin of Global Warming," ESSEC Working Papers WP1320, ESSEC Research Center, ESSEC Business School.
  5. Chevillon, Guillaume, 2012. "Local-Explosive Approximations to Null Distributions of the Johansen Cointegration Test, with an Application to Cyclical Concordance in the Euro Area," ESSEC Working Papers WP1210, ESSEC Research Center, ESSEC Business School.
  6. Chevillon, Guillaume, 2007. "Inference in the Presence of Stochastic and Deterministic Trends," ESSEC Working Papers DR 07021, ESSEC Research Center, ESSEC Business School.
  7. Chevillon, Guillaume & Rifflart, Christine, 2007. "Physical Market Determinants of the Price of Crude Oil and the Market Premium," ESSEC Working Papers DR 07020, ESSEC Research Center, ESSEC Business School.
  8. Guillaume Chevillon, 2006. "Multi-step Forecasting in Unstable Economies: Robustness Issues in the Presence of Location Shifts," Economics Series Working Papers 257, University of Oxford, Department of Economics.
  9. Guillaume Chevillon & Xavier Timbeau, 2006. "L’impact du taux de change sur le tourisme en France," Sciences Po publications info:hdl:2441/1743, Sciences Po.
  10. Guillaume Chevillon, 2005. "Direct multi-step estimation and forecasting," Documents de Travail de l'OFCE 2005-10, Observatoire Francais des Conjonctures Economiques (OFCE).
  11. Guillaume Chevillon & Xavier Timbeau, 2005. "Impact de l’appréciation de l’euro sur le secteur du tourisme," Documents de Travail de l'OFCE 2005-18, Observatoire Francais des Conjonctures Economiques (OFCE).
  12. Guillaume Chevillon, 2005. "Économétrie de la prévision," Documents de Travail de l'OFCE 2005-11, Observatoire Francais des Conjonctures Economiques (OFCE).
  13. Guillaume Chevillon, 2004. "A Comparison of Multi-step GDP Forecasts for South Africa," Documents de Travail de l'OFCE 2004-13, Observatoire Francais des Conjonctures Economiques (OFCE).
  14. Guillaume Chevillon & David F. Hendry, 2004. "Non-Parametric Direct Multi-step Estimation for Forecasting Economic Processes," Economics Papers 2004-W12, Economics Group, Nuffield College, University of Oxford.
  15. Guillaume Chevillon, 2004. ""Weak" trends for inference and forecasting in finite samples," Documents de Travail de l'OFCE 2004-12, Observatoire Francais des Conjonctures Economiques (OFCE).
  16. Guillaume Chevillon & Christine Rifflart, 2004. "Brouillard autour des puits de pétrole," Sciences Po publications info:hdl:2441/2478, Sciences Po.

Articles

  1. Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
  2. Chevillon, Guillaume & Mavroeidis, Sophocles, 2018. "Perpetual learning and apparent long memory," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 343-365.
  3. Guillaume Chevillon, 2017. "Robust cointegration testing in the presence of weak trends, with an application to the human origin of global warming," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 514-545, May.
  4. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
  5. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
  6. Chevillon, Guillaume & Massmann, Michael & Mavroeidis, Sophocles, 2010. "Inference in models with adaptive learning," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 341-351, April.
  7. 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.
  8. Chevillon, Guillaume & Rifflart, Christine, 2009. "Physical market determinants of the price of crude oil and the market premium," Energy Economics, Elsevier, vol. 31(4), pages 537-549, July.
  9. Guillaume Chevillon, 2007. "Direct Multi-Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
  10. Guillaume Chevillon & Xavier Timbeau, 2006. "L'impact du taux de change sur le tourisme en France," Revue de l'OFCE, Presses de Sciences-Po, vol. 98(3), pages 167-181.
  11. Edmund S. Phelps & Guillaume Chevillon, 2005. "Savoir, information et anticipations en macroéconomie," Revue de l'OFCE, Presses de Sciences-Po, vol. 93(2), pages 7-34.
  12. Guillaume Chevillon, 2005. "Analyse économétrique et compréhension des erreurs de prévision," Revue de l'OFCE, Presses de Sciences-Po, vol. 95(4), pages 327-356.
  13. Chevillon, Guillaume & Hendry, David F., 2005. "Non-parametric direct multi-step estimation for forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 21(2), pages 201-218.

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.

Working papers

  1. Chevillon, Guillaume & Hecq , Alain & Laurent, Sébastien, 2015. "Long Memory Through Marginalization of Large Systems and Hidden Cross-Section Dependence," ESSEC Working Papers WP1507, ESSEC Research Center, ESSEC Business School.

    Cited by:

    1. Hecq Alain & Palm Franz C. & Laurent Sébastien, 2016. "On the Univariate Representation of BEKK Models with Common Factors," Journal of Time Series Econometrics, De Gruyter, vol. 8(2), pages 91-113, July.
    2. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.

  2. Banerjee, Anurag N. & Chevillon, Guillaume & Kratz, Marie, 2013. "Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Coefficient Model," ESSEC Working Papers WP1314, ESSEC Research Center, ESSEC Business School.

    Cited by:

    1. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2018. "Can bubble theory foresee banking crises?," Journal of Financial Stability, Elsevier, vol. 36(C), pages 66-81.
    2. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2016. "Use of unit root methods in early warning of financial crises," Research Discussion Papers 27/2016, Bank of Finland.
    3. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2017. "Use of unit root methods in early warning of financial crises," ESRB Working Paper Series 45, European Systemic Risk Board.

  3. Guillaume Chevillon & Sophocles Mavroeidis, 2013. "Learning generates Long Memory," Post-Print hal-00661012, HAL.

    Cited by:

    1. Rambaccussing, Dooruj, 2015. "Modelling Housing Prices using a Present Value State Space Model," SIRE Discussion Papers 2015-80, Scottish Institute for Research in Economics (SIRE).
    2. Dooruj Rambaccussing, 2015. "Modelling Housing Prices using a Present Value State Space Model," Dundee Discussion Papers in Economics 285, Economic Studies, University of Dundee.
    3. Gilles de Truchis & Florent Dubois, 2014. "Unbalanced Fractional Cointegration and the No-Arbitrage Condition on Commodity Markets," AMSE Working Papers 1445, Aix-Marseille School of Economics, Marseille, France.
    4. Chevillon G. & Hecq A.W. & Laurent S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    5. Tatiana Damjanovic & Sarunas Girdenas & Keqing Liu, 2015. "Stationarity of Econometric Learning with Bounded Memory and a Predicted State Variable," Discussion Papers 1502, Exeter University, Department of Economics.
    6. Rambaccussing, Dooruj, 2015. "Modelling Housing Prices using a Present Value State Space Model," SIRE Discussion Papers 2015-32, Scottish Institute for Research in Economics (SIRE).

  4. Chevillon, Guillaume & Rifflart, Christine, 2007. "Physical Market Determinants of the Price of Crude Oil and the Market Premium," ESSEC Working Papers DR 07020, ESSEC Research Center, ESSEC Business School.

    Cited by:

    1. Ellen, Saskia ter & Zwinkels, Remco C.J., 2010. "Oil price dynamics: A behavioral finance approach with heterogeneous agents," Energy Economics, Elsevier, vol. 32(6), pages 1427-1434, November.
    2. Julien Chevallier & Sofiane Aboura, 2013. "Leverage vs. Feedback: Which Effect Drives the Oil Market ?," Post-Print hal-01531283, HAL.
    3. He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
    4. Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.
    5. Antonio J. Garzón & Luis Á. Hierro, 2018. "Fracking, Wars and Stock Market Crashes: The Price of Oil During the Great Recession," International Journal of Energy Economics and Policy, Econjournals, vol. 8(2), pages 20-30.
    6. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
    7. Sumit Ghosh & N. Sivakumar, 2015. "Beta Clustering of Impact of Crude-Oil Prices on the Indian Economy," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 4(1), pages 24-34.
    8. Biresselioglu, Mehmet Efe & Yelkenci, Tezer, 2016. "Scrutinizing the causality relationships between prices, production and consumption of fossil fuels: A panel data approach," Energy, Elsevier, vol. 102(C), pages 44-53.
    9. Claudio Dicembrino & Pasquale Lucio Scandizzo, 2012. "The Fundamental and Speculative Components of the Oil Spot Price: A Real Option Value Approach," CEIS Research Paper 229, Tor Vergata University, CEIS, revised 18 Apr 2012.
    10. Vansteenkiste, Isabel, 2011. "What is driving oil futures prices? Fundamentals versus speculation," Working Paper Series 1371, European Central Bank.
    11. Fan, Ying & Xu, Jin-Hua, 2011. "What has driven oil prices since 2000? A structural change perspective," Energy Economics, Elsevier, vol. 33(6), pages 1082-1094.
    12. Coleman, Les, 2012. "Explaining crude oil prices using fundamental measures," Energy Policy, Elsevier, vol. 40(C), pages 318-324.
    13. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    14. Robert Socha & Piotr Wdowiński, 2018. "Tendencje zmian cen na światowym rynku ropy naftowej po 2000 roku," Gospodarka Narodowa, Warsaw School of Economics, issue 1, pages 103-135.
    15. Robert Czudaj & Joscha Beckmann, 2012. "Spot and futures commodity markets and the unbiasedness hypothesis - evidence from a novel panel unit root test," Economics Bulletin, AccessEcon, vol. 32(2), pages 1695-1707.
    16. Elbakry, Ashraf E. & Nwachukwu, Jacinta C. & Abdou, Hussein A. & Elshandidy, Tamer, 2017. "Comparative evidence on the value relevance of IFRS-based accounting information in Germany and the UK," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 28(C), pages 10-30.
    17. Sina Aghaei, 2018. "A Data-Driven Approach for Modeling Stochasticity in Oil Market," Papers 1805.12110, arXiv.org.
    18. Kolodzeij, Marek & Kaufmann, Robert.K., 2014. "Oil demand shocks reconsidered: A cointegrated vector autoregression," Energy Economics, Elsevier, vol. 41(C), pages 33-40.
    19. Chai Jian & Wang Shubin & Xiao Hao, 2013. "Abrupt Changes of Global Oil Price," Journal of Systems Science and Information, De Gruyter, vol. 1(1), pages 38-59, February.
    20. Hache, Emmanuel & Lantz, Frédéric, 2013. "Speculative trading and oil price dynamic: A study of the WTI market," Energy Economics, Elsevier, vol. 36(C), pages 334-340.
    21. Jakobsson, Kristofer & Söderbergh, Bengt & Snowden, Simon & Li, Chuan-Zhong & Aleklett, Kjell, 2012. "Oil exploration and perceptions of scarcity: The fallacy of early success," Energy Economics, Elsevier, vol. 34(4), pages 1226-1233.
    22. Kaufmann, Robert K., 2016. "Price differences among crude oils: The private costs of supply disruptions," Energy Economics, Elsevier, vol. 56(C), pages 1-8.
    23. Tobi Olasojiand & Elijah Acquah-Andoh, 2016. "Evaluating The Short Run Effects Of U.S. Crude Oil Inventory Levels On Wti Crude Oil Price From 1993 - 2013," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 4(3), pages 64-84.
    24. Kaufmann, Robert K., 2011. "The role of market fundamentals and speculation in recent price changes for crude oil," Energy Policy, Elsevier, vol. 39(1), pages 105-115, January.
    25. Ai Han & Yanan He & Yongmiao Hong & Shouyang Wang, 2013. "Forecasting Interval-valued Crude Oil Prices via Autoregressive Conditional Interval Models," WISE Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    26. Zhao, Chunfu & Chen, Bin, 2014. "China’s oil security from the supply chain perspective: A review," Applied Energy, Elsevier, vol. 136(C), pages 269-279.
    27. Ekins, Paul & Pollitt, Hector & Barton, Jennifer & Blobel, Daniel, 2011. "The implications for households of environmental tax reform (ETR) in Europe," Ecological Economics, Elsevier, vol. 70(12), pages 2472-2485.
    28. Chevallier, Julien, 2010. "Modelling risk premia in CO2 allowances spot and futures prices," Economic Modelling, Elsevier, vol. 27(3), pages 717-729, May.
    29. Harsem, Øistein & Eide, Arne & Heen, Knut, 2011. "Factors influencing future oil and gas prospects in the Arctic," Energy Policy, Elsevier, vol. 39(12), pages 8037-8045.
    30. Sueyoshi, Toshiyuki, 2010. "An agent-based approach equipped with game theory: Strategic collaboration among learning agents during a dynamic market change in the California electricity crisis," Energy Economics, Elsevier, vol. 32(5), pages 1009-1024, September.
    31. Hahn, Warren J. & DiLellio, James A. & Dyer, James S., 2014. "What do market-calibrated stochastic processes indicate about the long-term price of crude oil?," Energy Economics, Elsevier, vol. 44(C), pages 212-221.
    32. Beckmann, Joscha & Belke, Ansgar & Czudaj, Robert, 2014. "Regime-dependent adjustment in energy spot and futures markets," Economic Modelling, Elsevier, vol. 40(C), pages 400-409.

  5. Guillaume Chevillon, 2006. "Multi-step Forecasting in Unstable Economies: Robustness Issues in the Presence of Location Shifts," Economics Series Working Papers 257, University of Oxford, Department of Economics.

    Cited by:

    1. Jennifer Castle & David Hendry, 2007. "Forecasting UK Inflation: the Roles of Structural Breaks and Time Disaggregation," Economics Series Working Papers 309, University of Oxford, Department of Economics.

  6. Guillaume Chevillon & Xavier Timbeau, 2006. "L’impact du taux de change sur le tourisme en France," Sciences Po publications info:hdl:2441/1743, Sciences Po.

    Cited by:

    1. Christian Stettler, 2017. "How do Overnight Stays React to Exchange Rate Changes?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 153(II), pages 123-165, June.

  7. Guillaume Chevillon, 2005. "Direct multi-step estimation and forecasting," Documents de Travail de l'OFCE 2005-10, Observatoire Francais des Conjonctures Economiques (OFCE).

    Cited by:

    1. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    2. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2015. "Robust approaches to forecasting," International Journal of Forecasting, Elsevier, vol. 31(1), pages 99-112.
    3. 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.
    4. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    5. Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    6. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
    7. Souhaib Ben Taieb & Rob J Hyndman, 2014. "Boosting multi-step autoregressive forecasts," Monash Econometrics and Business Statistics Working Papers 13/14, Monash University, Department of Econometrics and Business Statistics.
    8. Proietti, Tommaso, 2011. "The Multistep Beveridge-Nelson Decomposition," Working Papers 09/2011, University of Sydney Business School, Discipline of Business Analytics.
    9. Buncic, Daniel & Piras, Gion Donat, 2014. "Heterogeneous Agents, the Financial Crisis and Exchange Rate Predictability," Economics Working Paper Series 1436, University of St. Gallen, School of Economics and Political Science, revised Oct 2015.
    10. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2017. "The transmission of monetary policy shocks," Bank of England working papers 657, Bank of England.
    11. Eliana González Molano & Luis Fernando Melo Velandia & Anderson Grajales Olarte, 2007. "Pronósticos directos de la inflación colombiana," Borradores de Economia 458, Banco de la Republica de Colombia.
    12. Souhaib Ben Taieb & Rob J Hyndman, 2012. "Recursive and direct multi-step forecasting: the best of both worlds," Monash Econometrics and Business Statistics Working Papers 19/12, Monash University, Department of Econometrics and Business Statistics.
    13. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2010. "Variable Selection, Estimation and Inference for Multi-period Forecasting Problems," DNB Working Papers 250, Netherlands Central Bank, Research Department.
    14. Ferrara, L. & Marcellino, M. & Mogliani, M., 2012. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," Working papers 383, Banque de France.
    15. Xiong, Tao & Bao, Yukun & Hu, Zhongyi, 2013. "Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices," Energy Economics, Elsevier, vol. 40(C), pages 405-415.
    16. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
    17. Huck, Nicolas, 2010. "Pairs trading and outranking: The multi-step-ahead forecasting case," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1702-1716, December.
    18. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    19. Proietti, Tommaso, 2008. "Direct and iterated multistep AR methods for difference stationary processes," MPRA Paper 10859, University Library of Munich, Germany.
    20. Mansoor Maitah & Daniel Toth & Elena Kuzmenko & Karel Šrédl & Helena Rezbová & Petra Šánová, 2016. "Forecast of Employment in Switzerland: The Macroeconomic View," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 132-138.
    21. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
    22. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
    23. Janine Aron & John Muellbauer & Rachel Sebudde, 2015. "Inflation forecasting models for Uganda: is mobile money relevant?," CSAE Working Paper Series 2015-17, Centre for the Study of African Economies, University of Oxford.
    24. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 15(4), pages 649-677.
    25. Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
    26. Philip Franses, 2014. "Evaluating CPB’s Forecasts," De Economist, Springer, vol. 162(3), pages 215-221, September.
    27. Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
    28. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    29. John Haywood & Granville Tunnicliffe Wilson, 2009. "A test for improved multi-step forecasting," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 682-707, November.
    30. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    31. Gur Ali, Ozden & Pinar, Efe, 2016. "Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series," International Journal of Forecasting, Elsevier, vol. 32(2), pages 502-517.
    32. Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.
    33. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2014. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Post-Print hal-01385941, HAL.
    34. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    35. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2013. "Forecasting US growth during the Great Recession: Is the financial volatility the missing ingredient?," EconomiX Working Papers 2013-19, University of Paris Nanterre, EconomiX.

  8. Guillaume Chevillon, 2005. "Économétrie de la prévision," Documents de Travail de l'OFCE 2005-11, Observatoire Francais des Conjonctures Economiques (OFCE).

    Cited by:

    1. Pinshi, Christian & Mukendi, Christian & Ndombe, Patrick, 2015. "Prévision du coefficient de la réserve obligatoire de la Banque centrale du Congo
      [Forecasting of the coefficient of the reserve requirement of the Central bank of Congo]
      ," MPRA Paper 79769, University Library of Munich, Germany, revised May 2017.

  9. Guillaume Chevillon & David F. Hendry, 2004. "Non-Parametric Direct Multi-step Estimation for Forecasting Economic Processes," Economics Papers 2004-W12, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    2. Protić, Milan & Shamshirband, Shahaboddin & Petković, Dalibor & Abbasi, Almas & Mat Kiah, Miss Laiha & Unar, Jawed Akhtar & Živković, Ljiljana & Raos, Miomir, 2015. "Forecasting of consumers heat load in district heating systems using the support vector machine with a discrete wavelet transform algorithm," Energy, Elsevier, vol. 87(C), pages 343-351.
    3. Jari Hännikäinen, 2014. "Multi-step forecasting in the presence of breaks," Working Papers 1494, University of Tampere, School of Management, Economics.
    4. 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.
    5. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    6. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    7. Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    8. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.
    9. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
    10. Guillaume Chevillon, 2004. "A Comparison of Multi-step GDP Forecasts for South Africa," Economics Series Working Papers 212, University of Oxford, Department of Economics.
    11. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    12. Guérin, Pierre & Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    13. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    14. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo, vol. 56(2), pages 192-220, June.
    15. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
    16. Buncic, Daniel & Piras, Gion Donat, 2014. "Heterogeneous Agents, the Financial Crisis and Exchange Rate Predictability," Economics Working Paper Series 1436, University of St. Gallen, School of Economics and Political Science, revised Oct 2015.
    17. Eliana González Molano & Luis Fernando Melo Velandia & Anderson Grajales Olarte, 2007. "Pronósticos directos de la inflación colombiana," Borradores de Economia 458, Banco de la Republica de Colombia.
    18. Guillaume Chevillon, 2004. ""Weak" trends for inference and forecasting in finite samples," Documents de Travail de l'OFCE 2004-12, Observatoire Francais des Conjonctures Economiques (OFCE).
    19. Hendry, David F., 2006. "Robustifying forecasts from equilibrium-correction systems," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 399-426.
    20. Souhaib Ben Taieb & Rob J Hyndman, 2012. "Recursive and direct multi-step forecasting: the best of both worlds," Monash Econometrics and Business Statistics Working Papers 19/12, Monash University, Department of Econometrics and Business Statistics.
    21. Jalal Shiri & Shahaboddin Shamshirband & Ozgur Kisi & Sepideh Karimi & Seyyed M Bateni & Seyed Hossein Hosseini Nezhad & Arsalan Hashemi, 2016. "Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5217-5229, November.
    22. Alfred A. Haug & Christie Smith, 2007. "Local linear impulse responses for a small open economy," Working Papers 0707, University of Otago, Department of Economics, revised Apr 2007.
    23. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    24. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, August.
    25. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    26. Peng, Bo & Song, Haiyan & Crouch, Geoffrey I., 2014. "A meta-analysis of international tourism demand forecasting and implications for practice," Tourism Management, Elsevier, vol. 45(C), pages 181-193.
    27. Michael P. Clements & David F. Hendry, 2005. "Guest Editors' Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
    28. Ching Wai (Jeremy) Chiu & Bjørn Eraker & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2011. "Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach," Research Working Paper RWP 11-11, Federal Reserve Bank of Kansas City.
    29. Marie Bessec & Othman Bouabdallah, 2015. "Forecasting GDP over the Business Cycle in a Multi-Frequency and Data-Rich Environment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 360-384, June.
    30. Kisi, Ozgur & Shiri, Jalal & Karimi, Sepideh & Shamshirband, Shahaboddin & Motamedi, Shervin & Petković, Dalibor & Hashim, Roslan, 2015. "A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 731-743.
    31. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
    32. 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.
    33. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
    34. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    35. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    36. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
    37. John Haywood & Granville Tunnicliffe Wilson, 2009. "A test for improved multi-step forecasting," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 682-707, November.
    38. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Economics Working Papers ECO2008/16, European University Institute.
    39. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    40. Gur Ali, Ozden & Pinar, Efe, 2016. "Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series," International Journal of Forecasting, Elsevier, vol. 32(2), pages 502-517.
    41. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    42. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    43. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
    44. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    45. Johannes Mayr & Dirk Ulbricht, 2007. "VAR Model Averaging for Multi-Step Forecasting," ifo Working Paper Series 48, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    46. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    47. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
    48. Jennifer Castle & David Hendry, 2007. "Forecasting UK Inflation: the Roles of Structural Breaks and Time Disaggregation," Economics Series Working Papers 309, University of Oxford, Department of Economics.

  10. Guillaume Chevillon, 2004. ""Weak" trends for inference and forecasting in finite samples," Documents de Travail de l'OFCE 2004-12, Observatoire Francais des Conjonctures Economiques (OFCE).

    Cited by:

    1. Guillaume Chevillon, 2004. "A Comparison of Multi-step GDP Forecasts for South Africa," Economics Series Working Papers 212, University of Oxford, Department of Economics.

Articles

  1. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.

    Cited by:

    1. Chevillon G. & Hecq A.W. & Laurent S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    2. Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
    3. Chevillon, Guillaume & Mavroeidis, Sophocles, 2018. "Perpetual learning and apparent long memory," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 343-365.

  2. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.

    Cited by:

    1. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-04, Towson University, Department of Economics, revised Dec 2015.

  3. Chevillon, Guillaume & Massmann, Michael & Mavroeidis, Sophocles, 2010. "Inference in models with adaptive learning," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 341-351, April.

    Cited by:

    1. Stefano Eusepi & Bruce Preston, 2008. "Expectations, Learning And Business Cycle Fluctuations," CAMA Working Papers 2008-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Sophocles N. Brissimis & Petros M. Migiakis, 2016. "Inflation persistence, learning dynamics and the rationality of inflation expectations," Empirical Economics, Springer, vol. 51(3), pages 963-979, November.
    3. Giovanni Angelini & Luca Fanelli Fanelli, 2015. "Misspecification and Expectations Correction in New Keynesian DSGE Models," Quaderni di Dipartimento 1, Department of Statistics, University of Bologna.
    4. Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
    5. Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
    6. Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014. "A nonlinear panel data model of cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 179(2), pages 134-157.
    7. Norbert Christopeit & Michael Massmann, 2017. "Strong consistency of the least squares estimator in regression models with adaptive learning," WHU Working Paper Series - Economics Group 17-07, WHU - Otto Beisheim School of Management.
    8. Norbert Christopeit & Michael Massmann, 2013. "A Note on an Estimation Problem in Models with Adaptive Learning," Tinbergen Institute Discussion Papers 13-151/III, Tinbergen Institute.
    9. Norbert Christopeit & Michael Massmann, 2013. "Estimating Structural Parameters in Regression Models with Adaptive Learning," Tinbergen Institute Discussion Papers 13-111/III, Tinbergen Institute.
    10. Norbert Christopeit & Michael Massmann, 2012. "Strong Consistency of the Least-Squares Estimator in Simple Regression Models with Stochastic Regressors," Tinbergen Institute Discussion Papers 12-109/III, Tinbergen Institute.
    11. Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
    12. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2013. "Identification-robust analysis of DSGE and structural macroeconomic models," Journal of Monetary Economics, Elsevier, vol. 60(3), pages 340-350.
    13. Eric Gaus & Srikanth Ramamurthy, 2012. "Estimation of Constant Gain Learning Models," Working Papers 12-01, Ursinus College, Department of Economics, revised 01 Apr 2014.
    14. Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.
    15. Sophocles N. Brissimis & Petros M. Migiakis, 2013. "Inflation persistence and the rationality of inflation expectations," Working Papers 151, Bank of Greece.
    16. Norbert Christopeit & Michael Massmann, 2010. "Consistent Estimation of Structural Parameters in Regression Models with Adaptive Learning," Tinbergen Institute Discussion Papers 10-077/4, Tinbergen Institute.
    17. Eva A. Arnold, 2013. "The Role of Data Revisions and Disagreement in Professional Forecasts," Macroeconomics and Finance Series 201303, University of Hamburg, Department of Socioeconomics.
    18. William Branch & Bruce McGough, 2011. "Business cycle amplification with heterogeneous expectations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 47(2), pages 395-421, June.
    19. Chevillon, Guillaume & Mavroeidis, Sophocles, 2018. "Perpetual learning and apparent long memory," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 343-365.
    20. Norbert Christopeit & Michael Massmann, 2018. "Strong consistency of the least squares estimator in regression models with adaptive learning," Tinbergen Institute Discussion Papers 18-045/III, Tinbergen Institute.
    21. Agnieszka Markiewicz, 2012. "Model Uncertainty And Exchange Rate Volatility," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 815-844, August.

  4. 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.

    Cited by:

    1. Guillaume Chevillon, 2007. "Direct Multi-Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    2. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Wang, Jianzhou & Song, Yiliao & Liu, Feng & Hou, Ru, 2016. "Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 960-981.
    4. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.

  5. Chevillon, Guillaume & Rifflart, Christine, 2009. "Physical market determinants of the price of crude oil and the market premium," Energy Economics, Elsevier, vol. 31(4), pages 537-549, July.
    See citations under working paper version above.
  6. Guillaume Chevillon, 2007. "Direct Multi-Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    See citations under working paper version above.
  7. Guillaume Chevillon & Xavier Timbeau, 2006. "L'impact du taux de change sur le tourisme en France," Revue de l'OFCE, Presses de Sciences-Po, vol. 98(3), pages 167-181.
    See citations under working paper version above.
  8. Chevillon, Guillaume & Hendry, David F., 2005. "Non-parametric direct multi-step estimation for forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 21(2), pages 201-218.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 16 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ETS: Econometric Time Series (10) 2004-07-11 2004-12-20 2007-12-15 2013-10-18 2014-01-17 2015-06-13 2015-08-19 2015-08-25 2015-08-25 2015-09-26. Author is listed
  2. NEP-ECM: Econometrics (6) 2004-07-17 2006-03-18 2007-12-15 2013-10-18 2015-06-13 2015-08-19. Author is listed
  3. NEP-FOR: Forecasting (3) 2006-03-18 2013-10-18 2015-08-25
  4. NEP-CBA: Central Banking (2) 2012-02-01 2012-02-27
  5. NEP-DGE: Dynamic General Equilibrium (2) 2012-02-01 2012-02-27
  6. NEP-MAC: Macroeconomics (2) 2004-12-20 2006-03-18
  7. NEP-MIC: Microeconomics (2) 2007-12-08 2012-02-27
  8. NEP-ORE: Operations Research (2) 2015-06-13 2015-09-26
  9. NEP-URE: Urban & Real Estate Economics (2) 2013-10-18 2015-08-25
  10. NEP-AFR: Africa (1) 2004-12-20
  11. NEP-BEC: Business Economics (1) 2007-12-08
  12. NEP-CMP: Computational Economics (1) 2012-02-01
  13. NEP-CSE: Economics of Strategic Management (1) 2006-01-29
  14. NEP-EEC: European Economics (1) 2006-01-29
  15. NEP-ENE: Energy Economics (1) 2007-12-08
  16. NEP-ENV: Environmental Economics (1) 2014-01-17

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