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Marie Bessec

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. Marie Bessec, 2019. "Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data," Post-Print hal-02181552, HAL.

    Cited by:

    1. Pan, Zhiyuan & Xiao, Dongli & Dong, Qingma & Liu, Li, 2022. "Structural breaks, macroeconomic fundamentals and cross hedge ratio," Finance Research Letters, Elsevier, vol. 47(PA).
    2. Holmberg, Johan, 2021. "Earnings and Employment Dynamics: Capturing Cyclicality using Mixed Frequency Data," Umeå Economic Studies 991, Umeå University, Department of Economics.

  2. Marie Bessec & Julien Fouquau, 2018. "Short-run electricity load forecasting with combinations of stationary wavelet transforms," Post-Print hal-01644930, HAL.

    Cited by:

    1. Christina C. Bartenschlager & Jens O. Brunner, 2019. "Reaching for the stars: attention to multiple testing problems and method recommendations using simulation for business research," Journal of Business Economics, Springer, vol. 89(4), pages 447-479, June.
    2. Lee, Juyong & Cho, Youngsang, 2022. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Energy, Elsevier, vol. 239(PD).
    3. Barja-Martinez, Sara & Aragüés-Peñalba, Mònica & Munné-Collado, Íngrid & Lloret-Gallego, Pau & Bullich-Massagué, Eduard & Villafafila-Robles, Roberto, 2021. "Artificial intelligence techniques for enabling Big Data services in distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    4. Sen, Doruk & Tunç, K.M. Murat & Günay, M. Erdem, 2021. "Forecasting electricity consumption of OECD countries: A global machine learning modeling approach," Utilities Policy, Elsevier, vol. 70(C).
    5. Guo-Feng Fan & Li-Ling Peng & Xiangjun Zhao & Wei-Chiang Hong, 2017. "Applications of Hybrid EMD with PSO and GA for an SVR-Based Load Forecasting Model," Energies, MDPI, vol. 10(11), pages 1-22, October.
    6. Zhou, Cheng & Chen, Xiyang, 2019. "Predicting energy consumption: A multiple decomposition-ensemble approach," Energy, Elsevier, vol. 189(C).
    7. Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
    8. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    9. Yajing Gao & Xiaojie Zhou & Jiafeng Ren & Zheng Zhao & Fushen Xue, 2018. "Electricity Purchase Optimization Decision Based on Data Mining and Bayesian Game," Energies, MDPI, vol. 11(5), pages 1-19, April.
    10. Daniel v{S}tifani'c & Jelena Musulin & Adrijana Miov{c}evi'c & Sandi Baressi v{S}egota & Roman v{S}ubi'c & Zlatan Car, 2020. "Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory," Papers 2007.02673, arXiv.org.
    11. Wei, Nan & Yin, Lihua & Li, Chao & Wang, Wei & Qiao, Weibiao & Li, Changjun & Zeng, Fanhua & Fu, Lingdi, 2022. "Short-term load forecasting using detrend singular spectrum fluctuation analysis," Energy, Elsevier, vol. 256(C).
    12. Vincenzo Loia & Stefania Tomasiello & Alfredo Vaccaro & Jinwu Gao, 2020. "Using local learning with fuzzy transform: application to short term forecasting problems," Fuzzy Optimization and Decision Making, Springer, vol. 19(1), pages 13-32, March.
    13. Zhang, Jinliang & Wei, Yi-Ming & Li, Dezhi & Tan, Zhongfu & Zhou, Jianhua, 2018. "Short term electricity load forecasting using a hybrid model," Energy, Elsevier, vol. 158(C), pages 774-781.
    14. Mesbaholdin Salami & Farzad Movahedi Sobhani & Mohammad Sadegh Ghazizadeh, 2018. "Short-Term Forecasting of Electricity Supply and Demand by Using the Wavelet-PSO-NNs-SO Technique for Searching in Big Data of Iran’s Electricity Market," Data, MDPI, vol. 3(4), pages 1-26, October.
    15. Zhang, Jinliang & Siya, Wang & Zhongfu, Tan & Anli, Sun, 2023. "An improved hybrid model for short term power load prediction," Energy, Elsevier, vol. 268(C).
    16. Miguel López & Sergio Valero & Carlos Sans & Carolina Senabre, 2020. "Use of Available Daylight to Improve Short-Term Load Forecasting Accuracy," Energies, MDPI, vol. 14(1), pages 1-14, December.
    17. Koch, Christopher & Hirth, Lion, 2019. "Short-term electricity trading for system balancing: An empirical analysis of the role of intraday trading in balancing Germany's electricity system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    18. Lintao Yang & Honggeng Yang & Haitao Liu, 2018. "GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting," Sustainability, MDPI, vol. 10(1), pages 1-16, January.
    19. Ding, Jia & Wang, Maolin & Ping, Zuowei & Fu, Dongfei & Vassiliadis, Vassilios S., 2020. "An integrated method based on relevance vector machine for short-term load forecasting," European Journal of Operational Research, Elsevier, vol. 287(2), pages 497-510.
    20. Yuri S. Popkov & Alexey Yu. Popkov & Yuri A. Dubnov & Dimitri Solomatine, 2020. "Entropy-Randomized Forecasting of Stochastic Dynamic Regression Models," Mathematics, MDPI, vol. 8(7), pages 1-20, July.
    21. Dai, Yeming & Yang, Xinyu & Leng, Mingming, 2022. "Forecasting power load: A hybrid forecasting method with intelligent data processing and optimized artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    22. Tayab, Usman Bashir & Lu, Junwei & Yang, Fuwen & AlGarni, Tahani Saad & Kashif, Muhammad, 2021. "Energy management system for microgrids using weighted salp swarm algorithm and hybrid forecasting approach," Renewable Energy, Elsevier, vol. 180(C), pages 467-481.
    23. Kailai Ni & Jianzhou Wang & Guangyu Tang & Danxiang Wei, 2019. "Research and Application of a Novel Hybrid Model Based on a Deep Neural Network for Electricity Load Forecasting: A Case Study in Australia," Energies, MDPI, vol. 12(13), pages 1-30, June.
    24. V. Y. Kondaiah & B. Saravanan, 2022. "Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method," Energies, MDPI, vol. 15(14), pages 1-17, July.

  3. Kheira Benhami & Marie Bessec & Guillaume Gilquin, 2017. "Les tensions sur le marché du crédit de trésorerie en France dans une perspective historique," Post-Print hal-01645409, HAL.

    Cited by:

    1. Refait-Alexandre, Catherine & Serve, Stéphanie, 2020. "Multiple banking relationships: Do SMEs mistrust their banks?," Research in International Business and Finance, Elsevier, vol. 51(C).

  4. Marie Bessec & Julien Fouquau & Sophie Meritet, 2016. "Forecasting electricity spot prices using time-series models with a double temporal segmentation," Post-Print hal-01276807, HAL.

    Cited by:

    1. Bartosz Uniejewski & Jakub Nowotarski & Rafal Weron, 2016. "Automated variable selection and shrinkage for day-ahead electricity price forecasting," HSC Research Reports HSC/16/06, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    2. Marie Bessec & Julien Fouquau, 2018. "Short-run electricity load forecasting with combinations of stationary wavelet transforms," Post-Print hal-01644930, HAL.
    3. Mohammad Nure Alam, 2021. "Accessing the Effect of Renewables on the Wholesale Power Market," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 341-360.
    4. Hryshchuk, Antanina & Lessmann, Stefan, 2018. "Deregulated day-ahead electricity markets in Southeast Europe: Price forecasting and comparative structural analysis," IRTG 1792 Discussion Papers 2018-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Caputo, Antonio C. & Federici, Alessandro & Pelagagge, Pacifico M. & Salini, Paolo, 2023. "Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty," Applied Energy, Elsevier, vol. 350(C).

  5. Marie Bessec & Catherine Doz, 2014. "Short-term forecasting of French GDP growth using dynamic factor models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01515602, HAL.

    Cited by:

    1. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
    2. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    3. Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024. "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 3-25, June.
    4. Danilo Cascaldi-Garcia & Thiago Revil T. Ferreira & Domenico Giannone & Michele Modugno, 2021. "Back to the Present: Learning about the Euro Area through a Now-casting Model," International Finance Discussion Papers 1313, Board of Governors of the Federal Reserve System (U.S.).

  6. Bessec, M., 2012. "Short-term forecasts of French GDP: a dynamic factor model with targeted predictors," Working papers 409, Banque de France.

    Cited by:

    1. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    2. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    3. Enrico D’Elia & Francesca Faedda & Giacomo Giannone, 2020. "Un modello statistico per il monitoraggio delle entrate tributarie (MoME)," Working Papers wp2020-5, Ministry of Economy and Finance, Department of Finance.
    4. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
    5. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
    6. Mogliani, M. & Brunhes-Lesage, V. & Darné, O. & Pluyaud, B., 2014. "New estimate of the MIBA forecasting model. Modeling first-release GDP using the Banque de France's Monthly Business Survey and the “blocking” approach," Working papers 473, Banque de France.
    7. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    8. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    9. Ademmer, Martin & Boysen-Hogrefe, Jens & Carstensen, Kai & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Rossian, Thies & Stolzenburg, Ulrich, 2019. "Schätzung von Produktionspotenzial und -lücke: Eine Analyse des EU-Verfahrens und mögliche Verbesserungen," Kieler Beiträge zur Wirtschaftspolitik 19, Kiel Institute for the World Economy (IfW Kiel).
    10. Aysun, Uluc & Wright, Cardel, 2024. "A two-step dynamic factor modelling approach for forecasting inflation in small open economies," Emerging Markets Review, Elsevier, vol. 62(C).
    11. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.

  7. Bec, F. & Bessec, M., 2012. "Inventory Investment Dynamics and Recoveries: A Comparison of Manufacturing and Retail Trade Sectors," Working papers 400, Banque de France.

    Cited by:

    1. Jean Barthélemy & Magali Marx, 2012. "Generalizing the Taylor Principle: New Comment," SciencePo Working papers Main hal-03461113, HAL.

  8. Marie Bessec & Catherine Doz, 2012. "Prévision de court terme de la croissance du PIB français à l’aide de modèles à facteurs dynamiques," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01515627, HAL.

    Cited by:

    1. Zouri, Stéphane, 2019. "Business cycles,bilateral trade and international financial intergration : Evidence from Economic Community of West African States (ECOWAS)," MPRA Paper 98748, University Library of Munich, Germany.
    2. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    3. Zouri, Stéphane, 2019. "Business cycles,bilateral trade and international financial intergration : Evidence from Economic Community of West African States (ECOWAS)," MPRA Paper 95275, University Library of Munich, Germany.
    4. Nicolas Chatelais & Menzie Chinn & Arthur Stalla-Bourdillon, 2022. "Macroeconomic Forecasting Using Filtered Signals from a Stock Market Cross Section," Working papers 903, Banque de France.
    5. Zouri, Stéphane, 2020. "Business cycles, bilateral trade and financial integration: Evidence from Economic Community of West African States (ECOWAS)," International Economics, Elsevier, vol. 163(C), pages 25-43.

  9. Bessec, M. & Bouabdallah, O., 2012. "Forecasting GDP over the business cycle in a multi-frequency and data-rich environment," Working papers 384, Banque de France.

    Cited by:

    1. Catherine Doz & Anna Petronevich, 2017. "On the consistency of the two-step estimates of the MS-DFM: a Monte Carlo study," Working Papers halshs-01592863, HAL.
    2. Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    3. Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02491811, HAL.
    4. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
    5. Marie Bessec, 2019. "Revisiting the transitional dynamics of business cycle phases with mixed-frequency data," Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 711-732, August.
    6. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    7. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    8. Marie Bessec, 2015. "Revisiting the transitional dynamics of business-cycle phases with mixed frequency data," Post-Print hal-01276824, HAL.
    9. Fady Barsoum, 2015. "Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model," Working Paper Series of the Department of Economics, University of Konstanz 2015-19, Department of Economics, University of Konstanz.
    10. Zhang, Wei & He, Jie & Ge, Chanyuan & Xue, Rui, 2022. "Real-time macroeconomic monitoring using mixed frequency data: Evidence from China," Economic Modelling, Elsevier, vol. 117(C).
    11. Qian Chen & Xiang Gao & Shan Xie & Li Sun & Shuairu Tian & Shigeyuki Hamori, 2021. "On the Predictability of China Macro Indicator with Carbon Emissions Trading," Energies, MDPI, vol. 14(5), pages 1-24, February.
    12. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

  10. Marie Bessec & Julien Fouquau, 2008. "The non-linear link between electricity consumption and temperature in Europe: a threshold panel approach," Post-Print halshs-00222934, HAL.

    Cited by:

    1. Avraam, Charalampos & Ceferino, Luis & Dvorkin, Yury, 2023. "Operational and economy-wide impacts of compound cyber-attacks and extreme weather events on electric power networks," Applied Energy, Elsevier, vol. 349(C).
    2. Ibrahim Ahamada & Dramane Coulibaly, 2011. "How does financial development influence the impact of remittances on growth volatility?," Post-Print hal-00629898, HAL.
    3. Po-Chin Wu & Chung-Chih Lee, 2018. "The non-linear impact of monetary policy on international reserves: macroeconomic variables nexus," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 165-185, February.
    4. Kahia, Montassar & Moulahi, Tarek & Mahfoudhi, Sami & Boubaker, Sabri & Omri, Anis, 2022. "A machine learning process for examining the linkage among disaggregated energy consumption, economic growth, and environmental degradation," Resources Policy, Elsevier, vol. 79(C).
    5. Derumigny Alexis & Fermanian Jean-David, 2019. "On kernel-based estimation of conditional Kendall’s tau: finite-distance bounds and asymptotic behavior," Dependence Modeling, De Gruyter, vol. 7(1), pages 292-321, January.
    6. Chevallier, Julien, 2009. "Carbon futures and macroeconomic risk factors: A view from the EU ETS," Energy Economics, Elsevier, vol. 31(4), pages 614-625, July.
    7. Psiloglou, B.E. & Giannakopoulos, C. & Majithia, S. & Petrakis, M., 2009. "Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessment," Energy, Elsevier, vol. 34(11), pages 1855-1863.
    8. Anne-Laure Delatte & Julien Fouquau, 2012. "Le retour des motifs mercantilistes dans la demande de réserves internationales des pays émergents," Revue économique, Presses de Sciences-Po, vol. 63(5), pages 1013-1023.
    9. Andres Gonzalez & Timo Terasvirta & Dick van Dijk, 2005. "Panel Smooth Transition Regression Models," Research Paper Series 165, Quantitative Finance Research Centre, University of Technology, Sydney.
    10. Khan, Muhammad Arshad & Abbas, Faisal, 2016. "The dynamics of electricity demand in Pakistan: A panel cointegration analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1159-1178.
    11. Peter Kudela & Tomas Havranek & Dominik Herman & Zuzana Irsova, 2019. "Does Daylight Saving Time Save Electricity? Evidence from Slovakia," Working Papers IES 2019/4, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2019.
    12. Bašta, Milan & Helman, Karel, 2013. "Scale-specific importance of weather variables for explanation of variations of electricity consumption: The case of Prague, Czech Republic," Energy Economics, Elsevier, vol. 40(C), pages 503-514.
    13. Doğan, Buhari & Ghosh, Sudeshna & Hoang, Dung Phuong & Chu, Lan Khanh, 2022. "Are economic complexity and eco-innovation mutually exclusive to control energy demand and environmental quality in E7 and G7 countries?," Technology in Society, Elsevier, vol. 68(C).
    14. Rafik JBIR, 2021. "Temperature, energy consumption, and Co2 emission: testing for nonlinearity on USA Economy," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 12434-12445, August.
    15. Kang, J. & Reiner, D., 2021. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Cambridge Working Papers in Economics 2141, Faculty of Economics, University of Cambridge.
    16. Lee, Chien-Chiang & Chiu, Yi-Bin, 2011. "Electricity demand elasticities and temperature: Evidence from panel smooth transition regression with instrumental variable approach," Energy Economics, Elsevier, vol. 33(5), pages 896-902, September.
    17. Knaut, Andreas & Paulus, Simon, 2016. "When are consumers responding to electricity prices? An hourly pattern of demand elasticity," EWI Working Papers 2016-7, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI), revised 16 Mar 2017.
    18. Wu, Po-Chin & Liu, Shiao-Yen & Chen, Che-Ying, 2016. "Re-examining risk premiums in the Fama–French model: The role of investor sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 154-171.
    19. Po-Chin Wu & Shiao-Yen Liu & Ming-Fang Yang, 2017. "Nonlinear Exchange Rate Pass-Through: The Role of National Debt," Global Economic Review, Taylor & Francis Journals, vol. 46(1), pages 1-17, January.
    20. Kim, Young Se, 2015. "Electricity consumption and economic development: Are countries converging to a common trend?," Energy Economics, Elsevier, vol. 49(C), pages 192-202.
    21. Desiderio Romero-Jordán & Pablo del Río & Cristina Peñasco, 2014. "Household electricity demand in Spanish regions. Public policy implications," Working Papers 2014/24, Institut d'Economia de Barcelona (IEB).
    22. Meixuan Teng & Hua Liao & Paul J. Burke & Tianqi Chen & Chen Zhang, 2022. "Adaptive responses: the effects of temperature levels on residential electricity use in China," Climatic Change, Springer, vol. 172(3), pages 1-20, June.
    23. Wang, Huiqing & Wei, Weixian, 2020. "Coordinating technological progress and environmental regulation in CO2 mitigation: The optimal levels for OECD countries & emerging economies," Energy Economics, Elsevier, vol. 87(C).
    24. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    25. Chen Zhang & Hua Liao & Zhifu Mi, 2019. "Climate impacts: temperature and electricity consumption," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(3), pages 1259-1275, December.
    26. Wang, Yu Shan, 2013. "Oil price effects on personal consumption expenditures," Energy Economics, Elsevier, vol. 36(C), pages 198-204.
    27. Moral-Carcedo, Julián & Pérez-García, Julián, 2019. "Time of day effects of temperature and daylight on short term electricity load," Energy, Elsevier, vol. 174(C), pages 169-183.
    28. Chen, Haitao & Zhang, Bin & Liu, Hua & Cao, Jiguo, 2024. "The inequality in household electricity consumption due to temperature change: Data driven analysis with a function-on-function linear model," Energy, Elsevier, vol. 288(C).
    29. Ozhegov, Evgeniy & Popova, Evgeniya, 2017. "Demand for electricity and weather conditions: Nonparametric analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 55-73.
    30. Blazquez Leticia & Nina Boogen & Massimo Filippini, 2012. "Residential electricity demand for Spain: new empirical evidence using aggregated data," CEPE Working paper series 12-82, CEPE Center for Energy Policy and Economics, ETH Zurich.
    31. Zeng, Sheng & Su, Bin & Zhang, Minglong & Gao, Yuan & Liu, Jun & Luo, Song & Tao, Qingmei, 2021. "Analysis and forecast of China's energy consumption structure," Energy Policy, Elsevier, vol. 159(C).
    32. Matthew Ranson & Lauren Morris & Alex Kats-Rubin, 2014. "Climate Change and Space Heating Energy Demand: A Review of the Literature," NCEE Working Paper Series 201407, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Dec 2014.
    33. McDermott, Grant R. & Nilsen, Øivind A., 2011. "Electricity Prices, River Temperatures and Cooling Water Scarcity," Discussion Paper Series in Economics 18/2011, Norwegian School of Economics, Department of Economics.
    34. Małgorzata Cygańska & Magdalena Kludacz-Alessandri, 2021. "Determinants of Electrical and Thermal Energy Consumption in Hospitals According to Climate Zones in Poland," Energies, MDPI, vol. 14(22), pages 1-24, November.
    35. Po-Chin Wu & Shiao-Yen Liu & Sheng-Chieh Pan, 2014. "Does Misery Index Matter for the Persistence of Health Spending? Evidence from OECD Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(2), pages 893-910, September.
    36. Wang, Yaoping & Bielicki, Jeffrey M., 2018. "Acclimation and the response of hourly electricity loads to meteorological variables," Energy, Elsevier, vol. 142(C), pages 473-485.
    37. Räsänen, Teemu & Voukantsis, Dimitrios & Niska, Harri & Karatzas, Kostas & Kolehmainen, Mikko, 2010. "Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data," Applied Energy, Elsevier, vol. 87(11), pages 3538-3545, November.
    38. Huang, Junbing & Li, Xinghao & Wang, Yajun & Lei, Hongyan, 2021. "The effect of energy patents on China's carbon emissions: Evidence from the STIRPAT model," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    39. Marie Bessec & Julien Fouquau, 2018. "Short-run electricity load forecasting with combinations of stationary wavelet transforms," Post-Print hal-01644930, HAL.
    40. Chang, Chih-Hao & Chen, Zih-Bing & Huang, Shih-Feng, 2022. "Forecasting of high-resolution electricity consumption with stochastic climatic covariates via a functional time series approach," Applied Energy, Elsevier, vol. 309(C).
    41. Hekkenberg, M. & Moll, H.C. & Uiterkamp, A.J.M. Schoot, 2009. "Dynamic temperature dependence patterns in future energy demand models in the context of climate change," Energy, Elsevier, vol. 34(11), pages 1797-1806.
    42. Anne-Laure Delatte & Julien Fouquau, 2012. "What drove the massive hoarding of international reserves? A time-varying approach," Post-Print hal-00822294, HAL.
    43. Hekkenberg, M. & Benders, R.M.J. & Moll, H.C. & Schoot Uiterkamp, A.J.M., 2009. "Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands," Energy Policy, Elsevier, vol. 37(4), pages 1542-1551, April.
    44. Anne‐Laure Delatte & Julien Fouquau, 2012. "What Drove the Massive Hoarding of International Reserves in Emerging Economies? A Time‐varying Approach," Review of International Economics, Wiley Blackwell, vol. 20(1), pages 164-176, February.
    45. Duarte, Rosa & Pinilla, Vicente & Serrano, Ana, 2013. "Is there an environmental Kuznets curve for water use? A panel smooth transition regression approach," Economic Modelling, Elsevier, vol. 31(C), pages 518-527.
    46. Hu, Wenxuan & Scholz, Yvonne & Yeligeti, Madhura & Deng, Ying & Jochem, Patrick, 2024. "Future electricity demand for Europe: Unraveling the dynamics of the Temperature Response Function," Applied Energy, Elsevier, vol. 368(C).
    47. Anthoff, David & Tol, Richard S. J., 2011. "The Uncertainty about the Social Cost of Carbon: A Decomposition Analysis Using FUND," Papers WP404, Economic and Social Research Institute (ESRI).
    48. Chabouni, Naima & Belarbi, Yacine & Benhassine, Wassim, 2020. "Electricity load dynamics, temperature and seasonality Nexus in Algeria," Energy, Elsevier, vol. 200(C).
    49. Borck, Rainald, 2014. "Will skyscrapers save the planet?," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100566, Verein für Socialpolitik / German Economic Association.
    50. Waite, Michael & Cohen, Elliot & Torbey, Henri & Piccirilli, Michael & Tian, Yu & Modi, Vijay, 2017. "Global trends in urban electricity demands for cooling and heating," Energy, Elsevier, vol. 127(C), pages 786-802.
    51. Du, Kerui & Yu, Ying & Wei, Chu, 2020. "Climatic impact on China's residential electricity consumption: Does the income level matter?," China Economic Review, Elsevier, vol. 63(C).
    52. Po-Chin Wu & Shiao-Yen Liu & Kou-Bau Wang, 2017. "Does Unemployment Matter for Lottery Sales and their Persistence? A New Estimation Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(2), pages 581-592, January.
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    81. Deng, Nana & Wang, Bo & Qiu, Yueming & Liu, Jie & Shi, Han & Zhang, Bin & Wang, Zhaohua, 2022. "The discrepancies in the impacts of COVID-19 lockdowns on electricity consumption in China: Is the short-term pain worth it?," Energy Economics, Elsevier, vol. 114(C).
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    83. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand," Working Papers 1409, Department of Economics, University of Missouri.
    84. Davinson Stev Abril Salcedo & Luis Fernando Melo-Velandia & Daniel Parra-Amado, 2019. "Nonlinear relationship between the weather phenomenon El Niño and Colombian food prices," Borradores de Economia 1085, Banco de la Republica de Colombia.
    85. Yi, Fujin & Ye, Haijian & Wu, Ximing & Zhang, Y. Yvette & Jiang, Fei, 2020. "Self-aggravation effect of air pollution: Evidence from residential electricity consumption in China," Energy Economics, Elsevier, vol. 86(C).
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    87. Yabin Da & Bin Zeng & Jing-Li Fan & Jiawei Hu & Lanlan Li, 2023. "Heterogeneous responses to climate: evidence from residential electricity consumption," Climatic Change, Springer, vol. 176(8), pages 1-19, August.
    88. Fan, Jing-Li & Hu, Jia-Wei & Zhang, Xian, 2019. "Impacts of climate change on electricity demand in China: An empirical estimation based on panel data," Energy, Elsevier, vol. 170(C), pages 880-888.
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    90. Marilyn Brown & Matt Cox & Ben Staver & Paul Baer, 2016. "Modeling climate-driven changes in U.S. buildings energy demand," Climatic Change, Springer, vol. 134(1), pages 29-44, January.
    91. De Felice, Matteo & Alessandri, Andrea & Catalano, Franco, 2015. "Seasonal climate forecasts for medium-term electricity demand forecasting," Applied Energy, Elsevier, vol. 137(C), pages 435-444.
    92. Tiaoye Li & Lingjiang Tao & Mi Zhang, 2024. "Projection of Non-Industrial Electricity Consumption in China’s Pearl River Delta under Global Warming Scenarios," Sustainability, MDPI, vol. 16(5), pages 1-17, February.
    93. Tong Wu & Zhe You & Mengqi Gong & Jinhua Cheng, 2021. "Star Wars? Space Weather and Electricity Market: Evidence from China," Energies, MDPI, vol. 14(17), pages 1-14, August.
    94. Aneta Wlodarczyk & Marcin Zawada, 2009. "The Use of Weather Variables in the Modeling of Demand for Electricity in One of the Regions in the Southern Poland," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 99-110.
    95. Imani, Maryam, 2021. "Electrical load-temperature CNN for residential load forecasting," Energy, Elsevier, vol. 227(C).
    96. Moral Carcedo, Julián & Pérez García, Julián, 2015. "Temperature Effects on Firms’ Electricity Demand: An Analysis of Sectorial Differences in Spain," Working Papers in Economic Theory 2015/01, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    97. Gallo Cassarino, Tiziano & Sharp, Ed & Barrett, Mark, 2018. "The impact of social and weather drivers on the historical electricity demand in Europe," Applied Energy, Elsevier, vol. 229(C), pages 176-185.
    98. Alexis Gerossier & Robin Girard & Alexis Bocquet & George Kariniotakis, 2018. "Robust Day-Ahead Forecasting of Household Electricity Demand and Operational Challenges," Energies, MDPI, vol. 11(12), pages 1-18, December.
    99. Jovanović, Saša & Savić, Slobodan & Bojić, Milorad & Djordjević, Zorica & Nikolić, Danijela, 2015. "The impact of the mean daily air temperature change on electricity consumption," Energy, Elsevier, vol. 88(C), pages 604-609.
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    101. Sulemana Mahawiya, 2015. "Financial sector development and threshold effect of inflation in ECOWAS and SADC: A Panel smooth transition regression approach," Working Papers 539, Economic Research Southern Africa.
    102. Kani, Alireza H. & Abbasspour, Madjid & Abedi, Zahra, 2014. "Estimation of demand function for natural gas in Iran: Evidences based on smooth transition regression models," Economic Modelling, Elsevier, vol. 36(C), pages 341-347.
    103. Maren Diane Schmeck, 2016. "Pricing Options On Forwards In Energy Markets: The Role Of Mean Reversion'S Speed," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(08), pages 1-26, December.
    104. Park, Sungjun & Kim, Jinsoo, 2018. "The effect of interest in renewable energy on US household electricity consumption: An analysis using Google Trends data," Renewable Energy, Elsevier, vol. 127(C), pages 1004-1010.
    105. Monika Zimmermann & Florian Ziel, 2024. "Spatial Weather, Socio-Economic and Political Risks in Probabilistic Load Forecasting," Papers 2408.00507, arXiv.org, revised Dec 2024.
    106. Selima Sultana & Nastaran Pourebrahim & Hyojin Kim, 2018. "Household Energy Expenditures in North Carolina: A Geographically Weighted Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    107. Tan-Soo, Jie-Sheng & Qin, Ping & Zhang, Xiao-Bing, 2018. "Power stations emissions externalities from avoidance behaviors towards air pollution: Evidence from Beijing," Energy Policy, Elsevier, vol. 121(C), pages 336-345.
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    109. Andreas Hefti & Peiyao Shen & King King Li, 2021. "Igniting deliberation in high stake decisions: a field study," ECON - Working Papers 378, Department of Economics - University of Zurich.
    110. Zhang, Yue-Jun & Peng, Hua-Rong, 2017. "Exploring the direct rebound effect of residential electricity consumption: An empirical study in China," Applied Energy, Elsevier, vol. 196(C), pages 132-141.
    111. Figueiredo, Nuno Carvalho & Silva, Patrícia Pereira da & Bunn, Derek, 2016. "Weather and market specificities in the regional transmission of renewable energy price effects," Energy, Elsevier, vol. 114(C), pages 188-200.
    112. Gupta, Eshita, 2012. "Global warming and electricity demand in the rapidly growing city of Delhi: A semi-parametric variable coefficient approach," Energy Economics, Elsevier, vol. 34(5), pages 1407-1421.
    113. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    114. Mulder, Machiel & Scholtens, Bert, 2013. "The impact of renewable energy on electricity prices in the Netherlands," Renewable Energy, Elsevier, vol. 57(C), pages 94-100.
    115. Po-Chin Wu & Hsiao & I-Chung & Tsai & Meng-Hua, 2018. "Nonlinear Effect of Business Cycle on Lottery Sales Stability," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 8(4), pages 1-3.
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    120. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
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  11. Marie Bessec & Othman Bouabdallah, 2005. "What causes the forecasting failure of Markov-Switching models? A Monte Carlo study," Econometrics 0503018, University Library of Munich, Germany.

    Cited by:

    1. Katarzyna Maciejowska & Rafal Weron, 2015. "Short- and mid-term forecasting of baseload electricity prices in the UK: The impact of intra-day price relationships and market fundamentals," HSC Research Reports HSC/15/04, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    2. Mahua Barari & Nityananda Sarkar & Srikanta Kundu & Kushal Banik Chowdhury, 2014. "Forecasting House Prices in the United States with Multiple Structural Breaks," International Econometric Review (IER), Econometric Research Association, vol. 6(1), pages 1-23, April.
    3. W. Miles, 2008. "Boom–Bust Cycles and the Forecasting Performance of Linear and Non-Linear Models of House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 36(3), pages 249-264, April.
    4. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
    5. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
    6. Hujer, Reinhard & Vuletic, Sandra, 2007. "Econometric analysis of financial trade processes by discrete mixture duration models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 635-667, February.
    7. Niko Hauzenberger & Florian Huber & Michael Pfarrhofer & Thomas O. Zorner, 2018. "Stochastic model specification in Markov switching vector error correction models," Papers 1807.00529, arXiv.org, revised Sep 2019.
    8. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number hsbook0601, December.
    9. Joanna Janczura & Rafał Weron, 2013. "Goodness-of-fit testing for the marginal distribution of regime-switching models with an application to electricity spot prices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(3), pages 239-270, July.
    10. Serinaldi, Francesco, 2011. "Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape," Energy Economics, Elsevier, vol. 33(6), pages 1216-1226.
    11. Adam Misiorek & Rafal Weron, 2006. "Interval forecasting of spot electricity prices," HSC Research Reports HSC/06/05, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    12. Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    13. Brent Bundick, 2007. "Do federal funds futures need adjustment for excess returns? a state-dependent approach," Research Working Paper RWP 07-08, Federal Reserve Bank of Kansas City.
    14. Giordani, Paolo & Villani, Mattias, 2009. "Forecasting Macroeconomic Time Series With Locally Adaptive Signal Extraction," Working Paper Series 234, Sveriges Riksbank (Central Bank of Sweden).
    15. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.

Articles

  1. Marie Bessec & Julien Fouquau, 2022. "Green Attention in Financial Markets: A Global Warning," Annals of Economics and Statistics, GENES, issue 148, pages 29-64.

    Cited by:

    1. Cavallo, Eduardo & Cepeda, Ana & Panizza, Ugo, 2024. "Environmental Damage News and Stock Returns: Evidence from Latin America," CEPR Discussion Papers 19154, C.E.P.R. Discussion Papers.

  2. Marie Bessec, 2019. "Revisiting the transitional dynamics of business cycle phases with mixed-frequency data," Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 711-732, August.
    See citations under working paper version above.
  3. Bessec, Marie & Fouquau, Julien, 2018. "Short-run electricity load forecasting with combinations of stationary wavelet transforms," European Journal of Operational Research, Elsevier, vol. 264(1), pages 149-164.
    See citations under working paper version above.
  4. Marie Bessec & Julien Fouquau & Sophie Meritet, 2016. "Forecasting electricity spot prices using time-series models with a double temporal segmentation," Applied Economics, Taylor & Francis Journals, vol. 48(5), pages 361-378, January.
    See citations under working paper version above.
  5. 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.
    See citations under working paper version above.
  6. Marie Bessec & Catherine Doz, 2014. "Short-term forecasting of French GDP growth using dynamic factor models," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 11-50.
    See citations under working paper version above.
  7. Frederique Bec & Marie Bessec, 2013. "Inventory Investment Dynamics and Recoveries: A Comparison of Manufacturing and Retail Trade Sectors," Economics Bulletin, AccessEcon, vol. 33(3), pages 2209-2222.
    See citations under working paper version above.
  8. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
    See citations under working paper version above.
  9. Marie Bessec & Catherine Doz, 2012. "Prévision à court terme de la croissance du PIB français à l’aide de modèles à facteurs dynamiques," Économie et Prévision, Programme National Persée, vol. 199(1), pages 1-30.
    See citations under working paper version above.
  10. Marie Bessec, 2010. "Etalonnages du taux de croissance du PIB français sur la base des enquêtes de conjoncture," Economie & Prévision, La Documentation Française, vol. 0(2), pages 77-99.

    Cited by:

    1. Mogliani, M. & Brunhes-Lesage, V. & Darné, O. & Pluyaud, B., 2014. "New estimate of the MIBA forecasting model. Modeling first-release GDP using the Banque de France's Monthly Business Survey and the “blocking” approach," Working papers 473, Banque de France.
    2. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    3. Luboš Marek & Stanislava Hronová & Richard Hindls, 2019. "Možnosti odhadů krátkodobých makroekonomických agregátů na základě výsledků konjunkturních průzkumů [Possibilities of Estimations of Short-term Macroeconomic Aggregates Based on Business Survey Res," Politická ekonomie, Prague University of Economics and Business, vol. 2019(4), pages 347-370.

  11. Bessec, Marie & Fouquau, Julien, 2008. "The non-linear link between electricity consumption and temperature in Europe: A threshold panel approach," Energy Economics, Elsevier, vol. 30(5), pages 2705-2721, September.
    See citations under working paper version above.
  12. Bessec Marie & Bouabdallah Othman, 2005. "What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-24, June.
    See citations under working paper version above.
  13. Marie Bessec & François-Mathieu Robineau, 2003. "Comportements chartistes et fondamentalistes. Coexistence ou domination alternative sur le marché des changes?," Revue économique, Presses de Sciences-Po, vol. 54(6), pages 1213-1238.

    Cited by:

    1. Georges Prat & Remzi Uctum, 2015. "Expectation formation in the foreign exchange market: a time-varying heterogeneity approach using survey data," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3673-3695, July.
    2. Olivier Damette & Stéphane Goutte, 2015. "Tobin tax and trading volume tightening: a reassessment," Post-Print hal-01203841, HAL.
    3. Georges Prat & Remzi Uctum, 2014. "Expectation formation in the foreign exchange market: a time-varying heterogeneity approach using survey data," Working Papers hal-04141348, HAL.

  14. Bessec, Marie, 2003. "Mean-reversion vs. adjustment to PPP: the two regimes of exchange rate dynamics under the EMS, 1979-1998," Economic Modelling, Elsevier, vol. 20(1), pages 141-164, January.

    Cited by:

    1. J. Isaac Miller, 2008. "Testing the Bounds: Empirical Behavior of Target Zone Fundamentals," Working Papers 0803, Department of Economics, University of Missouri, revised 15 Apr 2009.
    2. Mr. Bassem M Kamar & Jean-Etienne Carlotti & Mr. Russell C Krueger, 2009. "Establishing Conversion Values for New Currency Unions: Method and Application to the planned Gulf Cooperation Council (GCC) Currency Union," IMF Working Papers 2009/184, International Monetary Fund.
    3. Frömmel, Michael & Schmidt, Torsten, 2006. "Bank Lending and Asset Prices in the Euro Area," RWI Discussion Papers 42, RWI - Leibniz-Institut für Wirtschaftsforschung.
    4. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2013. "Is exchange rate – Customer order flow relationship linear? Evidence from the Hungarian FX market," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 20-35.
    5. Frommel, Michael & MacDonald, Ronald & Menkhoff, Lukas, 2005. "Markov switching regimes in a monetary exchange rate model," Economic Modelling, Elsevier, vol. 22(3), pages 485-502, May.
    6. Jean-Louis Arcand & Max-Olivier Hongler & Shekhar Hari Kumar & Daniele Rinaldo, 2020. "Can one hear the shape of a target zone?," Papers 2002.00948, arXiv.org, revised Jun 2022.

Chapters

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