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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 & Julien Fouquau, 2024. "A Green Wave in Media: A Change of Tack in Stock Markets," Post-Print hal-04706501, HAL.

    Cited by:

    1. Benkraiem, Ramzi & Dimic, Nebojsa & Piljak, Vanja & Swinkels, Laurens & Vulanovic, Milos, 2025. "Media-based climate risks and international corporate bond market," Journal of International Money and Finance, Elsevier, vol. 151(C).
    2. Allahdadi, Mohammad R. & Fretheim, Torun & Vindedal, Kjetil, 2024. "Value of climate change news: A textual analysis," Global Finance Journal, Elsevier, vol. 63(C).

  2. 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.

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

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Lee, Juyong & Cho, Youngsang, 2022. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Energy, Elsevier, vol. 239(PD).
    9. Zhou, Cheng & Chen, Xiyang, 2019. "Predicting energy consumption: A multiple decomposition-ensemble approach," Energy, Elsevier, vol. 189(C).
    10. 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.
    11. Feng Gao & Jie Song & Xueyan Shao, 2025. "Short-term interval-valued load forecasting with a combined strategy of iHW and multioutput machine learning," Annals of Operations Research, Springer, vol. 346(3), pages 2009-2033, March.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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.
    17. Wang, Chuang & Zhao, Haishen & Liu, Yang & Fan, Guojin, 2024. "Minute-level ultra-short-term power load forecasting based on time series data features," Applied Energy, Elsevier, vol. 372(C).
    18. 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.
    19. 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.
    20. 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).
    21. 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).
    22. 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.
    23. Zhang, Jinliang & Siya, Wang & Zhongfu, Tan & Anli, Sun, 2023. "An improved hybrid model for short term power load prediction," Energy, Elsevier, vol. 268(C).
    24. 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.
    25. 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).
    26. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.

  4. 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. Catherine Refait-Alexandre & Stéphanie Serve, 2015. "« Multiple banking relationships: do SMEs mistrust their banks? »," Post-Print hal-01450968, HAL.

  5. 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 & Rafał Weron, 2016. "Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 9(8), pages 1-22, August.
    2. 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).
    3. 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".
    4. 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.
    5. 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.

  6. 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. Cascaldi-Garcia, Danilo & Ferreira, Thiago R.T. & Giannone, Domenico & Modugno, Michele, 2024. "Back to the present: Learning about the euro area through a now-casting model," International Journal of Forecasting, Elsevier, vol. 40(2), pages 661-686.
    2. 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.
    3. 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.).
    4. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.

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

    Cited by:

    1. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    2. Domenic Franjic & Karsten Schweikert, 2025. "Predictor Preselection for Mixed‐Frequency Dynamic Factor Models: A Simulation Study With an Empirical Application to GDP Nowcasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 255-269, March.
    3. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    4. 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.
    5. 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.
    6. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
    12. 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).

  8. Frédérique Bec & Marie Bessec, 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," Working Papers hal-03461113, HAL.

  9. 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. 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.
    3. Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie Chinn, 2023. "Forecasting real activity using cross-sectoral stock market information," Post-Print hal-04459605, HAL.
    4. Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie D. Chinn, 2022. "Macroeconomic Forecasting using Filtered Signals from a Stock Market Cross Section," NBER Working Papers 30305, National Bureau of Economic Research, Inc.
    5. 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.

  10. Marie Bessec & 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. Marie Bessec, 2019. "Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data," Post-Print hal-02181552, HAL.
    2. 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, September.
    3. 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).
    4. Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
    5. 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.
    6. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
    7. 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.
    8. 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.
    9. 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.
    10. Lu, Fei & Zeng, Qing & Bouri, Elie & Tao, Ying, 2024. "Forecasting US GDP growth rates in a rich environment of macroeconomic data," International Review of Economics & Finance, Elsevier, vol. 95(C).
    11. Catherine Doz & Anna Petronevich, 2017. "On the consistency of the two-step estimates of the MS-DFM: a Monte Carlo study," PSE Working Papers halshs-01592863, HAL.
    12. Marie Bessec, 2015. "Revisiting the transitional dynamics of business-cycle phases with mixed frequency data," Post-Print hal-01276824, HAL.
    13. 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.

  11. 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. 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.
    2. Anne-Laure Delatte & Julien Fouquau, 2012. "What Drove the Massive Hoarding of International Reserves in Emerging Economies? A Time-Varying Approach," Post-Print hal-01410598, 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. Falk, Martin & Lin, Xiang, 2018. "Sensitivity of winter tourism to temperature increases over the last decades," Economic Modelling, Elsevier, vol. 71(C), pages 174-183.
    6. 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.
    7. Anne-Laure Delatte & Julien Fouquau, 2011. "The determinants of International Reserves in the Emerging countries: a non linear approach," Post-Print hal-00822326, HAL.
    8. Monika Zimmermann & Florian Ziel, 2024. "Efficient mid-term forecasting of hourly electricity load using generalized additive models," Papers 2405.17070, arXiv.org, revised Feb 2025.
    9. 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.
    10. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    11. McDermott, Grant R. & Nilsen, Øivind Anti, 2012. "Electricity Prices, River Temperatures and Cooling Water Scarcity," IZA Discussion Papers 6842, Institute of Labor Economics (IZA).
    12. Nabil Aflouk & Jacques Mazier, 2013. "Exchange rate misalignments and economic growth: A threshold panel approach," Economics Bulletin, AccessEcon, vol. 33(2), pages 1333-1347.
    13. 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.
    14. 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.
    15. Ahamada, Ibrahim & Coulibaly, Dramane, 2011. "How does financial development influence the impact of remittances on growth volatility?," Economic Modelling, Elsevier, vol. 28(6), pages 2748-2760.
    16. Anne-Laure Delatte & Julien Fouquau, 2012. "What drove the massive hoarding of international reserves? A time-varying approach," Post-Print hal-00822294, HAL.
    17. Harish, Santosh & Singh, Nishmeet & Tongia, Rahul, 2020. "Impact of temperature on electricity demand: Evidence from Delhi and Indian states," Energy Policy, Elsevier, vol. 140(C).
    18. Alexis Tantet & Marc Stéfanon & Philippe Drobinski & Jordi Badosa & Silvia Concettini & Anna Cretì & Claudia D’Ambrosio & Dimitri Thomopulos & Peter Tankov, 2019. "e 4 clim 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy," Energies, MDPI, vol. 12(22), pages 1-37, November.
    19. Li, Muyuan & Yao, Jinfeng & Shen, Yanbo & Yuan, Bin & Simmonds, Ian & Liu, Yunyun, 2023. "Impact of synoptic circulation patterns on renewable energy-related variables over China," Renewable Energy, Elsevier, vol. 215(C).
    20. Petrick, Sebastian & Rehdanz, Katrin & Tol, Richard S. J., 2010. "The impact of temperature changes on residential energy consumption," Kiel Working Papers 1618, Kiel Institute for the World Economy (IfW Kiel).
    21. 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.
    22. Saehong Park & Seunghyoung Ryu & Yohwan Choi & Jihyo Kim & Hongseok Kim, 2015. "Data-Driven Baseline Estimation of Residential Buildings for Demand Response," Energies, MDPI, vol. 8(9), pages 1-21, September.
    23. 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.
    24. Imani, Maryam, 2021. "Electrical load-temperature CNN for residential load forecasting," Energy, Elsevier, vol. 227(C).
    25. 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.
    26. 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.
    27. 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).
    28. Ekonomou, L., 2010. "Greek long-term energy consumption prediction using artificial neural networks," Energy, Elsevier, vol. 35(2), pages 512-517.
    29. Kang, Jieyi & Reiner, David M., 2022. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Energy Economics, Elsevier, vol. 111(C).
    30. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
    31. Jian Chai & Ting Liang & Xiaoyang Zhou & Yunxiao Ye & Limin Xing & Kin Keung Lai, 2016. "Natural Gas Consumption of Emerging Economies in the Industrialization Process," Sustainability, MDPI, vol. 8(11), pages 1-16, October.
    32. 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.
    33. Anne-Laure Delatte & Julien Fouquau, 2012. "Le retour des motifs mercantilistes dans la demande de réserves internationales des pays émergents," Post-Print hal-00812053, HAL.
    34. 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.
    35. 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).
    36. -, 2011. "An assessment of the economic impact of climate change on the Energy Sector in Trinidad and Tobago," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 38584, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    37. 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.
    38. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    39. Andrés González & Timo Teräsvirta & Dick van Dijk & Yukai Yang, 2017. "Panel Smooth Transition Regression Models," CREATES Research Papers 2017-36, Department of Economics and Business Economics, Aarhus University.
    40. 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).
    41. 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.
    42. Kudela, Peter & Havranek, Tomas & Herman, Dominik & Irsova, Zuzana, 2020. "Does daylight saving time save electricity? Evidence from Slovakia," Energy Policy, Elsevier, vol. 137(C).
    43. Haben, Stephen & Giasemidis, Georgios & Ziel, Florian & Arora, Siddharth, 2019. "Short term load forecasting and the effect of temperature at the low voltage level," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1469-1484.
    44. 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).
    45. Borck, Rainald, 2016. "Will skyscrapers save the planet? Building height limits and urban greenhouse gas emissions," Regional Science and Urban Economics, Elsevier, vol. 58(C), pages 13-25.
    46. 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.
    47. 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).
    48. 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.
    49. 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.
    50. Afef Bouattour & Maha Kalai & Kamel Helali, 2024. "Threshold effects of technology import on industrial employment: a panel smooth transition regression approach," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 13(1), pages 1-33, December.
    51. Florian Fizaine & Sondès Kahouli, 2018. "On the power of indicators: how the choice of the fuel poverty measure affects the identification of the target population," Policy Papers 2018.01, FAERE - French Association of Environmental and Resource Economists.
    52. Tamara Sofía Propato & Diego Abelleyra & María Semmartin & Santiago R. Verón, 2021. "Differential sensitivities of electricity consumption to global warming across regions of Argentina," Climatic Change, Springer, vol. 166(1), pages 1-18, May.
    53. 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.
    54. Chabouni, Naima & Belarbi, Yacine & Benhassine, Wassim, 2020. "Electricity load dynamics, temperature and seasonality Nexus in Algeria," Energy, Elsevier, vol. 200(C).
    55. Chao Bi & Minna Jia & Jingjing Zeng, 2019. "Nonlinear Effect of Public Infrastructure on Energy Intensity in China: A Panel Smooth Transition Regression Approach," Sustainability, MDPI, vol. 11(3), pages 1-21, January.
    56. 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.
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    58. Xiaosheng Li & Xia Yan & Qingxian An & Ke Chen & Zhen Shen, 2016. "The coordination between China’s economic growth and environmental emission from the Environmental Kuznets Curve viewpoint," 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. 83(1), pages 233-252, August.
    59. 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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    61. Wang, Yu Shan, 2013. "Oil price effects on personal consumption expenditures," Energy Economics, Elsevier, vol. 36(C), pages 198-204.
    62. 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.
    63. Blázquez, Leticia & Boogen, Nina & Filippini, Massimo, 2013. "Residential electricity demand in Spain: New empirical evidence using aggregate data," Energy Economics, Elsevier, vol. 36(C), pages 648-657.
    64. 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.
    65. Monika Zimmermann & Florian Ziel, 2024. "Spatial Weather, Socio-Economic and Political Risks in Probabilistic Load Forecasting," Papers 2408.00507, arXiv.org, revised Dec 2024.
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    68. Rosa Duarte & Vicente Pinilla & Ana Serrano, 2012. "Is there an environmental Kuznets curve for water use? A panel smooth transition regression approach," Documentos de Trabajo dt2012-03, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    69. van der Wiel, K. & Stoop, L.P. & van Zuijlen, B.R.H. & Blackport, R. & van den Broek, M.A. & Selten, F.M., 2019. "Meteorological conditions leading to extreme low variable renewable energy production and extreme high energy shortfall," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 261-275.
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    71. Borck, Rainald, 2014. "Will skyscrapers save the planet?," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100566, Verein für Socialpolitik / German Economic Association.
    72. 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.
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    74. Kamal Chapagain & Somsak Kittipiyakul, 2018. "Performance Analysis of Short-Term Electricity Demand with Atmospheric Variables," Energies, MDPI, vol. 11(4), pages 1-34, April.
    75. Ranson, Matthew & Morris, Lauren & Kats-Rubin, Alex, 2014. "Climate Change and Space Heating Energy Demand: A Review of the Literature," National Center for Environmental Economics-NCEE Working Papers 280923, United States Environmental Protection Agency (EPA).
    76. 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).
    77. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    78. Botman, Lola & Lago, Jesus & Becker, Thijs & Vanthournout, Koen & Moor, Bart De, 2025. "A global probabilistic approach for short-term forecasting of individual households electricity consumption," Applied Energy, Elsevier, vol. 382(C).
    79. 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.
    80. Moral-Carcedo, Julián & Pérez-García, Julián, 2015. "Temperature effects on firms’ electricity demand: An analysis of sectorial differences in Spain," Applied Energy, Elsevier, vol. 142(C), pages 407-425.
    81. 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).
    82. 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.
    83. Saia, Artjom, 2023. "Digitalization and CO2 emissions: Dynamics under R&D and technology innovation regimes," Technology in Society, Elsevier, vol. 74(C).
    84. 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.
    85. 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).
    86. 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.
    87. 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.
    88. Lan Khanh Chu, 2024. "The role of technological innovation and population aging in environmental degradation in the Organization for Economic Co-operation and Development countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(1), pages 735-773, January.
    89. 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.
    90. 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.
    91. Kondi-Akara, Ghafi & Hingray, Benoit & Francois, Baptiste & Diedhiou, Arona, 2023. "Recent trends in urban electricity consumption for cooling in West and Central African countries," Energy, Elsevier, vol. 276(C).
    92. Richard Tol, 2013. "The economic impact of climate change in the 20th and 21st centuries," Climatic Change, Springer, vol. 117(4), pages 795-808, April.
    93. 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.
    94. Nguyen, Hang T. & Nabney, Ian T., 2010. "Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models," Energy, Elsevier, vol. 35(9), pages 3674-3685.
    95. 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.
    96. 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.
    97. Marilyn A. 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.
    98. 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.
    99. Yang, Shubo & Jahanger, Atif & Awan, Ashar, 2024. "Temperature variation and urban electricity consumption in China: Implications for demand management and planning," Utilities Policy, Elsevier, vol. 90(C).
    100. 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.
    101. 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.
    102. 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.
    103. 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).
    104. Yongxia Ding & Wei Qu & Shuwen Niu & Man Liang & Wenli Qiang & Zhenguo Hong, 2016. "Factors Influencing the Spatial Difference in Household Energy Consumption in China," Sustainability, MDPI, vol. 8(12), pages 1-20, December.
    105. 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).
    106. Apadula, Francesco & Bassini, Alessandra & Elli, Alberto & Scapin, Simone, 2012. "Relationships between meteorological variables and monthly electricity demand," Applied Energy, Elsevier, vol. 98(C), pages 346-356.
    107. 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.
    108. 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.
    109. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    110. 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.
    111. 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.
    112. Ge, Fei & Ye, Bin & Xing, Shengnan & Wang, Bao & Sun, Shuang, 2017. "The analysis of the underlying reasons of the inconsistent relationship between economic growth and the consumption of electricity in China – A case study of Anhui province," Energy, Elsevier, vol. 128(C), pages 601-608.
    113. 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.
    114. 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.
    115. Franz Harke & Philipp Otto, 2023. "Solar Self-Sufficient Households as a Driving Factor for Sustainability Transformation," Sustainability, MDPI, vol. 15(3), pages 1-20, February.
    116. Gao, Feng & Chi, Hong & Shao, Xueyan, 2021. "Forecasting residential electricity consumption using a hybrid machine learning model with online search data," Applied Energy, Elsevier, vol. 300(C).
    117. Li, Jianglong & Yang, Lisha & Long, Houyin, 2018. "Climatic impacts on energy consumption: Intensive and extensive margins," Energy Economics, Elsevier, vol. 71(C), pages 332-343.
    118. 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).
    119. 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.
    120. 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.
    121. 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.
    122. 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.
    123. 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.
    124. 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.
    125. 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.
    126. Song, Malin & Wang, Jianlin & Zhao, Jiajia, 2023. "Effects of rising and extreme temperatures on production factor efficiency: Evidence from China's cities," International Journal of Production Economics, Elsevier, vol. 260(C).
    127. Jose M. Garrido-Perez & David Barriopedro & Ricardo García-Herrera & Carlos Ordóñez, 2021. "Impact of climate change on Spanish electricity demand," Climatic Change, Springer, vol. 165(3), pages 1-18, April.
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  12. 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. 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.
    2. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    9. Giordani, Paolo & Villani, Mattias, 2010. "Forecasting macroeconomic time series with locally adaptive signal extraction," International Journal of Forecasting, Elsevier, vol. 26(2), pages 312-325, April.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    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, 2024. "A Green Wave in Media: A Change of Tack in Stock Markets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(5), pages 1026-1057, October.
    See citations under working paper version above.
  2. 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 A. & Cepeda, Ana & Panizza, Ugo, 2024. "Environmental Damage News and Stock Returns: Evidence from Latin America," IDB Publications (Working Papers) 13537, Inter-American Development Bank.
    2. Emanuele Campiglio & Luca De Angelis & Paolo Neri & Ginevra Scalisi, 2025. "From Climate Chat to Climate Shock: Non‐Linear Impacts of Transition Risk in Energy CDS Markets," Environmetrics, John Wiley & Sons, Ltd., vol. 36(3), April.
    3. Campiglio, Emanuele & De Angelis, Luca & Neri, Paolo & Scalisi, Ginevra, 2025. "From climate chat to climate shock: non‐linear impacts of transition risk in energy CDS markets," LSE Research Online Documents on Economics 127807, London School of Economics and Political Science, LSE Library.
    4. Ahmed, Walid M.A., 2024. "Attention to climate change and eco-friendly financial-asset prices: A quantile ARDL approach," Energy Economics, Elsevier, vol. 136(C).

  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    2. 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.
    3. Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Center for Research in Economics and Statistics.

  12. 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.
  13. 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.
  14. 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, 2014. "Expectation formation in the foreign exchange market: a time-varying heterogeneity approach using survey data," Working Papers 2014-235, Department of Research, Ipag Business School.
    2. Dammak, Wael & Frikha, Wajdi & Souissi, Mohamed Naceur, 2024. "Market turbulence and investor decision-making in currency option market," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).
    3. Olivier Damette & Stéphane Goutte, 2015. "Tobin tax and trading volume tightening: a reassessment," Post-Print hal-01203841, HAL.
    4. 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.

  15. 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. 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.
    2. Yuliya Lovcha & Alejandro Perez-Laborda, 2010. "Is exchange rate – customer order flow relationship linear? Evidence from the Hungarian FX market," MNB Working Papers 2010/10, Magyar Nemzeti Bank (Central Bank of Hungary).
    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. Miller, J. Isaac, 2011. "Testing the bounds: Empirical behavior of target zone fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 1782-1792, July.
    5. 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.
    6. Arcand, Jean-Louis & Kumar, Shekhar Hari & Hongler, Max-Olivier & Rinaldo, Daniele, 2023. "Can one hear the shape of a target zone?," Journal of Mathematical Economics, Elsevier, vol. 107(C).

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