IDEAS home Printed from https://ideas.repec.org/f/c/pgr363.html
   My authors  Follow this author

Luigi Grossi

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. Filippo Beltrami & Fulvio Fontini & Monica Giulietti & Luigi Grossi, 2021. "The zonal and seasonal CO2 marginal emissions factors for the Italian power market," Working Papers 01/2021, University of Verona, Department of Economics.

    Cited by:

    1. Beltrami, Filippo & Fontini, Fulvio & Grossi, Luigi, 2021. "The value of carbon emission reduction induced by Renewable Energy Sources in the Italian power market," Ecological Economics, Elsevier, vol. 189(C).

  2. Daniel Felix Ahelegbey & Emmanuel Senyo Fianu & Luigi Grossi, 2020. "Modeling Risk Contagion in the Italian Zonal Electricity Market," DEM Working Papers Series 182, University of Pavia, Department of Economics and Management.

    Cited by:

    1. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    2. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).

  3. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

    Cited by:

    1. Nie, Yan & Zhang, Guoxing & Zhong, Luhao & Su, Bin & Xi, Xi, 2024. "Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies," Energy Policy, Elsevier, vol. 184(C).
    2. Said Rosli & Sulaimi Mardhiati & Majid Rohayu Ab & Aini Ainoriza Mohd & Olanrele Olusegun Olaopin & Akinsomi Omokolade, 2024. "Evaluating Market Attributes and Housing Affordability: Gaining Perspective on Future Value Trends," Real Estate Management and Valuation, Sciendo, vol. 32(3), pages 87-100.
    3. Raja, Aitazaz Ali & Pinson, Pierre & Kazempour, Jalal & Grammatico, Sergio, 2024. "A market for trading forecasts: A wagering mechanism," International Journal of Forecasting, Elsevier, vol. 40(1), pages 142-159.
    4. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2024.
    5. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review," Energies, MDPI, vol. 16(6), pages 1-23, March.
    6. Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
    7. Xiaoqian Wang & Yanfei Kang & Rob J Hyndman & Feng Li, 2020. "Distributed ARIMA Models for Ultra-long Time Series," Monash Econometrics and Business Statistics Working Papers 29/20, Monash University, Department of Econometrics and Business Statistics.
    8. Ca’ Zorzi, Michele & Rubaszek, Michał, 2023. "How many fundamentals should we include in the behavioral equilibrium exchange rate model?," Economic Modelling, Elsevier, vol. 118(C).
    9. Racek, Daniel & Thurner, Paul W. & Davidson, Brittany I. & Zhu, Xiao Xiang & Kauermann, Göran, 2024. "Conflict forecasting using remote sensing data: An application to the Syrian civil war," International Journal of Forecasting, Elsevier, vol. 40(1), pages 373-391.
    10. Huang, Congzhi & Yang, Mengyuan, 2023. "Memory long and short term time series network for ultra-short-term photovoltaic power forecasting," Energy, Elsevier, vol. 279(C).
    11. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    12. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    13. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    14. Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common factors and the dynamics of cereal prices. A forecasting perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    16. Bernhard Tröster & Ulrich Gunter, 2023. "The Financialization of Coffee, Cocoa and Cotton Value Chains: The Role of Physical Actors," Development and Change, International Institute of Social Studies, vol. 54(6), pages 1550-1574, November.
    17. Tetiana Zatonatska & Olena Liashenko & Yana Fareniuk & Oleksandr Dluhopolskyi & Artur Dmowski & Marzena Cichorzewska, 2022. "The Migration Influence on the Forecasting of Health Care Budget Expenditures in the Direction of Sustainability: Case of Ukraine," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    18. Jeroen Rombouts & Marie Ternes & Ines Wilms, 2024. "Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning," Papers 2402.09033, arXiv.org, revised May 2024.
    19. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
    20. Oscar Espinosa & Valeria Bejarano & Jeferson Ramos & Boris Martínez, 2023. "Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021," Health Economics Review, Springer, vol. 13(1), pages 1-20, December.
    21. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    22. Rai, Amit & Shrivastava, Ashish & Jana, Kartick C., 2023. "Differential attention net: Multi-directed differential attention based hybrid deep learning model for solar power forecasting," Energy, Elsevier, vol. 263(PC).
    23. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    24. Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    25. Fernández, Joaquín Delgado & Menci, Sergio Potenciano & Lee, Chul Min & Rieger, Alexander & Fridgen, Gilbert, 2022. "Privacy-preserving federated learning for residential short-term load forecasting," Applied Energy, Elsevier, vol. 326(C).
    26. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    27. Paul Ghelasi & Florian Ziel, 2023. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," Papers 2305.16255, arXiv.org.
    28. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    29. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    30. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    31. Heymann, Fabian & Milojevic, Tatjana & Covatariu, Andrei & Verma, Piyush, 2023. "Digitalization in decarbonizing electricity systems – Phenomena, regional aspects, stakeholders, use cases, challenges and policy options," Energy, Elsevier, vol. 262(PB).
    32. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
    33. Ramos, Paulo Vitor B. & Villela, Saulo Moraes & Silva, Walquiria N. & Dias, Bruno H., 2023. "Residential energy consumption forecasting using deep learning models," Applied Energy, Elsevier, vol. 350(C).
    34. Ghelasi, Paul & Ziel, Florian, 2024. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 581-596.
    35. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    36. Katarzyna Maciejowska & Weronika Nitka, 2024. "Multiple split approach -- multidimensional probabilistic forecasting of electricity markets," Papers 2407.07795, arXiv.org.
    37. Bergsteinsson, Hjörleifur G. & Sørensen, Mikkel Lindstrøm & Møller, Jan Kloppenborg & Madsen, Henrik, 2023. "Heat load forecasting using adaptive spatial hierarchies," Applied Energy, Elsevier, vol. 350(C).
    38. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
    39. Takahashi, Carlos Kazunari & Figueiredo, Júlio César Bastos de & Scornavacca, Eusebio, 2024. "Investigating the diffusion of innovation: A comprehensive study of successive diffusion processes through analysis of search trends, patent records, and academic publications," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    40. Li, Xishu & Zuidwijk, Rob & de Koster, M.B.M, 2023. "Optimal competitive capacity strategies: Evidence from the container shipping market," Omega, Elsevier, vol. 115(C).
    41. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    42. Emmanuel Senyo Fianu, 2022. "Analyzing and Forecasting Multi-Commodity Prices Using Variants of Mode Decomposition-Based Extreme Learning Machine Hybridization Approach," Forecasting, MDPI, vol. 4(2), pages 1-27, June.
    43. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    44. Elalem, Yara Kayyali & Maier, Sebastian & Seifert, Ralf W., 2023. "A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1874-1894.
    45. Michael Pedersen, 2024. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," Papers 2404.04105, arXiv.org.
    46. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    47. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
    48. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org.
    49. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    50. Fałdziński, Marcin & Fiszeder, Piotr & Molnár, Peter, 2024. "Improving volatility forecasts: Evidence from range-based models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    51. Qi, Lingzhi & Li, Xixi & Wang, Qiang & Jia, Suling, 2023. "fETSmcs: Feature-based ETS model component selection," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1303-1317.
    52. Guo, Su & Zheng, Kun & He, Yi & Kurban, Aynur, 2023. "The artificial intelligence-assisted short-term optimal scheduling of a cascade hydro-photovoltaic complementary system with hybrid time steps," Renewable Energy, Elsevier, vol. 202(C), pages 1169-1189.
    53. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    54. Andrea Savio & Luigi De Giovanni & Mariangela Guidolin, 2022. "Modelling Energy Transition in Germany: An Analysis through Ordinary Differential Equations and System Dynamics," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    55. Radovan Šomplák & Veronika Smejkalová & Martin Rosecký & Lenka Szásziová & Vlastimír Nevrlý & Dušan Hrabec & Martin Pavlas, 2023. "Comprehensive Review on Waste Generation Modeling," Sustainability, MDPI, vol. 15(4), pages 1-29, February.

  4. Filippo Beltrami & Andrew Burlinson & Luigi Grossi & Monica Giulietti & Paul Rowley & Grant Wilson, 2020. "Where did the time (series) go? Estimation of marginal emission factors with autoregressive components," Working Papers 02/2020, University of Verona, Department of Economics.

    Cited by:

    1. Filippo Beltrami & Fulvio Fontini & Monica Giulietti & Luigi Grossi, 2022. "The Zonal and Seasonal CO2 Marginal Emissions Factors for the Italian Power Market," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(2), pages 381-411, October.
    2. Hamels, Sam & Himpe, Eline & Laverge, Jelle & Delghust, Marc & Van den Brande, Kjartan & Janssens, Arnold & Albrecht, Johan, 2021. "The use of primary energy factors and CO2 intensities for electricity in the European context - A systematic methodological review and critical evaluation of the contemporary literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).

  5. Luigi Grossi & Mauro Mussini, 2019. "Seasonality in tourist flows: Decomposing and testing changes in seasonal concentration," Working Papers 16/2019, University of Verona, Department of Economics.

    Cited by:

    1. Jing Zhang & Zhonglei Yu & Changhong Miao & Yuting Li & Shuai Qiao, 2022. "Cultural Tourism Weakens Seasonality: Empirical Analysis of Chinese Tourism Cities," Land, MDPI, vol. 11(2), pages 1-14, February.

  6. Rossetto, F. & Grossi, L. & Pollitt, M., 2019. "Assessing Market Power in the Italian Electricity Market: A synthetic supply approach," Cambridge Working Papers in Economics 1975, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Bigerna, Simona & Bollino, Carlo Andrea & D'Errico, Maria Chiara & Polinori, Paolo, 2022. "COVID-19 lockdown and market power in the Italian electricity market," Energy Policy, Elsevier, vol. 161(C).
    2. Savelli, Iacopo & Morstyn, Thomas, 2021. "Electricity prices and tariffs to keep everyone happy: A framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Omega, Elsevier, vol. 103(C).

  7. Luigi Grossi & Sven Heim & Kai Hüschelrath & Michael Waterson, 2018. "Electricity market integration and the impact of unilateral policy reforms," Post-Print hal-01952930, HAL.

    Cited by:

    1. Davide Ciferri & Maria Chiara D’Errico & Paolo Polinori, 2020. "Integration and convergence in European electricity markets," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(2), pages 463-492, July.
    2. Klaus Gugler & Adhurim Haxhimusa, 2016. "Cross-Border Technology Differences and Trade Barriers: Evidence from German and French Electricity Markets," Department of Economics Working Papers wuwp237, Vienna University of Economics and Business, Department of Economics.
    3. Hellwig, Michael & Schober, Dominik & Woll, Oliver, 2020. "Measuring market integration and estimating policy impacts on the Swiss electricity market," Energy Economics, Elsevier, vol. 86(C).
    4. Rubanda, Muhumuza Ezra & Senyonga, Livingstone & Ngoma, Mohammed & Adaramola, Muyiwa S., 2023. "Energy market integration: Harmonizing tariff recourse policies in East Africa," Utilities Policy, Elsevier, vol. 84(C).
    5. Haxhimusa, Adhurim, 2018. "The Effects of German Wind and Solar Electricity on French Spot Price Volatility: An Empirical Investigation," Department of Economics Working Paper Series 258, WU Vienna University of Economics and Business.
    6. Luigi Grossi & Mauro Mussini, 2017. "Inequality in Energy Intensity in the EU-28: Evidence from a New Decomposition Method," The Energy Journal, , vol. 38(4), pages 1-18, July.
    7. Gugler, Klaus & Haxhimusa, Adhurim, 2016. "Cross-Border Technology Differences and Trade Barriers: Evidence from German and French Electricity Markets," Department of Economics Working Paper Series 237, WU Vienna University of Economics and Business.
    8. Hung Xuan Do & Rabindra Nepal & Son Duy Pham & Tooraj Jamasb, 2023. "Electricity Market Crisis in Europe and Cross Border Price Effects: A Quantile Return Connectedness Analysis," CAMA Working Papers 2023-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Sikorska-Pastuszka, Magdalena & Papież, Monika, 2023. "Dynamic volatility connectedness in the European electricity market," Energy Economics, Elsevier, vol. 127(PA).
    10. Halužan, Marko & Verbič, Miroslav & Zorić, Jelena, 2022. "An integrated model for electricity market coupling simulations: Evidence from the European power market crossroad," Utilities Policy, Elsevier, vol. 79(C).
    11. Cassetta, Ernesto & Nava, Consuelo R. & Zoia, Maria Grazia, 2022. "EU electricity market integration and cross-country convergence in residential and industrial end-user prices," Energy Policy, Elsevier, vol. 165(C).
    12. Gugler, Klaus & Haxhimusa, Adhurim, 2019. "Market integration and technology mix: Evidence from the German and French electricity markets," Energy Policy, Elsevier, vol. 126(C), pages 30-46.
    13. Sousa, Joana & Soares, Isabel, 2020. "Demand response, market design and risk: A literature review," Utilities Policy, Elsevier, vol. 66(C).
    14. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.

  8. Lisa Flatley & Monica Giulietti & Luigi Grossi & Elisa Trujillo-Baute & Michael Waterson, 2016. "Analysing the potential economic value of energy storage," Working Papers 2016/2, Institut d'Economia de Barcelona (IEB).

    Cited by:

    1. Waterson, Michael, 2017. "The characteristics of electricity storage, renewables and markets," Energy Policy, Elsevier, vol. 104(C), pages 466-473.
    2. Williams, Olayinka & Green, Richard, 2022. "Electricity storage and market power," Energy Policy, Elsevier, vol. 164(C).
    3. Csereklyei, Zsuzsanna & Kallies, Anne & Diaz Valdivia, Andres, 2021. "The status of and opportunities for utility-scale battery storage in Australia: A regulatory and market perspective," Utilities Policy, Elsevier, vol. 73(C).
    4. Intini, Mario & Waterson, Michael, 2020. "Do British wind generators behave strategically in response to the Western Link interconnector?," CAGE Online Working Paper Series 455, Competitive Advantage in the Global Economy (CAGE).
    5. Best, Rohan & Li, Han & Trück, Stefan & Truong, Chi, 2021. "Actual uptake of home batteries: The key roles of capital and policy," Energy Policy, Elsevier, vol. 151(C).
    6. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    7. Jafari, Mehdi & Botterud, Audun & Sakti, Apurba, 2022. "Decarbonizing power systems: A critical review of the role of energy storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    8. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    9. Diego Aineto & Javier Iranzo-Sánchez & Lenin G. Lemus-Zúñiga & Eva Onaindia & Javier F. Urchueguía, 2019. "On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market," Energies, MDPI, vol. 12(11), pages 1-20, May.
    10. Luigi Grossi & Fany Nan, 2018. "The influence of renewables on electricity price forecasting: a robust approach," Working Papers 2018/10, Institut d'Economia de Barcelona (IEB).
    11. Lamp, Stefan & Samano, Mario, 2022. "Large-scale battery storage, short-term market outcomes, and arbitrage," Energy Economics, Elsevier, vol. 107(C).
    12. Albert Hiesl & Amela Ajanovic & Reinhard Haas, 2020. "On current and future economics of electricity storage," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 10(6), pages 1176-1192, December.
    13. Moita, Rodrigo & Monte, Daniel, 2022. "The limits in the adoption of batteries," Energy Economics, Elsevier, vol. 107(C).

  9. Grossi, Luigi & Heim, Sven & Waterson, Michael, 2014. "A vision of the European energy future? The impact of the German response to the Fukushima earthquake," Economic Research Papers 270236, University of Warwick - Department of Economics.

    Cited by:

    1. Waterson, Michael, 2017. "The characteristics of electricity storage, renewables and markets," Energy Policy, Elsevier, vol. 104(C), pages 466-473.
    2. Haxhimusa, Adhurim, 2018. "The Effects of German Wind and Solar Electricity on French Spot Price Volatility: An Empirical Investigation," Department of Economics Working Paper Series 258, WU Vienna University of Economics and Business.
    3. Klaus Gugler & Adhurim Haxhimusa & Mario Liebensteiner, 2016. "Integration and Efficiency of European Electricity Markets: Evidence from Spot Prices," Department of Economics Working Papers wuwp226, Vienna University of Economics and Business, Department of Economics.
    4. Lisa Flatley & Monica Giulietti & Luigi Grossi & Elisa Trujillo-Baute & Michael Waterson, 2016. "Analysing the potential economic value of energy storage," Working Papers 2016/2, Institut d'Economia de Barcelona (IEB).
    5. Jeong, Minsoo & You, Jung S., 2022. "Estimating the economic costs of nuclear power plant outages in a regulated market using a latent factor model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).

  10. Giulietti, Monica & Grossi, Luigi & Waterson, Michael, 2011. "A Rough Examination of the value of gas storage," Economic Research Papers 270757, University of Warwick - Department of Economics.

    Cited by:

    1. Martínez, Beatriz & Torró, Hipòlit, 2015. "European Natural Gas Seasonal Effects on Futures Hedging," Energy: Resources and Markets 198462, Fondazione Eni Enrico Mattei (FEEM).
    2. Martínez, Beatriz & Torró, Hipòlit, 2018. "Analysis of risk premium in UK natural gas futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 621-636.

  11. Angelica Gianfreda & Luigi Grossi, 2011. "Forecasting Italian Electricity Zonal Prices with Exogenous Variables," Working Papers 01/2011, University of Verona, Department of Economics.

    Cited by:

    1. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
    2. Marina Bertolini & Chiara D’Alpaos & Michele Moretto, 2016. "Investing in Photovoltaics: Timing, Plant Sizing and Smart Grids Flexibility," Working Papers 2016.60, Fondazione Eni Enrico Mattei.
    3. Bigerna, Simona, 2018. "Estimating temperature effects on the Italian electricity market," Energy Policy, Elsevier, vol. 118(C), pages 257-269.
    4. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    5. Lisi, Francesco & Pelagatti, Matteo M., 2018. "Component estimation for electricity market data: Deterministic or stochastic?," Energy Economics, Elsevier, vol. 74(C), pages 13-37.
    6. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    7. 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.
    8. Balagula, Yuri, 2020. "Forecasting daily spot prices in the Russian electricity market with the ARFIMA model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 89-101.
    9. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    10. Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023. "Forecasting electricity prices with expert, linear, and nonlinear models," International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
    11. Ismail Shah & Hasnain Iftikhar & Sajid Ali & Depeng Wang, 2019. "Short-Term Electricity Demand Forecasting Using Components Estimation Technique," Energies, MDPI, vol. 12(13), pages 1-17, July.
    12. Yan, Guan & Trück, Stefan, 2020. "A dynamic network analysis of spot electricity prices in the Australian national electricity market," Energy Economics, Elsevier, vol. 92(C).
    13. Genc, Talat S., 2016. "Measuring demand responses to wholesale electricity prices using market power indices," Energy Economics, Elsevier, vol. 56(C), pages 247-260.
    14. Martin-Valmayor, Miguel A. & Gil-Alana, Luis A. & Infante, Juan, 2023. "Energy prices in Europe. Evidence of persistence across markets," Resources Policy, Elsevier, vol. 82(C).
    15. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    16. Sapio, Alessandro & Spagnolo, Nicola, 2020. "The effect of a new power cable on energy prices volatility spillovers," Energy Policy, Elsevier, vol. 144(C).
    17. 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.
    18. Marta Castellini & Luca Di Corato & Michele Moretto & Sergio Vergalli, 2021. "Energy exchange among heterogeneous prosumers under price uncertainty," Working Papers 2021:24, Department of Economics, University of Venice "Ca' Foscari".
    19. Sergei Kulakov, 2020. "X-Model: Further Development and Possible Modifications," Forecasting, MDPI, vol. 2(1), pages 1-16, February.
    20. Mauro Bernardi & Francesco Lisi, 2020. "Point and Interval Forecasting of Zonal Electricity Prices and Demand Using Heteroscedastic Models: The IPEX Case," Energies, MDPI, vol. 13(23), pages 1-34, November.
    21. Bartosz Uniejewski & Rafal Weron, 2018. "Efficient forecasting of electricity spot prices with expert and LASSO models," HSC Research Reports HSC/18/02, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    22. Beltrami, Filippo & Burlinson, Andrew & Giulietti, Monica & Grossi, Luigi & Rowley, Paul & Wilson, Grant, 2020. "Where did the time (series) go? Estimation of marginal emission factors with autoregressive components," Energy Economics, Elsevier, vol. 91(C).
    23. Faddy Ardian & Silvia Concettini & Anna Creti, 2015. "Intermittent renewable generation and network congestion: an empirical analysis of Italian Power Market," Working Papers hal-01218543, HAL.
    24. Fianu, Emmanuel Senyo & Ahelegbey, Daniel Felix & Grossi, Luigi, 2022. "Modeling risk contagion in the Italian zonal electricity market," European Journal of Operational Research, Elsevier, vol. 298(2), pages 656-679.
    25. Zachmann, Georg, 2013. "A stochastic fuel switching model for electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 5-13.
    26. Rafal Weron & Michal Zator, 2014. "A note on using the Hodrick-Prescott filter in electricity markets," HSC Research Reports HSC/14/04, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    27. Alessandra Cataldi & Stefano Clò & Pietro Zoppoli, 2014. "The merit-order effect in the Italian Power Market: the impact of solar and wind generation on national wholesale electricity prices," Working Papers 9, Department of the Treasury, Ministry of the Economy and of Finance.
    28. Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2015. "Long term outlook of primary energy consumption of the Italian thermoelectric sector: Impact of fuel and carbon prices," Energy, Elsevier, vol. 87(C), pages 153-164.
    29. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.
    30. Sapio, Alessandro, 2015. "The effects of renewables in space and time: A regime switching model of the Italian power price," Energy Policy, Elsevier, vol. 85(C), pages 487-499.
    31. 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.
    32. Dagoumas, Athanasios S. & Koltsaklis, Nikolasos E. & Panapakidis, Ioannis P., 2017. "An integrated model for risk management in electricity trade," Energy, Elsevier, vol. 124(C), pages 350-363.
    33. Chen, Ying & Chua, Wee Song & Koch, Thorsten, 2018. "Forecasting day-ahead high-resolution natural-gas demand and supply in Germany," Applied Energy, Elsevier, vol. 228(C), pages 1091-1110.
    34. Lisi, Francesco & Nan, Fany, 2014. "Component estimation for electricity prices: Procedures and comparisons," Energy Economics, Elsevier, vol. 44(C), pages 143-159.
    35. Di Cosmo, Valeria, 2015. "Forward Price, Renewables and the Electricity Price: The Case of Italy," Papers WP511, Economic and Social Research Institute (ESRI).
    36. Brusaferri, Alessandro & Matteucci, Matteo & Portolani, Pietro & Vitali, Andrea, 2019. "Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices," Applied Energy, Elsevier, vol. 250(C), pages 1158-1175.
    37. Ciarreta, Aitor & Zarraga, Ainhoa, 2016. "Modeling realized volatility on the Spanish intra-day electricity market," Energy Economics, Elsevier, vol. 58(C), pages 152-163.
    38. Bigerna, Simona & Andrea Bollino, Carlo & Polinori, Paolo, 2015. "Marginal cost and congestion in the Italian electricity market: An indirect estimation approach," Energy Policy, Elsevier, vol. 85(C), pages 445-454.
    39. Auer, Benjamin R., 2016. "How does Germany's green energy policy affect electricity market volatility? An application of conditional autoregressive range models," Energy Policy, Elsevier, vol. 98(C), pages 621-628.
    40. Mulder, Machiel & Schoonbeek, Lambert, 2013. "Decomposing changes in competition in the Dutch electricity market through the residual supply index," Energy Economics, Elsevier, vol. 39(C), pages 100-107.
    41. Castellini, Marta & Menoncin, Francesco & Moretto, Michele & Vergalli, Sergio, 2021. "Photovoltaic Smart Grids in the prosumers investment decisions: a real option model," Journal of Economic Dynamics and Control, Elsevier, vol. 126(C).
    42. Luigi Grossi & Fany Nan, 2017. "Forecasting electricity prices through robust nonlinear models," Working Papers 06/2017, University of Verona, Department of Economics.
    43. Jakub Nowotarski & Jakub Tomczyk & Rafal Weron, 2013. "Modeling and forecasting of the long-term seasonal component of the EEX and Nord Pool spot prices," HSC Research Reports HSC/13/02, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    44. Sapio, Alessandro, 2019. "Greener, more integrated, and less volatile? A quantile regression analysis of Italian wholesale electricity prices," Energy Policy, Elsevier, vol. 126(C), pages 452-469.
    45. Angelica, Gianfreda & Lucia, Parisio & Matteo, Pelagatti, 2017. "The RES-induced Switching Effect Across Fossil Fuels: An Analysis of the Italian Day-Ahead and Balancing Prices and Their Connected Costs," Working Papers 360, University of Milano-Bicocca, Department of Economics, revised 03 Feb 2017.
    46. Simona Bigerna, Carlo Andrea Bollino and Paolo Polinori, 2016. "Market Power and Transmission Congestion in the Italian Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    47. Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    48. Luigi Grossi & Fany Nan, 2018. "The influence of renewables on electricity price forecasting: a robust approach," Working Papers 2018/10, Institut d'Economia de Barcelona (IEB).
    49. Beltrami, Filippo & Fontini, Fulvio & Grossi, Luigi, 2021. "The value of carbon emission reduction induced by Renewable Energy Sources in the Italian power market," Ecological Economics, Elsevier, vol. 189(C).
    50. Sirin, Selahattin Murat & Yilmaz, Berna N., 2020. "Variable renewable energy technologies in the Turkish electricity market: Quantile regression analysis of the merit-order effect," Energy Policy, Elsevier, vol. 144(C).
    51. Andreolli, Francesca & D’Alpaos, Chiara & Moretto, Michele, 2022. "Valuing investments in domestic PV-Battery Systems under uncertainty," Energy Economics, Elsevier, vol. 106(C).
    52. Avesani, Diego & Zanfei, Ariele & Di Marco, Nicola & Galletti, Andrea & Ravazzolo, Francesco & Righetti, Maurizio & Majone, Bruno, 2022. "Short-term hydropower optimization driven by innovative time-adapting econometric model," Applied Energy, Elsevier, vol. 310(C).
    53. Anne Opschoor & Dewi Peerlings & Luca Rossini & Andre Lucas, 2024. "Density Forecasting for Electricity Prices under Tail Heterogeneity with the t-Riesz Distribution," Tinbergen Institute Discussion Papers 24-049/III, Tinbergen Institute.
    54. Vincenzo Bianco, 2018. "The Future of the Italian Electricity Generation Sector. An Analysis of the Possible Strategic Models," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(3), pages 20-28.
    55. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    56. Ilaria Lucrezia Amerise & Agostino Tarsitano, 2020. "An L1 smoother for outlier cleaning of time series," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(1), pages 1-3.
    57. Ziel, Florian & Weron, Rafał, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, vol. 70(C), pages 396-420.
    58. Andrea Cervone & Ezio Santini & Sabrina Teodori & Donatella Zaccagnini Romito, 2014. "Electricity Price Forecast: a Comparison of Different Models to Evaluate the Single National Price in the Italian Energy Exchange Market," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 744-758.
    59. Sapio, Alessandro & Spagnolo, Nicola, 2016. "Price regimes in an energy island: Tacit collusion vs. cost and network explanations," Energy Economics, Elsevier, vol. 55(C), pages 157-172.

  12. Giulietti, Monica & Grossi, Luigi & Waterson, Michael, 2009. "Price transmission in the UK electricity market: was NETA beneficial?," Economic Research Papers 271287, University of Warwick - Department of Economics.

    Cited by:

    1. Ndebele, Tom & Marsh, Dan & Scarpa, Riccardo, 2019. "Consumer switching in retail electricity markets: Is price all that matters?," Energy Economics, Elsevier, vol. 83(C), pages 88-103.
    2. Deane, Paul & FitzGerald, John & Malaguzzi Valeri, Laura & Tuohy, Aidan & Walsh, Darragh, 2014. "Irish and British Electricity Prices: What Recent History Implies for Future Prices," Papers RB2014/2/6, Economic and Social Research Institute (ESRI).
    3. Richard Benjamin, 2016. "Tacit Collusion in Electricity Markets with Uncertain Demand," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 48(1), pages 69-93, February.
    4. Angelica Gianfreda & Luigi Grossi, 2011. "Forecasting Italian Electricity Zonal Prices with Exogenous Variables," Working Papers 01/2011, University of Verona, Department of Economics.
    5. David Newbery, 2019. "Strengths and Weaknesses of the British Market Model," Working Papers EPRG1907, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    6. Facchini, Angelo & Rubino, Alessandro & Caldarelli, Guido & Di Liddo, Giuseppe, 2019. "Changes to Gate Closure and its impact on wholesale electricity prices: The case of the UK," Energy Policy, Elsevier, vol. 125(C), pages 110-121.
    7. Stephen Davies, Catherine Waddams Price, and Chris M. Wilson, 2014. "Nonlinear Pricing and Tariff Differentiation: Evidence from the British Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    8. Amountzias, Chrysovalantis & Dagdeviren, Hulya & Patokos, Tassos, 2017. "Pricing decisions and market power in the UK electricity market: A VECM approach," Energy Policy, Elsevier, vol. 108(C), pages 467-473.
    9. Yanrui Wu, 2012. "Electricity Market Integration Global Trends and Implications for the EAS Region," Economics Discussion / Working Papers 12-19, The University of Western Australia, Department of Economics.
    10. Gorecki, Paul K., 2011. "The Internal EU Electricity Market: Implications for Ireland," Research Series, Economic and Social Research Institute (ESRI), number RS23.
    11. Pollitt, M. J., 2011. "Lessons from the History of Independent System Operators in the Energy Sector, with applications to the Water Sector," Cambridge Working Papers in Economics 1153, Faculty of Economics, University of Cambridge.
    12. Pollitt, Michael G., 2012. "Lessons from the history of independent system operators in the energy sector," Energy Policy, Elsevier, vol. 47(C), pages 32-48.
    13. Goutam Dutta & Krishnendranath Mitra, 2017. "A literature review on dynamic pricing of electricity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1131-1145, October.
    14. Bosco, Bruno & Parisio, Lucia & Pelagatti, Matteo, 2013. "Price-capping in partially monopolistic electricity markets with an application to Italy," Energy Policy, Elsevier, vol. 54(C), pages 257-266.
    15. Guo, Sui & Li, Huajiao & An, Haizhong & Sun, Qingru & Hao, Xiaoqing & Liu, Yanxin, 2019. "Steel product prices transmission activities in the midstream industrial chain and global markets," Resources Policy, Elsevier, vol. 60(C), pages 56-71.
    16. Yongli Wang & Shanshan Song & Mingchen Gao & Jingyan Wang & Jinrong Zhu & Zhongfu Tan, 2020. "Accounting for the Life Cycle Cost of Power Grid Projects by Employing a System Dynamics Technique: A Power Reform Perspective," Sustainability, MDPI, vol. 12(8), pages 1-28, April.
    17. di Cosmo, Valeria & Lynch, Muireann A., 2015. "Competition and the Single Electricity Market: Which Lessons for Ireland," Papers WP497, Economic and Social Research Institute (ESRI).
    18. Szőke, Tamás & Hortay, Olivér & Balogh, Eszter, 2019. "Asymmetric price transmission in the Hungarian retail electricity market," Energy Policy, Elsevier, vol. 133(C).
    19. Daglish, Toby, 2016. "Consumer governance in electricity markets," Energy Economics, Elsevier, vol. 56(C), pages 326-337.
    20. Hakam, Dzikri Firmansyah, 2019. "Mitigating the risk of market power abuse in electricity sector restructuring: Evidence from Indonesia," Utilities Policy, Elsevier, vol. 56(C), pages 181-191.
    21. Brown, David P. & Eckert, Andrew, 2018. "The effect of default rates on retail competition and pricing decisions of competitive retailers: The case of Alberta," Energy Policy, Elsevier, vol. 118(C), pages 298-311.
    22. Seyed Safdar Hosseini & Zahra Alizadeh Khalifehmahaleh, 2013. "Market Structure and Price Adjustment in the Iranian Tea Market," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 18(2), pages 1-19, spring.
    23. Valadkhani, Abbas & Nguyen, Jeremy & Smyth, Russell, 2018. "Consumer electricity and gas prices across Australian capital cities: Structural breaks, effects of policy reforms and interstate differences," Energy Economics, Elsevier, vol. 72(C), pages 365-375.
    24. Boroumand, Raphaël Homayoun, 2015. "Electricity markets and oligopolistic behaviors: The impact of a multimarket structure," Research in International Business and Finance, Elsevier, vol. 33(C), pages 319-333.

  13. Arfini, Filippo & Donati, Michele & Grossi, L. & Paris, Quirino, 2008. "Revenue and Cost Functions in PMP: a Methodological Integration for a Territorial Analysis of CAP," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6636, European Association of Agricultural Economists.

    Cited by:

    1. Arfini, Filippo & Donati, Michele, 2011. "Organic Productions and Capacity to Respond to Market Signals and Policies: An Empirical Analysis of a Sample of FADN Farms," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114229, European Association of Agricultural Economists.
    2. Kamel Elouhichi & Maria Espinosa Goded & Pavel Ciaian & Angel Perni Llorente & Bouda Vosough Ahmadi & Liesbeth Colen & Sergio Gomez Y Paloma, 2018. "The EU-Wide Individual Farm Model for Common Agricultural Policy Analysis (IFM-CAP v.1): Economic Impacts of CAP Greening," JRC Research Reports JRC108693, Joint Research Centre.
    3. Heckelei, Thomas & Britz, Wolfgang & Zhang, Yinan, 2012. "Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(1), pages 1-16, April.
    4. Kamel Louhichi & Pavel Ciaian & Maria Espinosa & Angel Perni & Sergio Gomez y Paloma, 2018. "Economic impacts of CAP greening: application of an EU-wide individual farm model for CAP analysis (IFM-CAP)," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(2), pages 205-238.
    5. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "Farm-level economic impacts of EU-CAP greening measures," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205309, Agricultural and Applied Economics Association.
    6. Kamel Louhichi & Pascal Tillie & Aymeric Ricome & Sergio Gomez y Paloma, 2020. "Modelling Farm-household Livelihoods in Developing Economies Insights from three country case studies using LSMS-ISA data [Modélisation des moyens de subsistance des ménages agricoles dans les écon," Working Papers hal-02544905, HAL.
    7. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "EU-wide individual Farm Model for CAP Analysis (IFM-CAP): Application to Crop Diversification Policy," 2015 Conference, August 9-14, 2015, Milan, Italy 212155, International Association of Agricultural Economists.

Articles

  1. Lisi, Francesco & Grossi, Luigi & Quaglia, Federico, 2023. "Evaluation of Cost-at-Risk related to the procurement of resources in the ancillary services market. The case of the Italian electricity market," Energy Economics, Elsevier, vol. 121(C).

    Cited by:

    1. Gergo Varhegyi & Mutasim Nour, 2024. "Advancing Fast Frequency Response Ancillary Services in Renewable-Heavy Grids: A Global Review of Energy Storage-Based Solutions and Market Dynamics," Energies, MDPI, vol. 17(15), pages 1-29, July.

  2. Favero, Filippo & Grossi, Luigi, 2023. "Analysis of individual natural gas consumption and price elasticity: Evidence from billing data in Italy," Energy Economics, Elsevier, vol. 118(C).

    Cited by:

    1. Andrea Colabella & Luciano Lavecchia & Valentina Michelangeli & Raffaella Pico, 2023. "To eat or to heat: are energy bills squeezing people's spending?," Questioni di Economia e Finanza (Occasional Papers) 800, Bank of Italy, Economic Research and International Relations Area.
    2. Yousaf Raza, Muhammad & Lin, Boqiang, 2023. "Development trend of Pakistan's natural gas consumption: A sectorial decomposition analysis," Energy, Elsevier, vol. 278(PA).

  3. Fianu, Emmanuel Senyo & Ahelegbey, Daniel Felix & Grossi, Luigi, 2022. "Modeling risk contagion in the Italian zonal electricity market," European Journal of Operational Research, Elsevier, vol. 298(2), pages 656-679.
    See citations under working paper version above.
  4. Filippo Beltrami & Fulvio Fontini & Monica Giulietti & Luigi Grossi, 2022. "The Zonal and Seasonal CO2 Marginal Emissions Factors for the Italian Power Market," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(2), pages 381-411, October.
    See citations under working paper version above.
  5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    See citations under working paper version above.
  6. Beltrami, Filippo & Fontini, Fulvio & Grossi, Luigi, 2021. "The value of carbon emission reduction induced by Renewable Energy Sources in the Italian power market," Ecological Economics, Elsevier, vol. 189(C).

    Cited by:

    1. Xiaofeng Xu & Xiangyu Chen & Yi Xu & Tao Wang & Yifan Zhang, 2022. "Improving the Innovative Performance of Renewable Energy Enterprises in China: Effects of Subsidy Policy and Intellectual Property Legislation," Sustainability, MDPI, vol. 14(13), pages 1-24, July.
    2. Filippo Beltrami & Fulvio Fontini & Monica Giulietti & Luigi Grossi, 2022. "The Zonal and Seasonal CO2 Marginal Emissions Factors for the Italian Power Market," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(2), pages 381-411, October.
    3. Wang, Delu & Li, Chunxiao & Mao, Jinqi & Yang, Qing, 2023. "What affects the implementation of the renewable portfolio standard? An analysis of the four-party evolutionary game," Renewable Energy, Elsevier, vol. 204(C), pages 250-261.
    4. Md. Hasanur Rahman & Liton Chandra Voumik & Md. Jamsedul Islam & Md. Abdul Halim & Miguel Angel Esquivias, 2022. "Economic Growth, Energy Mix, and Tourism-Induced EKC Hypothesis: Evidence from Top Ten Tourist Destinations," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    5. Liu, Bingchun & Huo, Xiankai, 2024. "Prediction of Photovoltaic power generation and analyzing of carbon emission reduction capacity in China," Renewable Energy, Elsevier, vol. 222(C).
    6. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    7. Lu Gan & Dirong Xu & Xiuyun Chen & Pengyan Jiang & Benjamin Lev & Zongmin Li, 2023. "Sustainable portfolio re-equilibrium on wind-solar-hydro system: An integrated optimization with combined meta-heuristic," Energy & Environment, , vol. 34(5), pages 1383-1408, August.

  7. Beltrami, Filippo & Burlinson, Andrew & Giulietti, Monica & Grossi, Luigi & Rowley, Paul & Wilson, Grant, 2020. "Where did the time (series) go? Estimation of marginal emission factors with autoregressive components," Energy Economics, Elsevier, vol. 91(C).
    See citations under working paper version above.
  8. Grossi, Luigi & Nan, Fany, 2019. "Robust forecasting of electricity prices: Simulations, models and the impact of renewable sources," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 305-318.

    Cited by:

    1. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
    2. Sergio Cantillo-Luna & Ricardo Moreno-Chuquen & Jesus Lopez-Sotelo & David Celeita, 2023. "An Intra-Day Electricity Price Forecasting Based on a Probabilistic Transformer Neural Network Architecture," Energies, MDPI, vol. 16(19), pages 1-24, September.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Ana Cabrera-Tobar & Alessandro Massi Pavan & Giovanni Petrone & Giovanni Spagnuolo, 2022. "A Review of the Optimization and Control Techniques in the Presence of Uncertainties for the Energy Management of Microgrids," Energies, MDPI, vol. 15(23), pages 1-38, December.
    5. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
    6. Beltrami, Filippo & Burlinson, Andrew & Giulietti, Monica & Grossi, Luigi & Rowley, Paul & Wilson, Grant, 2020. "Where did the time (series) go? Estimation of marginal emission factors with autoregressive components," Energy Economics, Elsevier, vol. 91(C).
    7. Fianu, Emmanuel Senyo & Ahelegbey, Daniel Felix & Grossi, Luigi, 2022. "Modeling risk contagion in the Italian zonal electricity market," European Journal of Operational Research, Elsevier, vol. 298(2), pages 656-679.
    8. Halužan, Marko & Verbič, Miroslav & Zorić, Jelena, 2020. "Performance of alternative electricity price forecasting methods: Findings from the Greek and Hungarian power exchanges," Applied Energy, Elsevier, vol. 277(C).
    9. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    10. Nametala, Ciniro Aparecido Leite & Faria, Wandry Rodrigues & Lage, Guilherme Guimarães & Pereira, Benvindo Rodrigues, 2023. "Analysis of hourly price granularity implementation in the Brazilian deregulated electricity contracting environment," Utilities Policy, Elsevier, vol. 81(C).
    11. Ricardo Torres-López & David Casillas-Pérez & Jorge Pérez-Aracil & Laura Cornejo-Bueno & Enrique Alexandre & Sancho Salcedo-Sanz, 2022. "Analysis of Machine Learning Approaches’ Performance in Prediction Problems with Human Activity Patterns," Mathematics, MDPI, vol. 10(13), pages 1-18, June.
    12. Srđan Skok & Ahmed Mutapčić & Renata Rubesa & Mario Bazina, 2020. "Transmission Power System Modeling by Using Aggregated Distributed Generation Model Based on a TSO—DSO Data Exchange Scheme," Energies, MDPI, vol. 13(15), pages 1-15, August.
    13. Diego Aineto & Javier Iranzo-Sánchez & Lenin G. Lemus-Zúñiga & Eva Onaindia & Javier F. Urchueguía, 2019. "On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market," Energies, MDPI, vol. 12(11), pages 1-20, May.
    14. Arkadiusz Jedrzejewski & Grzegorz Marcjasz & Rafal Weron, 2021. "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Parameter-rich models estimated via the LASSO," WORking papers in Management Science (WORMS) WORMS/21/04, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    15. Beltrami, Filippo & Fontini, Fulvio & Grossi, Luigi, 2021. "The value of carbon emission reduction induced by Renewable Energy Sources in the Italian power market," Ecological Economics, Elsevier, vol. 189(C).
    16. Halužan, Marko & Verbič, Miroslav & Zorić, Jelena, 2022. "An integrated model for electricity market coupling simulations: Evidence from the European power market crossroad," Utilities Policy, Elsevier, vol. 79(C).
    17. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.

  9. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Post-Print hal-03794543, HAL.

  10. Grossi, Luigi & Mussini, Mauro, 2018. "A spatial shift-share decomposition of electricity consumption changes across Italian regions," Energy Policy, Elsevier, vol. 113(C), pages 278-293.

    Cited by:

    1. Chao Bao & Ruowen Liu, 2019. "Electricity Consumption Changes across China’s Provinces Using A Spatial Shift-Share Decomposition Model," Sustainability, MDPI, vol. 11(9), pages 1-15, April.
    2. Ruxu Sheng & Rong Zhou & Ying Zhang & Zidi Wang, 2021. "Green Investment Changes in China: A Shift-Share Analysis," IJERPH, MDPI, vol. 18(12), pages 1-15, June.
    3. Zhou, Bo & Zhang, Cheng & Wang, Qunwei & Zhou, Dequn, 2020. "Does emission trading lead to carbon leakage in China? Direction and channel identifications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    4. Miguel Blanco & Marcos Ferasso & Lydia Bares, 2021. "Evaluation of the Effects on Regional Production and Employment in Spain of the Renewable Energy Plan 2011–2020," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    5. Lin, Gang & Jiang, Dong & Fu, Jingying & Wang, Di & Li, Xiang, 2019. "A spatial shift-share decomposition of energy consumption changes in China," Energy Policy, Elsevier, vol. 135(C).
    6. Ruxu Sheng & Juntian Du & Songqi Liu & Changan Wang & Zidi Wang & Xiaoqian Liu, 2021. "Solar Photovoltaic Investment Changes across China Regions Using a Spatial Shift-Share Analysis," Energies, MDPI, vol. 14(19), pages 1-14, October.
    7. Marco Baudino, 2020. "Environmental Engel curves in Italy: A spatial econometric investigation," Papers in Regional Science, Wiley Blackwell, vol. 99(4), pages 999-1018, August.

  11. Monica Giulietti, Luigi Grossi, Elisa Trujillo Baute, and Michael Waterson, 2018. "Analyzing the Potential Economic Value of Energy Storage," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    See citations under working paper version above.
  12. Luigi Grossi & Sven Heim & Kai Hüschelrath & Michael Waterson, 2018. "Electricity market integration and the impact of unilateral policy reforms," Oxford Economic Papers, Oxford University Press, vol. 70(3), pages 799-820.
    See citations under working paper version above.
  13. Luigi Grossi & Mauro Mussini, 2017. "Inequality in Energy Intensity in the EU-28: Evidence from a New Decomposition Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).

    Cited by:

    1. Mussini, Mauro, 2020. "Inequality and convergence in energy intensity in the European Union," Applied Energy, Elsevier, vol. 261(C).
    2. Montalbano, P. & Nenci, S., 2019. "Energy efficiency, productivity and exporting: Firm-level evidence in Latin America," Energy Economics, Elsevier, vol. 79(C), pages 97-110.
    3. Grossi, Luigi & Mussini, Mauro, 2018. "A spatial shift-share decomposition of electricity consumption changes across Italian regions," Energy Policy, Elsevier, vol. 113(C), pages 278-293.
    4. Feng, Yanchao & Zhang, Juan & Geng, Yong & Jin, Shurui & Zhu, Ziyi & Liang, Zhou, 2023. "Explaining and modeling the reduction effect of low-carbon energy transition on energy intensity: Empirical evidence from global data," Energy, Elsevier, vol. 281(C).
    5. Christian Haas & Karol Kempa, 2018. "Directed Technical Change and Energy Intensity Dynamics: Structural Change vs. Energy Efficiency," The Energy Journal, , vol. 39(4), pages 127-151, July.
    6. Tomasz Rokicki & Radosław Jadczak & Adam Kucharski & Piotr Bórawski & Aneta Bełdycka-Bórawska & András Szeberényi & Aleksandra Perkowska, 2022. "Changes in Energy Consumption and Energy Intensity in EU Countries as a Result of the COVID-19 Pandemic by Sector and Area Economy," Energies, MDPI, vol. 15(17), pages 1-26, August.
    7. Yetkiner, Hakan & Berk, Istemi, 2023. "Energy intensity and directed fiscal policy," Economic Systems, Elsevier, vol. 47(2).
    8. Lin, Boqiang & Wang, Miao, 2021. "What drives energy intensity fall in China? Evidence from a meta-frontier approach," Applied Energy, Elsevier, vol. 281(C).
    9. Sinha, Avik & Balsalobre-Lorente, Daniel & Zafar, Wasif & Saleem, Muhammad Mansoor, 2021. "Analyzing Global Inequality in Access to Energy: Developing Policy Framework by Inequality Decomposition," MPRA Paper 111061, University Library of Munich, Germany, revised 2021.
    10. Dhani Setyawan & Irwanda Wisnu Wardhana, 2020. "Energy Efficiency Development in Indonesia: An Empirical Analysis of Energy Intensity Inequality," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 68-77.

  14. Grossi, Luigi & Heim, Sven & Waterson, Michael, 2017. "The impact of the German response to the Fukushima earthquake," Energy Economics, Elsevier, vol. 66(C), pages 450-465.

    Cited by:

    1. Jarvis, Stephen & Deschenes, Olivier & Jha, Akshaya, 2022. "The private and external costs of Germany’s nuclear phase-out," LSE Research Online Documents on Economics 113634, London School of Economics and Political Science, LSE Library.
    2. Gugler, Klaus & Haxhimusa, Adhurim & Liebensteiner, Mario, 2021. "Effectiveness of climate policies: Carbon pricing vs. subsidizing renewables," Journal of Environmental Economics and Management, Elsevier, vol. 106(C).
    3. Shi Chen & Wolfgang Karl Hardle & Brenda L'opez Cabrera, 2020. "Regularization Approach for Network Modeling of German Power Derivative Market," Papers 2009.09739, arXiv.org.
    4. Florian Follert & Werner Gleißner & Dominik Möst, 2021. "What Can Politics Learn from Management Decisions? A Case Study of Germany’s Exit from Nuclear Energy after Fukushima," Energies, MDPI, vol. 14(13), pages 1-15, June.
    5. Liebensteiner, Mario & Wrienz, Matthias, 2020. "Do Intermittent Renewables Threaten the Electricity Supply Security?," Energy Economics, Elsevier, vol. 87(C).
    6. Klaus Gugler & Adhurim Haxhimusa & Mario Liebensteiner, 2019. "Effective Climate Policy Doesn’t Have to be Expensive," Department of Economics Working Papers wuwp293, Vienna University of Economics and Business, Department of Economics.
    7. Zheng, Shanshan & Wang, Derek D., 2024. "The local economic impacts of mega nuclear accident: A synthetic control analysis of Fukushima," Economic Modelling, Elsevier, vol. 136(C).
    8. Jeong, Minsoo & You, Jung S., 2022. "Estimating the economic costs of nuclear power plant outages in a regulated market using a latent factor model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    9. Rinne, Sonja, 2018. "Radioinactive: Are nuclear power plant outages in France contagious to the German electricity price?," CIW Discussion Papers 3/2018, University of Münster, Center for Interdisciplinary Economics (CIW).
    10. Manuela G. Hartwig & Leslie Tkach-Kawasaki, 2020. "Correction to: Identifying the ‘Fukushima Effect’ in Germany through policy actors’ responses: evidence from the G-GEPON 2 survey," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 213-234, February.
    11. Philip Beran & Christian Pape & Christoph Weber, 2018. "Modelling German electricity wholesale spot prices with a parsimonious fundamental model – Validation and application," EWL Working Papers 1801, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Mar 2018.
    12. Manuela G. Hartwig & Leslie Tkach-Kawasaki, 2019. "Identifying the ‘Fukushima Effect’ in Germany through policy actors’ responses: evidence from the G-GEPON 2 survey," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2081-2101, July.

  15. Mussini, Mauro & Grossi, Luigi, 2015. "Decomposing changes in CO2 emission inequality over time: The roles of re-ranking and changes in per capita CO2 emission disparities," Energy Economics, Elsevier, vol. 49(C), pages 274-281.

    Cited by:

    1. Mussini, Mauro, 2020. "Inequality and convergence in energy intensity in the European Union," Applied Energy, Elsevier, vol. 261(C).
    2. ANDREOLI Francesco & MUSSINI Mauro & PRETE Vincenzo, 2019. "Urban poverty: Theory and evidence from American cities," LISER Working Paper Series 2019-07, Luxembourg Institute of Socio-Economic Research (LISER).
    3. Jianghua Liu & Mengxu Li & Yitao Ding, 2021. "Econometric analysis of the impact of the urban population size on carbon dioxide (CO2) emissions in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 18186-18203, December.
    4. Marta Pascual-Sáez & David Cantarero-Prieto & Jose R. Pires-Manso, 2017. "Gross inland energy consumption inequality in Europe: An empirical approach," Working Papers. Collection B: Regional and sectoral economics 1704, Universidade de Vigo, GEN - Governance and Economics research Network.
    5. Meng Yang & Yisheng Liu & Jinzhao Tian & Feiyu Cheng & Pengbo Song, 2022. "Dynamic Evolution and Regional Disparity in Carbon Emission Intensity in China," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    6. Wanbei Jiang & Weidong Liu, 2020. "Provincial-Level CO 2 Emissions Intensity Inequality in China: Regional Source and Explanatory Factors of Interregional and Intraregional Inequalities," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    7. Wu, Shimei & Chen, Zhan-Ming, 2023. "Carbon inequality in China: Evidence from city-level data," China Economic Review, Elsevier, vol. 78(C).
    8. Chen, Jiandong & Cheng, Shulei & Song, Malin & Wu, Yinyin, 2016. "A carbon emissions reduction index: Integrating the volume and allocation of regional emissions," Applied Energy, Elsevier, vol. 184(C), pages 1154-1164.
    9. Luigi Grossi & Mauro Mussini, 2017. "Inequality in Energy Intensity in the EU-28: Evidence from a New Decomposition Method," The Energy Journal, , vol. 38(4), pages 1-18, July.
    10. Francesca Battisti & Francesco Porro, 2023. "A multi-decomposition of Zenga-84 inequality index: an application to the disparity in CO $$_2$$ 2 emissions in European countries," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 957-981, September.
    11. Bel, Germà & Rosell, Jordi, 2017. "The impact of socioeconomic characteristics on CO2 emissions associated with urban mobility: Inequality across individuals," Energy Economics, Elsevier, vol. 64(C), pages 251-261.
    12. Rongrong Li & Xue-Ting Jiang, 2017. "Inequality of Carbon Intensity: Empirical Analysis of China 2000–2014," Sustainability, MDPI, vol. 9(5), pages 1-12, April.
    13. Agnolucci, Paolo & Arvanitopoulos, Theodoros, 2019. "Industrial characteristics and air emissions: Long-term determinants in the UK manufacturing sector," Energy Economics, Elsevier, vol. 78(C), pages 546-566.
    14. Mauro Mussini, 2017. "Decomposing Changes in Inequality and Welfare Between EU Regions: The Roles of Population Change, Re-Ranking and Income Growth," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(2), pages 455-478, January.
    15. Chen, Jiandong & Cheng, Shulei & Song, Malin, 2017. "Decomposing inequality in energy-related CO2 emissions by source and source increment: The roles of production and residential consumption," Energy Policy, Elsevier, vol. 107(C), pages 698-710.
    16. Chen, Lei & Xu, Linyu & Yang, Zhifeng, 2019. "Inequality of industrial carbon emissions of the urban agglomeration and its peripheral cities: A case in the Pearl River Delta, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 438-447.
    17. Shi, Kaifang & Yu, Bailang & Zhou, Yuyu & Chen, Yun & Yang, Chengshu & Chen, Zuoqi & Wu, Jianping, 2019. "Spatiotemporal variations of CO2 emissions and their impact factors in China: A comparative analysis between the provincial and prefectural levels," Applied Energy, Elsevier, vol. 233, pages 170-181.
    18. Francesco Andreoli & Mauro Mussini & Vincenzo Prete & Claudio Zoli, 2021. "Urban poverty: Measurement theory and evidence from American cities," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 19(4), pages 599-642, December.
    19. Chen, Jiandong & Cheng, Shulei & Song, Malin & Wang, Jia, 2016. "Interregional differences of coal carbon dioxide emissions in China," Energy Policy, Elsevier, vol. 96(C), pages 1-13.
    20. Wang, H. & Zhou, P., 2018. "Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis," Ecological Economics, Elsevier, vol. 154(C), pages 257-271.
    21. Wang, Shaojian & Fang, Chuanglin & Wang, Yang, 2016. "Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 505-515.

  16. Gianfreda, Angelica & Grossi, Luigi, 2012. "Forecasting Italian electricity zonal prices with exogenous variables," Energy Economics, Elsevier, vol. 34(6), pages 2228-2239.
    See citations under working paper version above.
  17. Monica Giulietti, Luigi Grossi, and Michael Waterson, 2012. "A Rough Analysis: Valuing Gas Storage," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).

    Cited by:

    1. Arthur Thomas & Olivier Massol & Benoît Sévi, 2020. "How are Day-Ahead Prices Informative for Predicting the Next Day’s Consumption of Natural Gas ?," Working Papers hal-03178474, HAL.
    2. Nick, Sebastian & Thoenes, Stefan, 2014. "What drives natural gas prices? — A structural VAR approach," Energy Economics, Elsevier, vol. 45(C), pages 517-527.
    3. Mouli-Castillo, Julien & Heinemann, Niklas & Edlmann, Katriona, 2021. "Mapping geological hydrogen storage capacity and regional heating demands: An applied UK case study," Applied Energy, Elsevier, vol. 283(C).

  18. Luigi Grossi & Fabrizio Laurini, 2011. "Robust estimation of efficient mean–variance frontiers," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(1), pages 3-22, April.

    Cited by:

    1. Maria Cristina Arcuri & Gino Gandolfi & Fabrizio Laurini, 2023. "Robust portfolio optimization for banking foundations: a CVaR approach for asset allocation with mandatory constraints," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 557-581, June.
    2. Bartosz Kaszuba, 2012. "Empirical Comparison of Robust Portfolios’ Investment Effects," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(1), pages 047-061, June.

  19. Giulietti, Monica & Grossi, Luigi & Waterson, Michael, 2010. "Price transmission in the UK electricity market: Was NETA beneficial?," Energy Economics, Elsevier, vol. 32(5), pages 1165-1174, September.
    See citations under working paper version above.
  20. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.

    Cited by:

    1. Maria Cristina Arcuri & Gino Gandolfi & Fabrizio Laurini, 2023. "Robust portfolio optimization for banking foundations: a CVaR approach for asset allocation with mandatory constraints," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 557-581, June.
    2. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    4. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    5. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    6. Grané, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.

  21. P. Ganugi & L. Grossi & G. Gozzi, 2005. "Testing Gibrat's law in Italian macro-regions: Analysis on a panel of mechanical companies," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(1), pages 101-126, February.

    Cited by:

    1. Anna Maria Fiori, 2020. "On firm size distribution: statistical models, mechanisms, and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 447-482, September.
    2. Omar Blanco & Simone Alfarano, 2016. "Granularity of the business cycle fluctuations: The Spanish case," Working Papers 2016/25, Economics Department, Universitat Jaume I, Castellón (Spain).
    3. Roberta Piergiovanni, 2010. "Gibrat's Law in the “Third Italy”: Firm Growth in the Veneto Region," Growth and Change, Wiley Blackwell, vol. 41(1), pages 28-58, March.
    4. Bartoloni, Eleonora & Baussola, Maurizio & Bagnato, Luca, 2020. "Waiting for Godot? Success or failure of firms’ growth in a panel of Italian manufacturing firms," Structural Change and Economic Dynamics, Elsevier, vol. 55(C), pages 259-275.
    5. Johan Krisnanto Runtuk & Poh Kiat Ng & Shih Yin Ooi & Remigius Purwanto & Arief Suardi Nur Chairat & Yu Jin Ng, 2023. "Sustainable Growth for Small and Medium-Sized Enterprises: Interpretive Structural Modeling Approach," Sustainability, MDPI, vol. 15(5), pages 1-12, March.

  22. Piero Ganugi & Luigi Grossi & Lisa Crosato, 2004. "Firm size distributions and stochastic growth models: a comparison between ICT and Mechanical Italian Companies," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(3), pages 391-414, February.

    Cited by:

    1. L. Crosato & P. Ganugi, 2007. "Statistical regularity of firm size distribution: the Pareto IV and truncated Yule for Italian SCI manufacturing," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(1), pages 85-115, June.
    2. P. Ganugi & L. Grossi & G. Gozzi, 2005. "Testing Gibrat's law in Italian macro-regions: Analysis on a panel of mechanical companies," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(1), pages 101-126, February.
    3. Anna Maria Fiori, 2020. "On firm size distribution: statistical models, mechanisms, and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 447-482, September.
    4. Cerqueti, Roy & Lupi, Claudio & Pietrovito, Filomena & Pozzolo, Alberto Franco, 2022. "Rank–size distributions for banks: A cross-country analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    5. Crosato, Lisa & Destefanis, Sergio & Ganugi, Piero, 2007. "Technology and Firm Size Distribution:Evidence from Italian Manufacturing," CELPE Discussion Papers 102, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    6. Junho Na & Jeong-dong Lee & Chulwoo Baek, 2017. "Is the service sector different in size heterogeneity?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 95-120, April.

  23. Luigi Grossi & Fabrizio Laurini, 2004. "Analysis of economic time series: effects of extremal observations on testing heteroscedastic components," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 20(2), pages 115-130, April.

    Cited by:

    1. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.

  24. Grossi Luigi, 2004. "Analyzing Financial Time Series through Robust Estimators," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-15, May.

    Cited by:

    1. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2008. "Estimating and Forecasting GARCH Volatility in the Presence of Outiers," Working Papers. Serie AD 2008-13, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    2. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    3. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.