Luca Barbaglia

Personal Details

First Name:	Luca
Middle Name:
Last Name:	Barbaglia
Suffix:
RePEc Short-ID:	pba1702
	[This author has chosen not to make the email address public]
	https://lucabarbaglia.github.io/

Affiliation

Joint Research Centre
European Commission

Sevilla, Spain
https://ec.europa.eu/jrc/en/about/jrc-site/seville
RePEc:edi:ipjrces (more details at EDIRC)

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. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," Working Papers 2022-06, Joint Research Centre, European Commission.
   • Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2023. "Testing big data in a big crisis: Nowcasting under Covid-19," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1548-1563.

   Cited by:

   1. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
   2. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org.
   3. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
   4. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas, 2023. "Nowcasting Economic Activity Using Electricity Market Data: The Case of Lithuania," Economies, MDPI, vol. 11(5), pages 1-21, May.

2. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
   • Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility spillovers and heavy tails: a large t-Vector AutoRegressive approach," Working Papers of Department of Decision Sciences and Information Management, Leuven 590528, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.

   Cited by:

   1. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, vol. 13(7), pages 1-14, March.

3. Ines Wilms & Luca Barbaglia & Christophe Croux, 2016. "Multi-class vector autoregressive models for multi-store sales data," Working Papers of Department of Decision Sciences and Information Management, Leuven 540947, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
   • Ines Wilms & Luca Barbaglia & Christophe Croux, 2018. "Multiclass vector auto‐regressive models for multistore sales data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(2), pages 435-452, February.

   Cited by:

   1. Baek, Changryong & Gates, Katheleen M. & Leinwand, Benjamin & Pipiras, Vladas, 2021. "Two sample tests for high-dimensional autocovariances," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).

4. Luca Barbaglia & Ines Wilms & Christophe Croux, 2016. "Commodity Dynamics: A Sparse Multi-class Approach," Papers 1604.01224, arXiv.org, revised Oct 2016.
   • Barbaglia, Luca & Wilms, Ines & Croux, Christophe, 2016. "Commodity dynamics: A sparse multi-class approach," Energy Economics, Elsevier, vol. 60(C), pages 62-72.
   • Luca Barbaglia & Ines Wilms & Christophe Croux, 2016. "Commodity dynamics: a sparse multi-class approach," Working Papers of Department of Decision Sciences and Information Management, Leuven 538113, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.

   Cited by:

   1. Jiang, Yonghong & Jiang, Cheng & Nie, He & Mo, Bin, 2019. "The time-varying linkages between global oil market and China's commodity sectors: Evidence from DCC-GJR-GARCH analyses," Energy, Elsevier, vol. 166(C), pages 577-586.
   2. Asadi, Mehrad & Roudari, Soheil & Tiwari, Aviral Kumar & Roubaud, David, 2023. "Scrutinizing commodity markets by quantile spillovers: A case study of the Australian economy," Energy Economics, Elsevier, vol. 118(C).
   3. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," EconStor Preprints 235529, ZBW - Leibniz Information Centre for Economics.
      • Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
      • Rabeh Khalfaoui & Eduard Baumöhl & Suleman Sarwar & Tomáš Výrost, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Post-Print hal-03797575, HAL.
   4. Hailan Pan & Xiaohuan Yang, 2021. "Fast clustering algorithm of commodity association big data sparse network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(4), pages 667-674, August.
   5. Jiang, Yonghong & Fu, Yuyuan & Ruan, Weihua, 2019. "Risk spillovers and portfolio management between precious metal and BRICS stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
   6. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
   7. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).

Articles

1. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2023. "Forecasting with Economic News," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 708-719, July.

   Cited by:

   1. Tiziana Assenza & Fabrice Collard & Patrick Fève & Stefanie Huber, 2024. "From Buzz to Bust: How Fake News Shapes the Business Cycle," ECONtribute Discussion Papers Series 287, University of Bonn and University of Cologne, Germany.
   2. Fève, Patrick & Assenza, Tiziana & Collard, Fabrice & Huber, Stefanie, 2024. "From Buzz to Bust: How Fake News Shapes the Business Cycle," TSE Working Papers 24-1516, Toulouse School of Economics (TSE).
   3. José Francisco Lima & Fernanda Catarina Pereira & Arminda Manuela Gonçalves & Marco Costa, 2023. "Bootstrapping State-Space Models: Distribution-Free Estimation in View of Prediction and Forecasting," Forecasting, MDPI, vol. 6(1), pages 1-19, December.

2. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2023. "Testing big data in a big crisis: Nowcasting under Covid-19," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1548-1563.
   • Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," Working Papers 2022-06, Joint Research Centre, European Commission.
   See citations under working paper version above.
3. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).

   Cited by:

   1. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
      • Muhammad Abubakr Naeem & Zhe Peng & Mouhammed Tahir Suleman & Rabindra Nepal & Syed Jawad Hussain Shahzad, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," CAMA Working Papers 2020-81, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   2. Mutaju Isaack Marobhe & Jonathan Mukiza Peter Kansheba, 2023. "High frequency volatility spillover between oil and non-energy commodities during crisis and tranquil periods," SN Business & Economics, Springer, vol. 3(4), pages 1-27, April.
   3. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
   4. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
   5. Sun, Yanpeng & Mirza, Nawazish & Qadeer, Abdul & Hsueh, Hsin-Pei, 2021. "Connectedness between oil and agricultural commodity prices during tranquil and volatile period. Is crude oil a victim indeed?," Resources Policy, Elsevier, vol. 72(C).
   6. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adewuyi, Adeolu O. & Lee, Chien-Chiang, 2022. "Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Energy Economics, Elsevier, vol. 113(C).
   7. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Hammoudeh, Shawkat, 2022. "The connectedness in the world petroleum futures markets using a Quantile VAR approach," Journal of Commodity Markets, Elsevier, vol. 27(C).
   8. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," EconStor Preprints 235529, ZBW - Leibniz Information Centre for Economics.
      • Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
      • Rabeh Khalfaoui & Eduard Baumöhl & Suleman Sarwar & Tomáš Výrost, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Post-Print hal-03797575, HAL.
   9. Hedi Ben Haddad & Imed Mezghani & Abdessalem Gouider, 2021. "The Dynamic Spillover Effects of Macroeconomic and Financial Uncertainty on Commodity Markets Uncertainties," Economies, MDPI, vol. 9(2), pages 1-22, June.
   10. Ben Amar, Amine & Bouattour, Mondher & Bellalah, Makram & Goutte, Stéphane, 2023. "Shift contagion and minimum causal intensity portfolio during the COVID-19 and the ongoing Russia-Ukraine conflict," Finance Research Letters, Elsevier, vol. 55(PA).
       • Amine Ben Amar & Mondher Bouattour & Makram Bellalah & Stéphane Goutte, 2023. "Shift contagion and minimum causal intensity portfolio during the COVID-19 and the ongoing Russia-Ukraine conflict," Post-Print hal-04122251, HAL.
       • Mondher Bouattour & Amine Ben Amar & Stéphane Goutte & Makram Bellalah, 2023. "Shift contagion and minimum causal intensity portfolio during the COVID-19 and the ongoing Russia-Ukraine conflict," Working Papers halshs-04064084, HAL.
   11. Cao, Yan & Cheng, Sheng, 2021. "Impact of COVID-19 outbreak on multi-scale asymmetric spillovers between food and oil prices," Resources Policy, Elsevier, vol. 74(C).
   12. Mohammad Isleimeyyeh & Amine Ben Amar & Stéphane Goutte & Ramzi Benkraiem, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," Post-Print hal-03674806, HAL.
       • Amar, Amine Ben & Goutte, Stéphane & Isleimeyyeh, Mohammad & Benkraiem, Ramzi, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," International Review of Financial Analysis, Elsevier, vol. 82(C).
       • Mohammad Isleimeyyeh & Amine Ben Amar & Stéphane Goutte, 2021. "Commodity markets dynamics: What do crosscommodities over different nearest-to-maturities tell us?," Working Papers halshs-03211699, HAL.
       • Amine Amar & Stéphane Goutte & Mohammad Isleimeyyeh & Ramzi Benkraiem, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," Working Papers halshs-03672476, HAL.
   13. Mishra, Aswini Kumar & Arunachalam, Vairam & Olson, Dennis & Patnaik, Debasis, 2023. "Dynamic connectedness in commodity futures markets during Covid-19 in India: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 82(C).
   14. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
   15. Derick Quintino & Cristiane Ogino & Inzamam Ul Haq & Paulo Ferreira & Márcia Oliveira, 2023. "An Analysis of Dynamic Correlations among Oil, Natural Gas and Ethanol Markets: New Evidence from the Pre- and Post-COVID-19 Crisis," Energies, MDPI, vol. 16(5), pages 1-14, February.
   16. Umar, Zaghum & Manel, Youssef & Riaz, Yasir & Gubareva, Mariya, 2021. "Return and volatility transmission between emerging markets and US debt throughout the pandemic crisis," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
   17. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
   18. Guo, Li-Yang & Feng, Chao, 2021. "Are there spillovers among China's pilots for carbon emission allowances trading?," Energy Economics, Elsevier, vol. 103(C).
   19. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Multiscale spillovers, connectedness, and portfolio management among precious and industrial metals, energy, agriculture, and livestock futures," Resources Policy, Elsevier, vol. 74(C).
   20. Adeleke, Musefiu A. & Awodumi, Olabanji B. & Adewuyi, Adeolu O., 2022. "Return and volatility connectedness among commodity markets during major crises periods: Static and dynamic analyses with asymmetries," Resources Policy, Elsevier, vol. 79(C).
   21. Miroslava Ivanova & Lilko Dospatliev, 2023. "Effects of Diesel Price on Changes in Agricultural Commodity Prices in Bulgaria," Mathematics, MDPI, vol. 11(3), pages 1-22, January.
   22. K. Abhaya Kumar & Prakash Pinto & Iqbal Thonse Hawaldar & Saheem Shaikh & Shravan Bhagav & B. Padmanabha, 2022. "Investigating the Nexus between Crude Oil Price and Stock Prices of Oil Exploration Companies," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 40-47, July.
   23. Chen, Hao & Xu, Chao & Peng, Yun, 2022. "Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China," Resources Policy, Elsevier, vol. 78(C).
   24. Shahzad, Farrukh & Bouri, Elie & Mokni, Khaled & Ajmi, Ahdi Noomen, 2021. "Energy, agriculture, and precious metals: Evidence from time-varying Granger causal relationships for both return and volatility," Resources Policy, Elsevier, vol. 74(C).
   25. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, vol. 13(7), pages 1-14, March.
   26. Vo, Long Hai & Le, Thai-Ha, 2021. "Eatery, energy, environment and economic system, 1970–2017: Understanding volatility spillover patterns in a global sample," Energy Economics, Elsevier, vol. 100(C).
   27. Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
   28. Li, Houjian & Li, Yanjiao & Guo, Lili, 2023. "Extreme risk spillover effect and dynamic linkages between uncertainty and commodity markets: A comparison between China and America," Resources Policy, Elsevier, vol. 85(PA).
   29. Néjib Hachicha & Amine Ben Amar & Ikrame Ben Slimane & Makram Bellalah & Jean-Luc Prigent, 2022. "Dynamic connectedness and optimal hedging strategy among commodities and financial indices," Post-Print hal-03745047, HAL.
       • Hachicha, Néjib & Ben Amar, Amine & Ben Slimane, Ikrame & Bellalah, Makram & Prigent, Jean-Luc, 2022. "Dynamic connectedness and optimal hedging strategy among commodities and financial indices," International Review of Financial Analysis, Elsevier, vol. 83(C).
   30. Feng, Qianqian & Sun, Xiaolei & Liu, Chang & Li, Jianping, 2021. "Spillovers between sovereign CDS and exchange rate markets: The role of market fear," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
   31. Ben Amar, Amine & Goutte, Stéphane & Isleimeyyeh, Mohammad, 2022. "Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 386-400.

4. Ines Wilms & Luca Barbaglia & Christophe Croux, 2018. "Multiclass vector auto‐regressive models for multistore sales data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(2), pages 435-452, February.
   • Ines Wilms & Luca Barbaglia & Christophe Croux, 2016. "Multi-class vector autoregressive models for multi-store sales data," Working Papers of Department of Decision Sciences and Information Management, Leuven 540947, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
   See citations under working paper version above.
5. Barbaglia, Luca & Wilms, Ines & Croux, Christophe, 2016. "Commodity dynamics: A sparse multi-class approach," Energy Economics, Elsevier, vol. 60(C), pages 62-72.
   • Luca Barbaglia & Ines Wilms & Christophe Croux, 2016. "Commodity Dynamics: A Sparse Multi-class Approach," Papers 1604.01224, arXiv.org, revised Oct 2016.
   • Luca Barbaglia & Ines Wilms & Christophe Croux, 2016. "Commodity dynamics: a sparse multi-class approach," Working Papers of Department of Decision Sciences and Information Management, Leuven 538113, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
   See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (3) 2016-07-02 2017-08-13 2022-10-03. Author is listed
2. NEP-ETS: Econometric Time Series (3) 2016-07-02 2017-08-13 2017-09-10. Author is listed
3. NEP-RMG: Risk Management (2) 2017-08-13 2017-09-10. Author is listed
4. NEP-AGR: Agricultural Economics (1) 2016-04-16
5. NEP-BIG: Big Data (1) 2022-10-03
6. NEP-COM: Industrial Competition (1) 2016-07-02
7. NEP-EEC: European Economics (1) 2022-10-03
8. NEP-ENE: Energy Economics (1) 2017-09-10
9. NEP-FOR: Forecasting (1) 2022-10-03
10. NEP-INT: International Trade (1) 2022-08-29
11. NEP-NET: Network Economics (1) 2022-08-29

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