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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)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Luca Barbaglia & Serena Fatica & Caterina Rho, 2024. "Flooded credit markets: physical climate risk and small business lending," Mo.Fi.R. Working Papers 186, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
  2. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
  3. Luca Barbaglia & Christophe Croux & Ines Wilms, 2022. "Detecting Anti-dumping Circumvention: A Network Approach," Papers 2207.05394, arXiv.org.
  4. 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," JRC Working Papers in Economics and Finance 2022-06, Joint Research Centre, European Commission.
  5. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
  6. 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.
  7. Luca Barbaglia & Ines Wilms & Christophe Croux, 2016. "Commodity Dynamics: A Sparse Multi-class Approach," Papers 1604.01224, arXiv.org, revised Oct 2016.

Articles

  1. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2024. "Forecasting GDP in Europe with textual data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 338-355, March.
  2. 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.
  3. 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.
  4. Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023. "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 569-596.
  5. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
  6. 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.
  7. Barbaglia, Luca & Wilms, Ines & Croux, Christophe, 2016. "Commodity dynamics: A sparse multi-class approach," Energy Economics, Elsevier, vol. 60(C), pages 62-72.

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," JRC Working Papers in Economics and Finance 2022-06, Joint Research Centre, European Commission.

    Cited by:

    1. Galdi, Giulio & Casarin, Roberto & Ferrari, Davide & Fezzi, Carlo & Ravazzolo, Francesco, 2023. "Nowcasting industrial production using linear and non-linear models of electricity demand," Energy Economics, Elsevier, vol. 126(C).
    2. Holtemöller, Oliver & Kozyrev, Boris, 2024. "Forecasting economic activity using a neural network in uncertain times: Monte Carlo evidence and application to the German GDP," IWH Discussion Papers 6/2024, Halle Institute for Economic Research (IWH).
    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. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    5. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    6. Cseres-Gergely, Zsombor & Kecht, Valentin & Le Blanc, Julia & Onorante, Luca, 2024. "The economic impact of general vs. targeted lockdowns: New insights from Italian municipalities," Economic Modelling, Elsevier, vol. 134(C).
    7. 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.

    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.

    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.

    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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).
    5. 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).
    6. 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).
    7. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).

Articles

  1. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2024. "Forecasting GDP in Europe with textual data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 338-355, March.

    Cited by:

    1. Julian Ashwin & Eleni Kalamara & Lorena Saiz, 2024. "Nowcasting Euro area GDP with news sentiment: A tale of two crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 887-905, August.

  2. 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. Maria Saveria Mavillonio, 2024. "Natural Language Processing Techniques for Long Financial Document," Discussion Papers 2024/317, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    2. Felix Drinkall & Janet B. Pierrehumbert & Stefan Zohren, 2024. "Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative LLMs," Papers 2407.17624, arXiv.org, revised Jan 2025.
    3. Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
    4. Michael D. Bauer & Daniel Huber & Eric Offner & Marlene Renkel & Ole Wilms, 2024. "Corporate Green Pledges," Working Paper Series 2024-36, Federal Reserve Bank of San Francisco.
    5. 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).
    6. 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.
    7. Barbaglia, Luca & Bellia, Mario & Di Girolamo, Francesca & Rho, Caterina, 2024. "Crypto news and policy innovations: Are European markets affected?," JRC Working Papers in Economics and Finance 2024-07, Joint Research Centre, European Commission.
    8. Yang, Jinglan & Liu, Jianghuai & Yao, Zheng & Ma, Chaoqun, 2024. "Measuring digitalization capabilities using machine learning," Research in International Business and Finance, Elsevier, vol. 70(PB).
    9. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2024. "Forecasting GDP in Europe with textual data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 338-355, March.
    10. Josué Thélissaint, 2024. "Assessing Cryptomarket Risks: Macroeconomic Forces, Market Shocks and Behavioural Dynamics," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-14, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    11. Julian Ashwin & Eleni Kalamara & Lorena Saiz, 2024. "Nowcasting Euro area GDP with news sentiment: A tale of two crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 887-905, August.

  3. 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.
    See citations under working paper version above.
  4. Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023. "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 569-596.

    Cited by:

    1. Barbaglia, Luca & Fatica, Serena & Rho, Caterina, 2023. "Flooded credit markets: physical climate risk and small business lending," JRC Working Papers in Economics and Finance 2023-14, Joint Research Centre, European Commission.
    2. Ming-Tsung Hung & Huai-Chun Lo, 2024. "Risk Analysis of Mortgage Loan Default for Bank Customers and AI Machine Learning," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(6), pages 1-3.

  5. 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. 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.
    2. 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. 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).
    4. Blanc-Blocquel, Augusto & Ortiz-Gracia, Luis & Oviedo, Rodolfo, 2024. "Efficient likelihood estimation of Heston model for novel climate-related financial contracts valuation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 225(C), pages 430-445.
    5. 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).
    6. 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).
    7. 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).
    8. Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    9. 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).
    10. Amal Abricha & Amine Ben Amar & Makram Bellalah, 2024. "Commodity futures markets under stress and stress-free periods: Further insights from a quantile connectedness approach," Post-Print hal-04515196, HAL.
    11. 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).
    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.
    13. Salah Uddin, Gazi & Lucey, Brian & Rahman, Md Lutfur & Stenvall, David, 2024. "Quantile coherency across bonds, commodities, currencies, and equities," Journal of Commodity Markets, Elsevier, vol. 33(C).
    14. 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.
    15. 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).
    16. 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.
    17. 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).
    18. 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.
    19. 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.
    20. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    21. 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.
    22. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    23. 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).
    24. 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).
    25. 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).
    26. 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.
    27. Guo, Li-Yang & Feng, Chao, 2021. "Are there spillovers among China's pilots for carbon emission allowances trading?," Energy Economics, Elsevier, vol. 103(C).
    28. Romain Menier & Guillaume Bagnarosa & Alexandre Gohin, 2024. "On the dependence structure of European vegetable oil markets," Post-Print hal-04523660, HAL.
    29. 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.
    30. 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).
    31. 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).
    32. Chuliá, Helena & Klein, Tony & Muñoz Mendoza, Jorge A. & Uribe, Jorge M., 2024. "Vulnerability of European electricity markets: A quantile connectedness approach," Energy Policy, Elsevier, vol. 184(C).
    33. 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).
    34. 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).
    35. 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).
    36. 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).

  6. 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.
    See citations under working paper version above.
  7. Barbaglia, Luca & Wilms, Ines & Croux, Christophe, 2016. "Commodity dynamics: A sparse multi-class approach," Energy Economics, Elsevier, vol. 60(C), pages 62-72.
    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 9 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 (4) 2016-07-02 2017-08-13 2022-10-03 2024-02-26. Author is listed
  2. NEP-ETS: Econometric Time Series (3) 2016-07-02 2017-08-13 2017-09-10. Author is listed
  3. NEP-URE: Urban and Real Estate Economics (3) 2024-02-19 2024-02-26 2024-08-12. Author is listed
  4. NEP-EEC: European Economics (2) 2022-10-03 2024-02-26
  5. NEP-ENT: Entrepreneurship (2) 2024-02-19 2024-08-12
  6. NEP-ENV: Environmental Economics (2) 2024-02-19 2024-08-12
  7. NEP-RMG: Risk Management (2) 2017-08-13 2017-09-10
  8. NEP-AGR: Agricultural Economics (1) 2016-04-16
  9. NEP-BAN: Banking (1) 2024-08-12
  10. NEP-BIG: Big Data (1) 2022-10-03
  11. NEP-COM: Industrial Competition (1) 2016-07-02
  12. NEP-ENE: Energy Economics (1) 2017-09-10
  13. NEP-EUR: Microeconomic European Issues (1) 2024-02-26
  14. NEP-FDG: Financial Development and Growth (1) 2024-02-19
  15. NEP-FOR: Forecasting (1) 2022-10-03
  16. NEP-GEO: Economic Geography (1) 2024-02-26
  17. NEP-INT: International Trade (1) 2022-08-29
  18. NEP-NET: Network Economics (1) 2022-08-29
  19. NEP-SBM: Small Business Management (1) 2024-08-12

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