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Alessandro Giovannelli

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First Name:Alessandro
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Last Name:Giovannelli
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RePEc Short-ID:pgi264
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Research output

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Working papers

  1. Alessandro Giovannelli & Marco Lippi & Tommaso Proietti, 2023. "Band-Pass Filtering with High-Dimensional Time Series," Papers 2305.06618, arXiv.org.
  2. Simone Tonini & Francesca Chiaromonte & Alessandro Giovannelli, 2022. "On the impact of serial dependence on penalized regression methods," LEM Papers Series 2022/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  3. Luca Mattia Rolla & Alessandro Giovannelli, 2022. "The Forecasting performance of the Factor model with Martingale Difference errors," Papers 2205.10256, arXiv.org, revised Jun 2023.
  4. Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
  5. Alessandro Giovannelli & Tommaso Proietti & Ambra Citton & Ottavio Ricchi & Cristian Tegami & Cristina Tinti, 2020. "Nowcasting GDP and its Components in a Data-rich Environment: the Merits of the Indirect Approach," CEIS Research Paper 489, Tor Vergata University, CEIS, revised 30 May 2020.
  6. Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.
  7. Umberto Triacca & Olivier Damette & Alessandro Giovannelli, 2020. "A Test of Sufficient Condition for Infinite-step Granger Noncausality in Infinite Order Vector Autoregressive Process," CEIS Research Paper 496, Tor Vergata University, CEIS, revised 18 Jun 2020.
  8. Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
  9. Forni, Mario & Giovannelli, Alessandro & Lippi, Marco & Soccorsi, Stefano, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," CEPR Discussion Papers 11161, C.E.P.R. Discussion Papers.
  10. Alessandro Giovannelli & Tommaso Proietti, 2014. "On the Selection of Common Factors for Macroeconomic Forecasting," CREATES Research Papers 2014-46, Department of Economics and Business Economics, Aarhus University.
  11. Leonardo Becchetti & Rocco Ciciretti & Alessandro Giovannelli, 2012. "Corporate Social Responsibility and Earnings Forecasting Unbiasedness," CEIS Research Paper 233, Tor Vergata University, CEIS, revised 08 Feb 2013.
  12. Alessandro Giovannelli, 2012. "Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies," CEIS Research Paper 255, Tor Vergata University, CEIS, revised 08 Nov 2012.

Articles

  1. Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
  2. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  3. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
  4. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
  5. Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  6. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2018. "Dynamic factor model with infinite‐dimensional factor space: Forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 625-642, August.
  7. Becchetti, Leonardo & Ciciretti, Rocco & Giovannelli, Alessandro, 2013. "Corporate social responsibility and earnings forecasting unbiasedness," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3654-3668.
  8. Alessandro Giovannelli, 2012. "Nonlinear Forecasting Using a Large Number of Predictors," Rivista italiana degli economisti, Società editrice il Mulino, issue 1, pages 143-150.

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. Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.

    Cited by:

    1. Xu, Qifa & Xu, Mengnan & Jiang, Cuixia & Fu, Weizhong, 2023. "Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China," Economic Systems, Elsevier, vol. 47(4).
    2. 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.
    3. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    4. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    5. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    6. Luke Mosley & Idris A. Eckley & Alex Gibberd, 2022. "Sparse temporal disaggregation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2203-2233, October.
    7. Barbara Guardabascio & Filippo Moauro & Luke Mosley, 2024. "Indirect estimation of the monthly transport turnover indicator in Italy," Empirical Economics, Springer, vol. 67(2), pages 531-566, August.
    8. Luke Mosley & Idris Eckley & Alex Gibberd, 2021. "Sparse Temporal Disaggregation," Papers 2108.05783, arXiv.org, revised Oct 2022.
    9. Alexander Jaax & Annabelle Mourougane & Frederic Gonzales, 2024. "Nowcasting services trade for the G7 economies," The World Economy, Wiley Blackwell, vol. 47(4), pages 1336-1386, April.
    10. Simone Tonini & Francesca Chiaromonte & Alessandro Giovannelli, 2022. "On the impact of serial dependence on penalized regression methods," LEM Papers Series 2022/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  2. Alessandro Giovannelli & Tommaso Proietti & Ambra Citton & Ottavio Ricchi & Cristian Tegami & Cristina Tinti, 2020. "Nowcasting GDP and its Components in a Data-rich Environment: the Merits of the Indirect Approach," CEIS Research Paper 489, Tor Vergata University, CEIS, revised 30 May 2020.

    Cited by:

    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.
    2. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    3. Stankevich, Ivan, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
    4. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    5. Joan Paredes & Javier J. Pérez & Gabriel Perez Quiros, 2023. "Fiscal targets. A guide to forecasters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 472-492, June.
    6. Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
    7. Barbara Guardabascio & Filippo Moauro & Luke Mosley, 2024. "Indirect estimation of the monthly transport turnover indicator in Italy," Empirical Economics, Springer, vol. 67(2), pages 531-566, August.

  3. Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.

    Cited by:

    1. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    2. Massacci, Daniele & Kapetanios, George, 2024. "Forecasting in factor augmented regressions under structural change," International Journal of Forecasting, Elsevier, vol. 40(1), pages 62-76.
    3. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    4. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2023. "A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return forecasting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    5. Trucíos, Carlos & Mazzeu, João H.G. & Hotta, Luiz K. & Valls Pereira, Pedro L. & Hallin, Marc, 2021. "Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1520-1534.
    6. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.

  4. Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Serge B. Provost & John N. Haddad, 2019. "A recursive approach for determining matrix inverses as applied to causal time series processes," METRON, Springer;Sapienza Università di Roma, vol. 77(1), pages 53-62, April.
    2. Proietti, Tommaso & Maddanu, Federico, 2024. "Modelling cycles in climate series: The fractional sinusoidal waveform process," Journal of Econometrics, Elsevier, vol. 239(1).

  5. Forni, Mario & Giovannelli, Alessandro & Lippi, Marco & Soccorsi, Stefano, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," CEPR Discussion Papers 11161, C.E.P.R. Discussion Papers.

    Cited by:

    1. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Jean-Armand Gnagne & Kevin Moran, 2020. "Forecasting Bank Failures in a Data-Rich Environment," Working Papers 20-13, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    3. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    4. Massacci, Daniele & Kapetanios, George, 2024. "Forecasting in factor augmented regressions under structural change," International Journal of Forecasting, Elsevier, vol. 40(1), pages 62-76.
    5. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    6. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org, revised Jan 2025.
    7. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    8. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2021. "Time-varying general dynamic factor models and the measurement of financial connectedness," Journal of Econometrics, Elsevier, vol. 222(1), pages 324-343.
    9. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2016. "Dynamic Factor Model with Infinite Dimensional Factor Space: Forecasting," Working Papers ECARES ECARES 2016-16, ULB -- Universite Libre de Bruxelles.
    10. Pietro Dallari & Antonio Ribba, 2015. "Dynamic Factor Models with In nite-Dimensional Factor Space: Asymptotic Analysis," Center for Economic Research (RECent) 115, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    11. Forni, Mario & Di Bonaventura, Luca & Pattarin, Francesco, 2018. "The Forcasting Performance of Dynamic Factor Models with Vintage Data," CEPR Discussion Papers 13034, C.E.P.R. Discussion Papers.
    12. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
    13. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    14. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    15. Fan Yang & Robert C. Qiu & Zenan Ling & Xing He & Haosen Yang, 2019. "Detection and Analysis of Multiple Events Based on High-Dimensional Factor Models in Power Grid," Energies, MDPI, vol. 12(7), pages 1-16, April.
    16. Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
    17. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    18. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    19. Trucíos, Carlos & Mazzeu, João H.G. & Hotta, Luiz K. & Valls Pereira, Pedro L. & Hallin, Marc, 2021. "Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1520-1534.
    20. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    21. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, rates, and prediction intervals," Papers 1811.10045, arXiv.org, revised Jul 2019.
    22. Philipp Gersing, 2024. "A Distributed Lag Approach to the Generalised Dynamic Factor Model (GDFM)," Papers 2410.20885, arXiv.org.
    23. Lippi, Marco & Deistler, Manfred & Anderson, Brian, 2023. "High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research," Econometrics and Statistics, Elsevier, vol. 26(C), pages 3-16.
    24. Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
    25. Duván Humberto Cataño & Carlos Vladimir Rodríguez-Caballero & Daniel Peña, 2019. "Wavelet Estimation for Dynamic Factor Models with Time-Varying Loadings," CREATES Research Papers 2019-23, Department of Economics and Business Economics, Aarhus University.
    26. Jean Armand Gnagne & Kevin Moran, 2018. "Monitoring Bank Failures in a Data-Rich Environment," Cahiers de recherche 1815, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    27. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
    28. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    29. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    30. Liang Zeng & Lei Wang & Hui Niu & Ruchen Zhang & Ling Wang & Jian Li, 2021. "Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling," Papers 2107.11972, arXiv.org, revised Jul 2024.
    31. Siegfried Hörmann & Gilles Nisol, 2021. "Prediction of Singular VARs and an Application to Generalized Dynamic Factor Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 295-313, May.
    32. F. Della Marra, 2017. "A forecasting performance comparison of dynamic factor models based on static and dynamic methods," Economics Department Working Papers 2017-ME01, Department of Economics, Parma University (Italy).
    33. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
    34. Simone Tonini & Francesca Chiaromonte & Alessandro Giovannelli, 2022. "On the impact of serial dependence on penalized regression methods," LEM Papers Series 2022/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  6. Alessandro Giovannelli & Tommaso Proietti, 2014. "On the Selection of Common Factors for Macroeconomic Forecasting," CREATES Research Papers 2014-46, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Barbarino, Alessandro & Bura, Efstathia, 2024. "Forecasting Near-equivalence of Linear Dimension Reduction Methods in Large Panels of Macro-variables," Econometrics and Statistics, Elsevier, vol. 31(C), pages 1-18.
    3. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
    4. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    5. Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
    6. Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.

  7. Leonardo Becchetti & Rocco Ciciretti & Alessandro Giovannelli, 2012. "Corporate Social Responsibility and Earnings Forecasting Unbiasedness," CEIS Research Paper 233, Tor Vergata University, CEIS, revised 08 Feb 2013.

    Cited by:

    1. Shantanu Dutta & Supriya Katti & B. V. Phani & Pengcheng Zhu, 2022. "Corporate social responsibility spending as a building block for sustainable corporate ethical identity: Lessons from Indian business groups," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 696-717, April.
    2. Bofinger, Yannik & Heyden, Kim J. & Rock, Björn, 2022. "Corporate social responsibility and market efficiency: Evidence from ESG and misvaluation measures," Journal of Banking & Finance, Elsevier, vol. 134(C).
    3. Chen, Chen & Chen, Yangyang & Hsu, Po-Hsuan & Podolski, Edward J., 2016. "Be nice to your innovators: Employee treatment and corporate innovation performance," Journal of Corporate Finance, Elsevier, vol. 39(C), pages 78-98.
    4. Kevin Krieger & Nathan Mauck, 2024. "Sustainability and Dividends: Complements or Substitutes?," Sustainability, MDPI, vol. 16(14), pages 1-16, July.
    5. Nguyen Thi Thanh Binh, 2024. "An application of artificial neural networks in corporate social responsibility decision making," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(1), March.
    6. Hans B. Christensen & Luzi Hail & Christian Leuz, 2021. "Mandatory CSR and sustainability reporting: economic analysis and literature review," Review of Accounting Studies, Springer, vol. 26(3), pages 1176-1248, September.
    7. Xiaoying Liang & Hongjun Wu, 2022. "Does the Tone in Corporate Social Responsibility Reports Misdirect Analysts’ Forecasts in China?," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    8. Charmaine Glegg & Oneil Harris & Thanh Ngo, 2018. "Corporate social responsibility and the wealth gains from dividend increases," Review of Financial Economics, John Wiley & Sons, vol. 36(2), pages 149-166, April.
    9. Cahan, Steven F. & Chen, Chen & Chen, Li & Nguyen, Nhut H., 2015. "Corporate social responsibility and media coverage," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 409-422.
    10. Gupta, Kartick & Krishnamurti, Chandrasekhar, 2021. "Corporate social responsibility, competition, and firm value," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    11. Acar Berkan & Becchetti Leonardo & Manfredonia Stefano, 2021. "Media coverage, corporate social irresponsibility conduct, and financial analysts' performance," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1456-1470, September.
    12. Becchetti, Leonardo & Palestini, Arsen & Solferino, Nazaria & Elisabetta Tessitore, M., 2014. "The socially responsible choice in a duopolistic market: A dynamic model of “ethical product” differentiation," Economic Modelling, Elsevier, vol. 43(C), pages 114-123.
    13. Aswani, Jitendra & Chidambaran, N.K. & Hasan, Iftekhar, 2021. "Who benefits from mandatory CSR? Evidence from the Indian Companies Act 2013," Emerging Markets Review, Elsevier, vol. 46(C).
    14. Ni, Juan & Jin, Shuchang & Hu, Yi & Zhang, Lei, 2023. "Informative or distracting: CSR disclosure of peer firms and analyst forecast accuracy," International Review of Financial Analysis, Elsevier, vol. 87(C).
    15. Chepurko, Iuliia & Dayanandan, Ajit & Donker, Han & Nofsinger, John, 2018. "Are socially responsible firms less likely to restate earnings?," Global Finance Journal, Elsevier, vol. 38(C), pages 97-109.
    16. Peter Huber & Eva Abramuszkinová Pavlíková & Marcela Basovníková, 2017. "The Impact of CSR Certification on Firm Profitability, Wages and Sales," WIFO Working Papers 535, WIFO.
    17. Wassim Dbouk & Dawei Jin & Haizhi Wang & Jianrong Wang, 2018. "Corporate Social Responsibility and Rule 144A Debt Offerings: Empirical Evidence," IJFS, MDPI, vol. 6(4), pages 1-18, November.
    18. Becchetti, Leonardo & Cucinelli, Doriana & Ielasi, Federica & Rossolini, Monica, 2023. "Corporate social irresponsibility: The relationship between ESG misconduct and the cost of equity," International Review of Financial Analysis, Elsevier, vol. 89(C).
    19. Li Liu & Gary Gang Tian, 2021. "Mandatory CSR disclosure, monitoring and investment efficiency: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 595-644, March.
    20. Koh, SzeKee & Durand, Robert B. & Limkriangkrai, Manapon, 2015. "The value of Saints and the price of Sin," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 56-72.
    21. Bofinger, Yannik & Heyden, Kim J. & Rock, Björn & Bannier, Christina E., 2022. "The sustainability trap: Active fund managers between ESG investing and fund overpricing," Finance Research Letters, Elsevier, vol. 45(C).
    22. Yusoff, Iliyas & Chen, Chen & Lai, Karen & Naiker, Vic & Wang, Jun, 2023. "Foreign exchange exposure and analysts’ earnings forecasts," Journal of Banking & Finance, Elsevier, vol. 146(C).
    23. Gul, Ferdinand A. & Krishnamurti, Chandrasekhar & Shams, Syed & Chowdhury, Hasibul, 2020. "Corporate social responsibility, overconfident CEOs and empire building: Agency and stakeholder theoretic perspectives," Journal of Business Research, Elsevier, vol. 111(C), pages 52-68.
    24. Vincenzo D'Apice & Giovanni Ferri & Mariantonietta Intonti, 2021. "Sustainable disclosure versus ESG intensity: Is there a cross effect between holding and SRI funds?," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1496-1510, September.
    25. Ajit Dayanandan & Han Donker & John Nofsinger, 2018. "Corporate goodness and profit warnings," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 553-573, August.
    26. Breuer, Wolfgang & Müller, Torbjörn & Rosenbach, David & Salzmann, Astrid, 2018. "Corporate social responsibility, investor protection, and cost of equity: A cross-country comparison," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 34-55.
    27. Krishnamurti, Chandrasekhar & Shams, Syed & Pensiero, Domenico & Velayutham, Eswaran, 2019. "Socially responsible firms and mergers and acquisitions performance: Australian evidence," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    28. Tsionas, Mike G. & Philippas, Dionisis & Philippas, Nikolaos, 2022. "Multivariate stochastic volatility for herding detection: Evidence from the energy sector," Energy Economics, Elsevier, vol. 109(C).
    29. Annalisa Fabretti & Stefano Herzel & Mustafa C. Pinar, 2014. "Delegated Portfolio Management under Ambiguity Aversion," CEIS Research Paper 304, Tor Vergata University, CEIS, revised 06 Feb 2014.
    30. Anagnostopoulou, Seraina C. & Tsekrekos, Andrianos E. & Voulgaris, Georgios, 2021. "Accounting conservatism and corporate social responsibility," The British Accounting Review, Elsevier, vol. 53(4).

  8. Alessandro Giovannelli, 2012. "Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies," CEIS Research Paper 255, Tor Vergata University, CEIS, revised 08 Nov 2012.

    Cited by:

    1. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    2. De Gooijer Jan G. & Zerom Dawit, 2020. "Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.

Articles

  1. Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
    See citations under working paper version above.
  2. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    See citations under working paper version above.
  3. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    See citations under working paper version above.
  4. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.

    Cited by:

    1. Yoichi Tsuchiya, 2024. "Conservatism and information rigidity of the European Bank for Reconstruction and Development's growth forecast: Quarter‐century assessment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1399-1421, August.
    2. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    3. Yoichi Tsuchiya, 2021. "Thirty‐year assessment of Asian Development Bank's forecasts," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 35(2), pages 18-40, November.
    4. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    5. Kexin Ding & Ani L. Katchova, 2024. "Testing the optimality of USDA's WASDE forecasts under unknown loss," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 846-865, October.

  5. Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
    See citations under working paper version above.
  6. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2018. "Dynamic factor model with infinite‐dimensional factor space: Forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 625-642, August.
    See citations under working paper version above.
  7. Becchetti, Leonardo & Ciciretti, Rocco & Giovannelli, Alessandro, 2013. "Corporate social responsibility and earnings forecasting unbiasedness," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3654-3668.
    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 17 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-FOR: Forecasting (14) 2012-05-15 2012-11-17 2014-12-24 2014-12-29 2015-03-22 2016-03-23 2016-04-09 2016-04-23 2016-05-08 2020-10-26 2021-02-15 2021-02-15 2022-07-11 2022-08-15. Author is listed
  2. NEP-ETS: Econometric Time Series (10) 2012-11-17 2016-03-23 2016-04-09 2016-05-08 2021-02-15 2021-02-15 2021-02-15 2022-07-11 2022-08-15 2023-06-26. Author is listed
  3. NEP-ECM: Econometrics (6) 2014-12-24 2017-07-23 2021-02-15 2021-02-15 2022-08-15 2023-06-26. Author is listed
  4. NEP-MAC: Macroeconomics (5) 2014-12-24 2016-04-09 2021-02-15 2021-02-15 2022-07-11. Author is listed
  5. NEP-ORE: Operations Research (4) 2012-11-17 2017-07-23 2020-10-26 2021-02-15
  6. NEP-EEC: European Economics (2) 2012-11-17 2021-02-15
  7. NEP-BIG: Big Data (1) 2021-02-15
  8. NEP-FMK: Financial Markets (1) 2020-10-26
  9. NEP-GRO: Economic Growth (1) 2023-07-10
  10. NEP-MFD: Microfinance (1) 2023-07-10
  11. NEP-PKE: Post Keynesian Economics (1) 2016-05-08

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