PELAGATTI MATTEO MARIA

Role
Full Professor  
Academic disciplines
Economic Statistics (SECS-S/03)
Email
[email protected]
Office phone
0264485834
Room:
  • U07, Floor: 2, Room: 2103
Reception hours

By appointment

Biography

Matteo Pelagatti is professor of Economic and Business Statistics (Statistica Economica) at the Department of Economics, Management and Statistics of the University of Milano-Bicocca. He holds a PhD in Statistics from the University of Milan, enriched by a semester of training and research at the Humboldt University of Berlin. His research interests are mainly in the fields of time series analysis, energy markets, robust statistics and financial econometrics, but occasionally cover also health sciences and other social sciences. His research has been published in international outlets such as the Journal of Econometrics, Journal of Applied Econometrics, Energy Journal, Energy Economics, Journal of Banking & Finance, and PLOS One, and he is the author of the book Time Series Modelling with Unobserved Components published by Chapman & Hall/CRC.

orcid.org/0000-0002-1860-7535

Publications

  • Gianfreda, A., Maranzano, P., Parisio, L., Pelagatti, M. (2023). Testing for integration and cointegration when time series are observed with noise. ECONOMIC MODELLING, 125(August 2023) [10.1016/j.econmod.2023.106352]. Detail

  • Maranzano, P., Pelagatti, M. (2024). Spatiotemporal Event Studies for Environmental Data Under Cross-Sectional Dependence: An Application to Air Quality Assessment in Lombardy. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 29, 147-168 [10.1007/s13253-023-00564-z]. Detail

  • Sbrana, G., Pelagatti, M. (2023). Optimal hierarchical EWMA forecasting. INTERNATIONAL JOURNAL OF FORECASTING [10.1016/j.ijforecast.2022.12.008]. Detail

  • Bonini, M., Monti, G., Pelagatti, M., Ceriotti, V., Re, E., Bramè, B., et al. (2022). Ragweed pollen concentration predicts seasonal rhino-conjunctivitis and asthma severity in patients allergic to ragweed. SCIENTIFIC REPORTS, 12(1) [10.1038/s41598-022-20069-y]. Detail

  • Golia, S., Grossi, L., Pelagatti, M. (2023). Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices. FORECASTING, 5(1), 81-101 [10.3390/forecast5010003]. Detail

Full list

Research projects

The impact of agriculture on air quality and the COVID-19 pandemic
Year: 2020
Grantors: FONDAZIONE CARIPLO
I numeri indice per il confronto nello spazio: aspetti teorici e applicazioni ad alcune città italiane
Year: 2005
Call: 2005-006 - PRIN 2005

Awards

Awards

  • Targa ADEIMF 2013, Associazione Docenti Economia Intermediari Mercati Finanziari, 2013

Editorial boards

  • Associate Editor di rivista o collana editoriale - STATISTICAL METHODS & APPLICATIONS, 2019 - 2023

Management or corporate responsibility

  • Direttore del Dipartimento di Economia, Metodi Quantitativi e Strategie di Impresa - Università degli Studi di MILANO-BICOCCA, 2019 - 2022

Congresses/Conferences

  • Partecipazione al comitato organizzativo - Beernomics 2024(Italia), 2024
  • Partecipazione al comitato organizzativo - European R Users Meeting 2020, 2020
  • Partecipazione al comitato organizzativo - First Italian Workshop of Econometrics and Empirical Economics (IWEEE): Panel Data Models and Applications(Italia), 2018
  • Partecipazione al comitato organizzativo - IAAE 2016 Annual Conference(Italia), 2016

Further links