Cosimo Magazzino was born in Grottaglie (TA, Italy) in 1980. He obtained his BA in Public Ad-ministration and his Ph.D. in Political Sciences at Roma Tre University (Rome, Italy).
|Born||February 14, 1980|
Grottaglie (TA), Italy
|Education||University of Roma Tre (Italy)|
|Institutions||University of Roma Tre|
“Niccolò Cusano” University
|Top Italian Scientist in Business Sciences|
He is currently a Professor of Economic Policy, Environmental and Energy Economics, and Economics of Monetary Integration at the Department of Political Sciences, Roma Tre University and a Professor of Environmental and Energy Economics at “Niccolò Cusano” University. He is a member of the Ph.D. Council on Political Science, Roma Tre University.
Education and career
Cosimo Magazzino graduated from the University of Roma Tre in Public Policy in 2007. He got a Ph.D. from the University of Roma Tre with a research project on the political-economic cycle. The study was done under the mentoring of Professors Gian Cesare Romagnoli (Roma Tre University) and Francesco Forte (Sapienza-University of Rome). He got a position as a Researcher in 2007 at Roma Tre University. In 2016 he was appointed Associate Professor of Economic Policy at the University of Roma Tre.
Over the years, he has held numerous teaching courses in Development Economics, Econometrics, Econometrics for Financial Markets, Economic Policy, European Economic Policy, Environmental and Energy Economics, Environmental and Tourism Economics, Economics of Globalization, Economics and Development Policy, Health Economics, Introductory Econometrics, Mathematics for Social Sciences, and Stata Laboratory at several universities (Roma Tre University; Faculty of Economics, University of International Studies of Rome-UNINT; “Niccolò Cusano” University; Universitas Libertatis; University of Bari).
Cosimo Magazzino coordinated the Ministry of Economy and Finance (MEF) Research program “Quality of public finances and impact on potential output” in 2011.
Cosimo Magazzino’s research interests include: public finance; energy econometrics; environmental Kuznets curve; time series econometrics; panel data models; Machine Learning experiments; Artificial Neural Networks analysis; environmental sustainability; circular economy; waste management; transportation infrastructure; agricultural economics.
Studies on Environmental Economics and Energy Economics
Cosimo Magazzino’s research in Environmental Economics explored the implications of the nuclear power phase-out, the nexus among CO2 emissions, energy use and economic growth, an empirical assessment of the Environmental Kuznets Curve (EKC), the link between renewable energy consumption and environmental degradation,the relationship among waste generation, wealth, and GHG emissions, the connection between logistics performance and environmental quality, the nexus between information technology and environmental pollution, the link between biomass energy and environmental pollution, the relation between natural gas consumption and economic growth.
Studies on COVID-19 effects
Cosimo Magazzino’s research on CoronaVirus Disease 2019 (COVID-19) analyzed the effects of vaccination on COVID-19 mortality, fossil fuels externality, the nexus between COVID-19 deaths, air pollution and economic growth, the link between air pollution and COVID-19 deaths.
Studies on Public Finance
Cosimo Magazzino’s research in Public Finance evaluated the fiscal sustainability of a single coun-try or a panel of countries, the comovement of public revenues, the optimal government size, the twin deficits phenomenon, an empirical assessment of Wagner’s Law.
In his studies, Cosimo Magazzino employed and developed several different empirical methodolo-gies, in particular Machine Learning (ML) and Artificial Neural Networks (ANNs) algorithms, time-series and panel data approach, Wavelet Analysis (WA), Responsiveness Scores (RA) ap-proach.
- Shahzad, U., Jena, S.K., Tiwari, A.K., Doğan, B., Magazzino, C., (2022), Time-frequency analysis between Bloomberg Commodity Index (BCOM) and WTI crude oil prices, Re-sources Policy, 78, 102823.
- Magazzino, C., Mele, M., Schneider, N., Shahzad, U., (2022), Does Export Product Diversification Spur Energy Demand in the APEC region? Application of a New Neural Net-works Experiment and a Decision Tree Model, Energy & Buildings, 258, 111820.
- Magazzino, C., Giolli, L., (2021), The relationship among railway networks, energy consumption, and real added value in Italy. Evidence from ARDL and Wavelet Analysis, Research in Transportation Economics, 90, 101126.
- Magazzino, C., Mele, M., Schneider, N., (2021), Testing the convergence and the divergence in five Asian countries: From a GMM model to a new Machine Learning approach, Journal of Economic Studies.
- Magazzino, C., Mutascu, M., Mele, M., Sarkodie, S.A., (2021), Energy consumption and economic growth in Italy: A wavelet analysis, Energy Reports, 7, 1520-1528.
- Magazzino, C., Schneider, N., (2020), The Causal Relationship between Primary Energy Consumption and Economic Growth in Israel: A Multivariate Approach, International Review of Environmental and Resource Economics, 14, 4, 417-491.
- Magazzino, C., Cerulli, G., (2019), The Determinants of CO2 Emissions in MENA Countries: A Responsiveness Scores Approach, International Journal of Sustainable Development & World Ecology, 26, 6, 522-534.
- Magazzino, C., (2017), Renewable energy consumption-economic growth nexus in Italy, International Journal of Energy Economics and Policy, 7, 6, 119-127.
- Cosimo Magazzino - Personal Website
- Cosimo Magazzino - ORCID
- Cosimo Magazzino - Università Roma Tre
- Cosimo Magazzino - Google Scholar
- ↑ Soytas, U., Magazzino, C., Mele, M., Schneider, N., (2022), Economic and Environmental Implications of the Nu-clear Power Phase-out in Belgium: Insights from Time-Series Models and a Partial Differential Equations Algorithm, Structural Change and Economic Dynamics, 63, 241-256.
- ↑ Magazzino, C., Mele, M., Schneider, N., Vallet, G., (2020), The Relationship between Nuclear Energy Consumption and Economic Growth: Evidence from Switzerland, Environmental Research Letters, 15.
- ↑ Magazzino, C., Mele, M., (2022), A New Machine Learning Algorithm to Explore the CO2 Emissions-Energy Use-Economic Growth Trilemma, Annals of Operations Research.
- ↑ Magazzino, C., Gallegati, Marco, Giri, F., (2022), The Environmental Kuznets Curve in a long-term perspective: parametric vs semi-parametric models, Environmental Impact Assessment Review, 98, 106973.
- ↑ Magazzino, C., Toma, P., Fusco, G., Valente, D., Petrosillo, I., (2022), Renewable energy consumption, environ-mental degradation and economic growth: the greener the richer?, Ecological Indicators, 139, 108912.
- ↑ Chopra, R., Magazzino, C., Shah, M.I., Sharma, G.D., Rao, A., Shahzad, U., (2022), The role of renewable energy and natural resources for sustainable agriculture in ASEAN countries: Do carbon emissions and deforestation affect agriculture productivity?, Resources Policy, 76, 102578.
- ↑ Magazzino, C., Mele, M., Schneider, N., (2021), A Machine Learning approach on the relationship among solar and wind energy production, coal consumption, GDP, and CO2 emissions, Renewable Energy, 167, 99-115.
- ↑ Magazzino, C., Falcone, P.M., (2022), Assessing the relationship among waste generation, wealth, and GHG emis-sions in Switzerland: some policy proposals for the optimization of the municipal solid waste in a circular economy perspective, Journal of Cleaner Production, 351, 131555.
- ↑ Magazzino, C., Mele, M., Schneider, N., Sarkodie, S.A., (2021), Waste generation, Wealth and GHG emissions from the waste sector: Is Denmark on the path towards Circular Economy?, Science of the Total Environment, 755, 1, 142510.
- ↑ Magazzino, C., Mele, M., Schneider, N., (2020), The relationship between municipal solid waste and greenhouse gas emissions: Evidence from Switzerland, Waste Management, 113, 508-520.
- ↑ Magazzino, C., Mele, M., Schneider, N., (2022), A New Artificial Neural Networks Algorithm to Analyze the Nexus Among Logistics Performance, Energy Demand, and Environmental Degradation, Structural Change and Economic Dynamics, 60, 315-328.
- ↑ Magazzino, C., Alola, A.A.., Schneider, N., (2021), The Trilemma of Innovation, Logistics Performance, and Environmental Quality in 25 topmost Logistics Countries: A Quantile Regression Evidence, Journal of Cleaner Production, 322, 129050.
- ↑ Magazzino, C., Mele, M., Morelli, G., Schneider, N., (2021), The nexus between information technology and environmental pollution: Application of a new machine learning algorithm to OECD countries, Utilities Policy, 72, 101256.
- ↑ Magazzino, C., Porrini, D., Fusco, G., Schneider, N., (2021), Investigating the link among ICT, electricity consumption, air pollution, and economic growth in EU countries, Energy Sources, Part B: Economics, Planning, and Policy.
- ↑ Magazzino, C., Mele, M., Schneider, N., Shahbaz, M., (2021), Can Biomass Energy Curtail Environmental Pollution? A Quantum Model Approach to Germany, Journal of Environmental Management, 287, 112293.
- ↑ Magazzino, C., Mele, M., Schneider, N., (2021), A D2C Algorithm on the Natural Gas Consumption and Economic Growth: Challenges faced by Germany and Japan, Energy, 219, 19586.
- ↑ Magazzino, C., Mele, M., Coccia, M., (2022), A machine learning algorithm to analyse the effects of vaccination on COVID-19 mortality, Epidemiology and Infection, 150, e168, 1–12.
- ↑ Magazzino, C., Mele, M., Schneider, N., (2022), Assessing a Fossil Fuels Externality with a New Neural Networks and Image Optimization Algorithm: The Case of Atmospheric Pollutants as Cofounders to COVID-19 Lethality, Epidemiology and Infection, 150, e1, 1-16.
- ↑ Magazzino, C., Mele, M., Sarkodie, S.A., (2021), The nexus between COVID-19 deaths, air pollution and economic growth in New York state: evidence from Deep Machine Learning, Journal of Environmental Management, 286, 112241.
- ↑ Mele, M., Magazzino, C., (2021), Pollution, Economic Growth and COVID-19 Deaths in India: A Machine Learning Evidence, Environmental Science and Pollution Research, 28, 2669-2677.
- ↑ Mele, M., Magazzino, C., Schneider, N., Strezov, V., (2021), https://doi.org/10.1016/j.envres.2020.110663[ NO2 levels as a contributing factor to COVID-19 deaths: The first empirical estimate of threshold values], Environmental Research, 194, 110663.
- ↑ Magazzino, C., Mele, M., Schneider, N., (2020), The relationship between air pollution and COVID-19-related deaths: An application to three French cities, Applied Energy, 279, 115835.
- ↑ Magazzino, C., Mutascu, M.I., (2022), The Italian fiscal sustainability in a long-run perspective, The Journal of Economic Asymmetries, 26, e00254.
- ↑ Magazzino, C., Mutascu, M., (2019), A wavelet analysis of Italian fiscal sustainability, Journal of Economic Structures, 8, 19.
- ↑ Brady, G.L., Magazzino, C., (2019), The sustainability of Italian fiscal policy: myth or reality?, Economic Research-Ekonomska Istraživanja, 32, 1, 772-796.
- ↑ Magazzino, C., Brady, G.L., Forte, F., (2019), A panel data analysis of the fiscal sustainability of G-7 countries, The Journal of Economic Asymmetries, 20.
- ↑ Brady, G.L., Magazzino, C., (2018), Sustainability and comovement of Government Debt in EMU Countries: A Panel Data Analysis, Southern Economic Journal, 85, 1, 189-202.
- ↑ Brady, G.L., Magazzino, C., (2018), Fiscal sustainability in the EU, Atlantic Economic Journal, 46, 3, 297-311.
- ↑ Magazzino, C., Mele, M., (2021), A dynamic factor and neural networks analysis of the comovement of public revenues in the EMU, Italian Economic Journal, 8, 289-338.
- ↑ Magazzino, C., Di Liddo G., Porcelli, G., (2017), Government Size, Decentralisation and Growth, Applied Economics, 50, 25, 2777-2791.
- ↑ Forte, F., Magazzino, C., (2011), Optimal Size Government and Economic Growth in EU Countries, Economia Politica – Journal of Analytical and Institutional Economics, XXVIII, 3, 295-321.
- ↑ Forte, F., Magazzino, C., (2013), Twin Deficits in the European Countries, International Advances in Economic Research, 19, 3, 289-310.
- ↑ Magazzino, C., (2012), Wagner versus Keynes: Public Spending and National Income in Italy at a Disaggregated Level, Journal of Policy Modeling, 34, 6, November-December, 890-905.