Emanuele Massetti

Assistant Professor

Member Of:
  • School of Public Policy
  • Climate and Energy Policy Laboratory
Office Location:
DM Smith 202
Overview

Emanuele Massetti is Assistant Professor at the School of Public Policy of the Georgia Institute of Technology, where he teaches Introduction to Statistics (undergraduate), Environmental Economics (graduate) and Cost-Benefit Analysis (graduate and undergraduate).

Emanuele is a CESifo Research Network Affiliate, an Associate REsearcher at Fondazione Eni Enrico Mattei (FEEM) and Affiliate Researcher at the Euro-Mediterranean Center on Climate Change (CMCC).

Before joining Georgia Tech Emanuele was Senior Researcher at the Sustainable Development Unit of Fondazione Eni Enrico Mattei (FEEM).

He holds a PhD in Economics from Catholic University of Milan, a MSc in Economics from University College London and a MA in Economics from Brown University. In 2011-2013 Emanuele was Postdoctoral Fellow at the Yale School of Forestry and Environmental Studies.

His main research interests are in Environmental, Energy and Agricultural Economics and he is one of the authors of WITCH, an Integrated Assessment Model to study optimal climate mitigation policies. His research work now focuses on methods to estimate impacts of and adaptation to climate change.

Emanuele has worked as consultant for the EBRD, the OECD, the UNDP and the UNEP. In 2011-2014 he was Lead Author for the Working Group III of the Fifth Assessment Report of the IPCC.

 

Education:
  • PhD, Catholic University of Milan, Economics
Interests
Research Fields:
  • Energy, Climate and Environmental Policy
Courses
  • PUBP-3120: Stat Analysis-Pub Policy
  • PUBP-3600: Sustain,Tech & Policy
  • PUBP-6312: Economics-Environ Polcy
  • PUBP-8205: Adv Research Methods II
Recent Publications

Journal Articles

  • Investments in and macroeconomic costs of climate mitigation in the Working Group III contribution to the Fifth Assessment Report of the IPCC.
       In: Energy Policy [Peer Reviewed]

    October 2017

    Trainer (2017) criticizes cost estimates of climate change mitigation presented in the Working Group III Report to the IPCC and is concerned by lack of transparency and dubious practices in summarizing the literature. This commentary shows that this critique is based on several mistakes. Trainer (2017) mixes evidence on investment changes and evidence on macroeconomic costs, which are discussed in two different parts of the report because they are different indicators of the economic impact of climate mitigation policy. This commentary also argues that when the report was prepared evidence on investments in mitigation technologies was limited but methodologically sound and transparently reported, contrary to what suggested by Trainer (2017).

  • A Ricardian Analysis of the Impact of Climate Change on Italian Agriculture
       In: European Review of Agricultural Economics [Peer Reviewed]

    August 2017

    This research investigates the potential impact of warming on Italian agriculture. Using a detailed dataset of 16,000 farms across Italy, the study examines likely warming impacts in different regions and for different sectors of Italian agriculture. The study finds that farm net revenues are very sensitive to seasonal changes in temperature and precipitation. Livestock and crop farms have different responses to climate as do rainfed farms and irrigated crop farms. The overall results suggest mild consequences from marginal changes in climate but increasingly harmful effects from more severe climate scenarios. 

  • The Use of Cross-Sectional Analysis to Measure Climate Impacts on Agriculture: Theory and Evidence
       In: Review of Environmental Economics and Policy [Peer Reviewed]

    2017

    This article examines the methodological issues associated with using cross-sectional methods to study climate impacts on agriculture. In particular, we describe and address concerns that have been raised about this method, including missing variable bias, irrigation, prices, and carbon fertilization. We review cross-sectional studies of estimated climate impacts on agriculture around the world. These studies suggest that both temperature and precipitation have modest effects on farmland value and net revenue. The studies also suggest that marginal warming will likely be harmful in low latitudes but beneficial in higher latitudes and that marginal increases in rainfall will be beneficial in semiarid locations but harmful in very wet places. The impacts differ for rain-fed versus irrigated farms and for crops versus livestock. The results imply that global warming will likely have only modest impacts on global food production for the next century since the harm from higher temperatures will likely be offset by the benefits of carbon fertilization and adaptations by farmers.

  • U.S. Sulfur Dioxide Emission Reductions: Shifting Factors and a Carbon Dioxide Penalty
       In: The Electricity Journal

    2017

  • How Well Do Degree Days over the Growing Season Capture the Effect of Climate on Farmland Values?

    2016

    Farmland values have traditionally been valued using seasonal temperature and precipitation but degree days over the growing season offer a more compact alternative. We find that degree days and daily temperature are interchangeable over the growing season. However, the impact of degree days in spring and summer is quite different. Climate effects outside the growing season are also significant. Cross sectional evidence suggests seasonal temperature and precipitation are very important whereas temperature extremes have relatively small effects. 

Conferences

Working Papers

  • A Ricardian Analysis of the Impact of Climate Change on European Agriculture

    March 2016

    © 2016 Springer Science+Business Media DordrechtThis research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Climate, soil, geography and regional socio-economic variables are matched with farm level data from 41,030 farms across Western Europe. We demonstrate that a median quantile regression outperforms OLS given farm level data. The results suggest that European farms are slightly more sensitive to warming than American farms with impacts from (Formula presented.)5 to (Formula presented.)32 % by 2100 depending on the climate scenario. Farms in Southern Europe are predicted to be particularly sensitive, suffering losses of (Formula presented.)5 to (Formula presented.)9 % per degree Celsius.

Presentations