Data and Code for: Estimating macro-fiscal effects of climate shocks

Principal Investigator(s):  View help for Principal Investigator(s) Berkay Akyapi, University of Florida; Matthieu Bellon, European Stability Mechanism; Emanuele Massetti, International Monetary Fund

Version:  View help for Version V1

Name File Type Size Last Modified
  ABM2024_replication_package_v2 07/01/2024 05:49:AM

Project Citation: 

Akyapi, Berkay, Bellon, Matthieu, and Massetti, Emanuele. Data and Code for: Estimating macro-fiscal effects of climate shocks. Nashville, TN: American Economic Association [publisher], 2025. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-06-06. https://doi.org/10.3886/E199241V1

Project Description

Summary:  View help for Summary The literature studying the macroeconomics of weather has focused on temperature and precipitation annual averages, while micro studies have focused more on extreme weather measures. We construct hundreds of variables from high frequency, high spatial resolution weather measurements. Using the LASSO, we identify the parsimonious subset of variables that can best explain GDP and key macro-fiscal variables. We find that an increase in the occurrence of high temperatures and severe droughts, and scarcer mild temperatures reduce GDP. These variables substantially improve the share of GDP variations explained by weather. Additional evidence suggests that fiscal policy mitigates these shocks.

Scope of Project

Subject Terms:  View help for Subject Terms climate; extreme weather; GDP; fiscal policy; big data
JEL Classification:  View help for JEL Classification
      C33 Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
      C55 Large Data Sets: Modeling and Analysis
      E62 Fiscal Policy
      O40 Economic Growth and Aggregate Productivity: General
      O44 Environment and Growth
      Q54 Climate; Natural Disasters and Their Management; Global Warming
Geographic Coverage:  View help for Geographic Coverage World
Time Period(s):  View help for Time Period(s) 1/1/1979 – 12/31/2019
Collection Date(s):  View help for Collection Date(s) 6/1/2021 – 12/31/2023
Universe:  View help for Universe Countries of the world.
Data Type(s):  View help for Data Type(s) aggregate data

Methodology

Data Source:  View help for Data Source
  • Gruss, B. and S. Kebhaj (2019). Commodity terms of trade: A new database. IMF Working Papers 2019 (021)
  • Mbaye, S., M. Moreno Badia, and K. Chae (2018). Global debt database: Methodology and sources. IMF Working Paper No. 18/111.
  • IMF World Economic Outlook, 1979-2019
  • World Bank World Development Indicators, 1979-2019
  • the UCDP/PRIO Armed Conflict Dataset version 23.1
  • the Varieties of Democracies project, 2023
  • the ERA5 dataset, 1979-2019
  • Abatzoglou, J. T., S. Z. Dobrowski, S. A. Parks, and K. C. Hegewisch (2018). Terraclimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Scientific data 5 (1), 1–12
Unit(s) of Observation:  View help for Unit(s) of Observation country
Geographic Unit:  View help for Geographic Unit country

Related Publications

Download this project

Published Versions

V1 [2025-06-06]

Export Metadata

Dublin Core

DDI 2.5

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.