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© 2022 International Monetary Fund

WP/22/156

IMF Working Paper

Fiscal Affairs Department

Estimating Macro-Fiscal Effects of Climate Shocks From Billions of Geospatial Weather Observations Prepared by Berkay Akyapi, Matthieu Bellon, and Emanuele Massetti *

Authorized for distribution by James Roaf July 2022

IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

ABSTRACT: A growing literature estimates the macroeconomic effect of weather using variations in annual country-level averages of temperature and precipitation. However, averages may not reveal the effects of extreme events that occur at a higher time frequency or higher spatial resolution. To address this issue, we rely on global daily weather measurements with a 30-km spatial resolution from 1979 to 2019 and construct 164 weather variables and their lags. We select a parsimonious subset of relevant weather variables using an algorithm based on the Least Absolute Shrinkage and Selection Operator. We also expand the literature by analyzing weather impacts on government revenue, expenditure, and debt, in addition to GDP per capita. We find that an increase in the occurrence of high temperatures and droughts reduce GDP, whereas more frequent mild temperatures have a positive impact. The share of GDP variations that is explained by weather as captured by the handful of our selected variables is much higher than what was previously implied by using annual temperature and precipitation averages. We also find evidence of counter-cyclical fiscal policies that mitigate adverse weather shocks, especially excessive or unusually low precipitation episodes.

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Title Page

WORKING PAPERS

Estimating Macro-Fiscal Effects of Climate Shocks From Billions of Geospatial Weather Observations

Prepared by Berkay Akyapi, Matthieu Bellon, and Emanuele Massetti*

Contents

  • 1 Introduction

  • 2 Methods

    • 2.1 Empirical model specification

    • 2.2 Local projection method

    • 2.3 Selecting relevant weather variables and estimating their effects

  • 3 Data

    • 3.1 Weather data sources and aggregation over time and space

    • 3.2 Variable definitions

    • 3.3 Summary statistics

  • 4 GDP Results

    • 4.1 Climate variable selection

    • 4.2 The effect of weather variables on GDP growth

    • 4.3 Comparisons with the literature

    • 4.4 The dynamic effects of climate shocks

    • 4.5 Heterogeneity

  • 5 Macro-Fiscal Outcomes

    • 5.1 A systematic empirical approach to macro-fiscal impacts

    • 5.2 Estimates of the impact of climate shocks on macro-fiscal outcomes

  • 6 Conclusion

  • A Appendix

    • A.1 Source Data

    • A.2 Definition of weather variables

    • A.3 Data Analysis

    • A.4 Additional Result Tables

    • A.5 Additional Figures

  • List of Figures

    • 1 Illustrating the role of high spatial resolution when using absolute thresholds

    • 2 Variable selection and OLS estimation outcomes as λ varies (country and year effects)

    • 3 Persistence of selected weather shocks on GDP per capita

    • 4 Global distribution of standard deviations of climate shocks

    • 5 Weather Coefficients Across Groups

    • A.1 Computing the share of grid-days with weather conditions in a specific interval

    • A.2 GDP – climate variable selection and OLS estimation outcomes without year effects

    • A.3 GDP – variable selection and OLS estimation outcomes with quadratic trends

    • A.4 GDP – variable selection and OLS estimation outcomes on the balanced sample

    • A.5 Persistence of the effect of average annual temperature shocks on GDP per capita

    • A.6 Government revenue – climate variable selection and OLS estimation outcomes

    • A.7 Government expenditure – climate variable selection and OLS estimation outcomes

  • List of Tables

    • 1 The effect of changes in selected climate variables on GDP per capita growth

    • 2 Estimation of the effect of climate shocks on GDP growth: comparisons with the literature

    • 3 Estimates of macro-fiscal effects of selected climate variables

    • A.1 Definitions of climate variables

    • A.2 Trends in weather variables

    • A.3 Summary statistics of macro-fiscal variables

    • A.4 Summary statistics of climate variables

    • A.5 Correlation Matrix Between Baseline Variables

    • A.6 Summary statistics for sub-groups

    • A.7 Climate variables selected by LASSO after the random search and their GDP effect: baseline specification

    • A.8 Climate variables selected by LASSO after the random search and their GDP effect: without year effects

    • A.9 Climate variables selected by LASSO after the random search and their GDP effect: with quadratic trends

    • A.10 Climate variables selected by LASSO after the random search and their GDP effect: balanced sample

    • A.11 Climate variables selected by LASSO for government EXPENDITURE after the random search and their estimated effect

    • A.12 Climate variables selected by LASSO for government REVENUE after the random search and their estimated effect

    • A.13 Climate variables selected by LASSO for government DEBT after the random search and their estimated effect

    • A.14 The effect of changes in selected climate variables on GDP per capita growth

    • A.15 Estimation of the effect of climate on GDP growth: comparisons with the literature

    • A.16 Macro-fiscal effects: robustness to alternative climate variables

    • A.17 Macro-fiscal effects: the role of fiscal space

*

We thank seminar participants at the IMF, the World Bank, and the EAERE 27th annual conference, for helpful comments and discussions.

Estimating Macro-Fiscal Effects of Climate Shocks From Billions of Geospatial Weather Observations
Author: Berkay Akyapi, Mr. Matthieu Bellon, and Emanuele Massetti