What Do We Learn from the Weather? The New Climate-Economy Literature
Open accessAbstract
A rapidly growing body of research applies panel methods to examine how temperature, precipitation, and windstorms influence economic outcomes. These studies focus on changes in weather realizations over time within a given spatial area and demonstrate impacts on agricultural output, industrial output, labor productivity, energy demand, health, conflict, and economic growth, among other outcomes. By harnessing exogenous variation over time within a given spatial unit, these studies help credibly identify (i) the breadth of channels linking weather and the economy, (ii) heterogeneous treatment effects across different types of locations, and (iii) nonlinear effects of weather variables. This paper reviews the new literature with two purposes. First, we summarize recent work, providing a guide to its methodologies, datasets, and findings. Second, we consider applications of the new literature, including insights for the “damage function” within models that seek to assess the potential economic effects of future climate change. (JEL C51, D72, O13, Q51, Q54)
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Weather variation within a location and calendar month is essentially random.
“Such variation is considered to be essentially random (Dell et al., 2014; Hsiang, 2016)”
From Temperature and mental health: Evidence from the spectrum of mental health outcomes (2019) · cites this paper as Dell et al., 2014
An increasing number of studies use longitudinal empirical approaches in their analyses controlling for unobserved heterogeneity and common time trends via fixed effects.
“An increasing number of studies use longitudinal empirical approaches in their analyses controlling for unobserved heterogeneity and common time trends via fixed effects (Dell et al., 2014).”
From Improving the evidence base: A methodological review of the quantitative climate migration literature (2021) · cites this paper as Dell et al., 2014
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- Authors
- Dell, M., Jones, B. F., & Olken, B. A.
- Affiliations
- Harvard University (US)
- Northwestern University (US)
- Massachusetts Institute of Technology (US)
- Venue
- Journal of Economic Literature
- Publisher
- American Economic Association
- Published
- 2014-09-01
- Volume
- 52
- Issue
- 3
- Pages
- 740-798
- ISSN
- 0022-0515 (ISSN-L)
- OpenAlex
- W2104834906
- Cited by
- 2,300
- References
- 205
- Citations by year
- 2026: 265 · 2025: 281 · 2024: 285 · 2023: 251 · 2022: 220 · 2021: 217 · 2020: 188 · 2019: 137 · 2018: 129 · 2017: 127 · 2016: 91 · 2015: 76 · 2014: 23 · 2013: 5 · 2012: 5
- FWCI
- 262.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Economic Literature (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Climate change impacts on agriculture
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
- Keywords
- temperature effects, precipitation, windstorms, agricultural production, industrial production, labor productivity, energy demand, weather and health, conflict, economic growth, treatment effect heterogeneity, panel data methods
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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