Working Paper: NBER ID: w25537
Authors: Charles D. Kolstad; Frances C. Moore
Abstract: This paper reviews methods that have been used to statistically measure the effect of climate on economic value, using historic data on weather, climate, economic activity and other variables. This has been an active area of research for several decades, with many recent developments and discussion of the best way of measuring climate damages. The paper begins with a conceptual framework covering issues relevant to estimating the costs of climate change impacts. It then considers several approaches to econometrically estimate impacts that have been proposed in the literature: cross-sections, linear and non-linear panel methods, long-differences, and partitioning variation. For each method we describe the kind of impacts (short-run vs long-run) estimated, the type of weather or climate variation used, and the pros and cons of the approach.
Keywords: climate change; economic impacts; weather observations; panel data; adaptation
JEL Codes: H41; Q51; Q54
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| greenhouse gas emissions (Q54) | physical changes in climate (Q54) |
| statistical approaches using historical data (C51) | insights into climate impacts (Q54) |
| cross-sectional variation (C21) | long-run changes in climate impacts (Q54) |
| panel data (C23) | interannual weather variations (Q54) |
| adaptation (Y60) | economic effects of climate change (Q54) |
| short-run responses to weather (Q54) | long-run impacts of climate change (Q54) |
| understanding differences between short-run and long-run responses (E44) | developing effective climate adaptation and mitigation policies (Q54) |