Spatial Correlation, Trade, and Inequality: Evidence from the Global Climate

Dingel, Jonathan I.; Meng, Kyle C.; Hsiang, Solomon

doi:10.2139/ssrn.3333239

Cited by 9 publications

(12 citation statements)

References 56 publications

(74 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Specifically, the authors exploit a naturally-occurring, quasi-random global climatic phenomenon -the El Niño Southern Oscillation (ENSO) -which drives the annual global spatial correlation of cereal productivity. Using a half-century of global agricultural trade data, Dingel, Meng and Hsiang (2018) find that year-to-year ENSO variation alters the distribution of the gains from trade so as to increase welfare inequality in a way that is consistent with their model's theoretical prediction. Having validated their prediction, Dingel, Meng and Hsiang (2018) consider the consequences of accounting for this general equilibrium mechanism in projections of climate change impacts.…”

Section: What To Do With Global Public Goodssupporting

confidence: 54%

“…Using a half-century of global agricultural trade data, Dingel, Meng and Hsiang (2018) find that year-to-year ENSO variation alters the distribution of the gains from trade so as to increase welfare inequality in a way that is consistent with their model's theoretical prediction. Having validated their prediction, Dingel, Meng and Hsiang (2018) consider the consequences of accounting for this general equilibrium mechanism in projections of climate change impacts. They show that projections that include a rise in the spatial correlation of cereal productivity due to climate change predict a 20% greater increase in global welfare inequality by the end of the 21st century compared to projections that omit this general equilibrium effect.…”

Section: What To Do With Global Public Goodssupporting

confidence: 54%

“…A weaker version of the first objective is to validate a predicted effect from a model of economic exchange against a null hypothesis of no effect. This is the approach taken by Dingel, Meng and Hsiang (2018) who…”

Section: What To Do With Global Public Goodsmentioning

confidence: 99%

See 2 more Smart Citations

Quasi-Experimental Methods in Environmental Economics: Opportunities and Challenges

Deschênes

Meng

2018

Self Cite

View full text Add to dashboard Cite

Smith, and Reed Walker for helpful discussions and feedback. All errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

show abstract

Section: What To Do With Global Public Goodssupporting

confidence: 54%

Section: What To Do With Global Public Goodssupporting

confidence: 54%

See 1 more Smart Citation

Quasi-Experimental Methods in Environmental Economics: Opportunities and Challenges

Deschênes

Meng

2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…Second, we need to think about general equilibrium effects across space and spillover effects across sectors in our models. Collaborations between trade and climate economists (Dingel, Meng, and Hsiang 2018), as well as academics working on supply chains (for example, Seetharam 2018), will likely yield fruitful insights. Finally, it is shocking how little work has been done on the effects of climate change on nonmarket goods other than mortality.…”

Section: Room For Expert Elicitation?mentioning

confidence: 99%

Quantifying Economic Damages from Climate Change

Auffhammer

2018

Journal of Economic Perspectives

334

129

View full text Add to dashboard Cite

Climate scientists have spent billions of dollars and eons of supercomputer time studying how increased concentrations of greenhouse gases and changes in the reflectivity of the earth’s surface affect dimensions of the climate system relevant to human society: surface temperature, precipitation, humidity, and sea levels. Recent incarnations of physical climate models have become sophisticated enough to be able to simulate intensities and frequencies of some extreme events, like tropical storms, under different warming scenarios. In a stark juxtaposition, the efforts involved in and the public resources targeted at understanding how these physical changes translate into economic impacts are disproportionately smaller, with most of the major models being developed and maintained with little to no public funding support. The goal of this paper is first to shed light on how (mostly) economists have gone about calculating the “social cost of carbon” for regulatory purposes and to provide an overview of the past and currently used estimates. In the second part, I will focus on where empirical economists may have the highest value added in this enterprise: specifically, the calibration and estimation of economic damage functions, which map weather patterns transformed by climate change into economic benefits and damages. A broad variety of econometric methods have recently been used to parameterize the dose (climate) response (economic outcome) functions. The paper seeks to provide an accessible and comprehensive overview of how economists think about parameterizing damage functions and quantifying the economic damages of climate change.

show abstract

“…Adjustments in trading patterns could also partially alleviate some uneven impacts of climate (Jones and Olken, 2010;Costinot, Donaldson, and Smith, 2016), but large-scale patterns of unequal damages could potentially be worsened by trade (Newbery and Stiglitz, 1984;Dingel, Hsiang, and Meng, 2017).…”

Section: Some Policy Considerations Concerning Climate Changementioning

confidence: 99%

The Distribution of Environmental Damages

Hsiang¹,

Oliva²,

Walker³

2019

Review of Environmental Economics and Policy

Self Cite

144

View full text Add to dashboard Cite

Most regulations designed to reduce environmental externalities impose costs on individuals and firms. An active body of research has explored how these costs are disproportionately born by different sectors of the economy and/or across different groups of individuals. However, much less is known about the distributional characteristics of the environmental benefits created by these policies, or conversely, the differences in environmental damages associated with existing environmental externalities. We review this burgeoning literature and develop a simple and general framework for focusing future empirical investigations. We apply our framework to findings related to the economic impact of air pollution, deforestation, and climate, highlighting important areas for future research. A recurring challenge to understanding the distributional effects of environmental damages is distinguishing between cases where (i) populations are exposed to different levels or changes in an environmental good, and (ii) where an incremental change in the environment may have very different implications for some populations. In the latter case, it is often difficult to empirically identify the underlying sources of heterogeneity in marginal damages, as damages may stem from either non-linear and/or heterogeneous damage functions. Nonetheless, understanding the determinants of heterogeneity in environmental benefits and damages is crucial for welfare analysis and policy design.

show abstract

Spatial Correlation, Trade, and Inequality: Evidence from the Global Climate

Cited by 9 publications

References 56 publications

Quasi-Experimental Methods in Environmental Economics: Opportunities and Challenges

Quasi-Experimental Methods in Environmental Economics: Opportunities and Challenges

Quantifying Economic Damages from Climate Change

The Distribution of Environmental Damages

Contact Info

Product

Resources

About