Climate Change: Past, Present, and Future
Paper Session
Friday, Jan. 6, 2017 7:30 PM – 9:30 PM
Hyatt Regency Chicago, Crystal A
- Chair: Antonio Bento, University of Southern California
Mortality, Climate Change, and Adaptation: The Consistency of Relative Minimum Mortality Temperatures Across the World
Abstract
Human health impacts are likely to be one of the largest costs associated with climate change. To estimate these costs, it is essential to understand how, and how much, populations will adapt to a changing climate, yet adaptation remains one of the least empirically understood aspects of society's response to climate change. We assemble comprehensive panel data on mortality in six countries that account for 46% of the global population - Brazil, China, France, India, Mexico, and the USA - and combine them with high resolution daily climate data to estimate the causal effect of temperature on mortality. Our flexible, non-linear model accounts for location fixed effects and trends in mortality for each region. Consistent with previous studies, we find the impacts of temperature on mortality have a U-shaped response - both hot days and cold days cause excess mortality. However, elevated and minimum mortality occurs at different temperatures in each country, suggesting that relative heat matters and populations take adaptive actions around an optimal temperature. To understand adaptation across space, we estimate responses for each administrative region within these countries, for a total of 177 non-linear estimates. Controlling for income and population density within each region, we find that populations exhibit lower mortality at hot and cold temperatures as their exposure to those temperatures increases. This explains the existence of a relative minimum mortality response, as it appears that adaptive actions are made in response to frequency of exposure regardless of the income level of the population. We then perform a back-of-the-envelope calculation on the costs of adaptation using a revealed preference approach and outline a methodology for using this empirical approach to calculate global, adaptation-adjusted projections of climate impacts.Adaptation and the Climate Penalty on Ozone
Abstract
We propose a novel approach to estimate adaptation to climate change based on a decomposition of meteorological variables into long-run trends and deviations from those trends (weather shocks). Our estimating equation simultaneously exploits weather variation to identify the impact of weather shocks, and climatic variation to identify the effect of longer-run observed changes. We then compare the short- and long-run effects to provide a measure of adaptation. We apply our methodology to study the impact of climate change on air quality, and estimate the so-called climate penalty on ozone. This penalty means that climate change might offset some of the improvements in air quality expected from reductions in ozone precursors. We have three main findings. First, a changing climate appears to be affecting ground-level ozone concentrations in two ways. A temperature shock of 1C increases ozone levels by 1.7 parts per billion (ppb) on average. A change of similar magnitude in a 30-year moving average increases ozone concentration by 1.2 ppb. Therefore, by omitting climate normals, the standard fixed-effect approach would underestimate the impact of climate change on ozone concentrations by over 40 percent. Second, we find evidence of adaptive behavior. For a change of 1C in temperature, our measure of adaptation in terms of ozone concentration is 0.45 ppb. If adaptive responses are not taken into account, the climate penalty on ozone would be overestimated by approximately 17 percent. Third, adaptation in counties with levels of ozone above the EPA’s standards appears to be over 66 percent larger than adaptation in counties in “attainment”. This difference is what we call regulation-induced adaptation. The remainder is our measure of residual adaptation.Human Productivity in a Warmer World: The Impact of Climate Change on the Global Workforce
Abstract
Anthropogenic climate change poses many threats to human wellbeing. Although a growing literature has empirically quantified the impacts of climate on outcomes as diverse as agricultural output, mortality, violent conflict, and energy demand, there remains a critical, yet vastly understudied, component of climate’s impact on welfare: labor productivity. This fundamental building block of economic development and human wellbeing is highly vulnerable to a warming climate, as heat stress can weaken cognitive ability, impose biophysical constraints on work intensity, and induce shorter work hours. We combine time use data with high-resolution daily climate data to estimate the causal impact of changes in temperature on hours worked at subnational resolution in 8 previously unstudied countries (Mexico, Guatemala, Nicaragua, Brazil, France, UK, Spain, India). Our empirical approach allows for a non-linear relationship between labor supply and temperature and controls for seasonal trends as well as location-specific, time-invariant unobservable factors that correlate both with climate and economic outcomes. We find that around the world, average daily work hours are reduced by up to an hour on the hottest days, relative to a day in the middle of a country’s temperature distribution. However, the temperature response of working hours varies by country and sector of employment. In Western Europe, only “high-risk” workers (i.e. those employed in a sector where work is primarily performed outdoors) exhibit reduced hours on the hottest days. By contrast, in developing countries reduced hours are observed across all sectors on the hottest days. There is no significant evidence of short-run adaptation through temporal substitutions. Our findings generalize the relationship between temperature and labor across many settings and represent the first estimates of climate’s impact on the global workforce.Discussant(s)
Benjamin Olken
, Massachusetts Institute of Technology
Benjamin F. Jones
, Northwestern University
Maximilian Auffhammer
, University of California-Berkeley
Tatyana Deryugina
, University of Illinois-Urbana-Champaign
JEL Classifications
- Q0 - General
- Q5 - Environmental Economics