(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)
Severe Weather and Automobile Assembly Productivity
Gérard P. Cachon, Santiago Gallino and Marcelo Olivares
Abstract: It is expected that climate change could lead to an increased frequency of severe weather. In turn, severe weather intuitively should hamper the productivity of work that occurs outside. But what is the effect of rain, snow, fog, heat and wind on work that occurs indoors, such as the production of automobiles? Using weekly production data from 64 automobile plants in the United States over a ten-year period, we ﬁnd that adverse weather conditions lead to a signiﬁcant reduction in production. For example, one additional day of high wind advisory by the National Weather Service (i.e., maximum winds generally in excess of 44 miles per hour) reduces production by 26%, which is comparable in order of magnitude to the estimated productivity drop during the launch of a new vehicle. Furthermore, the location with the best weather (Arlington, Texas) only loses 2% of production per year due to the weather, whereas the location with the most adverse weather (Lordstown, OH) suffers an annual production loss of 11%. Our ﬁndings are useful both for assessing the potential aggregate productivity shock associated with inclement weather as well as guiding managers on where to locate a new production facility – in addition to the traditional factors considered in plant location (e.g., labor costs, local regulations, proximity to customers, access to suppliers), we add the prevalence of bad weather.
Welfare Costs of Long-Run Temperature Shifts
Ravi Bansal, Marcelo Ochoa
Abstract: This article makes a contribution towards understanding the impact of temperature fluctuations on the economy and financial markets. We present a long-run risks model with temperature related natural disasters. The model simultaneously matches observed temperature and consumption growth dynamics, and key features of financial markets data. We use this model to evaluate the role of temperature in determining asset prices, and to compute utility-based welfare costs as well as dollar costs of insuring against temperature fluctuations. We find that the temperature related utility-costs are about 0.78% of consumption, and the total dollar costs of completely insuring against temperature variation are 2.46% of world GDP. If we allow for temperature-triggered natural disasters to impact growth, insuring against temperature variation raise to 5.47% of world GDP. We show that the same features, long-run risks and recursive-preferences, that account for the risk-free rate and the equity premium puzzles also imply that temperature-related economic costs are important. Our model implies that a rise in global temperature lowers equity valuations and raises risk premiums.
Temperature, Aggregate Risk, and Expected Returns
Ravi Bansal, Marcelo Ochoa
Abstract: In this paper we show that temperature is an aggregate risk factor that adversely affects economic growth. Our argument is based on evidence from global capital markets which shows that the covariance between country equity returns and temperature (i.e., temperature betas) contains sharp information about the cross-country risk premium; countries closer to the Equator carry a positive temperature risk premium which decreases as one moves farther away from the Equator. The differences in temperature betas mirror exposures to aggregate growth rate risk, which we show is negatively impacted by temperature shocks. That is, portfolios with larger exposure to risk from aggregate growth also have larger temperature betas; hence, a larger risk premium. We further show that increases in global temperature have a negative impact on economic growth in countries closer to the Equator, while its impact is negligible in countries at high latitudes. Consistent with this evidence, we show that there is a parallel between a country’s distance to the Equator and the economy’s dependence on climate sensitive sectors; in countries closer to the Equator industries with a high exposure to temperature are more prevalent. We provide a Long-Run Risks based model that quantitatively accounts for cross-sectional differences in temperature betas, its link to expected returns, and the connection between aggregate growth and temperature risks.
Weather and climate events are no joke, even from a purely perspective of business productivity.
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