On March 24, 2020, India's Prime Minister announced the world's largest COVID-19 lockdown, bringing to a near-halt the economic and social lives of more than one billion Indian residents. This paper quantifies the economic impacts and behavioral changes induced by this unprecedented policy using two unique data sources: Facebook mobility data and a representative sample of previously surveyed low income Delhi households. Compliance with the lockdown was widespread: intra-city movement declined by 80% following the announcement. The economic consequences have been accordingly severe, with income and days worked falling by 86 and 72% respectively. Nevertheless, observance of public health directives was high: mask usage rose by 73 percentage points and handwashing became nearly universal, while time spent outdoors and smoking both declined. We also show how government provided social assistance may have averted more dire predictions of widespread famine, resource scarcity, access to medical care, and security. But the declines in mental health and the near-exhaustion of personal savings, amidst a rising infection rate, indicate an important and evolving role for policy-makers as the crisis continues.
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How do people value their climate? This paper demonstrates a new approach to estimating preferences for nonmarket goods using social media data. I combine more than a billion Twitter updates with natural language processing algorithms to construct a rich panel dataset of expressed sentiment for the United States and six other English-speaking countries around the world. In the U.S., I find consistent and statistically significant declines in expressed sentiment from both hot and cold temperatures. To better understand how preferences may adapt, I document heterogeneity in both regional and seasonal responses. I complete the U.S. analysis with a suite of validation exercises to understand the magnitude of these effects and two methods to estimate willingness-to-pay for climate amenities. Finally, I document similar relationships between temperature and expressed sentiment for four out of the six non-U.S. countries I examine.
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The changing global climate is producing increasingly unusual weather relative to preindustrial conditions. In an absolute sense, these changing conditions constitute direct evidence of anthropogenic climate change. However, human evaluation of weather as either normal or abnormal will also be influenced by a range of factors including expectations, memory limitations, and cognitive biases. Here we show that experience of weather in recent years—rather than longer historical periods—determines the climatic baseline against which current weather is evaluated, potentially obscuring public recognition of anthropogenic climate change. We employ variation in decadal trends in temperature at weekly and county resolution over the continental United States, combined with discussion of the weather drawn from over 2 billion social media posts. These data indicate that the remarkability of particular temperatures changes rapidly with repeated exposure. Using sentiment analysis tools, we provide evidence for a “boiling frog” effect: The declining noteworthiness of historically extreme temperatures is not accompanied by a decline in the negative sentiment that they induce, indicating that social normalization of extreme conditions rather than adaptation is driving these results. Using climate model projections we show that, despite large increases in absolute temperature, anomalies relative to our empirically estimated shifting baseline are small and not clearly distinguishable from zero throughout the 21st century.
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Linkages between climate and mental health are often theorized but remain poorly quantified. In particular, it is unknown whether the rate of suicide, a leading cause of death globally, is systematically affected by climatic conditions. Using compre-hensive data from multiple decades for both the United States and Mexico, we find that suicide rates rise 0.7% in US counties and 2.1% in Mexican municipalities for a 1 °C increase in monthly average temperature. This effect is similar in hotter versus cooler regions and has not diminished over time, indicating limited historical adaptation. Analysis of depressive language in > 600 million social media updates further suggests that mental well-being deteriorates during warmer periods. We project that unmitigated climate change (RCP8.5) could result in a combined 9–40 thousand additional suicides (95% confidence interval) across the United States and Mexico by 2050, representing a change in suicide rates comparable to the estimated impact of economic recessions, suicide prevention programmes or gun restriction law.
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We conduct the largest ever investigation into the relationship between meteorological conditions and the sentiment of human expressions. To do this, we employ over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that cold temperatures, hot temperatures, precipitation, narrower daily temperature ranges, humidity, and cloud cover are all associated with worsened expressions of sentiment, even when excluding weather-related posts. We compare the magnitude of our estimates with the effect sizes associated with notable historical events occurring within our data.
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The existing empirical literature on the impacts of climate change on the electricity sector has focused on changing electricity consumption patterns. In this paper, we show that incorporating impacts on the frequency and intensity of peak load consumption during hot days implies sizable required investments in peak generating capacity (or major advances in storage technology or the structure of electricity prices), which results in substantially larger impacts than those from just changes in overall consumption.
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