と題したエントリ(原題は「Profile*1 of Solomon Hsiang, who uses big data to inform climate change policies..」)でMostly Economicsが、IMFの季刊誌Finance & Development9月号の人物紹介記事の冒頭を引用している。この季刊誌の記事は本ブログでも何回か紹介したことがあるが、日本語版があることに今回初めて気づいたので*2その該当記事の訳と併せてMostly Economicsの引用部を紹介してみる。

Solomon Hsiang is a smart man. He listens to his wife.
Over breakfast a day or two after the California pandemic lockdown in March 2020, Google researcher Brenda Chen asked a question. Couldn’t her husband’s Global Policy Laboratory at the University of California, Berkeley, shed some light on the world’s fight against COVID-19?
“A lab called ‘the Global Policy Lab’ should be able to tackle this question,” she recalls saying.
He raised it with his team on a conference call that morning. The lab uses sophisticated statistical analysis of economic data—econometrics—and advanced computing power to address questions related to climate change, development, violence, migration, and disasters. When the group reconvened after a day of research, “we realized that nobody knew if all these lockdown policies would really work,” says Hsiang, a 37-year-old economist and climate physicist.
Over the next 10 days, Hsiang and 14 researchers worked around the clock gathering vast amounts of data on dozens of pandemic policies such as business and school closings, travel bans, social distancing mandates, and quarantines from China, France, Iran, Italy, South Korea, and the United States. Applying econometric tools, they found that the anti-contagion policies significantly slowed the spread of disease, averting 495 million infections. The paper they cranked out appeared June 8, 2020, in the journal Nature. It has been accessed 309,000 times and cited by 361 news outlets, according to Nature.
The episode shows how Hsiang (pronounced “Shung”) is helping to transform the way economists conduct research. He’s leading a new generation in leveraging newly available giant databases, massive modern computing power, and large, interdisciplinary teams to address thorny global issues such as climate change and the pandemic. Previous work on the economics of climate change relied largely on sweeping assumptions rather than hard data and was carried out mostly by solo researchers or a few collaborators.
Within just a decade of earning his doctorate from Columbia, Hsiang has published a raft of startling and sometimes controversial findings. He and various research partners showed that rising temperatures increase civil conflict and slow economic growth; that as tropical storms grow more intense, the economic effects are more severe and last longer; and that trying to fight climate change by mimicking volcanic eruptions to dim the sun would reduce global crop yields. Now he’s leading researchers in a years-long effort to calculate the true cost worldwide of greenhouse gas carbon emissions.


回避された感染者数(確認された感染者数ベース) 同(総感染者数ベース)
中国 3700万 2億8500万
韓国 1150万 3800万
イタリア 210万 4900万
イラン 500万 5400万
フランス 140万 4500万
米国 480万 6000万


Of course, Hsiang has detractors. The University of Sussex’s Richard Tol, the creator of the widely used FUND model for estimating climate change’s economic effects, has been a frequent critic.
“My main issue is that he uses weather shocks to study climate change,” Tol says. “Weather shocks are unexpected. Climate change is slow and predictable. As a result, he overstates the impacts.”
Hsiang rejects that, saying, “we have been doing a lot of innovation to study how populations adapt,” and argues that his use of data and econometrics produces quite different findings from the FUND model.
Others say it’s a waste of time to calculate the cost of carbon because there will always be too much missing data to get it right. “We don’t need a full optimization model to make certain decisions,” write Nobel laureate economist Joseph Stiglitz and Britain’s Nicholas Stern in a February 2021 paper. Policies should be built around the goals set in the 2015 Paris Agreement, they say.
Hsiang maintains that policymakers need to rely on data-based findings. “Almost everyone’s intuition for the role of the climate in the economy is not right,” he says.
“The advent of large-scale data collection, high-powered computing, and the application of science to policy means that we can now build transparent and evidence-based systems to guide our thinking,” he says. “The future of managingall planetary resources fairly and sustainably, even beyond climate change, will rely on these tools.”
As for the alarming effects of climate change and the world’s tardy, confused, and incoherent response, Hsiang takes a long view, harking back to the days when leaders consulted oracles to divine the future.
“We are at the state of scientific sophistication where we can understand future pathways and make thoughtful decisions in advance,” he says. “This is the first time in human history where we saw something this big coming and have the opportunity to do something about it.”