Masahiro Yoshida's website
Working Papers (under revision)
Climate Change and the Decline of Labor Share (with Xincheng Qiu)
(R&R (3rd round) at American Economic Journal: Macroeconomics)
(Talks 2024: Waseda (macro) 2025: Economic Society World Congress)
[Abstract] We study the impact of climate change on the labor share. Using a newly constructed dataset combining US county-level labor shares with climate variables, we find that ex- treme temperatures reduce labor share. This adverse effect is more pronounced in in- dustries with higher outdoor exposure and automation potential. We also show that ex- treme temperatures accelerate the adoption of industrial robots. Overall, climate change accounts for 14% of the decline in labor share during 2001–2019. In the last century, however, the opposing effects of decreased cold days and increased hot days offset each other, consistent with the well-documented constancy of labor share.
Climate Change and the Rise of Adult Male Dropouts
(R&R at Journal of Labor Economics)
Media (non-technical summary)
(Talks 2023: Waseda, Hitotsubashi (urban/trade), Kyoto (urban), GRIPS
2024: Keio, Tokyo Labor Workshop, Trans-pacific Labor Seminars, JEA (Fall), Economic Society Australiasian Meeting, 2025: Kansai Labor workshop)
[Abstract] Male labor force participation rates (LFPR) in developed economies have been de- clining since the 1970s. This paper argues that modern climate change has fueled dropouts of adult males by eroding the traditional advantage of working outdoors. Using exposure to climate change across US commuting zones constructed from gran- ular daily weather records for nearly half a century, I find that extreme temperature days hurt the LFPR of prime-age males. In the new century, climate change accounts for approximately 10-15 percent of the nationwide decline in LFPR. I find that out- door jobs—prevalent across sectors and prominent in disadvantaged regions—are likely hotbeds of dropout. Disability accounts for a substantial proportion of climate-induced dropouts, but the majority of these are likely due to preference; the decline in LFPR has been catalyzed by the spread of housing amenities (e.g., air conditioning and cable TV) and access to affluent family backgrounds. Overall, the results suggest that climate change exacerbates socioeconomic inequality.
Working Papers
Climate Change and Unemployment Dynamics: Evidence from US Counties (with Similan Rujiwattanapong)
(Under review)
(Talks 2025: Waseda (micro/macro))
[Abstract] Historically, unemployment peaks in the first and third quarters---the arrival of cold winters and hot summers. This paper attributes non-seasonally-adjusted unemployment fluctuations to temperature shocks and assesses the impact of climate change on unemployment seasonality. Combining granular daily weather across US counties with monthly unemployment rates over the period 1990-2019, we find that extreme temperature days fuel unemployment by freezing hiring and triggering layoffs and thus, insurance claims and recipients. Climate change accounts for about half of the decline in unemployment seasonality and monthly fluctuation. Accelerated future warming will propagate the unemployment seasonality through milder winters and harsher summers.
Immigration, Robots and American Life
Media (non-technical summary)
(Talks 2024: Waseda (empirical), JEA (spring))
[Abstract] Foreign labor represents a growing fraction of risky occupations that appear to be close substitutes of industrial robots. I investigate how dependency on immigrants interacted with robot adoption shaped a workplace injury risk in high-hazard sectors. Associating a wave of unskilled immigrants and workplace injuries across industries during 1992-2019, I find that immigrant workers substantially replaced native fatalities by crowding out natives out of risky jobs. Associated with cross-industry investment of robots, I also find that robot installation dramatically reduced injury risk, but the aggregate nationwide risk remains unabated from poor investments to riskier labor-intensive sectors (e.g., agriculture and construction). Then, I test a hypothesis that immigration inflow impeded the automation and preserved an injury risk for remaining laborers, including natives. Over-dependency on foreign labor may preserve the risky technology generating a social cost (e.g., disabilities; usage of opioids).
Immigration, Automation and the U.S. Cities: A Task-based Framework for Welfare Analysis (updated from Ph.D. dissertation)
[Abstract] This paper revisits the longstanding question of how immigration shapes regional wages through its effects on automation. I develop a dynamic spatial framework in which tasks are allocated among industrial robots, natives, and immigrants, and semi-parametrically recover cross-factor substitution schedules from commuting-zone-level elasticities of eco-
nomic outcomes with respect to immigration, instrumented by 1940 ethnic settlement patterns. Accounting for immigration-induced automation can reverse the estimated wage effects of immigration over 1980–2015. Low-skilled immigration initially reduces the wages of native workers in routine occupations but raises them in the long run by slowing automation adoption, enhancing domestic welfare. Finally, a universal basic income targeted to natives would increases reliance on both automation and immigrants by raising routine native wages.
Singularity, Seniority and Productivity: Evidence from Japanese Chess Grandmasterships: 1968-2022 (with Hideo Owan)
[Abstract] This study examines how digital revolutions shape the seniority premium among knowledge workers, using move-level game data from 40 years of professional Japanese chess (Shogi) league. We use two measures of productivity: a relative measure based on annual Grandmaster League rankings and an absolute measure based on the optimality of players’ moves as evaluated by an AI engine. We find that the AI revolution in the 2010s shifted peak performance to older ages, whereas the ICT revolution in the 1990s shifted it to younger ages, according to both measures. These results suggest the AI can reduce age-related disadvantages among knowledge workers by democratizing access to high-quality learning.
Publications
Deadline Credibility and Trade Efficiency (International Journal of Game Theory, 2026)
[Abstract] Many real-world negotiations are persistently delayed, yet imposing deadlines is costly because it induces inefficient separations. Do all deadlines in one-on-one market transac- tions need to be perfectly credible? To improve trade efficiency, I propose a mechanism that introduces an intermediate, imperfectly credible deadline to facilitate agreement. Using a canonical seller–buyer dynamic bargaining model with a credible deadline, I analytically characterize the optimal degree of credibility of such a deadline that maximizes trade effi- ciency, leading to early agreements without triggering separations. Under a non-zero risk of separation, the seller is tempted to discount the price to secure a payoff, while the buyer is more likely to accept at the intermediate deadline because pricing resembles ultimatum offers. A laboratory experiment provides direct evidence of the mechanism’s effects that extend beyond the theoretical benchmark.