
Masahiro Yoshida's website
Working papers
Empirical works
Climate Change and the Decline of Labor Share (with Xincheng Qiu) (Submitted)
(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 Outdoor Jobs: the Rise of Adult Male Dropouts
(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.
Climate Change and Unemployment Seasonality: Evidence from US Counties (with Similan Rujiwattanapong)
(Talks 2025: Waseda (micro))
[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).
[Abstract] The aging economies facing secular labor shortage are bound to respond by admitting foreign labor or by adopting labor-saving technology. This paper proposes that inflows of regional foreign labor guides the adoption of automation. I develop a task-based framework, in which tasks are optimally allocated across robots, and domestic or foreign labor. Then, I semi-parametrically recover cross-factor substitution schedules from a series of commuting zone-level immigration elasticities on economic outcomes, which are estimated using a 1940 ethnic settlement pattern. The dynamic model predicts that immigration's impact on wages between 1980 and 2015 could be reversed by including effects from immigration-induced adjustments of automation. I find that low-skilled immigration alone reduces routine occupation native wage, but raises wages in the long run by retarding the adoption of automation, resulting in enhanced domestic welfare. Finally, I find that a universal basic income policy targeted to U.S. citizens will boost dependence on automation and foreign labor by upshifting routine occupation native wages.
Singularity, Seniority and Productivity: Evidence from Japanese Chess Grandmasterships: 1968-2022 (with Hideo Owan)
[Abstract] This study examines the impact of the ICT and AI revolutions on the performance of professional Japanese Chess (Shogi) players, using data from the last 40 years of the Grandmaster League. The ICT revolution, marked by the introduction of game databases, and the AI revolution, characterized by the development of advanced AI engines, significantly influenced professionals across different age groups. We employed two types of performance measures in this study. The first is a relative measure, the annual ranking in the Grandmaster League, and the second is an absolute measure, measuring the optimality of a player's moves as evaluated by a Japanese chess AI engine. Our findings indicate that the ICT revolution accelerated peak performance ages for professionals, while the AI revolution delayed them according to both relative and absolute measures. These findings highlight the importance of adaptability and continuous learning in response to technological advancements.
Theoretical works
Deadline Credibility and Trade Efficiency (R&R at International Journal of Game Theory)
[Abstract] Many real-world negotiations are chronically delayed until deadlines, but hard dead- lines are costly in generating separations. Must all deadlines in one-on-one market trades be perfectly credible? To refine the institutional role of deadlines, I propose a mechanism of an imperfectly credible soft deadline to facilitate the agreement. Employing a canonical seller–buyer dynamic bargaining model with a hard deadline, I analytically derive an optimal deadline credibility that the soft deadline elicits agreements without triggering separations and, consequently, maximizes the trade efficiency. Under a reasonably soft risk of breakdown, the seller is tempted to discount a price to secure a profit and the buyer is more likely to compromise right before the soft deadline, as the pricing resembles an ultimatum. The results of a laboratory experiment qualitatively support the mechanism’s efficacy with even larger magnitudes.