Published work
Published work
Yim, H. and Dall’erba, S. "Impact of Extreme Weather Events on the U.S. Domestic Supply Chain of Food Manufacturing." Proceedings of the National Academy of Sciences, 2025.
Yim, H. and Seo, B. "Spatial Panel Analysis of Ambient Air Pollution in Korea." The Korean Economic Review, 2024.
Yim, H. and Seo, B. "Impact of air pollution on health status and medical expenditure: A panel data assessment in Korea." Journal of Economic Research, 2023.
Yim, H. et al. "Impacts of Ambient Air Pollution on Health Risk in Korea: A Spatial Panel Model Assessment." Journal of Economic Theory and Econometrics, 2021.
Work in progress
Yim, H. and Dall’erba, S. “Understanding the Impact of Future Climate Conditions on Agricultural Trade and Agrifood Supply Chain. “
Abstract: This chapter assesses how projected climate change may reshape U.S. agricultural trade networks and their cascading effects on food manufacturing. Future climate variables—including growing degree days, precipitation, and drought and wetness (SPEI)—are drawn from CMIP6 global climate models used in the IPCC Sixth Assessment Report with statistically downscaled projections applied to improve spatial resolution. We analyze eight climate models and three horizons (2030, 2050, and 2075) under alternative socioeconomic pathways (SSP245 and SSP585). By integrating these projections with population-driven demand growth, we analyze how agricultural trade flows and food input sourcing evolve under climate change.
Yim, H. and Dall’erba, S. “Factors Driving the Impact of Temperature, Precipitation, and Extreme Events in Agriculture: A Meta-analysis of World-wide Literature.”
Abstract: This chapter conducts a comprehensive meta-analysis of the Ricardian literature on agricultural adaptation, synthesizing evidence on how climate factors affect farmland values and net revenues across 1,925 estimates from 76 studies. We quantify the heterogeneous impacts of temperature and precipitation on agricultural profitability and land values worldwide, exploring variation by crop type, irrigation status, and methodological approach. This analysis highlights the drivers of climate sensitivity in agricultural profitability net of adaptation.