TY - JOUR A1 - Šedová, Barbora A1 - Kalkuhl, Matthias T1 - Who are the climate migrants and where do they go? BT - Evidence from rural India JF - World development N2 - In this paper, we move from the large strand of research that looks at evidence of climate migration to the questions: who are the climate migrants? and where do they go? These questions are crucial to design policies that mitigate welfare losses of migration choices due to climate change. We study the direct and heterogeneous associations between weather extremes and migration in rural India. We combine ERAS reanalysis data with the India Human Development Survey household panel and conduct regression analyses by applying linear probability and multinomial logit models. This enables us to establish a causal relationship between temperature and precipitation anomalies and overall migration as well as migration by destination. We show that adverse weather shocks decrease rural-rural and international migration and push people into cities in different, presumably more prosperous states. A series of positive weather shocks, however, facilitates international migration and migration to cities within the same state. Further, our results indicate that in contrast to other migrants, climate migrants are likely to be from the lower end of the skill distribution and from households strongly dependent on agricultural production. We estimate that approximately 8% of all rural-urban moves between 2005 and 2012 can be attributed to weather. This figure might increase as a consequence of climate change. Thus, a key policy recommendation is to take steps to facilitate integration of less educated migrants into the urban labor market. KW - climate change KW - migration KW - household analysis KW - India KW - econometrics Y1 - 2020 U6 - https://doi.org/10.1016/j.worlddev.2019.104848 SN - 0305-750X SN - 1873-5991 VL - 129 PB - Elsevier Science CY - Amsterdam ER - TY - JOUR A1 - Wenz, Leonie A1 - Kalkuhl, Matthias A1 - Steckel, Jan Christoph A1 - Creutzig, Felix T1 - Teleconnected food supply shocks JF - Environmental research letters N2 - The 2008-2010 food crisis might have been a harbinger of fundamental climate-induced food crises with geopolitical implications. Heat-wave-induced yield losses in Russia and resulting export restrictions led to increases in market prices for wheat across the Middle East, likely contributing to the Arab Spring. With ongoing climate change, temperatures and temperature variability will rise, leading to higher uncertainty in yields for major nutritional crops. Here we investigate which countries are most vulnerable to teleconnected supply-shocks, i.e. where diets strongly rely on the import of wheat, maize, or rice, and where a large share of the population is living in poverty. We find that the Middle East is most sensitive to teleconnected supply shocks in wheat, Central America to supply shocks in maize, and Western Africa to supply shocks in rice. Weighing with poverty levels, Sub-Saharan Africa is most affected. Altogether, a simultaneous 10% reduction in exports of wheat, rice, and maize would reduce caloric intake of 55 million people living in poverty by about 5%. Export bans in major producing regions would put up to 200 million people below the poverty line at risk, 90% of which live in Sub-Saharan Africa. Our results suggest that a region-specific combination of national increases in agricultural productivity and diversification of trade partners and diets can effectively decrease future food security risks. KW - food security KW - trade shocks KW - vulnerability KW - climate change KW - teleconnections Y1 - 2016 U6 - https://doi.org/10.1088/1748-9326/11/3/035007 SN - 1748-9326 VL - 11 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Sedova, Barbora A1 - Kalkuhl, Matthias A1 - Mendelsohn, Robert T1 - Distributional impacts of weather and climate in rural India JF - Economics of disasters and climate change N2 - Climate-related costs and benefits may not be evenly distributed across the population. We study distributional implications of seasonal weather and climate on within-country inequality in rural India. Utilizing a first difference approach, we find that the poor are more sensitive to weather variations than the non-poor. The poor respond more strongly to (seasonal) temperature changes: negatively in the (warm) spring season, more positively in the (cold) rabi season. Less precipitation is harmful to the poor in the monsoon kharif season and beneficial in the winter and spring seasons. We show that adverse weather aggravates inequality by reducing consumption of the poor farming households. Future global warming predicted under RCP8.5 is likely to exacerbate these effects, reducing consumption of poor farming households by one third until the year 2100. We also find inequality in consumption across seasons with higher consumption during the harvest and lower consumption during the sowing seasons. KW - climate change KW - weather KW - inequality KW - household analysis KW - India KW - econometrics Y1 - 2019 U6 - https://doi.org/10.1007/s41885-019-00051-1 SN - 2511-1280 SN - 2511-1299 VL - 4 IS - 1 SP - 5 EP - 44 PB - Springer CY - Cham ER - TY - JOUR A1 - Kalkuhl, Matthias A1 - Wenz, Leonie T1 - The impact of climate conditions on economic production BT - evidence from a global panel of regions JF - Journal of Environmental Economics and Management N2 - We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise. KW - climate change KW - climate damages KW - climate impacts KW - growth regression KW - global warming KW - panel regression KW - cross-sectional regression KW - damage KW - function KW - social costs of carbon Y1 - 2020 U6 - https://doi.org/10.1016/j.jeem.2020.102360 SN - 0095-0696 SN - 1096-0449 VL - 103 PB - Elsevier CY - San Diego ER -