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  - 
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  -