Abstract
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.
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Notes
This publication Contains modified Copernicus Climate Change Service Information [2019]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus Information or Data it contains.
Observations with missing values relevant for the analysis were dropped from the sample. Observations, where rural/urban categorization changes between the two IHDS rounds were dropped, likewise.
The poverty line is a nation-wide set poverty line that is adjusted for rural/urban and state-specific purchasing power.
During IHDS-I households were interviewed either in 2004 or 2005 and in IHDS-II either in 2011 or 2012 in one of the 12 months.
As mentioned in “Household Data”, IHDS collected data on consumption using information from the last 30 days and from the last 365 days.
These regression results are available form the authors upon the request.
We also conducted a correlation analysis between the binary variable Poor and the district-specific climates. The absolute values of all correlation coefficients are lower than 0.15, which signalizes that the distribution of rural poor is only partially conditioned by climate.
References
Abdullah ANM, Zander KK, Myers B, Stacey N, Garnett ST (2016) A short-term decrease in household income inequality in the Sundarbans, Bangladesh Following Cyclone Aila. Nat Hazards 83(2):1103–1123
Alderman H., Behrman J, Kohler H-P, Maluccio JA, Watkins S (2001) Attrition in longitudinal household survey data: some tests for three developing-country samples. Demographic Res 5(4):79–124. https://doi.org/10.4054/demres.2001.5.4
Angrist JD, Pischke J-S (2009) Mostly harmless econometrics: an empiricist’s companion. Princeton University Press, New Jersey
Auffhammer M, Carleton TA (2018) Regional crop diversity and weather shocks in India. Asian Dev Rev 35(2):113–130
Auffhammer M, Ramanathan V, Vincent JR (2012) Climate change, the monsoon, and rice yield in India. Clim Chang 111(2):411–424
Auffhammer M, Hsiang S, Schlenker W, Sobel A (2013) Using weather data and climate model output in economic analyses of climate change. Rev Environ Econ Policy 7(2):181–198
Berrisford P, Dee D, Poli P, Brugge R, Fielding K, Fuentes M, Kallberg P, Kobayashi S, Uppala S, Simmons A (2011) The ERA-interim archive, version 2.0. https://www.ecmwf.int/en/elibrary/8174-era-interim-archive-version-20
Brune L, Giné X, Goldberg J, Yang D (2011) Commitments to save: a field experiment in Rural Malawi. The World Bank, https://doi.org/10.1596/1813-9450-5748
Bryan G, Chowdhury S, Mobarak AM (2014) Underinvestment in a profitable technology: the case of seasonal migration in Bangladesh. Econometrica 82(5):1671–1748
Bui AT, Dungey M, Nguyen CV, Pham TP (2014) The impact of natural disasters on household income, expenditure, poverty and inequality: evidence from Vietnam. Appl Econ 46(15):1751–1766
Burgess R, Deschenes O, Donaldson D, Greenstone M (2014) The unequal effects of weather and climate change: evidence from mortality in India. Cambridge, United States: Massachusetts Institute of Technology, Department of Economics Manuscript
Burgess R, Deschenes O, Donaldson D, Greenstone M (2017) Weather, climate change and death in India. University of Chicago
Burke M, Hsiang S, Miguel E (2015) Global non-linear effect of temperature on economic production. Nature 527(7577):235
Carleton TA (2017) Crop-damaging temperatures increase suicide rates in India. Proc Natl Acad Sci 114(33):8746–8751
Chaudhuri S, Paxson C (2002) Smoothing consumption under income seasonality: buffer stocks vs credit markets. Working paper
Colmer J (2018) Weather, labor reallocation and industrial production: evidence from India. Working paper
Copernicus Climate Change Service (C3S) (2017) ERA5: fifth generation of ECMWF atmospheric reanalyses of the global climate. https://cds.climate.copernicus.eu/cdsapp#!/home
Dash S, Jenamani R, Kalsi S, Panda S (2007) Some evidence of climate change in twentieth-century India. Clim Chang 85(3-4):299–321
Dercon S, Krishnan P (2000) Vulnerability, seasonality and poverty in Ethiopia. The Journal of Development Studies 36(6):25–53
Desai S, Vanneman R, National Council of Applied Economic Research (2005) India Human Development Survey (IHDS), 2005. Technical report, New Delhi, India
Desai S, Vanneman R, National Council of Applied Economic Research (2015) India Human Development Survey-II (IHDS-II), 2011-12. Technical report, New Delhi, India
Diffenbaugh NS, Burke M (2019) Global warming has increased global economic inequality. Proc Natl Acad Sci 116(20):9808–9813
Donaldson D, Storeygard A (2016) The view from above: applications of satellite data in economics. J Econ Perspect 30(4):171–98
Duflo E, Udry C (2004) Intrahousehold resource allocation in cote d’ivoire: social norms, separate accounts and consumption choices. Technical report, National Bureau of Economic Research
Dunne JP, John JG, Adcroft AJ, Griffies SM, Hallberg RW, Shevliakova E, Stouffer RJ, Cooke W, Dunne KA, Harrison MJ et al (2012) GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: physical formulation and baseline simulation characteristics. J Clim 25(19):6646–6665. https://doi.org/10.1175/jcli-d-11-00560.1
Easterly W (2007) Inequality does cause underdevelopment: insights from a new instrument. J Dev Econ 84(2):755–776
Feng S, Lu J, Nolen P, Wang L et al (2016) The effect of the wenchuan earthquake and government aid on rural households. IFPRI book chapters, pp 11–34
Fishman R (2016) More uneven distributions overturn benefits of higher precipitation for crop yields. Environ Res Lett 11(2):024004
Goswami BN, Venugopal V, Sengupta D, Madhusoodanan M, Xavier PK (2006) Increasing trend of extreme rain events over India in a warming environment. Science 314(5804):1442–1445
Griliches Z, Hausman JA (1986) Errors in variables in panel data. J Econom 31(1):93–118. https://doi.org/10.1016/0304-4076(86)90058-8
Guiteras R (2009) The impact of climate change on indian agriculture. Manuscript, Department of Economics, University of Maryland, College Park, Maryland
Hahn J, Hausman J, Kuersteiner G (2007) Long difference instrumental variables estimation for dynamic panel models with fixed fffects. J Econom 140(2):574–617. https://doi.org/10.1016/j.jeconom.2006.07.005
Hallegatte S, Rozenberg J (2017) Climate change through a poverty lens. Nat Clim Chang 7(4):250
Hempel S, Frieler K, Warszawski L, Schewe J, Piontek F (2013) A trend-preserving bias correction–the ISI-MIP approach. Earth Syst Dyn 4(2):219–236. https://doi.org/10.5194/esd-4-219-2013
Hsiang S, Oliva P, Walker R (2019) The distribution of environmental damages. Rev Environ Econ Policy 13(1):83–103
International Labour Organization (2016) India labour market update. Technical report, International Labour Organization, New Delhi
Islam N, Winkel J (2017) Climate change and social inequality. DESA working paper (152)
Jayachandran S (2006) Selling labor low: wage responses to productivity shocks in developing countries. J Polit Econ 114(3):538–575
Kalkuhl M, Wenz L (2018) The impact of climate conditions on economic production evidence from a global panel of regions
Karim A, Noy I (2016) Poverty and natural disasters—a qualitative survey of the empirical literature. The Singapore Economic Review 61(01):1640001
Keerthiratne S, Tol RS (2018) Impact of natural disasters on income inequality in Sri Lanka. World Dev 105:217–230
King AD, Harrington LJ (2018) The inequality of climate change from 1.5 C to 2 C of global warming. Geophysical Research Letters
Krishna Kumar K, Rupa Kumar K, Ashrit R, Deshpande N, Hansen J (2004) Climate impacts on Indian agriculture. Int J Climatol 24(11):1375–1393. https://doi.org/10.1002/joc.1081
Kumar KK, Kumar KR, Ashrit R, Deshpande N, Hansen J (2004) Climate impacts on Indian agriculture. Int J Climatol 24(11):1375–1393
Lobell DB, Sibley A, Ortiz-Monasterio JI (2012) Extreme heat effects on wheat senescence in India. Nat Clim Chang 2(3):186
Massetti E, Mendelsohn R, Chonabayashi S (2016) How well do degree days over the growing season capture the effect of climate on farmland values? Energy Econ 60:144–150
Mendelsohn R, Dinar A, Williams L (2006) The distributional impact of climate change on rich and poor countries. Environ Dev Econ 11(2):159–178
Munshi K, Rosenzweig M (2016) Networks and misallocation: insurance, migration, and the rural-urban wage gap. Am Econ Rev 106(1):46–98
Narloch U, Bangalore M (2018) The multifaceted relationship between environmental risks and poverty: new insights from Vietnam. Environ Dev Econ 23 (3):298–327
Padma Kumari B, Londhe AL, Daniel S, Jadhav DB (2007) Observational evidence of solar dimming: offsetting surface warming over India. Geophys Res Lett 34 (21):1–5
Ramanathan V, Chung C, Kim D, Bettge T, Buja L, Kiehl J, Washington W, Fu Q, Sikka D, Wild M (2005) Atmospheric brown clouds: impacts on South Asian climate and hydrological cycle. Proc Natl Acad Sci 102(15):5326–5333
Riahi K, Rao S, Krey V, Cho C, Chirkov V, Fischer G, Kindermann G, Nakicenovic N, Rafaj P (2011) RCP 8.5—a scenario of comparatively high greenhouse gas emissions. Clim Change 109(1-2):33–57. https://doi.org/10.1007/s10584-011-0149-y
Sanghi A, Mendelsohn R (2008) The impacts of global warming on farmers in Brazil and India. Glob Environ Chang 18(4):655–665
Schlenker W, Roberts MJ (2009) Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc Natl Acad Sci 106(37):15594–15598
Schleussner C-F, Lissner TK, Fischer EM, Wohland J, Perrette M, Golly A, Rogelj J, Childers K, Schewe J, Frieler K et al (2016) Differential climate impacts for policy-relevant limits to global warming: the case of 1.5 C and 2 C. Earth Syst Dyn 7:327–351
Selvaraju R (2003) Impact of El Niño–Southern Oscillation on Indian foodgrain production. Int J Climatol 23(2):187–206
Skoufias E, Quisumbing AR (2005) Consumption insurance and vulnerability to poverty: a synthesis of the evidence from Bangladesh, Ethiopia, Mali, Mexico and Russia. Eur J Dev Res 17(1):24–58
Skoufias E, Essama-Nssah B, Katayama RS (2011) Too little too late: welfare impacts of rainfall shocks in Rural Indonesia. The World Bank
Taraz V (2018) Can farmers adapt to higher temperatures? evidence from India. World Dev 112:205–219
Tashiro T, Wardlaw IF (1989) A comparison of the effect of high temperature on grain development in wheat and rice. Ann Bot 64(1):59–65
United Nations Development Programme (2018) Sustainable development goals. http://www.undp.org/content/undp/en/home/sustainable-development-goals.html
Warr P, Aung LL (2019) Poverty and inequality impact of a natural disaster: Myanmar’s 2008 cyclone nargis. World Dev 122:446–461
Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O, Schewe J (2013) The inter-sectoral impact model intercomparison project (ISI–MIP): project framework. Proc Natl Acad Sci 111(9):3228–3232. https://doi.org/10.1073/pnas.1312330110
Webster PJ, Magana VO, Palmer T, Shukla J, Tomas R, Yanai M, Yasunari T (1998) Monsoons: processes, predictability, and the prospects for prediction. J Geophys Res Oceans 103(C7):14451–14510
Weedon G, Gomes S, Viterbo P, Shuttleworth W, Blyth E, Österle H, Adam J, Bellouin N, Boucher O, Best M (2011) Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J Hydrometeorol 12(5):823–848. https://doi.org/10.1175/2011jhm1369.1
Zaveri E, Lobell DB (2019) The role of irrigation in changing wheat yields and heat sensitivity in India. Nat Commun 10(1):1–7
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Appendices
Appendix A: Cross-Correlations
Appendix B: Consumption Types
Appendix C: Seasonal Effects
Appendix D: Sensitivity Analyses
Appendix E: Vulnerabilities
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Sedova, B., Kalkuhl, M. & Mendelsohn, R. Distributional Impacts of Weather and Climate in Rural India. EconDisCliCha 4, 5–44 (2020). https://doi.org/10.1007/s41885-019-00051-1
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DOI: https://doi.org/10.1007/s41885-019-00051-1