Skip to main content

Advertisement

SpringerLink
Log in

Do economic development and disaster adaptation measures reduce the impact of natural disasters? A district-level analysis, Odisha, India

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

Natural disasters are a regular phenomenon in Odisha due to its unique geo-climatic conditions. Frequent occurrences of natural disasters affect different aspects of human life and cause huge damage to private and public property. We examine the effects of economic development, basic disaster adaptation measures, and exposure to disaster on disaster fatalities due to floods, heat-wave, and lightning. We use district-level panel data for 30 districts in Odisha over the period 1999–2011. The FE Poisson estimates suggest that economic development (proxied by per capita income) is not adequate to minimize fatalities from natural disasters. The results further confirm that better disaster adaptation measures such as better medical facilities, adequate road infrastructure, higher primary enrolment, village electrification, forest cover, and financial accessibility help in mitigating disaster fatalities to some extent. In addition, the estimates indicate that disaster-specific exposures such as high incidences of floods, excessive rainfall during monsoon, high temperature, and humidity lead to an increase in disaster fatalities. In sum, our results conclude that adequate disaster adaptation measures and better disaster management policies are essential to mitigate fatalities from natural disasters in the districts of Odisha, India.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Source: Report of the Expert Group to Review the Methodology for Measurement of Poverty, 2014, Planning Commission, Government of India. b Human Development Index for all states in 2011–12 (Rural & Urban Combined). Note: Authors’ own compilation. Data Source: Mukherjee et al. (2014). c Percentage literate population for 2011–12. Note: Authors’ own compilation. Data Source: Census of India, 2011

Fig. 2

Data source: Various Annual Report on Natural Calamities, Government of Odisha

Similar content being viewed by others

Notes

  1. In developing nations, natural disasters claimed lives to the extent of 90 percent because these nations experience higher poverty, higher population density, and unsafe building practice. Moreover, economically weaker sections generally live in highly disaster-prone areas in these nations (Secretary-General of the United Nations Kofi Annan, 1999).

  2. India’s rank is 14th in terms of the overall Climate Risk Index (Kreft et al. 2017).

  3. Annual Report on Natural Calamities 2012–13, Government of Odisha.

  4. Kindly see Sect. 4 for a detailed discussion of the count data model used in this study.

  5. Previous studies have used both FE negative binomial and FE Poisson model in country-wise flood fatalities data Ferreira et al. 2013). Moreover, a few studies used the FE negative binomial model in country-wise earthquake fatalities data (Anbarci et al. 2005; Escaleras et al. 2007). Bahinipati, and Patnaik (2015) and Das (2016) used FE negative binomial and FE Poisson estimates in district-wise disaster data in Odisha. Therefore, we use the FE negative binomial and FE Poisson model in our study.

  6. National Sample Survey (NSS) survey report titled ‘Income, Expenditure, Productive Assets and Indebtedness of Agricultural Households in India, 2012–13′ estimated average monthly income per agricultural households in all 28 India states. Odisha’s average monthly income per agricultural household’s income is Rs. 4976 in 2012–2013, which is below the average monthly income of 22 states in India. Regarding the health index, Odisha’s rank is 24th out of 28 states in India (Mukherjee and Chakraborty 2011). Similarly, in terms of rural inequality, Odisha’s rank is 21st out of 28 states in India (Databook for PC; 22nd December 2014, Planning Commission, Government of India). In terms of infant mortality rates, Odisha’s rank is highest among the Indian states (Economic Survey 2009–10). In terms of liability to flood-prone area, Odisha ranks 20th out of 28 states in India (Page No-95, Government of India 2011).

  7. https://www.desinventar.net/DesInventar/profiletab.jsp?countrycode=019&continue=y (Data was collected 2nd May 2017).

  8. The correlation only shows the relationship between the variables, but it cannot capture the true cause and effect relationship between variables. In Table 7, per capita income is negatively correlated with flood fatalities, while it is positively related to heat-waves and lightning fatalities. In regression analysis, per capita income is negatively related to flood fatalities, heat-waves, and lightning fatalities, respectively (see Tables 2, 3 and 4). The results show that correlation does not estimate the sign of the coefficient correctly, whereas regression estimates provide correct signs of coefficients because it controls for cause and effect of the variables.

  9. Hilbe (2011: 474) argued that the conditional FE negative binomial model ‘is not a true fixed-effects model,’ and it is unable to control time-invariant fixed effects robustly (Allison and Waterman 2002). Moreover, it controls for fixed effects with a very specific set of assumptions (Guimaraes 2008).

  10. We have divided 30 districts into 10 agro-climatic regions.

References

  • Allison, P. D., & Waterman, R. (2002). Fixed effects negative binomial regression models. In R. M. Stolzenberg (Ed.), Sociological methodology 2002. Oxford: Basil Blackwell.

  • Anbarci, N., Escaleras, M., & Register, C. A. (2005). Earthquake fatalities: The interaction of nature and political economy. Journal of Public Economics, 89, 1907–1933. https://doi.org/10.1016/j.jpubeco.2004.08.002.

    Article  Google Scholar 

  • Annan, K. A. (1999). An increasing vulnerability to natural disasters. International Herald Tribune, September 10. www.un.org/News/ossg/sg/stories/annan_press.html.

  • Bahinipati, C. S. (2014). Assessment of vulnerability to cyclones and floods in Odisha, India: a district-level analysis. Current Science, 107(12), 1997–2007.

    Google Scholar 

  • Bahinipati, C. S., & Patnaik, U. (2015). The damages from climatic extremes in India: Do disaster-specific and generic adaptation measures matter? Environmental Economics and Policy Studies, 17(1), 157–177.

    Article  Google Scholar 

  • Cameron, A. C., & Trivedi, P. K. (1998). Regression analysis of count data. Nueva York: Cambridge University Press.

    Book  Google Scholar 

  • Cameron, A. C., & Trivedi, P. K. (2010). Microeconometrics using Stata (Vol. 2). College Station, TX: Stata Press.

    Google Scholar 

  • Das, S. (2016). Television is more effective in bringing behavioral change: Evidence from heat-wave awareness campaign in India. World Development, 88, 107–121. https://doi.org/10.1016/j.worlddev.2016.07.009.

    Article  Google Scholar 

  • Escaleras, M., Anbarci, N., & Register, C. A. (2007). Public sector corruption and major earthquakes: A potentially deadly interaction. Public Choice, 132, 209–230. https://doi.org/10.1007/s11127-007-9148-y.

    Article  Google Scholar 

  • Fankhauser, S., & McDermott, T. K. (2014). Understanding the adaptation deficit: Why are poor countries more vulnerable to climate events than rich countries? Global Environmental Change, 27, 9–18. https://doi.org/10.1016/j.gloenvcha.2014.04.014.

    Article  Google Scholar 

  • Ferreira, S., Hamilton, K., & Vincent, J. R. (2013). Does development reduce fatalities from natural disasters? New evidence for Floods. Environment and Development Economics, 18, 649–679. https://doi.org/10.1017/S1355770X13000387.

    Article  Google Scholar 

  • Government of India. (2011). Report of working group on flood management and region specific issues for XII plan. New Delhi, India: Government of India Planning Commission. Available at https://www.zaragoza.es/contenidos/medioambiente/onu/985-eng.pdf.

  • Government of India. (2012–13). Income, expenditure, productive assets and indebtedness of agricultural households in India, 2012–13. National Sample Survey (NSS). Ministry of Statistics and Programme Implementation, New Delhi.

  • Government of Odisha (2006–07). Annual report on natural calamities, Revenue & Disaster Management Department Special Relief Commissioner, Bhubaneswar.

  • Government of Odisha. (2012–13). Annual report on natural calamities, Revenue & Disaster Management Department Special Relief Commissioner, Bhubaneswar.

  • Government of Orissa. (2004). Orissa human development report, Nabakrushna Choudhury Centre for Development Studies, Bhubaneswar.

  • Guha-Sapir, D., Hargitt, D. & Hoyois, P. (2004). Thirty years of natural disasters 1974–2003: The numbers. Centre for Research on the Epidemiology of Disasters (CRED), Louvain-la-Neuve, Belgium: Presses universitaires de Louvain.

  • Guimaraes, P. (2008). The fixed effects negative binomial model revisited. Economics Letters, 99, 63–66. https://doi.org/10.1016/j.econlet.2007.05.030.

    Article  Google Scholar 

  • Hilbe, J. M. (2011). Negative binomial regression. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Intergovernmental Panel on Climate Change, Climate Change (2001). Impacts, adaptation and vulnerability, James McCarthy, Osvaldo Caniziani, Neil Leary, David Dokken, & Kasey White (Eds.), Chapter 8 (pp. 451–486).

  • Kahn, M. E. (2005). The death toll from natural disasters: the role of income, geography, and institutions. Review of Economics and Statistics, 87, 271–284. https://doi.org/10.1162/0034653053970339.

    Article  Google Scholar 

  • Kellenberg, D. K., & Mobarak, A. M. (2008). Does rising income increase or decrease damage risk from natural disasters? Journal of Urban Economics, 63, 788–802. https://doi.org/10.1016/j.jue.2007.05.003.

    Article  Google Scholar 

  • Kreft, S., Eckstein, D. Melchior, I. Global Climate Risk Index (2017). Who suffers most from extreme weather events? Weather-related loss events in 2015 and 1996 to 2015. Germanwatch Nord-Süd Initiative eV.

  • Mazumdar, J., & Paul, S. K. (2016). Socioeconomic and infrastructural vulnerability indices for cyclones in the eastern coastal states of India. Natural Hazards, 82(3), 1621–1643.

    Article  Google Scholar 

  • Mazumdar, J., & Paul, S. K. (2018). A spatially explicit method for identification of vulnerable hotspots of Odisha, India from potential cyclones. International Journal of Disaster Risk Reduction, 27, 391–405.

    Article  Google Scholar 

  • Mukherjee, S., & Chakraborty, D. (2011). “Is There any interdependence between economic growth and human development? Evidence from Indian states. Indian Journal of Human Development, 5(2), 467–494.

    Article  Google Scholar 

  • Mukherjee, S., Chakraborty, D., & Sikdar, S. (2014). Three decades of human development across Indian states: Inclusive growth or perpetual disparity?. New Delhi: National Institute of Public Finance and Policy.

    Google Scholar 

  • Padli, J., Habibullah, M. S., & Baharom, A. H. (2010). Economic impact of natural disasters’ fatalities. International Journal of Social Economics, 37, 429–441. https://doi.org/10.1108/03068291011042319.

    Article  Google Scholar 

  • Parida, Y. (2019). Economic impact of floods in the Indian states. Environment and Development Economics. https://doi.org/10.1017/S1355770X19000317.

    Article  Google Scholar 

  • Parida, Y., Bhardwaj, P., Sahoo, P. K., & Nayak, T. (2019). Effect of flood and fire accidents on economic growth in Odisha, India: District level analysis. International Journal of Big Data Mining for Global Warming. https://doi.org/10.1142/S2630534819500074.

    Article  Google Scholar 

  • Parida, Y., Dash, D. P., Bhardwaj, P., & Chowdhury, J. R. (2018). Effects of drought and flood on farmer suicides in Indian states: An empirical analysis. Economics of Disasters and Climate Change, 2, 159–180.

    Article  Google Scholar 

  • Raschky, P. A. (2008). Institutions and the losses from natural disasters. Natural Hazards and Earth System Sciences, 8, 627–634. https://doi.org/10.5194/nhess-8-627-2008.

    Article  Google Scholar 

  • Roy, B. C., & Mruthyunjaya y Selvarajan, S. (2002). Vulnerability to induced natural disasters with special emphasis on coping strategies of the rural poor in coastal Orissa, India. In Artículo de Congreso COP (Vol. 8).

  • Schumacher, I., & Strobl, E. (2011). Economic development and losses due to natural disasters: The role of hazard exposure. Ecological Economics, 72, 97–105. https://doi.org/10.1016/j.ecolecon.2011.09.002.

    Article  Google Scholar 

  • Sharma, U., & Patwardhan, A. (2008). Methodology for identifying vulnerability hotspots to tropical cyclone hazard in India. Mitigation and Adaptation Strategies for Global Change, 13(7), 703–717.

    Article  Google Scholar 

  • Stromberg, D. (2007). Natural disasters, economic development, and humanitarian aid. The Journal of Economic Perspectives, 21, 199–222.

    Article  Google Scholar 

  • Toya, H., & Skidmore, M. (2007). Economic development and the impacts of natural disasters. Economic Letters, 94, 20–25. https://doi.org/10.1016/j.econlet.2006.06.020.

    Article  Google Scholar 

  • Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge, Massachusetts: MIT Press.

    Google Scholar 

  • World Bank. (2012). Disaster risk management in South Asia: A regional overview. Washington, DC: The World Bank.

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank three anonymous referees, conference participate and Devi Prasad Dash for their valuable comments and suggestions. Special thanks Benudhar Jena, Joint Director, Directorate of Economics & Statistics, Government of Odisha and Prashanta Nayak for providing gross district domestic product data and district level disaster data.

Author information

Authors and Affiliations

  1. Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi, 110067, India

    Yashobanta Parida & Prarthna Agarwal Goel

  2. Verghese Kurien Centre of Excellence, Institute of Rural Management Anand (IRMA), Anand, Gujarat, India

    Yashobanta Parida

  3. Department of Economics, University School of Humanities and Social Sciences, Guru Gobind Singh Indraprastha University, Dwarka, New Delhi, 110078, India

    Prarthna Agarwal Goel

  4. Hobart and William Smith Colleges, 300 Pulteney Street, Geneva, New York, NY, 14456, USA

    Joyita Roy Chowdhury

  5. Vikram Deb Autonomous College, Berhampur University, Berhampur, Odisha, India

    Prakash Kumar Sahoo

  6. Department of Economics, P.N Autonomous College, Khurdha, Odisha, India

    Tapaswini Nayak

  7. Department of Economics, University of Utah, Salt Lake City, UT, 84112, USA

    Joyita Roy Chowdhury

Authors
  1. Yashobanta Parida
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prarthna Agarwal Goel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Joyita Roy Chowdhury
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Prakash Kumar Sahoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tapaswini Nayak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yashobanta Parida.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix: A

Appendix: A

See Tables 5, 6, and 7

Table 5 Summary of the literature
Full size table
Table 6 Definition and summary statistics
Full size table
Table 7 Correlation of the variables
Full size table

.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Parida, Y., Agarwal Goel, P., Roy Chowdhury, J. et al. Do economic development and disaster adaptation measures reduce the impact of natural disasters? A district-level analysis, Odisha, India. Environ Dev Sustain 23, 3487–3519 (2021). https://doi.org/10.1007/s10668-020-00728-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-020-00728-8

Keywords

JEL Classification

Search

Navigation