This article strives to work out the causal relationship between natural disasters and economic growth in Pakistan. The study empirically tests the linkage using econometric techniques autoregressive distributed lag bound model by Pesaran (2001) and Granger causality test. We develop a proxy for the loss of natural disasters by a similar method as Noy (2009) and Bergholt et.al, (2012) did. The results of ARDL bounds testing approach evidence a negative long run relationship between the proxies of natural disasters and economic growth. The results of Granger Causality depict the uni-directional causality from natural disasters to economic growth both in short-run and long-run. Overall, the study determines that natural disasters deteriorate economic growth in Pakistan. This is the first study in Pakistan to assess the causal relationship among natural disasters and economic growth. So, further empirical evidence may link natural disasters to microeconomics and financial indicators. In future, researchers might control the impact of foreign development aid, remittances, political stability and country’s corruption rating. Natural disasters are an alarming issue and, addressing the questions related to their impacts on welfare of human being and economic growth of the countries contain significant importance in order to attract the attention of global development agencies and policymakers. As per INFORM (2015) risk index, Pakistan has the highest vulnerability towards natural disasters after Afghanistan. So, the study contains more significant value in context of Pakistan.
Caselli, F., G. Esquivel, and F. Lefort. 1996. Reopening the convergence debate: A new look at cross-country growth empirics. Journal of Economic Growth 1(3): 363–389.
Cavallo, E.A., A. Powell, and O. Becerra. 2010. Estimating the direct economic damages of the earthquake in Haiti. Economic Journal 120(546): F298–F312.
CRED (Centre for Research on the Epidemiology of Disasters). 2010. Em-Dat: International disaster database. Brussels: Centre for Research on the Epidemiology of Disasters, Université Catholique de Louvain.
Engle, R. F. and Granger, C. W. J., 1987, Co-integration and Error Correction: Representation, Estimation and Testing. Econometrica 55, 251–276.
Fisker, P.S. 2012. Earthquakes and economic growth. Working paper No. 01/2012. Development Research Working Paper Series. LaPaz: Institute for Advanced Development(INESAD)
Freeman, P.K. 2000. Infrastructure, Natural Disasters, and Poverty. International Institute for Applied Systems Analysis (IIASA) draft:
Gourio, F. 2008. Disasters and recoveries. American Economic Review 98(2): 68–73.
Ghirmay, T., 2004. Financial development and economic growth in sub-Saharan African countries: evidence from time Series analysis. African Development Review 16, 415–432.
Granger, C.W., 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424–438.
Granger, C. W., & Newbold, P. 1974. Spurious regressions in econometrics. Journal of econometrics, 2(2), 111-120.
Granger, C.W.,1988. Some recent developments in a concept of causality. Journal of Econometrics 39, 199–211.
Gunes, S. 2007. Functional income distribution in Turkey: a cointegration and VECM analysis.Journal of Economic and social Research, 9(2), 23-36.
Guo, J., Liu, H., Wu, X., Gu, J., Song, S., & Tang, Y. 2015. Natural Disasters, Economic Growth and Sustainable Development in China—An Empirical Study Using Provincial Panel Data. Sustainability, 7(12), 16783-16800.
Hamid, A., Akram, N., Bashir, S. and Janjua, Y.2011: an intuitive analysis of the impacts of floods on achieving MDgS in Pakistan. Current Research Journal of Economic Theory 3, 118–28.
Harris, R., Sollis, R., 2003. Applied Time Series Modelling and Forecasting. Wiley, West Sussex.
Haug, A. A. (2002). Temporal Aggregation and the Power of Cointegration Tests: a Monte Carlo Study*. Oxford Bulletin of Economics and Statistics, 64(4), 399-412.
Johansen, S., Juselius, K., 1990. Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxford Bulletin of Economics and Statistics 52, 169–210.
Johansen, S.,1988. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control 12, 231–254.
Kahn, M.E. 2005. The death toll from natural disasters: The role of income, geography, and institutions. Review of Economics and Statistics 87(2): 271–284.
Kunreuther, H. “Issue and Question, A Background Paper for ProVention.” Innovations in Managing Catastrophic Risks: How Can They Help the Poor?. World Bank/Warton Workshop, January 9-10, 2001.
Loayza, N., E. Olaberria, J. Rigolini, and L. Christiaensen. 2009. Natural disasters and growth going beyond the averages. Policy Research Working Paper Series: 4980. The World Bank.
Long, F. 1978. The Impact of natural disasters on the Third world agriculture: An Exploratory Survey of the Need for Some New Dimensions in Development Planning. American Journal of Economics and Sociolgy, Inc, 149-163.
Morley, B., 2006. Causality between economic growth and migration: an ARDL bounds testing approach. Economics Letters 90, 72–76.
Mujumdar, N. World development report, 2000/2001: attacking poverty. Indian Journal of Agricultural Economics 56(1): 146, 2001.
Nakamura, E., J. Steinsson, R.J. Barro, and J.F. Ursua. 2010. Crises and recoveries in an empirical model of consumption disasters. Working paper No. 15920, National Bureau of Economic Research (NBER), USA.
Narayan, P.K., Smyth, R., 2006. Higher education, real income and real investment in China: evidence from Granger causality tests. Education Economics 14, 107–125.
Narayan, P.K., Smyth, R., 2005. Electricity consumption, employment and real income in Australia: evidence from multivariate Granger causality tests. Energy Policy 33, 1109–1116.
Narayan, P.K., 2005. The saving and investment nexus for China: evidence from cointegration tests. Applied Economics 37, 1979–1990.
Noy, I.M. 2009. The macroeconomic consequences of disasters. Journal of Development Economics 88(2): 221–231.
Odhiambo, N.M. 2008. Financial depth, savings and economic growth in Kenya: a dynamic causal linkage. Economic Modelling 25 (4), 704–713.
Okuyama, Y. 2003. Economics of natural disasters: A critical review. Research paper No. 2003-2, Regional Research Institute, West Virginia University.
Pesaran, M., Pesaran, B., 1997. Working with Microfit 4.0: Interactive Economic Analysis. Oxford University Press, Oxford.
Pesaran, M., Shin, Y., Smith, R., 2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16, 289–326.
Raddatz, T. J., Reick, C. H., Knorr, W., Kattge, J., Roeckner, E., Schnur, R., ... & Jungclaus, J. 2007. Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century?. Climate Dynamics, 29(6), 565-574.
Raddatz, Claudio (2009). The Wrath of God. Policy Research Working Paper 5039. Washington, DC: World Bank.
Romer, P. (1990). Endogenous technological change. Journal of Political Economy, 98(5), S71–S102.
Schumacher, I., & Strobl, E. (2011). Economic development and losses due to natural disasters: the role of hazard exposure. Ecological Economics, 72, 97-105.
Shabnam, N. (2014). Natural Disasters and Economic Growth: A Review. International Journal of Disaster Risk Science 5(2): 157-163.
Skidmore, M., and H. Toya. 2002. Do natural disasters promote long-run growth? Economic Inquiry 40(4): 664–687.
Takaendesa, P., Odhiambo, N.M., 2007. Financial development and economic growth: an empirical analysis of two Southern African countries. Studies in Economics and Econometrics 31 (3), 61–80.
Skidmore, M. and H. Toya (2002). “Do natural disasters promote long run growth?” Economic Inquiry 40(4): 664-687.