Abstract
This paper studies the relationship between natural disasters and economic growth in the disaster-prone country of Iran, using a spatial Durbin panel model and covering the time period from 2010 to 2016 and including 29 provinces. The results of the empirical investigation suggest that there is a statistically significant positive relationship between the spatially-lagged occurrence of natural disasters and the change of the first difference of the natural logarithm of GDP per capita. Moreover, the estimations support the findings of previous cross-country studies, namely that we cannot find empirical evidence for a statistically significant direct effect of natural disasters on economic growth in the short term. When including time-lags, we can see a statistically significant positive effect of natural disasters on economic growth after two years. When taking into account the disaster type, which is mainly earthquake and flood in the case of Iran, the results suggest that the positive spillover effects are, rather, driven by earthquakes, and that there is a direct positive effect of floods in the short run. These findings extend existing literature and add new insights that are not just relevant for the case of Iran. The novelty of this study is that established and innovative approaches are used to study natural disasters on the provincial level, instead of the country level, and also take into account spatial spillover effects after disaster events that have been rarely discussed in literature.
Highlights
Extreme weather phenomena and other natural disasters, which have been attributed to climate change, are dominating the political and public discourse recently again
The natural disaster events might destroy or interrupt businesses and production sites, which are the competition of neighboring provinces, causing a higher demand for products and services from the neighboring provinces, which might create new jobs
The coefficient suggests that gross domestic product (GDP) per capita increases on average by 4% two years after the disaster event. These results are supported by other types of spatial panel models that are reported in Tables A6 and A7 of the Appendix A, which include the commonly used spatial models as presented in Elhorst (2014), and report the results of different estimation techniques such as maximum likelihood estimation (MLE) and ordinary least squares (OLS)
Summary
Extreme weather phenomena and other natural disasters, which have been attributed to climate change, are dominating the political and public discourse recently again. Iran, as it is an interesting case study in this context. East and North Africa (MENA) region which has experienced many natural disasters over the past thirty years, affecting more than 40 million people and costing their economies about US$20 billion (World Bank WB). Main disaster events in the region are floods, earthquakes, storms and droughts, with Iran being the most affected country. In April 2019, Iran experienced the most severe flood ever recorded in the MENA region, affecting more than 10 million people and causing damage of more than US$2.5 billion. Over the past 30 years two of the most-deadly earthquakes of modern times hit Iran which killed combined more than 65,000 people and caused damage of almost US$9 billion
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