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.

With the implementation of the Joint Comprehensive Plan of Action (JCPOA) in 2016, Iran experienced a short period without international sanctions which resulted in an annual increase in the gross domestic product (GDP) in the following two years. However, it was not just the formal economy that was affected by the sanctions. Previous studies have shown that sanctions can negatively affect the shadow (or informal) economy and may even have a larger impact on the informal economy than on the formal economy. Nighttime lights (NTL) data allow us to study shadow economy activities that are not reported in the official GDP. This study uses a panel of NTL (the DMSP/OLS and VIIRS/DNB harmonized dataset) from 1992 to 2018 for 31 Iranian provinces to investigate the association between the lifting of sanctions and the growth of the shadow economy. The empirical results suggest an increase in shadow economy activity with the lifting of sanctions while controlling for other drivers of informal activities.

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