Regional effects of terrorism on economic growth in Turkey: A geographically weighted regression approach

Abstract

Abstract The economic growth effects of terrorism have generally been examined in a cross-country framework where socio-economic differences among the countries are ignored. This highly restrictive assumption may result in heterogeneity bias, which could be overcome by resorting to country studies rather than cross-country analysis. Moreover, the relationship between the terrorist incidents and various factors may not be stationary in space. The majority of terrorist incidents in Turkey are concentrated mainly in Eastern, and South Eastern Turkey and big cities. Thus, the geographical dispersion of terrorist incidents in Turkey may result in uneven regional impact, necessitating local parameter estimates. This study analyses the effects of terrorism on economic growth across provinces of Turkey for the time period 1987—2001. Following a traditional global regression analysis, spatial variations in the relationships are examined with geographically weighted regression (GWR) to obtain locally different parameter estimates. A GWR approach allows the modeling of relationships that vary over space by introducing distance-based weights to provide parameter estimates for each variable and each geographical location. Empirical evidence indicates that a GWR model significantly improves the model fitting over the traditional global model. Even though the traditional convergence analysis reveals that terrorism hinders economic growth, GWR results indicate that its provincial effects are more pronounced for the Eastern and South Eastern provinces compared to the Western provinces. Moreover, empirical findings suggest that there is a considerable variation in speeds of convergence of provinces, which cannot be captured by the traditional beta convergence analysis.

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