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.

Even though the convergence of regional per capita income has been a highly debated issue internationally, empirical evidence regarding Turkey is limited as well as contradictory. This article is an attempt to investigate regional income inequality and the convergence dynamics in Turkey for the time period 1987-2001. First, the Theil coefficient of concentration index is used to analyze the dispersion aspects of the convergence process. The geographically based decomposition of inequality suggests a strong correlation between the share of interregional inequality and spatial clustering. Then, we estimate convergence dynamics employing alternative spatial econometric methods. In addition to the global models, we also estimate local models taking spatial variations into account. Empirical analysis indicates that geographically weighted regression improves model fitting with better explanatory power. There is considerable variation in speed of convergence of provinces, which cannot be captured by the traditional beta convergence analysis.

The ongoing Turkish-Greek antagonism has triggered the interest of defense economists to investigate the various aspects of the arms race between Turkey and Greece. However, empirical studies examining the long-run relationship between the military expenditures of the two countries offer little evidence in favor of such an interaction. This paper attributes the poor results of the previous literature to the adherence to linear cointegration techniques and argues that if the adjustment towards long-run equilibrium is asymmetric, nonlinear co-integration models should be employed. Accordingly, this paper considers threshold autoregressive (TAR) and momentum threshold autoregressive (M-TAR) models as alternative adjustment processes for the cointegration relationship, following Enders and Siklos (2001). The results indicate that the relationship between the variables can be characterized by a threshold cointegration specification following an M-TAR type adjustment process.Arms race, Threshold cointegration, TAR and M-TAR models,