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Bu çalışmada, 2002-2017 yılları arasında TR düzey-2’de 26 bölgeye yapılan kamu yatırımlarının mekânsal etkileri ve nüfus yoğunluğunun kamu yatırımları üzerindeki etkisi incelenmiştir. Mekânsal panel veri yönteminin kullanıldığı çalışmada, SAR (Mekansâl Gecikme Modeli), SEM (Mekânsal Hata Modeli), SDM (Mekansâl Durbin Modeli) ve SAC (Mekânsal Otokorelasyon Modeli) modellerinin hem sabit etkili hem de tesadüfi etkili modelleri için AIC ve BIC değerlerine bakılmıştır ve en düşük AIC ve BIC değerleri olan modeller seçilmiştir. Buna göre, sabit etkili mekânsal Durbin (SDM) modelinin ve tesadüfi etkili mekânsal gecikme (SAR) modelinin, diğer mekânsal modellere göre daha uygun oldukları sonucuna ulaşılmıştır. Bu modellere göre 2002-2017 yılları arasında yapılan kamu yatırımlarının, mekânsal etki içerdiği belirlenmiştir (SEM ve SAC modelleri de benzer sonuçları vermiştir).
This study examined the spatial effects of public investments in 26 regions at TR level 2 between 2002 and 2017 and the impact of population intensity on public investments. In the study using the spatial panel data method, the AIC and BIC values for both fixed and random-effective models of the SAR (Mekanal Delay Model), SEM (Mekanal Error Model), SDM (Mekanal Durbin Model) and SAC (Mekanal Autocorrelation Model) were considered, and the models with the lowest AIC and BIC values were selected. Accordingly, the fixed-effective spatial Durbin (SDM) model and the random-effective spatial delay (SAR) model are more suitable than other spatial models. According to these models, the public investments made between 2002 and 2017 have been determined to have a spatial impact (SEM and SAC models have given similar results).
In this study, the spatial effects of public investments and the effect of the population density on public investments between the years 2002 and 2017 in level 2 regions are investigated. Both fixed and random spatial panel models, SAR (Spatial Autoregressive Model), SEM (Spatial Error Model), SDM (Spatial Durbin Model) and SAC (Spatial Autocorrelation Model) are used. For the selection of the fit model, AIC and BIC values are examined and the models with the lowest values are selected. By these values, it is concluded that the fixed effect spatial Durbin model (SDM) and the random effect spatial lag model (SAR) are more suitable models than the other spatial panel models. According to these models, it is determined that the public investment between the years 2002-2017 contains spatial effects (Also SEM and SAC models have similar results).
Field : Sosyal, Beşeri ve İdari Bilimler
Journal Type : Ulusal
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