Increased connectivity between regions in Indonesia is believed to impact the productivity capacity of each region, as well as its economic growth. Moreover, the influence of connectivity on the surrounding area is commonly known as the indirect effect (spillover effect). This effect can increase the number of products, goods and services used as production factors. The study aims to examine the effect of transportation infrastructure on economic growth. We used spatial modelling to estimate the impact of transportation infrastructure on the economy of 34 provinces in Indonesia in 2017. We applied the spatial lag of X model (SLX), spatial autoregressive model (SAR), spatial error model (SEM), spatial autoregressive combined model (SAC), spatial Durbin model (SDM), spatial Durbin error model (SDEM), and spatial autoregressive combined mixed model (SAC mixed). According to the estimation results, the SAC mixed model is the best spatial model, as it has the smallest value of the Akaike information criterion (AIC) and significant coefficients of ρ (rho) and λ (lambda) parameters. The results show that the indicators “bus stations”, “domestic investment” and “foreign investment” have a direct effect on the economic growth in 34 Indonesian provinces. In addition, we revealed the presence of indirect effects (spillovers) between provinces in Indonesia for the same variables.

Original languageEnglish
Pages (from-to)911-920
Number of pages10
JournalEconomy of Regions
Issue number3
Publication statusPublished - 2020


  • Moran's Index
  • Regional productivity
  • Spatial Durbin error model
  • Spatial Durbin model
  • Spatial autoregressive
  • Spatial econometrics
  • Spatial error model
  • Spatial modelling
  • Spatial spillover
  • Transportation infrastructure


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