GDP Gross Domestic Product GRDP Gross Regional Domestic Product GCI Global Competitiveness Index TFP Factor Productivity SFP Single Factor Productivity MFP Multi Factor Productivity ICT Information, Communication and Technology UNIDO United Nation Industrial Development Organization OECD Organization for Economic Cooperation and Development OLS Ordinary Square FEM Fixed Effect Method REM Random Effect Method R & D Research and Development ILO International Organization Komite Pemantauan Pelaksanaan Otonomi Daerah/ Regional Autonomy Implementation Monitoring Committee Abstract Both SFP and TFP are believed as tools to measure productivity. This means that those measurements can be used to assess economic performance. However, each measurement has its own superiority, which relies on the purposes and the availability of sources to calculate it. Indonesia’s economy which consists of 11 sectors shows a positive growth in around last 10 years. Those sectors are manufacturing sector, agriculture sector and trade sector. Among those sectors, there are several sectors having bigger share on national GDP compare to the rest. However, the magnitude of each sector share in GDP is not solely determined by the sector itself, but it also influenced by other factors. One believed as the supporting factor is infrastructure. Therefore, this will examine the role of infrastructure on the productivity in manufacturing sector in Indonesia and analyze which kind of infrastructures that highly contributes to the productivity. The paper is measuring productivity labor productivity as one form of SFP. Based on the calculation, this paper excludes the TFP calculation as the productivity measurement due to unconvincing result. To assess the role of infrastructures in productivity in the manufacturing sector in Indonesia during 2000-2009, by using a panel data set which includes all provinces, the estimation is conducted. The result shows that the best method to estimate the model is Random Effect method. Further analysis
From the Figure 15, Figure 16 on average labor productivity and education infrastructure (most significant) and also based on average labor productivity and roads (least significant), there are two provinces that can be considered as outliers. The first is Nusa Tenggara Timur experiences high proportion of basic school per labor but low labor productivity and high proportion of road per labor but low labor productivity. Second is Kalimantan Timur which experiences high labor productivity but low proportion of basic school per labor and high labor productivity but low proportion of road per labor. Further analysis on two provinces, Table 5 shows the general characteristics of each province. For Nusa Tenggara Timur Province, low productivity and low basic school ratio per labor might be due to the geographical condition and also the dominant sector that contribute to the economy. These also apply for Kalimantan Timur Province. To sum up, from two analysis on provincial case (Nusa Tenggara Timur and Kalimantan Timur) it can be seen that characteristics of a province have an effect on labor productivity and must be taken into account when determining infrastructure provisions. It also reveals that contribution of infrastructure on labor productivity vary across provinces.