KONTRIBUSI INFRASTRUKTUR TERHADAP PERTUMBUHAN EKONOMI SUMATERA SELATAN

This study aims to analyze the contribution of infrastructure for economic growth in South Sumatera. The subjects are 10 District/Municipal reasonable legal in South Sumatera, years of observation 2007-2011. The data used are secondary data, namely the economic growth, roads, electricity, drinking w...

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Bibliographic Details
Main Authors: , Jaka Atmajaya, , Drs. Ahmad Jamli, M.A.
Format: Theses and Dissertations NonPeerReviewed
Published: [Yogyakarta] : Universitas Gadjah Mada 2014
Subjects:
ETD
Online Access:https://repository.ugm.ac.id/130161/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=70576
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Summary:This study aims to analyze the contribution of infrastructure for economic growth in South Sumatera. The subjects are 10 District/Municipal reasonable legal in South Sumatera, years of observation 2007-2011. The data used are secondary data, namely the economic growth, roads, electricity, drinking water, hospital beds, and health centers. Analysis instrument that is used to determine the contribution of infrastructure for economic growth in South Sumatera is the panel data regression. Panel data regression estimation technique that used is fixed effect model (FEM). The research finds that in general the condition of infrastructures in South Sumatera were not ideal yet. The statistical test shows that only the electricity have a positive and significant contribution for economic growth in the amount of 0,35 percent. Roads have a negative contribution in the amount of 0,9 percent and significant. Drinking water and hospital beds have a positive contribution in the amount of 0,06 percent but insignificant. Health centers have a negative contribution in the amount of 0,09 percent but insignificant. The coefficient of determination shown by the R-square of 0,99 indicates that the variation of the independent variables in the model can explain the variation in economic growth level of 99 percent, the remaining 1 percent is explained by other variables out of the model.