Pola Interaksi Spasial Human Capital dan Dampak Human Capital Spillover terhadap Pertumbuhan Ekonomi : Studi Empiris 10 Negara ASEAN

Abstract

This research originated from the idea of human capital in the form of education and health attached to the workforce. Given the abundance and concentration of human capital spillover in an area with different quantities and qualities to be considered, workers with a certain level of education and expertise decide to move to other areas. The openness of the ASEAN economy allows the labor of one country to mobilize one country to another within the ASEAN region. The purposes of this study are: (1) Analyzing patterns of spatial interaction of human capital in ASEAN member countries; (2) Analyzing the impact of human capital spillover on economic growth in ASEAN member countries. The first objective of the study was discussed with Global Moran's index statistics and local Moran's index statistics or Local Indicator Spatial Association (LISA). The second objective of this study was discussed using spatial econometrics namely Spatial Autoregressive Model (SAR) fixed effect, Spatial Error Model (SEM) fixed effect, and Spatial Durbin Model (SDM) fixed effect. This research uses the shahih model to answer the second research objective with SDM FE. The results of this study obtained the conclusions as follows: (1) The results of the analysis using Global Moran's I identified that the Educated Worker Share (EWS) 2015 has a spatial pattern clustered with a coefficient of 0.110 with a significance level of α = 5%, Labor 2004 identified the spatial pattern clustering with significance level α = 5 %. (2) Based on LISA calculation results obtained empirical results that: (a). the changing pattern of spatial interaction of Singapore's economic growth which, originally with its characteristics nature as its advanced state, has spatial interaction with other developed countries, it turns out that in 2015 it is portrayed by Singapore as its country as a developed country interacting spatially with low-income countries. (b). Philippines originally in 2004 with high UWS characteristics interact spatially with high UWS countries, it turns out in 2015 photographed that the Philippines characteristics low UWS interact spatially with high UWS country. (c) Indonesia originally in 2004 with characteristics labor that interacts spatially with a lot of labor power, it turns out in 2015 photographed Indonesia with characteristics labor that spatial interact with many countries whose labor is low. (3). Based on the result of human resource estimate FE obtained that (a). significant variables are 5 ie spatial lag Economic Growth (ρ), Capital, RLS, W_ UWS, and W_Tenaga Kerja. (b) The coefficient of 0.305589 is significant on the meaning of spatial lag dependence, or the influence of 10 countries observed with ASEAN economic growth. The spatial impact of neighboring countries' economic growth to domestic countries in ASEAN remains significant with the effect of every 1% growth of neighboring countries contributing to domestic growth of 0.3 percent through the impact of human capital spillover on the economic growth of ASEAN member countries.