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dc.contributor.authorDewi, Vivin Novita
dc.contributor.authorSetiawan
dc.contributor.authorRahayu, Santi Puteri
dc.date.accessioned2015-12-05T07:43:28Z
dc.date.available2015-12-05T07:43:28Z
dc.date.issued2015-12-07
dc.identifier.citation[1] L. Anselin. A Test for Spatial Auto-Correlation in Seemingly Unreleted Regressions. Economics Letters 28, 335-341, 1988. [2] Dimas and Woyanti. Penyerapan Tenaga kerja di DKI Jakarta. Jurnal Bisnis dan Ekonomi (JBE), 16: 32-41, 2009. [3] M.Z Tadjoeddin and A. Chowdhury Employment Function for Indonesia: An Econometric Analysis At The Sectoral Level. The Journal of Developing Areas, Vol. 46, No. 1, 2012. [4] M. Setiawan. Strategi Pengembangan UKM Berdasarkan Sektor Ekonomi Dalam Rangka Peningkatan Penyerapan Tenaga Kerja di Indonesia. Seminar Internasional Simposium kebudayaan Indonesia-Malaysia ke-X (SKIM X), 2007. [5] L. Anselin. Spasial Econometric: Methods and Models. Kluwer Academic publishers, 1988. [6] D. Gujarati. Basic Econometric 4th Edition. Mc.Grow Hill, 2004. [7] W.H. Greene. Econometric Analysis: Fifth Edition. Ney Jersey: Pearson Education LTD, 2002. [8] J.P Lesage and K. Pace. Spatial and Spatiotemporal Econometrics. Elsevier, 1999. [9] L.D.C Cahyadi. Analisis Faktor-Faktor yang Mempengaruhi Penyerapan Tenaga Kerja Industri kreatif kota Denpasar, Tesis, Udayana University, 2013. [10] http://www.rri.wvu.edu/wp-content/uploads/2013/07/Fullpaper [11] http://www.bps.go.id/index.php/publikasi [12] http://sourceforge.net/projects/jump-pilot/files/OpenJUMP/1.8.0/ [13] https://www.academia.edu/10758035/Panduan_Operasional_Analisis_Data_Spasial [14] http://www.aecr.org/web/congresos/2010/htdocs/pdf/p131.pdfin_ID
dc.identifier.issn2477-3328
dc.identifier.urihttp://hdl.handle.net/11617/6314
dc.description.abstractEmployment becomes one of the most important focuses of development in Indonesia. Analysis of employment and its factors could be the consideration in making employment policies. Several studies of employment related to a particular economic sector have been carried out. For a comparison, this paper discussed the model of labor absorption with three economic sectors. The source of data was derived from all the provinces in Indonesia for five years. Spatial model was estimated with Maximum Likelihood Estimation (MLE) for each year of observation. Moran’s I and LM test were used to identify the spatial dependency. SUR model was estimated with Ordinary Least Square (OLS) and General Least Square (GLS). The variables used to estimate labor absorption were the output and real wage. The result indicated that the spatial dependency was significant particularly in the agricultural sector with a spatial error model. Meanwhile, labor absorption was significantly affected by the output and real wage for both OLS estimation and GLS estimation for SUR model. Service sector had the highest R2 value. UR model with GLS estimation was evidenced to be more efficient than OLS estimation, in addition, standard error of parameters using GLS estimation evenly was lower than OLS estimation.in_ID
dc.language.isoenin_ID
dc.publisherUniversitas Muhammadiyah Surakartain_ID
dc.subjectsectoral employmentin_ID
dc.subjectspatialin_ID
dc.subjectSURin_ID
dc.subjectGLSin_ID
dc.subjectMLEin_ID
dc.titleSectoral Employment in Indonesia With Spatial and Seemingly Unrelated Regression (SUR) Modelapproachin_ID
dc.typeArticlein_ID


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