DETERMINANTS OF TECHNICAL EFFICIENCY AND TOTAL FACTOR PRODUCTIVITY CHANGE OF THE MANUFACTURING INDUSTRY IN EAST JAVA: EFFORTS TO INCREASE PERFORMANCE AND INDUSTRIAL COMPETITIVENESS
Abstract
This research aims to calculate and analyze the level of technical efficiency and total factor productivity change of manufacture industry, and to examine the factors that influence the value of technical efficiency of manufacture industry in East Java. The method used for this research is Data Envelopment Analysis (DEA) and Malmquist Index with Bootstrapping approach, and Tobit regression. This research used micro data from Indonesian Large and Medium-Scale Industry Survey within the year of 2007 to 2013. The results of this research are: (1) the estimated result of DEA with bootstrapping approach using output-oriented variable return to scale (VRS) assumption shows that the level of technical efficiency of manufacture industry in East Java has been not good enough and overall, it still has the potential to increase its output to reach an efficient condition; (2) the estimated result of Tobitregression demonstrates that the level of technical efficiency of the company is influenced by the company’s size, HHI, capital labor ratio, export and types of company ownership; (3) the estimated result of Malmquist Index with Bootstrapping approach shows that theaverage of total factor productivity change (TFPCH) of manufacture industry from 2007 to 2013 has
exhibited a positive change. The main factor that affects TFPCH, in order, are technological change, efficiency change, and efficiency scale change.
References
Amornkitvikai, Yot & Charles Harvie. 2010. Identifying and Measuring Technical Inefficiency Factors: Evidence from Unbalanced Panel Data for Thai Listed Manufacturing Enterprises. Economics Working Paper
Asmara, Alla dkk. 2013. Faktor-Faktor yang Mempengaruhi Perkembangan Investasi pada Industri Tekstil dan Produk Tekstil (TPT) Indonesia. Jurnal Bisnis dan
Manajemen. 12 (3): 12-23
Assaf, A & Matawie. 2010. Improving The Accurancy of DEA Efficiency Analysis: A Bootstrap Application to The Health Care Foodservice Industry. Journal of
Applied Economics, (42): 3547-3558
Badan Pusat Statistik (BPS). 2016. Survei Industri Besar dan Sedang. Jakarta: Biro Pusat Statistik
--------------------------------------. 2016. Produk Domestik Bruto Berdasaran Harga Konstan Menurut Lapangan Usaha, (Online), (http://bps.go.id, diakses 5
Oktober 2017).
Coelli, Rao, dkk. 2005. An Introduction to Efficiency and Productivity Analysis. Second Edition. United States: Springer Science & Business Media, Inc
Departmen Perindustrian Republik Indonesia. 2009. Laporan Pengembangan Sektor Industri Tahun 2004-2009. Jakarta: Kementrian Perindustrian
Green, William H. 2012. 7th Econometric Analysis. 7th Edition. New York: Pearson Education
Simmar, L & Wilson P.W. 1998. Sensivity Analysis of Efficiency Scores. How to Bootstrap in Nonparametric Frontier Models. Management Science Journal,
44(1): 49-60.
Spermann, Alexander. 2008. Tobit Model. Bahan Pengajaran Ekonometrika. University of Freirbug.
Suhardi, I., Y., dan Llewelyn, R. 2001. Penggunaan Model Regresi Tobit untuk Menganalisa Faktor-Faktor yang Berpengaruh Terhadap Kepuasan Konsumen
untuk Jasa Pengangkutan Barang. Jurnal Manajemen dan Kewirausahaan, (3): 106-112.
Suryawati. 2009. Analisis Struktur, Perilaku, dan Kinerja Industri Tekstil dan Pakaian Jadi di Provinsi DIY. Jurnal Akuntansi dan Manajemen, (1): 35-46.
Svedin, Dick & Jesper Stage. 2016. Impacts of Foreign Direct Investment on Efficiency in Swedish. Journal Economics : 5 (1): 2-17.
Taylor, John B & Lionel Frost. 2006. Microeconomics. 3th Edition. Australia: John Wiley & Sons.
