Department / Course Research Organization of Social Science (BKC)
Title / Position Visiting Senior Researcher
Language English
Publication Date 2020
Type Research paper (scientific journal)
Peer Review Yes
Title Productivity and technological progress of the Japanese manufacturing industries, 2000–2014: estimation with data envelopment analysis and log-linear learning model.
Contribution Type Joint Work
Journal Asia-Pacific Journal of Regional Science
Journal Type Another Country
Publisher Springer
Volume, Issue, Page 4,343-387
Total page number
Responsible for Design, data analysis, results and discussion of the findings
Authorship Lead author , Last author , Corresponding author
Author and coauthor Aduba J.J., Asgari B.
Details How has the Japanese manufacturing sector fared in productivity and technological learning in recent years? To answer this, we summarized the manufacturing industry into a 3-digit sub-sector (25 sub-sectors) and evaluated the entire manufacturing industry. Our study covers 15 years of production cycles (2000–2014). Using data envelopment analysis and log-linear learning models, we empirically estimated the productivity and technological learning of these industries. The result shows negative (− 0.6%) total factor productivity (TFP) growth between 2000 and 2014. TFP was particularly affected by 2001, and 2008/2009 financial crisis. TFP regress also deepened in recent years (2011–2014) which we blamed on both internal and external shocks in the system. We showed that positive TFP observed in other years resulted from technical progress and efficiency improvement. Industry-level results were consistent with the annual mean result which suggest a common economic downturn. Estimated progress ratios from learning models show that individual industry exhibits unique learning rates, with some industries showing technological learning (i.e., decreasing unit cost of production) between 2000 and 2007 and others between 2010 and 2014. Industries viz. production machinery, electrical devices and circuit, chemical, pharmaceutical, and food manufacturing showed sustained learning between 2001 and 2013, implying huge cost saving as outputs expand. The overall result, however, showed that learning got worst and was lost at some point between 2008 and 2014. We conclude that productivity differentials explained by learning rates show that technological progress and innovations in Japanese manufacturing were capital intensive and cost-inefficient and that the Japanese manufacturing industry has not fully regained its competitiveness as the world’s leading manufacturing hub. We argued that for productivity improvement in Japanese manufacturing industries, there is a need for policy thrust to restore and ensure sustained learning within and across the industries.