EconPapers    
Economics at your fingertips  
 

Productivity and technological progress of the Japanese manufacturing industries, 2000–2014: estimation with data envelopment analysis and log-linear learning model

Joseph Junior Aduba () and Behrooz Asgari ()
Additional contact information
Joseph Junior Aduba: Ritsumeikan University
Behrooz Asgari: Ritsumeikan Asia Pacific University

Asia-Pacific Journal of Regional Science, 2020, vol. 4, issue 2, No 4, 343-387

Abstract: Abstract How has the Japanese manufacturing sector fared in productivity and technological learning in recent years? To answer this, we summarized the manufacturing industry into 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 loglinear 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 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.

Keywords: Efficiency; Productivity; Total-factor-productivity; Learning-by-doing; Technological learning; Manufacturing Industry (search for similar items in EconPapers)
JEL-codes: D24 L60 O33 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s41685-019-00131-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:apjors:v:4:y:2020:i:2:d:10.1007_s41685-019-00131-w

Ordering information: This journal article can be ordered from
https://www.springer ... cience/journal/41685

DOI: 10.1007/s41685-019-00131-w

Access Statistics for this article

Asia-Pacific Journal of Regional Science is currently edited by Yoshiro Higano

More articles in Asia-Pacific Journal of Regional Science from Springer
Bibliographic data for series maintained by Sonal Shukla ().

 
Page updated 2020-09-12
Handle: RePEc:spr:apjors:v:4:y:2020:i:2:d:10.1007_s41685-019-00131-w