Estimation of technical change and TFP growth based on observable technology shifters
Almas Heshmati () and
Masoomeh Rashidghalam ()
Additional contact information
Masoomeh Rashidghalam: University of Tabriz
Journal of Productivity Analysis, 2020, vol. 53, issue 1, No 3, 36 pages
Abstract This paper models and estimates total factor productivity (TFP) growth parametrically. The model is a generalization of the traditional production function model where technology is represented by a time trend. It decomposes TFP growth into an unobservable time trend induced technical change, scale economies and an observable technology shifter index’s components. The empirical results are based on unbalanced panel data at the global level for 190 countries observed over the period 1996–2013. It uses a number of exogenous growth factors in modeling four technology shifter indices to explore development infrastructure, finance, technology and human development determinants of TFP growth. Our results show that unobservable technical change remains the most important component of TFP growth. Our findings also show that technical changes and TFP growth are unexpectedly negative across all country income groups and years.
Keywords: Technical change; Total factor productivity growth; Technology indicators; Technology shifters (search for similar items in EconPapers)
JEL-codes: C33 C43 D24 O33 O47 O50 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s11123-019-00558-5 Abstract (text/html)
Access to full text is restricted to subscribers.
Working Paper: Estimation of Technical Change and TFP Growth based on Observable Technology Shifters (2017)
Working Paper: Estimation of Technical Change and TFP Growth Based on Observable Technology Shifters (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:53:y:2020:i:1:d:10.1007_s11123-019-00558-5
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2
Access Statistics for this article
Journal of Productivity Analysis is currently edited by William Greene, Chris O'Donnell and Victor Podinovski
More articles in Journal of Productivity Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().