EconPapers    
Economics at your fingertips  
 

Modeling the effect of competition on US manufacturing sectors’ efficiency: an order-m frontier analysis

Michael Polemis (), Thanasis Stengos and Nickolaos G. Tzeremes
Additional contact information
Nickolaos G. Tzeremes: University of Thessaly

Journal of Productivity Analysis, 2020, vol. 54, issue 1, No 3, 27-41

Abstract: Abstract The study applies the probabilistic framework of nonparametric frontier estimation to model the effect of competitive conditions on sectors’ production efficiency levels. We utilize conditional order-m robust frontiers to model the dynamic effects of competition on a sample of U.S. manufacturing sectors over the period 1958–2009. Contrary to the existing studies, we apply for the first time in the Industrial Organization literature the latest advances of robust nonparametric frontier analysis to disentagle the dynamic effects alongside the effects of competition on sectors’ productive efficiency levels. The results derived from the time-dependent robust conditional estimators unveil a non-linear relationship between product market competition and productive efficiency. Our findings suggest that for higher competition levels the effect is positive up to a certain threshold after which the effect becomes negative.

Keywords: Conditional efficiency; Probabilistic frontier analysis; Order-m estimators; Product Market Competition; Manufacturing; L60; C14; O14 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11123-020-00583-9 Abstract (text/html)
Access to full text is restricted to subscribers.

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:kap:jproda:v:54:y:2020:i:1:d:10.1007_s11123-020-00583-9

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2

DOI: 10.1007/s11123-020-00583-9

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 ().

 
Page updated 2025-04-02
Handle: RePEc:kap:jproda:v:54:y:2020:i:1:d:10.1007_s11123-020-00583-9