EconPapers    
Economics at your fingertips  
 

Nonparametric Measures of Capacity Utilization of the Tunisian Manufacturing Industry: Short- and Long-Run Dual Approach

Maha Kalai ()
Additional contact information
Maha Kalai: University of Sfax

Journal of the Knowledge Economy, 2019, vol. 10, issue 1, No 17, 318-334

Abstract: Abstract This paper tried to develop a nonparametric method of obtaining the minimum of the long-run average total cost curve of a firm to define its production capacity. It provided a benchmark for the measurement of the capacity utilization rate at the observed output level of the industry. In the case of the long-run constant returns to scale, the minimum of the short-run average total cost curve is determined to measure the short-run capacity utilization. When applied empirically, we measured the annual capacity utilization rates of the Tunisian manufacturing industry and its six sectors over the period 1961–2014. In addition, we developed a nonparametric analysis based on the data envelopment analysis methodology for the quasi-fixed capital factor of the short-run average total cost curve with variable returns to scale using an iterative search procedure. From the estimated results of the capacity utilization, we noticed a significant under-utilization of the production capacity in the manufacturing sector.

Keywords: Data envelopment analysis; Capacity utilization; Most productive scale size; Efficiency (search for similar items in EconPapers)
JEL-codes: C4 D24 L2 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s13132-017-0463-3 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:jknowl:v:10:y:2019:i:1:d:10.1007_s13132-017-0463-3

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/13132

DOI: 10.1007/s13132-017-0463-3

Access Statistics for this article

Journal of the Knowledge Economy is currently edited by Elias G. Carayannis

More articles in Journal of the Knowledge Economy from Springer, Portland International Center for Management of Engineering and Technology (PICMET)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:jknowl:v:10:y:2019:i:1:d:10.1007_s13132-017-0463-3