The University of Southampton
University of Southampton Institutional Repository

Stochastic frontier modelling of working capital efficiency across Europe: evidence from a stochastic frontier analysis

Stochastic frontier modelling of working capital efficiency across Europe: evidence from a stochastic frontier analysis
Stochastic frontier modelling of working capital efficiency across Europe: evidence from a stochastic frontier analysis

This paper adopts the stochastic frontier analysis (SFA) to model working capital efficiency (WCE) on a sample of 6170 European firms from 2009 to 2018. We find: (i) larger firms are more efficient with their working capital management (WCM) than smaller firms, (ii) higher cash holding contributes to WCE, (iii) high competition is less conducive to WCE than low competition, (iv) export and sales growth potential decrease WCE and (v) WCE increases with access to bank credit. In the analysis, a distinction is made between the “old” EU countries and the “new” EU countries. The results are sensitive to the year of admission into the EU. The results are robust to omitted variable bias, using a more novel approach.

Determinants of WCE, Inventory, Stochastic frontier analysis, Trade payables, Trade receivables, Working capital efficiency, Working capital management
0040-1625
Afrifa, Godfred Adjapong
b38efd3a-338e-4910-af21-c7f673ebf095
Tingbani, Ishmael
e6b2741a-d792-4adf-84cc-a2f64d5545ca
Adesinac, Oluseyi Oluseun
27529b21-3d0e-47b4-8ff2-090492220ee4
Afrifa, Godfred Adjapong
b38efd3a-338e-4910-af21-c7f673ebf095
Tingbani, Ishmael
e6b2741a-d792-4adf-84cc-a2f64d5545ca
Adesinac, Oluseyi Oluseun
27529b21-3d0e-47b4-8ff2-090492220ee4

Afrifa, Godfred Adjapong, Tingbani, Ishmael and Adesinac, Oluseyi Oluseun (2022) Stochastic frontier modelling of working capital efficiency across Europe: evidence from a stochastic frontier analysis. Technological Forecasting and Social Change, 184, [122012]. (doi:10.1016/j.techfore.2022.122012).

Record type: Article

Abstract

This paper adopts the stochastic frontier analysis (SFA) to model working capital efficiency (WCE) on a sample of 6170 European firms from 2009 to 2018. We find: (i) larger firms are more efficient with their working capital management (WCM) than smaller firms, (ii) higher cash holding contributes to WCE, (iii) high competition is less conducive to WCE than low competition, (iv) export and sales growth potential decrease WCE and (v) WCE increases with access to bank credit. In the analysis, a distinction is made between the “old” EU countries and the “new” EU countries. The results are sensitive to the year of admission into the EU. The results are robust to omitted variable bias, using a more novel approach.

Text
WORKING CAPITAL EFFICIENCY ACROSS EUROPE - EVIDENCE FROM STOCHASTIC FRONTIER ANALYSIS (1) - Accepted Manuscript
Restricted to Repository staff only until 11 September 2024.
Request a copy
Text
1-s2.0-S0040162522005339-main - Version of Record
Download (663kB)

More information

Accepted/In Press date: 29 August 2022
e-pub ahead of print date: 11 September 2022
Published date: November 2022
Additional Information: Publisher Copyright: © 2022 The Authors
Keywords: Determinants of WCE, Inventory, Stochastic frontier analysis, Trade payables, Trade receivables, Working capital efficiency, Working capital management

Identifiers

Local EPrints ID: 470235
URI: http://eprints.soton.ac.uk/id/eprint/470235
ISSN: 0040-1625
PURE UUID: a45d0ef5-3a7f-45de-93d4-2652332b2a9e
ORCID for Ishmael Tingbani: ORCID iD orcid.org/0000-0002-4012-1224

Catalogue record

Date deposited: 05 Oct 2022 16:32
Last modified: 17 Mar 2024 04:02

Export record

Altmetrics

Contributors

Author: Godfred Adjapong Afrifa
Author: Oluseyi Oluseun Adesinac

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×