Meta-frontier and measures of efficiency emphasising optimal corporate governance risk across countries

• DOI: https://doi.org/10.1108/CG-09-2020-0414
• Published date: 19 August 2021
• Date: 19 August 2021
• Pages: 89-113
• Subject Matter: Strategy,Corporate governance
• Author: Walaa Wahid ElKelish,Panagiotis Zervopoulos

Meta-frontier and measures of eff‌iciency

emphasising optimal corporate

governance risk across countries

Walaa Wahid ElKelish and Panagiotis Zervopoulos

Abstract

Purpose –This paper aims to investigatethe internal and external determinants of firms’efficiency and

develop optimal corporate governance risk benchmarks for the manufacturing sector across different

countries.

Design/methodology/approach –Corporate governance risk data were acquired from Institutional

ShareholderServices Europe SA. Data on firms’ efficiencyand for explanatory and controlvariables were

taken from the DataStream database. The generalised directional distance function data envelopment

analysis (GDDF-DEA) model and its stochastic extension provided corporate efficiency measures and

optimal corporategovernance benchmarks. The authors used ordinaryleast squares multiple regression

analysiswith wild bootstrapping to test the study hypotheses.

Findings –The authors found significantdifferences between firms’ optimal and actual efficiencyinput/

output variables and corporate governance risks in the manufacturing sector acrosscountries. Internal

firm characteristics such as group affiliations, product market competition and insider ownership and

external institutional factors such as the legal system, the rule of law, control of corruption, law

enforcementand cultural values are vitaldeterminants of firms’ efficiency.

Practical implications –This paper provides valuable guidance to enable corporate managers,

regulatorsand policymakers to enhance firms’ efficiencyand corporate governance practices.

Originality/value –This paper develops optimalcorporate governance risk benchmarks and identifies

the most critical internal and external factors affecting firms’ efficiency in the manufacturing sector in

various countries. It also used a novel GDDF-DEA model, with the multi-parametric model for bias

correctionof efficiency estimator.

Keywords Data envelopment analysis, Corporate governance, Eff‌iciency,

Directional distance function, Manufacturing sector

Paper type Research paper

1. Introduction

In recent years, corporate governance systems have been subject to intense pressures

after international corporate failures, including Enron and WorldCom. Regulators have

introduced mandatory regulations such as the Sarbanes-Oxley Act (SOX) (2002) to control

corporate behaviour, guarantee audit independence and ensure market stability. However,

these regulations were not enough to prevent subsequent problems such as the sub-prime

mortgage financial crisis (2008). This was partly attributed to a failure of corporate

governance to protect the interests of shareholders and other stakeholders (De Haan and

Vlahu, 2016;Kirkpatrick, 2009). Several corporate governance practices are still under

flexible self-regulation across countries and mandatory regulations only cover marginal

practices that may encourage management manipulations (Blair, 2003;Bratton, 2002;

Brown and Caylor, 2006). For example, the mandatory SOX (2002) regulations in the US do

not address vital issues such as management bias towards short-term investments

Walaa Wahid ElKelish is

based at the Department of

Accounting, University of

Sharjah, College of

Business Administration,

Sharjah, United Arab

Emirates.

Panagiotis Zervopoulos is

based at the Department of

Management, University of

Sharjah, College of

Business Administration,

Sharjah, United Arab

Emirates.

JEL classif‌ication –M40, M41

Received 15 September 2020

Revised 10 May 2021

17 June 2021

Accepted 26 July 2021

DOI 10.1108/CG-09-2020-0414 VOL. 22 NO. 1 2022, pp. 89-113, ©Emerald Publishing Limited, ISSN 1472-0701 jCORPORATE GOVERNANCE jPAGE 89

(Gordon, 2007), limited shareholder engagement, board structure (Jackson, 2010)or

compensation committees (Anand, 2006). They may also fail to address differences in firm-

specific characteristics (Bainbridge, 2002;Harris and Raviv, 2008).Subsequent regulations

such as the Dodd–Frank Wall Street Reform and Consumer Protection Act (Dodd–Frank

Act) (2010) and the New York stock exchange (NYSE/NASDAQ) (2009) listingrequirements

on executive compensation provisions and board and audit committee composition,

enhance some aspects of the SOX (2002) but more improvements are needed to avoid

corporate failure in the future.

Several previous studies have investigated the relationship between corporate governance

and firms’ valuation (Starks and Wei, 2013) and efficiency (Huang et al.,2011). However,

they provide limited evidence in single regions. They also had mixed results for several

reasons, including using single corporate governance and firm performance indicators,

applying simple models to measure firm efficiency and omitting technology heterogeneity

within and across industries. There are also concerns aboutthe accuracy of the accounting

performance measures used in previous studies, which may depend on various factors

such as demand, market growth, exchange rate and taxes and may be unsuitable for

assessing certain dysfunctional projects (Destefanis and Sena, 2007;Shabbir et al.,2020;

Shleifer and Vishny, 1986;Zhang and Ouyang, 2017). Financial accounting ratios also mix

input and output variables (Pi and Timme, 1993) and are unstable for measuring efficiency

(Maudos et al., 2002). Previous studies have only highlighted reactive corporate

governance practices, which precludes proactive improvements (El Mahdy, 2019;

Hermuningsih et al.,2020). Corporate governance also only partially explains efficiency

variations because of the absence of local institutional factors such as regulations and

social and economic conditions (Dedman and Filatotchev, 2008;Judge et al.,2008;

Shabbir et al.,2020). This paper, therefore, investigated the main internal and external

factors affecting firms’ efficiency. It establishes proactiveoptimal corporate governance risk

benchmarks, considering within-industry heterogeneity across countries. We defined

corporate governance as the “set of organisational practices aimed at monitoring and, if

needed, restraining managerial discretion” (Filatotchev and Nakajima, 2014, p. 291). Firm

technical efficiency was definedas “the ratio of the quantities of the actual output produced

and the maximum producible output from the quantity of input it has used” (Ray, 2019,

p. 422).

This paper contributes to the literature in several ways. Firstly, it evaluates firms’ technical

efficiency in the manufacturing industry and highlights the most essential firm-specific and

external institutional factors across countries. Secondly, it develops proactive optimal

corporate governance benchmarks to improve efficiency and avoid corporate crises in the

future. It will, therefore, help corporate managers, regulators and policymakers to

understand how to enhance firm efficiency and corporate governance. Thirdly, it

incorporates corporate governance risk variables as endogenous undesirable output

variables under management control. This overcomes the problem of simultaneity, which

implies that the objective is the identification of their minimal optimal levels.The optimisation

of corporate governance risk variables and other variables leads firms to efficiency.

Fourthly, it uses a novel generaliseddirectional distance function (GDDF) data envelopment

analysis (DEA) model, with the multi-parametric model for bias correction (MPBC) of

efficiency estimators. Thisnew mixed methodological approach develops optimal corporate

governance benchmarks, deals with desirable and undesirable variables, corrects the bias

of efficiencies arising from the dimensionality of the production set and yields efficiency

estimators consistent with the meta-frontier theory (Zervopoulos et al.,2019).

The empirical results show significant differences between optimal and actual firm

efficiency input/output variables and corporate governance risk mechanisms in the

manufacturing industry across countries. They show that several internal and external

factors influence firms’ efficiency such as group affiliations, product market competition,

PAGE 90 jCORPORATE GOVERNANCE jVOL. 22 NO. 1 2022