This paper aims to investigate the internal and external determinants of firms’ efficiency and develop optimal corporate governance risk benchmarks for the manufacturing sector across different countries.
Corporate governance risk data were acquired from Institutional Shareholder Services Europe SA. Data on firms’ efficiency and for explanatory and control variables 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 corporate governance benchmarks. The authors used ordinary least squares multiple regression analysis with wild bootstrapping to test the study hypotheses.
The authors found significant differences between firms’ optimal and actual efficiency input/output variables and corporate governance risks in the manufacturing sector across countries. 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 enforcement and cultural values are vital determinants of firms’ efficiency.
This paper provides valuable guidance to enable corporate managers, regulators and policymakers to enhance firms’ efficiency and corporate governance practices.
This paper develops optimal corporate 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 correction of efficiency estimator.
