Efficiency in Vietnamese Banking: A Meta-Regression Analysis Approach

Abstract

This study explains the differences and variances in the efficiency scores of the Vietnamese banking sector retrieved from 27 studies published in refereed academic journals under the framework of meta-regression analysis. These scores are mainly based on frontier efficiency measurements, which essentially are Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) for Vietnamese banks over the period of 2007–2019. The meta-regression is estimated by using truncated regression to obtain bias-corrected scores. Our findings suggest that only the year of publication is positively correlated with efficiency, whilst the opposite is true for the data type, and sample size.

Fintech Credit and Bank Efficiency: International Evidence

“…Note that the efficiency scores of DMUs derived from the DEA approach are affected by the selection of inputs and outputs. The literature suggests that the choice of inputs and outputs is determined based on three main approaches, including the intermediation approach and production approach and the revenue (or value-added) approach (Drake et al 2006;Ho et al 2021;Le and Ngo 2020). In our study, the intermediation approach was adopted, since it is more appropriate to examine the whole banking system.…”

Predicting the performance of MSMEs: a hybrid DEA-machine learning approach

“…The role of environmental variables such as ownership, size, corporate governance, and other macroeconomic factors can also be used in a second-stage regression to explain or predict the efficiency (Boubaker et al, 2019(Boubaker et al, , 2020Le et al, 2021). Since the DEA efficiency scores are bounded between 0 and 1, most of those studies used Tobit or truncated regressions (Daraio et al, 2010;Ho et al, 2021;Ngo et al, 2019b;Pilar et al, 2018). Given the big data era, there is an increasing but limited trend of using ML with DEA as a hybrid approach for analytical purposes (Khezrimotlagh et al, 2019).…”

“…Obviously, one can train a model to estimate the impacts of the explanatory variables on the dependent variable, such as the CSW-RA-DEA efficiency scores derived from the DEA approach, following traditional econometric approaches. Since the efficiency scores are bounded between 0 and 1, it can be argued that Tobit or truncated regression is more appropriate for this second-stage DEA (Boubaker et al, 2019;Ho et al, 2021;Ngo et al, 2019b). For example, a simple search on Google Scholar on 20 November 2021 with the keywords "DEA", "efficiency", "Tobit", and "two stage" returned 6540 results; a similar search using the keywords "DEA", "efficiency", "truncated", and "two stage" resulted in 4680 results.…”

A meta‐analysis of aquaculture technical efficiency studies

“…Given that the efficiency score for each study was estimated using different production technologies, directly comparing the findings of different studies in different locations, under different time spans, and across different groups of aquaculture products is a difficult task. One possible way to address this issue is to consider each study as cross‐sectional data and to pool the samples of these studies to obtain conclusions using meta‐regression 29 . Therefore, the use of meta‐regression is timely, as it examines the correlation between the main findings (MTE as an dependent variable) and the characteristics of the studies (e.g., sample size, the number of input and output variables and frontier methods).…”

“…Some studies applying meta‐regression analysis (e.g., Ho et al 29 and Fall et al 37 ) have suggested including the impact factor of the journal () in which the study was published to reflect the different levels of quality of the publication outlet. It is commonly believed that studies published in journals with an impact factor generally have much better quality control, ensuring that the research has been conducted in a robust manner.…”