The efficiency of public vocational institutions by DEA: case of VTACs of Batna province, Algeria

Achi, Adel

doi:10.1504/ijmie.2020.107999

Cited by 1 publication

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The statistical methods are the most used to explain the variations in efficiency. Among these methods, for example, the non-parametric tests (Ahmad and Rahman, 2012;Hacini and Dahou, 2018); the ordinary least square (OLS) regression (Goswami et al, 2019;Mansour and El Moussawi, 2020); the Tobit regression (Achi, 2020;Tandon et al, 2014); the Bootstrapped IJPPM 72,5 truncated regression (Assaf and Barros, 2011;Gulati and Kumar, 2017); and the logistic regression (Adusei, 2016;Kumar and Gulati, 2008). In regression analysis, efficiency scores computed by the DEA model is the dependent variable and the explanatory variables are the independent ones.…”

Section: Algerian Banks 1479mentioning

confidence: 99%

“…Once the efficiency scores of Algerian banks have been computed, we can further examine the effect of explanatory variables on deposit producing and revenue earning efficiencies. In fact, the difference in efficiency is not only affected by inputs consumed by DMUs but also by other explanatory variables (Achi, 2020). The estimation of PLS regression coefficients was conducted using XLSTAT 2021.3.1.…”

Section: Determinants Of Algerian Banks Efficiencymentioning

confidence: 99%

“…Among these methods, for example, the non-parametric tests (Ahmad and Rahman, 2012; Hacini and Dahou, 2018); the ordinary least square (OLS) regression (Goswami et al. , 2019; Mansour and El Moussawi, 2020); the Tobit regression (Achi, 2020; Tandon et al. , 2014); the Bootstrapped truncated regression (Assaf and Barros, 2011; Gulati and Kumar, 2017); and the logistic regression (Adusei, 2016; Kumar and Gulati, 2008).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Efficiency and its determinants in the Algerian banks: network data envelopment analysis and partial least squares regression

Achi

2021

IJPPM

Self Cite

View full text Add to dashboard Cite

PurposeThe purpose of this paper is to evaluate the efficiency of Algerian banks and examine the effects of explanatory factors on their performance.Design/methodology/approachIn this paper, a methodology of two-stage network data envelopment analysis (DEA) is used to explore the efficiency of a sample of 13 Algerian banks during the 2013–2017 period. In the first stage, the network DEA is used to assess the overall and stages efficiencies. In the second stage, the partial least squares (PLS) regression is conducted to determine the potential effects of explanatory factors on stages efficiency.FindingsThe main empirical results indicate that Algerian banks need an efficiency improvement in both stages. The overall efficiency of the Algerian banking system improves over the study period. The deposit producing efficiency is positively affected by bank size and bank age. The revenue earning efficiency is negatively associated with bank size and bank age. The domestic banks are more efficient than foreign banks in the deposit producing stage and the foreign banks are more efficient than domestic banks in the revenue earning stage.Practical implicationsThe results might be used as guidelines for both managers and policymakers in order to improve banks and banking system performance.Originality/valueTo the best of our knowledge, this study is the first that uses the DEA in investigating the efficiency of Algerian banks by dividing the overall efficiency into deposit producing and revenue earning efficiencies. Unlike most studies that have usually used OLS regression, Tobit regression and bootstrapped truncated regression, this study is the first in the bank efficiency literature that uses PLS regression to investigate the potential effect of explanatory variables on deposit producing and revenue earning efficiencies.

show abstract