Re-examining the determinants of capital structure in Nigeria

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Segun Thompson Bolarinwa ◽  
Abiodun Adewale Adegboye
Keyword(s):  
Capital Structure ◽  
Design Methodology ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Short Term ◽  
Content Type ◽  
Frontier Analysis ◽  
Speed Of Adjustment ◽  
Dea Method ◽  
Difference Gmm

PurposeThe paper investigates the determinants of capital structure and the speed of adjustment of capital structure decisions of Nigerian firms.Design/methodology/approachThe paper adopts three methods: difference GMM, system GMM and stochastic frontier analysis (SFA).FindingsThe empirical results show that firms' efficiency affects the capital structure decisions of Nigerian firms. At the same time, short-term debt has a higher speed of adjustment in the context of Nigerian firms. The roles of other control variables are established in the paper.Social implicationsNigerian firms should adopt short-term debt in order to achieve their targeted debt levels. Managers of Nigerian firms are also advised to be more efficient in order to attract higher performance.Originality/valueThe paper is the first literature to measure the efficiency of firms using SFA method. Extant studies in the literature have neglected the determinant while four papers that adopt the determinant data envelope analysis (DEA) method. This is also the first study to document the speed of adjustment in capital structure decisions in the context of Nigerian firms.

A closer look at stochastic frontier analysis in economics

2020 ◽  
Vol 4 (3) ◽  
pp. 3-28
Author(s):  
Hung T. Nguyen
Keyword(s):  
Design Methodology ◽  
Stochastic Frontier Analysis ◽  
Regression Discontinuity ◽  
Stochastic Frontier ◽  
Literature Survey ◽  
Regression Discontinuity Design ◽  
Open Problems ◽  
Content Type ◽  
Frontier Analysis ◽  
Copula Modeling

Purpose While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely, regular models, copula modeling, nonparametric estimation by Grenander’s method of sieves, empirical likelihood and causality issues in SFA using regression discontinuity design (RDD) (sharp and fuzzy RDD). The purpose of this paper is to encourage more research in these directions. Design/methodology/approach A literature survey. Findings While there are many useful applications of SFA to econometrics, there are also many important open problems. Originality/value This is the first survey of SFA in econometrics that emphasizes important issues and techniques such as copulas.

Operational efficiency of shipping companies

2020 ◽  
Vol 15 (5) ◽  
pp. 875-897
Author(s):  
Saravanan Venkadasalam ◽  
Azhar Mohamad ◽  
Imtiaz Mohammad Sifat
Keyword(s):  
Design Methodology ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Negative Relationship ◽  
The Philippines ◽  
Data Envelopment ◽  
Comprehensive Investigation ◽  
Bankruptcy Risk ◽  
Content Type ◽  
Frontier Analysis

PurposeThis paper is the first comprehensive investigation of the shipping industry's efficiency in five countries from the ASEAN region: Malaysia, Singapore, the Philippines, Thailand and Vietnam.Design/methodology/approachEmploying Data Envelopment Analysis and Stochastic Frontier Analysis, this paper compares efficiency dynamics of 45 international and offshore shipping providers engaged in fishing and ferrying.FindingsThe results indicate consistently diminishing efficiency from 2011 to 2017, a phenomenon that persists even in the traditionally efficient companies. Thereafter, this paper develops Altman Z-scores for the sampled companies and notice that despite rising inefficiency, most firms remain unencumbered by bankruptcy concerns, especially those with large capital buffers.Research limitations/implicationsIn general, this paper observes a negative relationship between bankruptcy risk and efficiency. Furthermore, the paper notices that reducing inputs does not help boost efficiency.Originality/valueIn terms of novel contributions, this paper is the first (to the best of knowledge) to set a Z-score for the ASEAN-based shipping companies.

Intellectual capital: a determinant of firms' operational efficiency

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kanishka Gupta ◽  
T.V. Raman
Keyword(s):  
Intellectual Capital ◽  
Stochastic Frontier Analysis ◽  
Stock Exchange ◽  
Stochastic Frontier ◽  
Value Added ◽  
Financial Sector ◽  
Operational Efficiency ◽  
Content Type ◽  
Frontier Analysis ◽  
The Impact

PurposeIntellectual capital (IC) has been recognized in improving the efficiency of businesses and gaining competitive edge in the developed world. The present study offers perspectives into the effect of IC on the efficiency of the Indian financial sector companies.Design/methodology/approachFor the purpose of evaluating efficiency, the research has used stochastic frontier analysis (SFA). All Indian financial sector companies listed in National Stock Exchange (NSE-500) for the timeframe of ten years (2008–2018) have been considered. The paper has employed modified Pulic's Value Added Intellectual Coefficient (VAICTM) as a proxy to measure IC. Correlation and panel data regression have been used in order to examine the relationship.FindingsThe results of the study indicate positive and significant relationship between IC and efficiency of the firm. The results also show that all the components of IC, that is, human capital, relational capital, process capital and capital employed have a significant impact on firms' efficiency. Additionally, it has been seen that sample companies do not invest in research and development leading to no innovation capital.Practical implicationsThe research will assist managers in managing and controlling the IC, investors in matters related to investment and financial experts in improving the company's IC and value creation.Originality/valueThe current research is one of the pioneering studies in the context of Indian financial sector that examines the impact of modified VAIC on operational efficiency calculated using SFA.

Performance analysis of electricity distribution sector post the implementation of electricity act 2003: empirical evidence from India

2020 ◽  
Vol 17 (5) ◽  
pp. 669-696
Author(s):  
Pavan Khetrapal
Keyword(s):  
Stochastic Frontier Analysis ◽  
Corporate Strategy ◽  
Unobserved Heterogeneity ◽  
Stochastic Frontier ◽  
Operational Efficiency ◽  
Electricity Distribution ◽  
Content Type ◽  
Frontier Analysis ◽  
Explanatory Variables ◽  
Utility Managers

PurposeThe objective of the present study is to evaluate and analyse the performance of Indian electricity distribution utilities post the implementation of landmark Electricity Act 2003.Design/methodology/approachStochastic frontier analysis (SFA) that incorporates exogenous influences on operational efficiency is adopted in the present study. Specifically, a stochastic frontier production function model with a technical inefficiency effects model (Battese and Coelli, 1995) is chosen as a preferred model. In this model, the function that explains the inefficiency scores is estimated in a single stage with the production technology. This avoids the problem of inconsistency which is possible in the two-stage approach.FindingsThe sample involved 52 Indian electricity distribution utilities for seven-year period from 2006 to 2013. Major findings of SFA show that Indian electricity distribution utilities post the implementation of Electricity Act (2003) had, on average, experienced efficiency improvement during the observed period. The overall mean technical effciency score is estimated as 78.5% which indicates that there exist wide scope for effciency improvement in the sector. Further, the empirical findings also indicate that publicly owned distribution utilities obtain average technical efficiencies of 71.3%, which is lower than privately owned distribution utilities, which achieve average technical efficiencies of 85.7%.Research limitations/implicationsPower supply quality indicators such as SAIFI, SAIDI, CAIFI, etc. and unobserved heterogeneity also influence the efficiency analysis of electricity distribution utilities. Hence, these parameters as explanatory variables can be incorporated in the future work.Practical implicationsThe results obtained from this empirical study would likely be helpful for utility managers and policymakers to know how well they are performing, and how a better corporate strategy a particular utility can formulate to improve its operational efficiency and also its position in the marketplace.Originality/valueThis paper is amongst the first significant attempts that implement SFA approach to the panel dataset over a longer period of time – 2006 to 2013, so, as to evaluate and analyse the operational efficiency of Indian electricity distribution utilities in a single framework after the enactment of Electricity Act (2003). Unlike previous studies, this study investigates the degree to which various exogenous (or environmental) factors influence efficiency levels in these utilities.

scholarly journals The cost efficiency of Vietnamese banks – the difference between DEA and SFA

2020 ◽  
Vol 22 (2) ◽  
pp. 209-227
Author(s):  
Phong Hoang Nguyen ◽  
Duyen Thi Bich Pham
Keyword(s):  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Random Noise ◽  
Stochastic Frontier ◽  
Time Consistency ◽  
Efficiency Frontier ◽  
Content Type ◽  
Frontier Analysis ◽  
The Difference ◽  
The Cost

PurposeThe paper aims to enrich previous findings for an emerging banking industry such as Vietnam, reporting the difference between the parametric and nonparametric methods when measuring cost efficiency. The purpose of the study is to assess the consistency in issuing policies to improve the cost efficiency of Vietnamese commercial banks.Design/methodology/approachThe cost efficiency of banks is assessed through the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA). Next, five tests are conducted in succession to analyze the differences in cost efficiency measured by these two methods, including the distribution, the rankings, the identification of the best and worst banks, the time consistency and the determinants of efficiency frontier. The data are collected from the annual financial statements of Vietnamese banks during 2005–2017.FindingsThe results show that the cost efficiency obtained under the SFA models is more consistent than under the DEA models. However, the DEA-based efficiency scores are more similar in ranking order and stability over time. The inconsistency in efficiency characteristics under two different methods reminds policy makers and bank administrators to compare and select the appropriate efficiency frontier measure for each stage and specific economic conditions.Originality/valueThis paper shows the need to control for heterogeneity over banking groups and time as well as for random noise and outliers when measuring the cost efficiency.

Measuring efficiency of Vietnamese banks

2017 ◽  
Vol 29 (2) ◽  
pp. 171-182 ◽  
Author(s):  
Thanh Ngo ◽  
David Tripe
Keyword(s):  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Control Variable ◽  
Banking System ◽  
Alternative Methods ◽  
Content Type ◽  
Frontier Analysis ◽  
Using Data ◽  
The Cost

Purpose This paper aims to examine alternative methods for treating nonperforming loans (NPLs) in bank cost-efficiency studies using stochastic frontier analysis (SFA). Design/methodology/approach The authors consider three methods of treating NPLs in SFA: as an additional control variable, as an environmental factor or as a deduction from total loans. Using data from the Vietnamese banking system (2003-2010), the authors then compare these results with those of the base model (where total loans is used regardless of the NPLs) to see which one is more appropriate for this study. Findings The authors observed that the first two methods are inappropriate for the analysis: one cannot find the significant relationship between NPLs and the banks’ total cost, and the other cannot account for any inefficiency at all. The authors suggested that the third method of separating NPLs from total loans can provide better insights. Using the proposed method, the authors showed that the cost-efficiency of Vietnamese banks over the period examined was moderate with a slight decreasing trend. When NPLs are separated, the cost-efficiency decreases in state-owned banks and big banks, whereas it increases in small and private banks. Research limitations/implications Research is limited to Vietnamese banks during a certain period, and it would be useful to apply the same technique to other data sets. Practical implications The paper suggests a new approach to account for NPLs in cost SFA studies in banking. Originality/value The paper provides a much more searching analysis of NPLs in banking than has generally been seen in previous research.

Stochastic cost frontier analysis – a sensitivity analysis on cost measures

2016 ◽  
Vol 28 (4) ◽  
pp. 401-410 ◽  
Author(s):  
Thanh Ngo ◽  
David Tripe
Keyword(s):  
New Zealand ◽  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Banking System ◽  
Alternative Methods ◽  
Data Sets ◽  
Content Type ◽  
Frontier Analysis ◽  
Cost Frontier

Purpose This paper aims to examine alternative methods for recording and treating costs in studies of bank efficiency. Design/methodology/approach This study used stochastic frontier analysis (SFA) models with core costs and total costs to estimate the cost efficiency of banks in two different economies, Vietnam where the banking system is under-developed (and thus is dominated by traditional banking activities) and New Zealand where the banking system is well-developed (and thus non-traditional banking activities play an important role). Findings The authors found that models using total cost tend to underestimate the banks’ cost efficiency. This underestimation relates to the extent of modern activities in a banking system: it is larger in an advanced banking system (i.e. New Zealand) and smaller in a less-developed banking system (i.e. Vietnam). Research limitations/implications Research is limited to two countries, and it would be useful to apply the same technique to other data sets. Practical implications The paper suggests a new approach to cost SFA studies in banking. Originality/value The paper provides a much more searching analysis of costs in banking than has generally been seen in previous research.

How do Spanish unlisted family firms rebalance their capital structures?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zélia Serrasqueiro ◽  
Fernanda Matias ◽  
Julio Diéguez-Soto
Keyword(s):  
Capital Structure ◽  
Transaction Costs ◽  
Family Firms ◽  
Adjustment Costs ◽  
Dynamic Panel Data ◽  
Future Research ◽  
Short Term ◽  
Content Type ◽  
Speed Of Adjustment

PurposeThis paper seeks to analyze the family firm's capital structure decisions, focusing on the speed of adjustment (SOA) as well as on the effect of distance from the target capital structure on the SOA towards target short-term and long-term debt ratios in unlisted small and medium-sized family firms.Design/methodology/approachMethodologically, we use dynamic panel data estimators to estimate the effects of distance on the speeds of adjustment towards those targets. Data for the period 2006–2014 were collected for two research sub-samples: one sub-sample with 398 family firms; the other sub-sample contains 217 non-family firms.FindingsThe results show that the deviation from the target debt ratios impacts negatively on the speeds of adjustment towards target short-term and long-term debt ratios in unlisted family firms. These results suggest that family firms, deviating from target debt ratios, face deviation costs, i.e. insolvency costs, inferior to the adjustment costs, i.e. transaction costs. Therefore, family firms stay away from the target debt ratios for a long time than do non-family firms.Research limitations/implicationsThe research sample comprises a low number of family firms, therefore for future research we suggest increasing the size of the sample of family firms to get a deeper understanding of family firms' SOA towards capital structure. Additionally, we suggest the analysis of other potential determinants of the speed of adjustment towards target capital structure.Practical implicationsThe results obtained suggest that the distance from the target short-term and long-term debt ratios can be avoided if these firms do not depend almost exclusively on internal finance to adjust towards target capital structure. Moreover, for policymakers, we suggest the creation/promotion of alternative external finance sources, allowing reduced transaction costs that contribute to a faster adjustment of small family firms towards target capital structure.Originality/valueThe most previous research focusing on capital structure decisions have focused on listed family firms. To fill this gap, this study examines the speed of adjustment towards target debt ratios in the context of unlisted family firms. Moreover, transaction costs are a function of debt maturity, therefore this study examines separately the speeds of adjustment towards target short-term and long-term debt ratios. This paper shows that the adjustment costs (i.e. transaction costs) could hold back family firms from rebalancing its capital structure.

A comparative approach of stochastic frontier analysis and data envelopment analysis estimators: evidence from banking system

2020 ◽  
Vol 47 (7) ◽  
pp. 1787-1810
Author(s):  
Kekoura Sakouvogui
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Data Envelopment ◽  
Content Type ◽  
Frontier Analysis ◽  
Efficiency Measures ◽  
Clustering Approach ◽  
Over Time

PurposeThe consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.Design/methodology/approachDue to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.FindingsThe results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.Originality/valueThis research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.

Benchmarking the economic and environmental performance of water utilities: a comparison of frontier techniques

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maria Molinos-Senante ◽  
Alexandros Maziotis ◽  
Ramon Sala-Garrido
Keyword(s):  
Stochastic Frontier Analysis ◽  
Methodological Approach ◽  
Stochastic Frontier ◽  
Assessment Method ◽  
Water Utilities ◽  
Content Type ◽  
Frontier Analysis ◽  
Efficiency Assessment ◽  
Lower Variability ◽  
The Impact

PurposeThe purpose of this paper is to estimate and compare the efficiency of several water utilities using three frontier techniques. Moreover, this study estimates the impact of several qualities of service variables on water utilities’ performance.Design/methodology/approachThe paper utilizes three frontier techniques such as data envelopment analysis (DEA), stochastic frontier analysis (SFA) and stochastic non-parametric envelopment of data (StoNED) to estimate efficiency scores.FindingsEfficiency scores for each methodological approach were different being on average, 0.745, 0.857 and 0.933 for SFA, DEA and StoNED methods, respectively. Moreover, it was evidenced that water leakage had a statistically significant impact on water utilities’ costs.Research limitations/implicationsThe choice of an adequate and robust method for benchmarking the efficiency of water utilities is very relevant for water regulators because it affects decision making process such as water tariffs and design incentives to improve the performance and quality of service of water utilities.Originality/valueThis paper evaluates and compares the performance of a sample of water utilities using three different frontier methods. It has been revealed that the choice of the efficiency assessment method matters. Unlike SFA and DEA, a lower variability was shown in the efficiency scores obtained from the StoNED method.

Sign in / Sign up

Export Citation Format

Share Document