Exports’ effects on productivity from the view of industry heterogeneity

2018 ◽  
Vol 13 (3) ◽  
pp. 773-790 ◽  
Author(s):  
Yifan Jiao ◽  
Qing Liu ◽  
Tianzhuo Liu

Purpose The relationship between exports and productivity has always been a hot topic for scholars, but no unified conclusions have been made by theory and empirical research so far. There is no denying that the relationship between the two is important though, exploring the factors affecting the relationship can bring much more reflection and inspiration. Design/methodology/approach After using stochastic frontier analysis which includes stochastic factors to calculate total factor productivity, this paper makes regressions on the panel data of Chinese manufacturing industries from 2004 to 2013. In addition, it also tests the roles of industry heterogeneity plays in analyzing the relationships between exports and productivity. Findings It turns out that in China, exports inhibit the growth of productivity overall, and scale effect is not reflected in the export sector. From the perspective of sub-sectors, exports dampen the productivity significantly in labor-intensive industries, which may be because of low learning ability. In industries with low R&D investment, exports also have significant and negative effects on industry productivity, which is because the R&D capital is not efficient and sufficient to be converted to productivity. In industries with high foreign capital rate, exports prohibit the growth of productivity because of the existence of much processing trade. In industries with low competition pressure, exports hinder the productivity because firms in such industries are possibly not competitive enough to survive in the fierce international market. Originality/value To the best of the authors’ knowledge, previous research studies did not take the industry heterogeneity into consideration when discussing the effects of exports on productivity. In this paper, cost types, R&D investment, energy consumption efficiency, export destination, foreign investment rate, state-owned ratio, competition pressure and international competitiveness are all discussed in the analysis of export and productivity. This study provides new insights to help understand the mechanism of export and productivity and the conclusions are of rich policy implications.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kanishka Gupta ◽  
T.V. Raman

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.


2019 ◽  
Vol 15 (2) ◽  
pp. 85-91
Author(s):  
Ririn Puji Astuti ◽  
M. Syirod Saleh ◽  
Muhammad Subardin

This study aims to find out the efficiency of the administration of Palembang City, 2002 – 2016 period in building the area with and components that caused whether or not administrative expenditure of an area was efficient. This study uses data secondary data that is realization data of administrative expenditure, average employe’s expenditure, capital expenditure and local revenue. This data was tested by stochastic frontier analysis (SFA). The results of estimation from the stochastic frontier analysis (SFA) found that the administrative expenditure of the city of Palembang was inefficiency. The average variable of employee expenditure has a negative related and has a significant effect to administration costs in Palembang City. The relationship of variable capital expenditure with the administration costs of the regional government in the city of Palembang has a positive and significant effect. And the Local Revenue variables have a positive and significant effect to administration costs in Palembang City.


2016 ◽  
Vol 17 (2) ◽  
pp. 187-200 ◽  
Author(s):  
Qi HUANG ◽  
Marshall S. JIANG ◽  
Jianjun MIAO

This study aims to gain a better understanding of how effective government subsidization is in helping foster firms’ innovation. Drawing on the exploration/exploita- tion perspective and based on data collected from Statistical Yearbook on Science and Technology Activities of Industrial Enterprises, we look into the relationship between gov- ernment subsidization and Chinese firms’ innovation efficiency by applying a stochastic frontier analysis. The results show that when government subsidies are provided in small scale, firms’ innovation efficiency decreases; only when government subsidies increase to a certain scale, does firms’ innovation efficiency start to increase. We suggest that govern- ment subsidization would generate better innovation performance should it concentrate on a smaller number of firms at one time. As existing research is still inconclusive regarding the relationship between government subsidization and firms’ technological innovation output, we shed light on the issue by revealing a “U-shaped” relationship between the two.


2020 ◽  
Vol 17 (5) ◽  
pp. 669-696
Author(s):  
Pavan Khetrapal

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.


2020 ◽  
Vol 22 (2) ◽  
pp. 209-227
Author(s):  
Phong Hoang Nguyen ◽  
Duyen Thi Bich Pham

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.


2017 ◽  
Vol 29 (2) ◽  
pp. 171-182 ◽  
Author(s):  
Thanh Ngo ◽  
David Tripe

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.


2016 ◽  
Vol 28 (4) ◽  
pp. 401-410 ◽  
Author(s):  
Thanh Ngo ◽  
David Tripe

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.


Author(s):  
Saleem Shaik ◽  
Albert J. Allen ◽  
Seanicaa Edwards ◽  
James Harris

Stochastic frontier analysis, which is used to estimate technical efficiency, is extended to examine the market structure, conduct and performance hypothesis for the U.S. trucking industry. The technical efficiency measure takes into account not only the relationship between inputs used in the production of output, but it also examines the importance of market structure conduct factors to the performance of the firm. An empirical application to U.S. trucking carriers over the period 1994-2003 is examined. Results reveal that average haul, average load, debt-to-equity and market concentration significantly affected technical efficiency. Capital, fixed and variable input variables were significant in the production function equation.


2020 ◽  
Vol 47 (7) ◽  
pp. 1787-1810
Author(s):  
Kekoura Sakouvogui

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maria Molinos-Senante ◽  
Alexandros Maziotis ◽  
Ramon Sala-Garrido

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.


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