Stochastic Frontier Analysis Approach Research Articles

Assessing Production and Marketing Efficiency of Organic Horticultural Commodities: A Stochastic Frontier Analysis

Inefficiency is a problem in the production process, including in the organic farming sector. Over a long term period, this problem can disrupt the productivity of agricultural crops. This research aims to analyze the production and marketing efficiency of organic cabbage farming in the Kopeng agropolitan area, Indonesia. We utilized a Cobb–Douglas production efficiency analysis with the Stochastic Frontier Analysis (SFA) approach. The variables in this study include organic cabbage production, land area, seedlings, organic fertilizers, organic pesticides, and labor. We conducted in-depth interviews with 60 organic cabbage farmers in Kopeng, Indonesia, from January to August 2023. The research results showed that organic cabbage cultivation was economically inefficient in production, technical, and marketing. The use of organic fertilizers, the ability to diversify products on limited land, and the use of pesticides, have not been utilized optimally yet. The results of the marketing efficiency analysis showed that it was efficient. Organic plants were believed to have their market share and to have a higher selling value than non-organic ones. The implication was that the government needed to provide training in producing organic fertilizers and pesticides to reduce production costs so that organic farming could be technically and financially efficient. This research enriched the discussion regarding the need to analyze production and marketing efficiency to find strategies to increase organic cabbage productivity.

Efficiency Assessment on Codified Knowledge Products: An SFA Approach

Knowledge applied to innovation is increasingly recognized as an explanatory factor of economic growth. Innovation derives from applying knowledge to generate new products or processes. National Innovation Systems (NIS) performs as the formal or informal network of people within institutions, interacting to produce and apply knowledge to innovation. NIS can be understood as two subsystems: one based on scientifical and technological work, producing codified products (publications and patents), and the other centered on practical actions to diffuse, apply, and use knowledge. Our objective is to assess cost efficiency in the production of codified knowledge outputs (CKO), being our unit of analysis NIS (countries). To attain our goal, we apply a Stochastic Frontier Analysis (SFA) to estimate a cost frontier of CKO. The sample is a panel that includes 1189 observations, for 23 years (1996-2019), and 82 countries. Our main results identify determinants and patterns of efficiency and productivity, tendencies, and specifics of countries and groups of them.

Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach

This study measured the level of technical efficiency (TE) that exerted a significant impact on the Malaysian electric and electronic manufacturing industry, which consists of 13 sub-industries, from 2010 to 2015. Unbalanced panel data from 1880 firms was obtained from the Department of Statistics Malaysia. We used stochastic frontier (SFA) analysis with the transcendental logarithmic approach to estimate the empirical analysis parametric. The maximum likelihood estimated regression of the SFA parameters revealed a high total average TE of 0.944%. Both the manufacturing sub-industries for communications equipment (MSIC 263) and irradiation, electromedical, and electrotherapeutic equipment (MSIC 266) demonstrated the highest average TE value and consistency (0.989%). The consumer electronics manufacturing sub-industry (MSIC 264) yielded a notably lower TE level (0.846%). Changes in TE for all industries were monitored via standard deviation analysis. The low standard deviation (SD) for MSIC 263, 271, and 275 indicated continuous progress and demands for these industries, while the higher SD for MSIC 264, 266, 272, and 273 pointed out major changes that happened within the period. The findings demonstrated that studies on the TE levels indicate that the E&E manufacturing industry has highly expended and continuous efforts to update technologies and human capital innovations. Therefore, the practical implication is to achieve Sustainable Development Goal 9 for sustainable industrialization and fostering innovation by 2030.

The Production Efficiency of Small Medium Enterprises in West Sumatera Province

The purpose of this study is to determine the effect of capital, labor, and resources on the technical efficiency production of SMEs in West Sumatra and to see whether the SMEs production in West Sumatra is technically efficient. The type of data used in this study is panel data for 19 regencies/cities in West Sumatra from 2015 to 2021 using the Stochastic Frontier Analysis (SFA) approach. This research examines production efficiency technically at SMEs in the West Sumatra region. The result of this study indicates that the production factors of capital and resources have a positive and significant effect on the production of SMEs in West Sumatra, while labor has a negative and insignificant effect on the production of SMEs in West Sumatra. The result of the technical efficiency calculation shows that the mean level of technical efficiency of the SMEs production in West Sumatra from 2015 to 2021 is 0.543 or 54.3 percent, which means that production in SMEs is technically inefficient. This research implies that the government can compile regulations and road maps that can increase the productivity of SMEs in the West Sumatra region, and for SMEs to be able to engage more broadly with sustainable programs for production efficiency such as attending training and business guidance, using the rural business credit program from the government, as well as establishing cooperation partners for raw materials with other SMEs.

How does industrial intelligence affect total-factor energy productivity? Evidence from China’s manufacturing industry

The flourishing industrial intelligence profoundly impacts manufacturing production, while empirical studies about the nexus between industrial intelligence and energy issues remain insufficient. This study evaluates total-factor energy productivity based on the stochastic frontier analysis (SFA) approach and then analyzes the energy productivity effects of industrial intelligence by employing the panel data of China’s manufacturing industry. We find that the total-factor energy productivity shows vast regional differences, and most regions have experienced a decline. Additionally, industrial intelligence significantly improves total-factor energy productivity, and the core results still hold after a set of robustness tests. Mechanism tests reveal the positive effects are mainly due to technological change and industrial structure upgrading. Heterogeneity analysis indicates that the impact of industrial intelligence is more pronounced in regions with higher economic development, more advanced information technology, and greater human capital. These findings provide insightful references for further intellectualization and carbon reduction in China’s manufacturing industry.

Impacts of internet access and use on grain productivity: evidence from Central China

The impacts of Internet use on farming productivity in China have been extensively examined. However, existing studies focus on non-grain crops and often do not distinguish between Internet access and Internet use. This study investigates the effects of both Internet access and Internet use for farming purposes on farmers’ technical efficiency (TE) using data collected from 855 grain-farmers in Central China. The TE is evaluated following a stochastic frontier analysis approach. Endogenous switching regression models are used to address the potential endogeneity issue associated with Internet access or use. Our empirical results show that the use of the Internet for obtaining farming-related information is crucial for improving farmers’ TE. Having access to the Internet itself does not necessarily improve TE. This is also true when considering the effects through the two channels of technology adoption and risk management. Furthermore, using the Internet for non-farming purposes could impede the improvement of TE. Heterogeneity analysis indicates that the Internet can help to reduce the discrepancy of TE among grain farmers.

Assessing Technical Efficiency in Malaysian Pineapple Farms: A Stochastic Frontier Analysis Approach

Pineapple cultivation proves to be a significant component of Malaysia's agricultural sector. This research was aimed at quantifying technical efficiency of Johor small-scale pineapple agriculturists. Stochastic Frontier Analysis (SFA), a statistical method used to estimate production or cost frontiers, was the preferred method for this purpose. This approach was also used to identify key elements, such as socio-economic characteristics, that influence technical implementation in pineapple farms. A total of 290 pineapple growers participated in the study, and data was collected between 2019 and 2021 during the growing season. The mean observed score of 0.681 is an indication of agriculturists non- maximum efficiency operation activity. However, the inefficiency model showed that aspects such as agricultural experience, extension visits, and participation in workshops significantly reduced inefficiency. The main problem in production points to suboptimal farming applications: agriculturists abstain from using all available agricultural inputs to achieve maximum production. The findings of the study emphasise the need for agriculturists’ proficiency refinement and upskilling in pineapple cultivation agrarian andragogy.
 Keywords: stochastic frontier analysis, technical efficiency

Management systems and productive efficiency along the certification life-cycle

Firms in the world today are pushed to demonstrate objectively that they are able to comply with increasingly stringent requirements to become part of sustainable supply chains. One of the most widely applied practice is the implementation of management systems’ certifications that contribute to increase the efficiency and competitive advantage of firms. Relying in the resource-based view of the firm, the aim of this paper is to analyze the impact of ISO 9001, ISO 14001 and OHSAS 18001 certifications on the productive efficiency of the firm. Specifically, the analysis considers three stages of the certification life-cycle: certification itself, withdrawal (decertification), and retrieval (recovery).Based on a longitudinal sample of 918 European and Asian firms from 2010 to 2019, and relying on a stochastic frontier analysis approach, this work presents empirical evidence on the effects of these certifications on firms’ productive efficiency along the certification life-cycle. Differences in countries and industries have been also found.The main findings suggest that ISO 9001 is the main driver of productive efficiency, mainly when combined with ISO 14001 as well as in the triple certification. Withdrawals and retrievals are not found to increase productive efficiency in most of the cases, probably because of the internalization of these practices. However, productive efficiency is hindered by the simultaneous withdrawal of ISO 9001+ISO 14001, whereas it is increased with the withdrawal of OHSAS 18001. Finally, the retrieval of ISO 9001 hinders productive efficiency.The main contributions of this paper are three: to analyze the impact of different combinations of certifications on productive efficiency; to study this relationship along the certification lifecycle, and to contribute to the resource-based view theory because these practices are unique resources which management allow firms to gain competitive advantage.

A meta‐analysis of aquaculture technical efficiency studies

AbstractAs the world population grows, the aquaculture sector faces challenges in the use of production systems to ensure the adequacy of the food supply. Technical efficiency analysis has been shown to be useful for improving resource management and production. This study provides a literature update and uses meta‐regression analysis to examine the variations in aquaculture mean technical efficiency (MTE) scores based on 101 studies published from 1998 to 2023. The findings show that studies with larger model dimensions, different output measures, an input‐oriented model specification and that analyse the exogenous variables of efficiency scores, freshwater aquaculture, and European data produce a narrower variance in MTE scores. In contrast, studies that use panel data and nonparametric data envelopment analysis (DEA) generate wider variance in MTE scores. As a result of these investigations, the findings suggest the importance of selecting appropriate variables and sample sizes for efficiency estimates. Robustness checks of efficiency scores from the DEA and stochastic frontier analysis (SFA) approaches are recommended for future studies. Different policies and regulations should be implemented in different countries and across different farming systems.

Cost and quality of service performance in the Chilean water industry: A comparison of stochastic approaches

The evaluation of efficiency can be of great value to water companies and regulators to adopt policies and design incentives to enhance performance. This study delves into the implications of employing distinct methodologies, namely the classical Stochastic Frontier Analysis (SFA), Bayesian SFA, and Stochastic non-parametric Envelopment of Data (StoNED), to evaluate cost and quality of service efficiency within the water industry. Chilean water companies reported average efficiencies of 0.623, 0.583, and 0.522 using the SFA, BSFA, and StoNED approaches, respectively. Furthermore, the SFA analysis suggested that the performance of water companies experienced a decline of −0.59% per year from 2010 to 2018. In contrast, the BSFA and StoNED estimations indicated an opposite trend, with annual performance improvements of 0.51% and 0.17% respectively, over the same period. These findings underscore the critical role of selecting appropriate methodologies when interpreting and comparing efficiency results for making informed long-term decisions.

Microfinance's digital transformation for sustainable inclusion

PurposeThe purpose of this paper is to evaluate the performance of Microfinance Institutions (MFIs) offering FinTech services. This study contributes to the existing literature on microfinance digitalization, financial inclusion and sustainable development. The study also takes into consideration a behavioral perspective through the efficiency evaluation process of MFIs offering FinTech services.Design/methodology/approachThe following study employs the Stochastic Frontier Analysis approach to estimate the operational and social efficiency scores of the 387 MFIs over the period 2005–2019. Then, it tries to consider factors influencing MFIs' efficiency and assess their effects. Hence, two separate models for operation and social efficiency introducing a set of factors, including FinTech proxies and overconfidence proxies, are tested. The first model for operational efficiency uses a random-effects estimator while the second one for social efficiency uses a fixed-effects estimator.FindingsThe results show that innovative MFIs have weaker averages of operational efficiency than non-innovative ones but higher averages of social efficiency. This was justified by the fact that innovative MFIs are more socially oriented. Further, findings of this study depict that the proxies of FinTech affect negatively the level of operational efficiency of MFIs. They also depict a negative relationship between FinTech proxies and the level of social efficiency. These results hold through robustness tests.Originality/valueThe highlight of this study is that it takes heed of the indirect effect of technological innovation on the efficiency of MFIs. It has been proved that it moderates the impact of managerial overconfidence (manifested by excessive risk-taking, viz., high levels of PAR30, LGR and NIM) on the level of both operational and social efficiencies.

Assessment of space heating consumption efficiency based on a household survey in the hot summer and cold winter climate zone in China

Space heating demand in the hot summer and cold winter (HSCW) climate zone in China has increased rapidly over the past decade. It poses significant challenges for China's electricity supply infrastructure and building decarbonization. This study aims to understand the relative energy efficiency of household space heating and identify potential opportunities to reduce electricity usage at the household level. A stochastic frontier analysis approach is used to quantify the energy efficiency of households' space heating by forming an efficient frontier (minimum requirement of consumption given the characteristics of the household) and by comparing all households against that frontier. The results indicate that the average household space heating efficiency is 0.69. This indicates that households in the HSCW area have the ability to reduce their heating electricity consumption by 31% while still keeping the current level of indoor thermal comfort in the winter. The level of building energy efficiency standards (BEES) is the key factor influencing the space heating savings potential. Thus, Policy choices should focus on revising and optimizing superior BEES, and accelerating energy efficiency retrofits of existing residential buildings in this region.

PERFORMANCE IMPROVEMENT OF GINGER FARMERS IN PEATLAND, KUBU RAYA DISTRICT

The economic value of ginger agricultural commodities has many advantages as a healthy way of life for the society, and this value is reflected in the productivity of ginger farming. When used, peatlands have the potential to significantly boost ginger output, which in turn can help farmers perform more effectively. In the peatlands of Kubu Raya Regency, where ginger is grown, the purpose of this study is to investigate the technical efficacy of ginger farmers and the efforts they make to improve their crops' yields. The choice of locations for the research projects was made deliberatively with consideration given to the proximity of horticulture farmer groups. This study utilized a probability sampling approach and observed 57 representative samples of the farmers who responded to the survey. The software program known as FRONTIER 4.1 is used to aid in the stochastic frontier analysis (SFA) approach of data analysis. Based on the results of the study, the t value for the variable land area was 6.71 > 2.07 and the t value for the seed variable was 5.70 > 2.07 indicating that these two variables had a considerable influence on ginger yield. This data means that the technical efficacy of ginger farmers and the efforts they make can increase ginger yields. With this, it is important for farmers to pay attention to the performance given to ginger plants planted to obtain increased income.

Estimating the propagation of both reported and undocumented COVID-19 cases in Spain: a panel data frontier approximation of epidemiological models.

We use a stochastic frontier analysis (SFA) approach to model the propagation of the COVID-19 epidemic across geographical areas. The proposed models permit reported and undocumented cases to be estimated, which is important as case counts are overwhelmingly believed to be undercounted. The models can be estimated using only epidemic-type data but are flexible enough to permit these reporting rates to vary across geographical cross-section units of observation. We provide an empirical application of our models to Spanish data corresponding to the initial months of the original outbreak of the virus in early 2020. We find remarkable rates of under-reporting that might explain why the Spanish Government took its time to implement strict mitigation strategies. We also provide insights into the effectiveness of the national and regional lockdown measures and the influence of socio-economic factors in the propagation of the virus.

Energy Demand and Energy Efficiency in Developing Countries

This paper investigates relative aggregate energy efficiency for a panel of 39 developing countries by econometrically estimating an energy-demand function (EDF) using the stochastic frontier analysis (SFA) approach to provide relative energy efficiency scores over the period 1989 to 2008. Energy efficiency is arguably difficult to define or even conceptualise with several interpretations in the literature but here it is based on an economists’ perspective of efficiency. Hence, the estimates of ‘true’ energy efficiency found in the paper using this approach approximate the economically efficient use of energy capturing both technical and allocative efficiency and the results confirm that energy intensity should not be considered as a de facto standard indicator of energy efficiency. While, by controlling for a range of socio-economic factors, the measurements of energy efficiency obtained by the analysis are deemed more appropriate and hence it is argued that this analysis should be undertaken to avoid potentially misleading advice to policy makers. This study contributes to the literature since it is, as far as is known, the first attempt to apply the benchmarking parametric stochastic frontier technique to econometrically estimate energy efficiency for a large panel of only developing counties around the world. Moreover, the results from such analysis are arguably particularly relevant in a world dominated by environmental concerns, especially in the aftermath of energy price increase as a result of the unrest in Ukraine.

Efficiency Analysis of Takaful Companies' Performance Using Stochastic Frontier Analysis Approach: A Comparison Between Southeast Asia and The Middle East Regions

This study aims to measure the efficiency of Takaful companies in Southeast Asia and the Middle East region. The efficiency level of Takaful companies in Southeast Asia and the Middle East region was examined from 2016 to 2020. The sample consisted of 23 companies in Indonesia, 14 in Malaysia, three in UEA, and 31 in Saudi Arabia. The efficiency value of Islamic insurance companies was calculated using the Stochastic Frontier Analysis (SFA) method, afterward, the Mann-Whitney test was performed. The results showed that the efficiency median value of the companies in Southeast Asia was lower compared to the Middle East with respective values of 0.26 and 0.32. It was concluded from the results of the Mann-Whitney test that the differences in the median efficiency value of Islamic insurance companies in Southeast Asia and the Middle East were not significant. The novelty of this research is to provide new and significant information on the performance of Takaful Companies during 2016-2020. The results of this study have significant implications for policymakers in each of the countries examined to understand the efficiency condition of Takaful companies in the region. Furthermore, policymakers in Southeast Asia need to promote low-efficiency Takaful operators to expand their business. The lowest efficiency score for Takaful companies is in Indonesia, especially for small Takaful companies. The implication is that the Indonesian government or related agencies need to increase the popularity of Takaful companies among the public so that income and efficiency increase.

Natural disasters and regional industrial production efficiency: evidence from pre-war Japan

ABSTRACT In this paper we investigate whether destruction due to natural disasters induces industries to increase their regional production efficiency using the case of pre-war Japan, a setting of frequent disasters and technological upgrading. To this end we compile a regional sectoral dataset of natural disaster destruction and production for machinery and textiles. We then employ a stochastic frontier analysis (SFA) approach to estimate the role of disaster events on changes in production efficiency. Our results show that earthquakes led to increases in efficiency for both machinery and textiles, although they were substantially greater for textiles due to the recovery persisting longer. Overall earthquakes contributed 6.8% of efficiency gains in textiles and 3.1% in machinery. However, allowing events to compound in their impact showed that such gains were dampened when there were damaging earthquakes in subsequent years. In contrast, for climate-related natural disaster events there is only weak, if any, evidence that these played a significant role in determining productive efficiency.

Managerial ability impact on lending and bank credit quality: SFA approach

The banking sector is one of the vital sectors in connection with its role in distributing funds to the public through lending. This makes many researchers search for variables that affect lending by banks. Still, previous studies have focused more on definitive factors and seem to ignore intangible factors such as bank managerial ability. This study examines the effect of managerial ability and bank-specific factors on bank lending and credit quality. The estimation of managerial ability uses a stochastic frontier analysis approach, while panel regression with fixed effects is used to analyze the research model. This study uses a sample of banks registered on IDX during 2010 – 2021. The results show that managerial ability significantly positively affects lending and bank credit quality. Bank-specific factors such as bank size, workforce, and capital also significantly affect lending and bank credit quality. At the same time, this study did not find the effect of deposit growth on the dependent variable of lending and bank credit quality. The results of this study have implications that banks can expand and improve credit quality by increasing the ability of bank managers.

Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach

This work analyzes the impact of energy governance on energy efficiency in a set of 29 OECD countries. A Stochastic Frontier Analysis (SFA) approach is conducted to estimate the energy efficiency levels in this sample of countries between 2000 and 2015. Energy governance is measured by an Energy Efficiency Governance Index (EEGI) constructed in Barrera-Santana et al. (2020). The results suggest that increasing the average quality of energy governance by 10% could raise energy efficiency levels by around 9.20%, according to the estimate of our preferred SFA model. To achieve this outcome there are two key requirements: set quantified and achievable targets, and carry out an extensive evaluation of the results of energy policies. Our results are robust to different econometric approaches and variations of the EEGI.

The influence of institutional quality on environmental efficiency of energy consumption in BRICS countries

It has been observed in the literature that efficient energy use reduces production cost and carbon emissions into the environment. This study further argues that institutional quality enhances environmental efficiency of energy consumption. Therefore, this study was carried out with the aim of exploring the influence of institutional quality on environmental efficiency of energy use in BRICS countries for the period from 2001 to 2020. A two-step procedure was carried out to achieve the objectives of this study. First, the environmental efficiency of energy consumption was estimated using the stochastic Frontier analysis (SFA) technique. The results of the SFA approach show that the average environmental efficiency of energy use in BRICS countries is 61%, ranging from 37.5 to 100%. Furthermore, there is 39% room for improvement in environmental efficiency of energy use in BRICS countries. Moreover, the SFA results also indicate that South Africa has the highest average environmental efficiency, and China has the lowest environmental efficiency score among BRICS countries. Second, this study employed the system GMM technique to explore the impact of institutional quality on environmental efficiency of energy consumption in BRICS countries. The results of the system GMM show that institutional quality plays a significant role in improving environmental efficiency of energy consumption in BRICS countries. Finally, this study recommends some policy measures based on the study’s findings to improve environmental efficiency of energy consumption.