Stochastic Frontier Analysis Research Articles

Agricultural trade liberalization, governance quality, and technical efficiency in the agricultural sector of Southeast Asia

International trade has been regarded as an essential factor in enhancing a country's productivity and efficiency. Nevertheless, developing countries squander money and resources as a result of their deficient institutional quality, impeding their ability to profit from specialization and trade. Therefore, this study intends to investigate the impact of agricultural trade liberalization and governance quality on technical efficiency in Southeast Asia's agricultural sector using balanced panel data spanning from 2002 to 2021. The research utilizes translog stochastic frontier analysis (SFA) with a single-stage maximum likelihood estimation (MLE) to simultaneously calculate the time-varying technical efficiency scores and explore the core factors influencing agricultural inefficiency. The findings reveal that the average output-oriented technical efficiency for ASEAN-8 countries was 94 %. This suggests that there is significant potential to enhance technical efficiency in agricultural production by up to 6 % by addressing the adverse impacts of technical inefficiency. The research findings further point out that Malaysia is the most technically efficient country, having a technical efficiency score of 99.82 %, followed by Vietnam (99.75 %), Thailand (99.70 %), Lao PDR (98.90 %), Myanmar (95.42 %), Indonesia (91.64 %), the Philippines (90.65 %), and Cambodia (76.11 %). The results of disaggregated agricultural trade liberalization demonstrate a significant reduction in agricultural inefficiency in Southeast Asia through agricultural exports and imports. The findings also emphasize that improvements in the rule of law positively contribute to agricultural efficiency, whereas enhancements in terms of voice and accountability and regulatory quality appear to reduce it. Based on these findings, the government should consider enlarging open and liberalized trade policies in order to facilitate the exchange of technology and knowledge within the agriculture sector. Additionally, the government should involve farmers, agricultural cooperatives, local communities, and other relevant stakeholders in the decision-making process to ensure that policies address the specific needs and constraints faced by the sector.

The adoption of cotton combine services and farm technical efficiency: evidence from Kazakhstan and Uzbekistan

PurposeThis study examines the adoption of cotton combine services and its impact on farm technical efficiency in Kazakhstan and Uzbekistan. The research aims to determine whether mechanisation influences productivity and economic output at the farm level.Design/methodology/approachUsing farm-level data from 511 cotton growers in Kazakhstan and Uzbekistan collected in 2019, this study employs stochastic frontier analysis to measure potential output and technical inefficiency among cotton farmers. The analysis includes a translog functional form to account for the use of cotton combine services and other farming variables.FindingsThe findings indicate that while mechanisation through cotton combines can potentially increase technical efficiency by optimising the harvesting process, the benefits are not uniformly experienced across all farms. Variations in farm characteristics, such as labour availability and existing agricultural practices, influence the efficiency of technology adoption. Institutional factors and historical legacies also play a significant role in the adoption and impact of mechanisation.Research limitations/implicationsThe study is based on cross-sectional data from 2019, and the findings may not capture longer-term trends or recent developments in mechanisation policies in the study countries.Originality/valueThis research provides a nuanced understanding of the conditions under which cotton combine services enhance or hinder technical efficiency. It highlights the necessity for carefully tailored policies for mechanisation, especially in Uzbekistan, where rural labour is abundant and predominantly female. The study contributes to the broader discourse on agricultural mechanisation in developing countries by focusing on the specific context of Central Asia.

How Can Overinvestment in Farms Affect Their Technical Efficiency? A Case Study from Poland

Farm overinvestment is highly dangerous in how it affects productivity and profitability. Therefore, it imperatively needs to be measured in the context of investment support offered under the Common Agricultural Policy. In turn, technical efficiency is one of the best methods for measuring farm investment. This paper analyzes the technical efficiency of 3273 Polish farms based on unpublished FADN (Farm Accountancy Data Network) data from 2010–2019. The purpose of this study was to indicate the level of, and changes in, technical efficiency of Polish farms in function of their investment levels, with particular emphasis on overinvested holdings. Technical efficiency was examined using stochastic frontier analysis (SFA). The study proved a decline in technical efficiency in underinvested farms and in those affected by absolute overinvestment (i.e., ones where the assets-to-labor ratio grows while labor productivity drops).

Economies of scope in the Japanese banking industry

Economies of scope are usually considered a key factor in explaining bank diversification benefits, as joint production can help spread costs across different operations. However, previous studies have yielded little evidence of scope economies in the banking sector, which fails to explain the empirical results of diversification benefits, especially in Japan. Given that most relevant studies were conducted prior to 2000 and newer methodological approaches have emerged to enhance estimation accuracy, we refocus to this topic and explore the relationship with bank diversification. In this paper, we estimate economies of scope while considering the growing off-balance sheet activities within the Japanese banking industry. Using a sample including 120 Japanese banks from 2000 to 2020, we estimate the cost frontier with a translog cost function through the stochastic frontier analysis (SFA) approach. In addition to the traditional measures, we incorporate a new measure of scope economies proposed by Chavas and Kim (2010), allowing us to decompose the scope economies into four different effects. Our findings suggest that nearly all Japanese banks exhibit economies of scope, which may explain the diversification benefits observed in Japan. Furthermore, we find a negative relationship between economies of scope and the level of bank diversification.

Analysis of Industrial Water Use Efficiency Based on SFA–Tobit Panel Model in China

Over the past two decades, the industrial sector of China has experienced rapid development, which has correspondingly led to a significant increase in water resource consumption. To better understand the dynamics of industrial water use, and formulate appropriate water resource conservation and management policies, it is necessary to evaluate the evolution of industrial water use efficiency and its influencing factors in China. Given the high sensitivity and accuracy of the stochastic frontier analysis (SFA) model for efficiency assessment, the Tobit model is more suitable for regression analyses of truncated data. This study employed the SFA–Tobit panel model to evaluate the industrial water use efficiency of provinces in China from 2003 to 2021. The results indicate that national industrial water use efficiency improved from 0.41 to 0.65 during the study period. All provinces showed significant improvements, with developed provinces exhibiting higher industrial water use efficiency than undeveloped provinces. Regionally, the eastern areas demonstrated superior industrial water use efficiency compared to the western regions, with the central regions having the lowest overall water use efficiency. Moreover, the efficiency gap between regions has been narrowing. The national industrial water-saving potential is estimated at 31.306 billion cubic meters, with Jiangsu province having the highest saving potential at 3.709 billion cubic meters. In comparison, Beijing has the lowest at just 32,000 cubic meters. The Tobit regression results reveal that economic development and technological progress positively contribute to increased industrial water use efficiency. In contrast, water use intensity, openness, and urbanization levels negatively impacted the improvement of industrial water use efficiency. Therefore, it is necessary to increase investment in technological innovation, strictly control industrial water intensity, appropriately balance import and export trade with urbanization levels, and promote sustainable economic development. This study can provide effective support for the subsequent green transformation of China’s industry.

The Impact of Cultivated Land Fragmentation on Farmers’ Ecological Efficiency of Cultivated Land Use Based on the Moderating and Mediating Effects of the Cultivated Land Management Scale

To date, scholars have increasingly focused on the reduction in crop yields caused by cultivated land fragmentation, yet its effects on the ecological efficiency of cultivated land use are often overlooked. This oversight leads to land resource waste and environmental pollution. It is essential to explore this problem to achieve moderate-scale farming operations and promote the green transformation of agricultural land. This study theoretically analyzed the mechanisms by which cultivated land fragmentation and management scales influence the ecological efficiency of cultivated land use. Based on 2023 household data from Changde and Shaoyang, China, empirical tests were conducted using the stochastic frontier analysis method, Tobit model, and structural equation model. The research results indicate that: (1) The mean ecological efficiency of cultivated land use among the total sample households was 0.822, and the eco-efficiency in the plains was slightly lower than that in the hilly areas. (2) The scale of cultivated land management played a moderating role in the impact of cultivated land fragmentation on ecological efficiency, with differences observed between topographical types. The scale of management can offset part of the negative impact of cultivated land fragmentation on the ecological efficiency of cultivated land use. (3) Regarding the impact of cultivated land fragmentation on the ecological efficiency of cultivated land use, cultivated land management scale changes play a complete mediating role. These findings help provide policy implications to improve the ecological efficiency of cultivated land use. Policy support should be strengthened by promoting moderate-scale cultivated land operations, enhancing the comprehensive remediation of cultivated land fragmentation, and developing skilled farmers for long-term environmental sustainability.

Voluntary sustainability standards and technical efficiency of Honduran smallholder coffee producers

Sustainable coffee production promises to improve production techniques and enhance the socioeconomic conditions of smallholder farmers. Using primary survey data from 659 coffee producers in Honduras, this study assesses the impact of voluntary sustainability standards (VSS) on the technical efficiency of smallholder coffee production. The article uses the Stochastic Production Frontier Analysis model to analyze and compare the technical efficiency (TE) of certified and non-certified coffee producers. To provide reliable comparability between groups, the dataset was balanced using Covariate Balancing Propensity Score (CBPS). The results show that the mean technical efficiency was 52.86% for pooled certified farmers and 55.56% for non-certified smallholder coffee producers. Specifically, the technical efficiency of 4C farmers was 51.58%, 53.82% for the Fairtrade group, 60.56% for RA farmers, and 60.15% for the UTZ group, indicating substantial inefficiencies in the coffee production of the different certified groups. Results from Tobit’s model for the determinants of TE indicated that variables such as the age of the household head, access to credit, and training attendance are among the main factors that significantly drive the technical efficiency of certified and non-certified farmers. Based on the findings, enhancing education opportunities, improving infrastructure for better market access and farm management, and expanding credit access are recommended to improve efficiency in the study area. Honduran smallholder coffee producers have considerable potential to increase output with existing technology by improving their technical efficiency. Therefore, stakeholders’ efforts should focus on enhancing efficiency levels and capitalizing on potential gains for both certified and non-certified farmers, to ultimately improve the farmers’ livelihoods.

Resource allocation efficiency in 68 county-level traditional Chinese medicine hospitals in China: a data envelopment analysis.

Analysing and evaluating how efficiently health resources are allocated to county-level Traditional Chinese Medicine (TCM) hospitals in Zhejiang Province, this study aims to provide empirical evidence for improving operational efficiency and optimising resource allocation in these hospitals. The study employed a three-stage Data Envelopment Analysis (DEA) model to assess efficiency, using data from 68 county-level TCM hospitals. Four input and five output variables related to TCM services were selected for the analysis. The first-stage DEA results indicated that in 2022, the technical efficiency (TE) of TCM hospitals in Zhejiang Province was 0.788, the pure technical efficiency (PTE) was 0.876 and the scale efficiency (SE) was 0.903. The classification of hospitals into four groups based on the bed size showed statistically significant differences in returns to scale (p<0.001). The Stochastic Frontier Analysis regression results were significant at the 1% level across four regressions, showing that environmental variables such as per capita GDP, population density and the number of hospitals impacted efficiency. In the third stage DEA, after adjusting the input variables, the TE, PTE and SE improved to 0.809, 0.833 and 0.917, respectively. The adjusted mean TE rankings by region were West (0.860) > East (0.844) > South (0.805) > North (0.796) > Central (0.731). There is an imbalance between the inputs and outputs of county-level TCM hospitals. Each region must consider factors such as the local economy, population and medical service levels, along with the specific development characteristics of hospitals, to reasonably determine the scale of county-level TCM hospital construction. Emphasis should be placed on improving hospital management and technical capabilities, coordinating regional development, promoting the rational allocation and efficient use of TCM resources and enhancing the efficiency of resource allocation in county-level TCM hospitals.

Influence of financial inclusion and industrial robots on the efficiency of China's OFDI: A heterogeneous spatial stochastic frontier analysis

Enhancing the efficacy of China's outward foreign direct investment (COFDI) constitutes a significant avenue for realizing the sustainable development of China's economy. This study analyzes panel data from 63 countries from 2010 to 2021 to create a heterogeneous spatial stochastic frontier model to examine how financial inclusion and industrial robotics in host nations affect COFDI efficiency. The findings are as follows. To begin with, COFDI manifests positive spatial spillover effects across countries. Moreover, from a spatial perspective, financial inclusion diminishes COFDI efficiency, whereas the interaction between financial inclusion and industrial robots increases its efficiency. Industrial robots, thus, counteract the diminishing impact of financial inclusion on COFDI efficiency. Additionally, concerning the heterogeneity of location choice and investment motivation in COFDI, the interaction between financial inclusion and industrial robots in developed economies augments COFDI efficiency as opposed to emerging market economies. Conversely, technology-seeking investment mitigates the adverse effects of financial inclusion on the efficacy of COFDI when juxtaposed with resource-seeking investment. This study provides theoretical insights and practical recommendations for improving the efficiency and guiding the destination selection of COFDI.

Stochastic Frontier Analysis of the Romanian Food Industry

Stochastic Frontier Analysis of the Romanian Food Industry

Indonesian SDGS Problems: Technical Inefficiency Due to Economic Crime and Income Inequality

Objective: The study objective is investigating the technical inefficiency resulted from economic crime and its association with income inequality, with the study aims are modeling a stochastic frontier aggregate production function, measuring inefficiency, and mapping the economic inefficiency due to economic crime with income inequality association. Theoretical Framework: The main concepts are Crime Economics, Stochastic Frontier Analysis, and Aggregate Production Function. Method: The methodology comprises a stochastic frontier aggregate production function modelling to calculate technical inefficiency due to economic crime and mapping technical inefficiency due to economic crime with income inequality association. The data is Indonesian provincial data from 2016 to 2019 provided by Indonesian Statistics. Results and Discussion: The modelling reveals that aggregate production stochastic frontier is established and technical inefficiency due to economic crime is calculated. The mapping shows that some provinces experience positive association between technical inefficiency due to economic crime with income inequality. Research Implications: This study implies the importance of concerning theoritically and practically to technical inefficiency due to economic crime and its association with income inequality. These implication can encompass economic, social, and security sectors. Originality/Value: This study contributes to the literature by modeling the stochastic frontier aggregate production function that accommodates economic crime, measuring technical inefficiency due to economic crime, and mapping the technical inefficiency due to the economic crime with income inequality association. The relevance and value of this research are evidenced by SDGs components such as decent work and economic growth, reduced inequalities, and peace, justice, and strong institutions.

Enhanced methods for multicollinearity mitigation in stochastic frontier analysis estimation

Enhanced methods for multicollinearity mitigation in stochastic frontier analysis estimation

Hybrid method for benchmarking the operating costs of Brazilian energy distributors

Purpose: This study aims to propose a model for benchmarking evaluation, applied to the Brazilian regulatory system in establishing efficient operating costs for electricity distribution concessionaires. Theoretical framework: The application of data envelopment analysis to the regulation of electrical energy distribution is discussed, elucidating how different regulatory models accompany this modality. Methodology: The proposed methodology is based on a benchmarking evaluation model that integrates the associated use of Data Envelopment Analysis and Stochastic Frontier Analysis, through a methodology that establishes the evaluation of efficiency in Three Stages. Findings: The results of the performance assessment were expressed in terms of management efficiency, in which the effects of the operational environment and statistical noise are controlled, resulting in a rigorous measure of efficiency, by introducing manageable and unmanageable variables into the calculation directly from efficiency. Originality: The methodology allows to adjust operational costs, by levelling the operating environment of each electricity distribution concessionaire before repeating the DEA analysis, making the concessionaires' performance more coherent with the characteristics of the Brazilian market. Keywords: Electricity Distribution; Efficient Operating Costs; Benchmarking; Data Envelopment Analysis (DEA); Stochastic Frontier Analysis (SFA).

Consistency conditions for bank efficiency analysis in Ghana: A comparison of parametric and non-parametric techniques

This paper extends the concept of methodological crosschecking by examining whether bank efficiencies computed by the two frontier techniques, stochastic frontier analysis (SFA) and data envelopment analysis (DEA), are consistent. The study used a panel of 220 unbalanced observations from 27 Ghanaian banks between 2007 and 2016 to estimate cost and technical efficiencies and check for consistency using five criteria: efficiency distribution, ranking, ability to identify best or worst banks, stability of efficiencies, and relationship with accounting ratios. The results suggest that there is no consistency in the way parametric and non-parametric techniques rank or identify the best or worst banks. Also, there exists a weak relationship between the efficiency scores generated by both SFA and DEA and the non-frontier accounting ratios of Ghanaian banks. This suggests that the latter may contain some exogenous variables that make them weak measures of efficiency and should be used with caution, especially for bank supervision. However, the SFA approach yielded efficiency scores that were comparatively more stable over time. Therefore, the study concludes that the SFA approach is more practical and thus more appealing for regulatory purposes in Ghana due to the relatively consistent efficiency scores under the SFA approach compared to those under the DEA.

The heterogeneous impacts of climate finance on energy efficiency and renewable energy production in developing countries

Climate finance (CF) is considered to be a key financial innovation to enhance energy efficiency (EE) and facilitate the pathway to energy transition (ET). However, the varied impacts of CF on EE and renewable energy production (REP) have been masked. Thus, this study examines the heterogeneous impacts of CF on EE and REP for 81 developing countries (DCs) for the period 2002–2019. The method of moments quantile regression (MMQR) approach is used to control for distributional and unobserved individual heterogeneity. We calculate EE using parametric stochastic frontier analysis (SFA). Also, the effects of CF on EE and REP are investigated subject to income heterogeneity and based on Copenhagen (COP15) and Paris (COP21) climate accords. The findings revealed that DCs with lower REP benefit the most from increased CF, and the positive effects break down for countries with the largest distributions of REP. Besides, CF positively contributes to EE across all quantiles of DCs. The results further imply that the impacts of CF are income-dependent, with positive effects on the EE and REP of middle-income economies and more pronounced after the COP15 and COP21 climate accords. Several policy implications are forwarded based on the findings.

Stochastic Production Frontier Analysis and Technical Efficiency of Yellow Yam (Dioscorea cayenensis) Farmers in Orhiowmon Local Government Area of Edo State, Nigeria

Stochastic Production Frontier Analysis and Technical Efficiency of Yellow Yam (Dioscorea cayenensis) Farmers in Orhiowmon Local Government Area of Edo State, Nigeria

Technical Efficiency Of Rice Farming Around The Nickel Mining In Konawe Selatan District

South Konawe Regency has vast potential agricultural land, It can support the regional economy by supplying the food needs of the community and being a major player in trade across districts. In addition to providing food, the agricultural sector also serves as a market for goods produced by the industrial sector in rural communities and urban areas, a source of labor for industry, a source of capital for modern economic growth, particularly in its early stages, and a source of foreign exchange. Policy support is needed from the government in developing the agricultural sector considering the importance of synergy between the agricultural and mining sectors to minimize negative impacts in order to achieve economic balance so that it becomes the basis for local governments in taking appropriate policies to support the agricultural sector amidst mining activities. The purpose of this study is to examine lowland rice farming's technical effectiveness and production characteristics in the vicinity of South Konawe Regency's nickel mine. The data collected used primary and secondary data, with a total of 20 farmers as respondents. Stochastic Frontier Analysis (SFA) was utilized to analyze the data. The findings of the study indicate that lowland rice farming is technically efficient when it is conducted near nickel mining and that the production elements that actually affect lowland rice farming include land area, labour force, urea and NPK fertilisers, and insecticides.

Effect of Seed and Fertilizer Subsidies on the Technical Efficiency of Rice Farmers in Senegal

The aim of this study was to analyze the effect of seed and fertilizer subsidies (NPK and urea) on the technical efficiency of rice farmers in Senegal. Using data from the Annual Agricultural Survey (EAA) of the Directorate of Analysis, Forecasting and Agricultural Statistics of Senegal (DAPSA), the results of Stochastic Frontier Analysis (SFA) revealed that rice farmers in Senegal have on average a technical efficiency level of 0.545. This suggests that they could increase their current production by 45.5% while using the same level of inputs. Estimation of an SFA model for technical inefficiency revealed that seed and urea subsidies have a significant effect on reducing technical inefficiency. A farmer using subsidized seed saw a reduction in technical inefficiency level by 10.5% and using urea was associated with a 5.1% decrease in inefficiency. In contrast, the model showed no association between the use of subsidized NPK or the use of herbicides and technical inefficiency. And use of organic fertilizer was estimated to worsen technical inefficiency by 4.4% (perhaps reflecting greater reliance on lower-cost inputs among less productive farm households in Senegal). With regard to socio-demographic factors, the results further revealed older respondents experienced more severe technical inefficiency, and that women on average were 9.6% more inefficient than men. These barriers to improved efficiency among older farmers and women suggest targeted supports may be necessary alongside general subsidy programming.

How can agricultural water use efficiency be promoted in the North China Plain?

Water resources are reliable guarantees for high quality development of agriculture in the North China Plain. Improving agricultural water use efficiency is one of the essential ways to solve agricultural water resources shortage. This study measured agricultural water use efficiency (AWUE) using a stochastic frontier analysis (SFA) model and estimated agricultural water-saving potential (AWP) for 74 prefecture-level cities in the North China Plain. The main factors that influenced AWUE were further identified by developing spatial econometric models. The results showed that: (1) From 2000 to 2020, the AWUE of the study area ranged from 0.701 to 0.755 and first rose then fell, and then leveled off. (2) Spatially, the best AWUE was in the central part, followed by the north, and the worst was in the south, and nearly 65% of prefectural cities had annual average AWUE below 0.8. (3) Significant gaps in AWUE and AWP were observed in different regions. Shijiazhuang, Anyang, Hebi and Xinxiang should be considered as key targets to improve AWUE. (4) The effective irrigation degree, per sown area annual precipitation, and annual average temperature had positive effect on AWUE. Increasing the corn sowing area appropriately and reducing the input of per sown area machinery power could also improve AWUE. Therefore, adopting deep plowing measures, developing semi-arid agriculture, and advancing water-saving irrigation technology were feasible ways to improve AWUE and contribute to sustainable agriculture in the North China Plain. These findings can provide a reference for the formulation of high-water efficiency agricultural management strategies in other similar major grain-producing areas.

Comparative efficiency of Chilean water utilities: a Bayesian stochastic frontier approach

ABSTRACT Assessing the potential relationship between ownership and performance of water utilities is relevant for water regulators. Incorporating technological heterogeneity among groups of water utilities could solve any incomparability issues and lead to more appropriate policy implications. This can be done with the use of the metafrontier framework which assumes that utilities operate under different technologies. The study applies this framework to compare the efficiency of private water utilities (PWU) and concessionary water utilities (CWU) in Chile using Bayesian Stochastic Frontier Analysis (SFA) techniques. The results indicated that PWU performed better than CWU. Nevertheless, both types of water utilities presented considerable cost inefficiency. PWU and CWU should considerably reduce costs by 34% and 48% using the industry technology as a whole, respectively. The methodological approach proposed in this study could be used to compare the performance of other groups of water utilities to support the decision making of water regulators.