Stochastic Frontier Research Articles

Enhancing Efficiency: Halton Draws in the Generalized True Random Effects Model

This paper measures the impact of the number of Halton draws in excess of ⌈n⌉ on technical efficiency in the generalized true random effects (four-component) stochastic frontier model estimated by simulated maximum likelihood. A substantial set of Monte Carlo simulations demonstrates that increasing the number of Halton draws to ⌈n3/4⌉ (⌈n2/3⌉) decreases the mean squared error of the total technical efficiency estimates by 6.1 (4.9) percent. Furthermore, increasing the number of Halton draws either improves or has no detrimental impact on correlation, mean squared error, relative bias, and upward bias for persistent, transient, and total technical efficiency. An energy sector application is included, to demonstrate how these issues can arise in practice, and how increasing Halton draws can improve parameter and efficiency estimates in empirical work.

Regional efficiency analysis of fresh food cold chain logistics in China based on three-stage DEA model

PurposeAssessing the efficiency of fresh food cold chain logistics as accurately as possible is essential for industry development planning. This study was designed to analyze the efficiency of fresh food cold chain logistics in China.Design/methodology/approachA three-stage data envelopment analysis (DEA) model was used to analyze the efficiency of fresh food cold chain logistics in 30 provinces of China from 2013 to 2019. The stochastic frontier analysis (SFA) model in the second stage was used to eliminate the influence of external environmental factors and random disturbances on efficiency analysis results.Findings(1) The overall actual efficiency of fresh food cold chain logistics in China is unsatisfactory, with an average technical efficiency of 0.382 over the 7-year period. (2) The national average technical efficiency and average scale efficiency were overestimated by 29.9% and 40.0%, respectively, compared with the actual values. (3) The efficiency of fresh food cold chain logistics does not align with the level of regional economic development. (4) Distinct regional variations exist in the efficiency of fresh food cold chain logistics in China, with higher efficiencies observed in Northwest China and the Central Yangtze River regions, and the lowest efficiencies in the northeast regions.Originality/valueThis study applies a three-stage DEA model to assess the development and regional differences of fresh food cold chain logistics in China, enriching the application of models and empirical analysis in this field. By analyzing the situation in China, it provides ideas and references for other developing countries to develop cold chain logistics.

Climate Change Mitigation in the Dairy Sector: Uncovering Heterogeneity Through Eco‐Efficiency Clubs

ABSTRACTCombining climate change goals with economic targets is crucial for the dairy sector, which is a significant contributor to agricultural greenhouse gas (GHG) emissions worldwide. In this paper, we assess economic and climate change implications of dairy production with panel data of Irish dairy farms from 2013 to 2021. We calculate transient, persistent, and overall eco‐efficiency with respect to GHG emissions by way of stochastic frontier analysis. The innovative component of our analysis is the application of club convergence analysis to explore heterogeneity in transient eco‐efficiency development over time. This offers a nuanced understanding of farm‐level responses to climate challenges. We then explore correlations between convergence clubs and GHG mitigation technology usage. Despite high overall eco‐efficiency, our results uncover significant variability across farms, with some showing improvement and others decline in eco‐efficiency over time. We also find that changes in milk yield and specialization are positively related to better eco‐efficiency development, while GHG mitigation technologies do not play an important role. These insights suggest that the average high eco‐efficiency masks considerable underlying heterogeneity, presenting opportunities for tailored policy interventions. Our study contributes to the literature by highlighting the complex dynamics of eco‐efficiency in the dairy sector and underscoring the need for policy frameworks that account for farm‐level diversity.

Two-tier stochastic frontier analysis: heterogeneous error distributions and model selection

Two-tier stochastic frontier analysis: heterogeneous error distributions and model selection

Use Efficiency, Reduction Potential, and Effects of Fertilizers on Carbon Emissions in China’s Major Citrus Regions

Enhancing the efficiency of fertilizer utilization and advancing fertilizer reduction efforts constitutes a pivotal initiative for augmenting the quality and productivity of the citrus industry; this constitutes an indispensable prerequisite for attaining green and sustainable development. Utilizing panel data from seven prominent mandarin-producing regions and seven prominent tangerine-producing regions in China spanning from 2002 to 2022, this study employed the stochastic frontier analysis (SFA) method to develop a translog production function model for precisely measuring the fertilizer use efficiency for mandarins and tangerines. Employing the calculated optimal fertilizer use rates, we further ascertained the fertilizer reduction potential for mandarin and tangerine; then, we estimated the associated carbon emission reduction potential within these key citrus regions. The research revealed the following findings: the overall level of citrus fertilizer use efficiency in China is comparatively low, with the mean values for mandarin and tangerine fertilizer use efficiency being merely 0.4403 and 0.3887, respectively, indicating substantial room for improvement by approximately 60%; substantial potential exists for decreasing fertilizer use in China’s citrus industry, with average reduction potentials of 66.27% for mandarins and 64.83% for tangerines, signifying a notable redundancy in fertilizer application within major citrus-producing areas. The magnitude of carbon emission reduction potential through the diminution of citrus fertilizer use is tremendous. When optimal fertilizer rates are applied, the average carbon emission reductions resulting from fertilizer reduction in mandarins and tangerines amount to 815.8681 kg/hm2 and 602.3551 kg/hm2, respectively. The average carbon reduction potential for mandarins and tangerines reach levels of 55.9673% and 61.1299%, respectively, both surpassing the threshold of 55%. Significant differences exist in the technical efficiency of fertilizer input, reduction potential, and carbon emission mitigation potential among major citrus-producing regions. Citrus orchards in Guangdong exhibit higher potential for fertilizer reduction but demonstrate a relatively low level of technical efficiency. In contrast, Hunan Province shows an opposite trend, necessitating the development of region-specific strategies. Therefore, to minimize citrus fertilizer use and augment the technical efficiency of citrus fertilizer, it is imperative to comprehensively integrate and promote the “three new” technologies aimed at reducing fertilizer use and enhancing its efficiency within the citrus industry; implement a regional coordinated development strategy for citrus fertilizer reduction; and intensify policy guidance, publicity, and training efforts related to citrus fertilizer reduction, efficiency enhancement, and carbon emissions reduction.

Technical and Economic Efficiency of Production Factors in Javanese Tobacco Farming: A Case Study of Belun Village, East Java

This study analyzes the technical and economic efficiency of production factors in tobacco farming in Belun Village, Temayang Subdistrict, Bojonegoro District, East Java. Using stochastic frontier software 4.1, the analysis was conducted with a sample of 87 Javanese tobacco farmers. The production inputs evaluated include land area, seeds, urea fertilizer, NPK fertilizer, NPK Phonska Plus fertilizer, labor, pesticides, and production output. The results indicate that the gamma elasticity coefficient for technical efficiency is 0.949, with all variables being statistically significant at the 1% level (t-table 2.64), except for pesticide input, which is significant at the 5% level (t-table 1.99). In the economic efficiency analysis, seedlings were identified as the inefficient input with an efficiency estimate (EE) of > 1 (52.4), while other inputs showed EE < 1. The study concludes that 94.9% of the inefficiency stems from production factors, while 5.1% is attributed to external factors. Moreover, the inputs used in Javanese tobacco farming are neither technically nor economically efficient. To achieve full technical efficiency, farmers should reduce inputs such as land area, NPK fertilizer, and NPK Phonska Plus fertilizer, while increasing the use of seeds, pesticides, urea fertilizer, and labor.

DEA와 SFA 모형을 이용한 한국 프로야구의 비용효율성 분석

The purpose of this study is to analyze the cost efficiency of Korean professional baseball(KBO) teams through Data Envelopment Analysis(DEA) and Stochastic Frontier Analysis(SFA) and to examine its determinants.. In this study, we used 20 years of data from 2003 to 2022 for eight teams to examine the cost efficiency and its influencing factors of each team through DEA window analysis and SFA reflecting the time series. The empirical results showed that the cost efficiency of KBO teams is not high, but it is generally improving. Among them, the size of the stadium and the number of wins have a positive effect on cost efficiency, while the number of new stadiums and free agents has a negative effect on cost efficiency. In particular, the difference between the efficiency values derived from the two methods is quite large, which means that it is highly sensitive to external shocks due to the probable error. The fact that many teams react greatly to external shocks suggests that the support of parent companies and local governments greatly affects the sustainability of the teams due to the lack of self-reliance of the teams. In order to increase the self-reliance of KBO teams facing a new competitive environment after COVID-19, continuous efforts are needed to transform into solid companies, including positive external support and cooperation with local governments, as well as creating higher-quality cultural content and discovering diverse sources of revenue.

Explaining wine scores through stochastic frontier analysis. An intent to measure sensory non-observable attributes

ABSTRACT Experts give scores to wines, which are quality proxies for marketers and buyers. The production of scores proxying wine quality is explained by a set of observable objective attributes, plus another set of unobservable and subjective (sensory) features, and randomness. Is it possible to use a Stochastic Frontier Approach (SFA) to understand whether objective and subjective (sensory) characteristics of wines explain the differences in ‘producing’ wine scores? We estimate a wine quality stochastic frontier production function, using a database of 1800 top-scored wines, in 18 years-window encompassing objective determinants that largely explain the scores (price, production, year, grape, country, etcetera), being aware that sensory aspects related to wine grading are unobservable. We find that the observable variables explain part of the ‘efficiency’ in attaining scores and suggest that ‘inefficiency’ in score generation can be attributed to unobservable (sensory) variables.

Energy Price Distortions and Urban Carbon Emission Efficiency: Evidence from China’s Energy-Intensive Sectors

With a primary focus of achieving carbon neutrality, the energy-intensive industrial sectors (EIIs) contribute to more than half of China’s carbon dioxide (CO2) emissions. During the process of China’s rapid economic development, distorted energy prices gradually became the main obstacle to energy conservation and emission reductions in the EIIs. Therefore, this study focused on determining the mechanisms affecting the energy price distortions of carbon emission efficiency (CEE) in China’s EIIs. Based on a stochastic frontier analysis, the changing trend of CEE in China’s EIIs was evaluated. The channels impacting the energy price distortions of CEE were further analyzed by a mediating effect and moderated mediating effect model. The main contributions and findings include the following: energy price distortions have a significant negative impact on CEE by suppressing technological innovations and hindering the restructuring of energy consumption; governmental environmental regulatory policies mitigate their suppressing effect on technological innovations and reduce the preventing effect by improving the energy consumption structure. The results suggest that market-based price reforms and moderate environmental regulation by the government could help to improve CEE in China’s EIIs. These findings are of great significance for promoting the sustainable development of the energy-intensive industrial sectors and achieving carbon neutrality.

Measuring the time-invariant and time-varying technical efficiency of ports in Tunisia: a stochastic frontier analysis

Measuring the time-invariant and time-varying technical efficiency of ports in Tunisia: a stochastic frontier analysis

The Heterogeneous Impact of Economic and Environmental Policy Uncertainty on the Digital Economy: Fresh Evidence Based on the Bilateral Stochastic Frontier Model

The Heterogeneous Impact of Economic and Environmental Policy Uncertainty on the Digital Economy: Fresh Evidence Based on the Bilateral Stochastic Frontier Model

Efficiency and somatic cell count: Unraveling Holstein cow productivity through stochastic frontier modeling

The yield and quality decrease due to high somatic cell counts caused by mastitis, and this also negatively affects the profitability, efficiency, and sustainability of dairy farms. The main objective of this study was to investigate the effects of somatic cell counts on yield, milk chemicals, and the technical efficiency of Holstein dairy cows. A total of 165 lactating cows were involved in the research, and all cows were fed the diets as a total mixed ration three times a day. Milk samples were collected each day during milking and analyzed for chemical composition and somatic cell counts (SCC). The daily milk production of each cow was obtained from the SCR herd management program, which is integrated with the parlor. In conclusion, it was determined that for each group, the efficiency scores, SCC, and milk yield of cows varied between 0.80 and 0.99, 322.000 and 557.857 cells/mL, and 33.13 and 48.90 Kg/d, respectively; they also differed significantly in each group. Considering the findings, milk production can be increased by 7% without changing any input. Additionally, every 1% decrease in SCC will increase the efficiency of milk production by 0.55%. Cows with low technical efficiency (TE) scores produced 2.87 kg/d/cow less milk compared to animals with high TE. Reducing the SCC of the group with a low TE (456.878 cells/mL) to a SCC of high TE (438.869 cells/mL) will increase milk yield by 2.87 kg/d/cow on average. In conclusion, minimizing losses due to mastitis is paramount for enhancing dairy farm efficiency. This research underscores the interplay between TE and udder health, providing a comprehensive understanding of individual cow performance. Addressing inefficiencies and promoting udder health can significantly contribute to sustainable and economically viable dairy farming practices. Keywords: Dairy farm; Mastitis; Somatic cell count; Stochastic frontier analysis; Technical efficiency

MSME Lending And Bank Efficiency: Comparison Between Indonesia And Malaysia

MSMEs are one of the pillars of the country's economy; banking has a role in facilitating financing for MSMEs so that they can proliferate. On the other hand, banks must consider the cost efficiency they produce, considering that MSMEs are one of the sectors with high credit risk. This study aims to prove that financing for MSMEs can increase bank efficiency and that there are differences between banking in Indonesia and Malaysia. This study uses quantitative with an associative and comparative approach. The population of this study is banks listed on the Indonesia Stock Exchange and Bursa Malaysia in the 2020-2023 period. The Indonesian sample technique uses the purposive sampling method, and Malaysia uses the saturated sample method. The analysis technique uses stochastic frontier analysis (SFA), multiple linear regression, and difference tests with the help of statistical tools like Stata 17. The findings of the study show that financing for MSMEs affects bank efficiency. There is no difference between bank efficiency in Malaysia and Indonesia, but there is a significant difference between MSME financing in Malaysia and Indonesia. The theoretical implications of this study complement the theory regarding the relationship between MSME financing and bank efficiency. The practical implications of this research can provide recommendations to regulators in Indonesia to boost banking by increasing the financing ratio to MSMEs.

Resource productivity and determinants of technical efficiency among cassava farmers’ in north central, Nigeria

This research analyzed resource productivity and determinants of technical efficiency among cassava farmers in North Central, Nigeria. This research employed a multi-stage sampling technique. Primary data were used based on a well-designed questionnaire. Inferential and descriptive statistics were employed for data analysis. The results of resource productivity of inputs show that cassava cuttings and fertilizer have the highest and lowest elasticities, respectively. The mean-TE (Technical Efficiency) score of 74% (0.74) indicates that an average smallholder cassava producer in the sample needs about 26% (0.26) additional inputs to get to the frontier. In the TE components, the coefficients of labour, and fertilizers are significant different from zero at 1% probability level. The coefficients of agrochemicals, land inputs are significantly different from zero at 5% probability level, while the coefficient of cassava cuttings are significant different from zero at 10% probability level. In the TIE (technical inefficiency), component the coefficients of age, credit received, members of cooperatives are significant different from zero at 1% probability level. The policy formulations should be directed towards considering technological substitutions and mechanized agriculture. Excessive labour supply, characteristics of the developing agriculture in sub-Saharan Africa, could be pushed into the secondary sector of the Nigerian economy such as the cassava processing industry, therefore generating income, employment and maintaining Nigeria in the first (1st) position in the world ranking in term of cassava output. Also, it is recommended that improved cuttings, agrochemicals, and fertilizers should be made available to cassava farmers at appropriate time to increase productivity. Furthermore, credit should be made available to cassava farmers at a single digit interest rate, devoid of cumbersome administrative procedures. Keywords: Resource productivity, technical efficiency, cassava farmers, stochastic frontier model, Nigeria

Assessing Technical Inefficiency in Ecosystem Service Provision from an Input Perspective in the Cross Timbers region, United States.

We modeled the efficiency of ecosystem service provision-specifically timber production, carbon sequestration, and water yield-in the Cross Timbers region of the United States using stochastic frontier analysis from an input perspective. Inputs considered included natural capital and control variables such as temperature, precipitation, soil moisture, and natural disturbances, among others, that impact ecosystem service production. Inefficiency was modeled as a function of factors such as ownership, forest productivity, and natural disturbances. We utilized forest plot-level data obtained from the Forest Inventory and Analysis (FIA) program between 2008 and 2019. Our results indicated that ecosystem service production increased with higher levels of natural capital, higher temperatures, mesic soils, the presence of oaks, and damage caused by abiotic factors. We found evidence of technical inefficiency in the simultaneous provision of ecosystem services. From an input perspective, our findings revealed that, on average, 15.9% more input is used due to technical inefficiency in the Cross Timbers region. Specifically, private ownership and damage caused by abiotic factors resulted in excess input use of 16.4% and 14.3%, respectively, due to technical inefficiency. Managing the encroachment of invasive species like eastern redcedar can enhance ecosystem service production in the region, despite the high implementation costs. Collaboration among multidisciplinary extension professionals can help create comprehensive land management plans for the Cross Timbers, while landowners can also utilize cost-share programs to lower management expenses.

Assessing the Impact of Leverage Ratio on Banking Efficiency in Indonesia

This study analyzes the significance of the leverage ratio on the efficiency of banking companies with the aim of assessing the readiness and suitability of banking companies in facing the implementation of Basel 4 or Basel 3.1. Data from 47 banking companies in Indonesia from the period 2008 to 2023 were used as material for this study. The data used in the research were analyzed using the Dynamic Stochastic Frontier (DSF) method. This method allows for more accurate efficiency analysis by avoiding assumptions of technology at different times. The researchers hypothesize that banking companies with a leverage ratio level higher than the minimum limit applied in BASEL have better efficiency, and the results of this study show corresponding results within the leverage ratio limit of 20%.

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.

EFISIENSI TEKNIS DAN FAKTOR YANG MEMPENGARUHI PRODUKSI PADI LOKAL SIGUPAI DI KABUPATEN ACEH BARAT DAYA (Technical Efficiency and Factors Affecting the Production of Local Sigupai Rice in Aceh Barat Daya Regency)

Sigupai rice is highly sought after and has significant economic value. Despite its popularity, the production of Sigupai rice remains relatively low. This study aims to identify the factors influencing the production, technical efficiency, and sources of inefficiency in Sigupai rice farming in West Aceh District. Data was collected from all 31 Sigupai rice farmers in the region and analyzed using the stochastic frontier Cobb-Douglas production function. The results indicate that Sigupai rice farming has achieved a technical efficiency level of 0.80. Land area, seed quantity, and fertilizer were found to significantly influence rice production. However, farmers' age, experience in cultivating Sigupai rice, and education did not have a significant impact on technical inefficiency.To improve the efficiency of Sigupai rice farming, it is recommended to optimize input utilization, including proper land planning and soil management. Additionally, the use of certified Sigupai rice seeds and efficient fertilization techniques can contribute to increased productivity.

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).