Stochastic Frontier Analysis Framework Research Articles

Technical efficiency of biosecurity and animal welfare in the Taiwan egg industry

ABSTRACT Despite the pivotal role of the egg industry in the food supply chain, the absence of regular surveys over the past decades in Taiwan has resulted in a dearth of national-level data. This study endeavours to address the research void surrounding biosecurity while scrutinizing the technical efficiency of egg producers in an environment where there is no mandate to phase out battery cage systems and farmers have the autonomy to adjust their feeding strategies. We employ the stochastic frontier analysis framework to analyse farm-level data derived from a 2020 national survey of the egg industry in Taiwan, which includes 547 commercial egg farms, with 519 still utilizing battery cages and 28 farms having transitioned into alternative systems to meet higher Farm Animal Welfare standards. Our findings reveal that egg farmers who prioritize the improvement of biosecurity demonstrate greater technical efficiency. When considering the rearing systems, there is no significant difference in egg production rates between conventional and alternative systems. However, conventional systems exhibit higher efficiency in terms of total output. In essence, elevating FAW standards does not exert a discernible impact on the productivity of laying hens. Instead, farms employing conventional systems attain greater output due to their higher stocking density.

Towards energy conservation by constructing more transportation infrastructure?: An endogenous stochastic frontier analysis framework

Whether constructing more transportation infrastructure can be helpful for the achievement of energy conservation is a long-running and debatable issue. To answer this question, the relationship between transportation infrastructure and energy efficiency must first be clarified. Nonetheless, the existence of the endogeneity problem poses a challenge to defining the relationship. In this paper, an endogenous stochastic frontier analysis method is used to investigate the influence of transportation infrastructure on energy efficiency. Based on the prefecture-city level panel data in China, we find that after addressing the endogeneity problem, the impact of transportation infrastructure on energy efficiency increases dramatically. Moreover, this impact is more pronounced in small-scale cities compared to large and medium-scale cities. Regardless of the measurement of transportation infrastructure, instrumental variable, or production function form, we get the similar conclusions, demonstrating the robustness of our findings. Additional simulation analysis shows that the energy conservation potential would be 1222–2935 million kilowatt hours if the level of transportation infrastructure could be optimized. We recommend accelerating the transportation infrastructure construction, particularly in the small-scale cities so as to boost the energy efficiency and achieve energy conservation targets.

Saving energy by cleaning the air?: Endogenous energy efficiency and energy conservation potential

Estimating the impact of air quality on productivity poses significant challenges, primarily due to issues of endogeneity and the potential correlation between errors in the traditional two-step approach. This approach involves calculating productivity in the initial step and subsequently estimating the impact in the second step. To address these challenges, we employ an endogenous stochastic frontier analysis framework to identify the causal effect of air quality on energy efficiency in China. Our findings reveal a strong negative relationship between air quality and energy efficiency. A 10% increase in daily average PM2.5 concentrations results in a decrease in energy efficiency by 5%. The detrimental impact of air pollution on energy efficiency is particularly pronounced in cities characterized by outdated production technology or higher levels of market competition. Furthermore, our analysis highlights two primary mechanisms through which air pollution impedes the improvement of energy efficiency: by inhibiting innovation activities and constraining the development of the tertiary industry. Lastly, by assessing the potential improvement in air quality, we estimate a significant energy conservation potential of 1037.45–2192.79 million kilowatt-hours during the period from 2004 to 2017. On the condition that fossil energy still dominates the energy structure in current China, improved energy efficiency can lead to less emissions. The measures on reducing the air pollution can achieve much larger effects.

Regional Differences and Convergence of Technical Efficiency in China’s Marine Economy under Carbon Emission Constraints

With the continuous development of China’s marine economy and the increasing pollution in marine-related industries, how to implement a sustainable development strategy in the marine economy has become an important issue. Under the stochastic frontier analysis framework, this paper measures the technical efficiency of the marine economy in 11 coastal provinces in China under carbon emission constraints from 2006 to 2016 and analyzes regional differences and the dynamic evolution of technical efficiency and its influencing factors. Panel unit root test is applied to analyze the stochastic convergence of technical efficiency of the inter-regional marine economy. The result shows that: in the reference period, the technical efficiency of the marine economy is on the rise. Guangdong and Shanghai are in the lead. Technical level and industrial structure have a positive impact on technical efficiency, while the structure of property rights, FDI, energy prices, and energy structure have a negative effect on it. On the whole, the changes in the technical efficiency of coastal provinces present a process from concentration to differentiation. There is a stochastic convergence between the Pan-Pearl River Delta and the Yangtze River Delta. Raising the technological level, promoting low-carbon production in the marine industry, and strengthening inter-regional cooperation have a certain effect on the improvement of the technical efficiency of the marine economy.

The relative roles of domestic and foreign capital in aggregate production of GDP and CO2-equivalent emission across OECD countries.

This paper adopts a two-stage stochastic frontier analysis framework to analyse the roles of foreign and domestic capital in the aggregate production of gross domestic product (GDP) and CO2-equivalent emissions across 36 OECD countries from 1990 to 2014. The first stage estimates a quadratic output directional distance function to derive the marginal products of foreign and domestic capital with respective to GDP and emissions. The second stage examines explanations for variations in the marginal rate of technical substitution (MRTS) of foreign and domestic capital across OECD countries. Our paper finds two important empirical evidence findings on the role of foreign capital in the aggregate production of desirable and undesirable outputs. Firstly, that foreign capital appears to be more effective than domestic capital in generating GDP and curbing CO2-equivalent emissions. We find that one standard deviation of GDP (or $2333 billion in 2011 dollars) would require $1857 billion (in 2011 dollars) of foreign capital in comparison with $4867 billion of domestic capital, ceteris paribus. On the other hand, the reduction of CO2-equivalent emissions by one standard deviation would demand $4091 billion (in 2011 dollars) of foreign capital relative to $16,539 billion of domestic capital. Second, foreign capital is more effective in reducing emissions in countries characterised by higher GDP per capita, larger population density, and higher shares of manufacturing sectors and exports.

Modeling Spatial Interaction in Stochastic Frontier Analysis

We compare farm level efficiency rankings derived from non-spatial and a variety of spatial model specifications that account for unobserved heterogeneity in both the production and the efficiency sides of the stochastic frontier model in an empirical application on rice farming in the Philippines. We show how not accounting for unobserved spatial heterogeneity affects efficiency estimates and farm efficiency rankings. When not accounting for unobserved spatial heterogeneity efficiency, models show farms to be relatively more inefficient than they actually are (i.e., once unobserved spatial heterogeneity is incorporated in the models). More importantly from a policy perspective, the rankings of the farms in terms of efficiency are altered once unobserved spatial heterogeneity is incorporated in efficiency models. We recommend the use of unobserved effects in both production and efficiency within the stochastic frontier analysis framework to avoid making any misleading recommendations to farmers and policymakers.

Input-output efficiency of environmental protection enterprises and its influencing factors: An empirical analysis of 279 listed enterprises in China

The high quality of the environmental protection industry (EPI) plays an important role in China’s economic transformation. However, to date, no studies have conducted a comprehensive exploration of the factors that affect the input-output efficiency (IOE) of environmental protection enterprises (EPEs). Accordingly, this research uses the 2014 to 2018 unbalanced panel data of China’s EPEs listed on the Shanghai and Shenzhen Stock Exchanges and on the New Third Board as the research sample to measure the IOE of these enterprises under the framework of stochastic frontier analysis (SFA). This research also comprehensively examines various factors that affect efficiency. We found the following. (1) Although the improvement of the IOE of China’s EPEs superimposes the characteristics of market-driven and policy-driven efficiency drivers, there is negative feedback on fund-driven drivers. (2) The development of China’s EPI exhibits the characteristics of a blue ocean market, but efficiency enhancement must rely more on benign scale expansion and improvements in operations and management while simultaneously avoiding low-quality expansion. (3) As different types of influencing factors have obvious heterogeneous effects at the ownership, regional and segmented industry levels, to promote the improvement of the IOE of China’s EPEs, it is necessary to build a differentiated policy support system and assess its regulations and role in market leadership. At the same time, it is necessary to strengthen the supervision and control of blind expansion and increased leverage in certain areas.

Non-structural and structural models in productivity analysis: study of the British Isles during the 2007–2009 financial crisis

The paper compares unrestricted and restricted reduced-form estimates of productivity and efficiency performance constructed from non-structural stochastic frontier analysis (SFA) and the structural models of Olley–Pakes (OP), Ackerberg–Caves–Frazer (ACF), Pakes–McGuire (PM), and Midrigan–Xu (MX). These methods are used to estimate changes in firm-level manufacturing productivity in the British Isles before and after the 2007–2009 financial crisis using the Financial Analysis Made Easy (FAME) data set over the period 2005–2012. The empirical results indicate that overall technical efficiency was not impacted to any substantial degree by the financial crisis, according to all models. The empirical results also indicate substantial agreement in the predictions of productivity growth for the three models. The SFA framework (and related DEA approaches) is used internationally to set tariffs in regulated industries. To have SFA, and the OP/ACF/PM/MX models that are more highly leveraged on economic optimizing assumptions, provide comparable estimates of productivity and efficiency change is reassuring. However, it also would suggest that structural approaches may not provide regulators much new information about efficiency and productivity than would less structural approaches such as SFA, while being less transparent and more difficult to justify to regulators as well as to the courts to which regulated firms often turn for relief from tariffs they perceive to be unfair or onerous.

Shadow Banking, Bank Ownership, and Bank Efficiency in China

ABSTRACT This study uses 15 years of bank data and a one-stage stochastic frontier analysis framework to examine how shadow banking affects the profit and cost efficiency of Chinese banks. Our results indicate that shadow banking is negatively related to both profit and cost efficiency and positively related to earnings volatility, credit risk and liquidity risk of the Chinese banks. In examining the performance of foreign banks with that of local Chinese city commercial banks, we find that foreign banks in China are less profit- and cost-efficient, supporting the home-field-advantage hypothesis that domestic banks are more efficient than foreign banks.

Should Smallholder Farming In China Be Discouraged? Panel Evidence from Anhui Province

New agricultural management entities have appeared and been encouraged by the government in the People's Republic of China (PRC) in recent years. Mainstream opinion has stressed the need to take action to overcome the perceived inefficient, small-scale, subsistence smallholder economy that rejects the market economy, has no specialized labor and a low level of technology. However, the question as to whether smallholders are inefficient remains to be substantiated. Smallholder farming households play an important role in the agricultural community in PRC. We believe that smallholder farmers are not representative of inefficient agricultural producers. The smallholder business model, not only shows its tenacious vitality and regenerative ability, but it also plays an important role in the economic and political culture of the nation. We adopt the stochastic frontier analysis framework, which accounts for random errors in the production function, together with technical inefficiency effects that are associated with different management capabilities, to analyze the technical efficiency of smallholder farming households and the impact of their household endowments on technical efficiency of crop production in China. The data used in this paper are from the annual statistical surveys of 17 village-level, fixed-observation points in Anhui province from 2011 to 2014, collected by the Ministry of Agriculture. The sample smallholder farming households considered in this paper have typical significance in terms of both location and economic significance. Using these panel data, we avoid the loss of volatility of variables but utilize the dynamic characteristics of technical inefficiency changes. There is evidence that smallholder farming households are performing quite well, contrary to the findings of previous studies. The level of education, technical training, incidence of a cadre in the extended family, and nonfarm incomes have positive and significant impacts on the technical efficiencies of smallholder farming households. However, with the aging of smallholder farming households, increases in loans, increases in total farmland area and greater fragmentation of farmland, the crop production of smallholder farming households tended to be more technically inefficient. From the results of the empirical analysis, we suggest that the government increase investment in agricultural training and rural education, select and train more high-quality village cadres and encourage them to continue to assist in agricultural production of smallholder farming households, establish a unified urban-rural labor market, improve the rural financial credit mechanism so that rural financial institutions will not release loans arbitrarily, and make reasonable arrangements for land development projects.

Impact of factor price distortions on energy efficiency: Evidence from provincial-level panel data in China

The marketization of energy price is not only an important part of factor pricing reforms but also decisive for energy efficiency improvement. Thus, this study aims to measure factor price distortions and estimate their impact on energy efficiency based on an empirical analysis of 30 provinces of China during 2004–2013 using the stochastic frontier analysis framework. Results yielded three important findings: (1) Technical efficiency was the highest in eastern China, which still remains low at around 0.7980, followed by central China and western China, and there were growing gaps among the above areas. (2) Capital price was relatively high while energy price was relatively low compared with labor price, and the relative allocative efficiency of energy got worse over time. (3) Energy efficiency loss among the three regions showed convergence trends. Policy implications are summarized as follows: (1) Measures such as adjusting energy consumption structure and improving production technology and management levels can reverse the trend of declining technical efficiency. (2) The process of energy price marketization needs to be accelerated. (3) It is necessary to expand the depth and breadth of regional technology diffusion and break the barriers of technology transfer among regions in China.

Measuring sustainable intensification: Combining composite indicators and efficiency analysis to account for positive externalities in cereal production

We combine the use of a stochastic frontier analysis framework and composite indicators for farm provision of environmental goods to obtain a farm level composite indicator reflecting sustainable intensification. The novel sustainable intensification composite indicator that is developed accounts for multidimensional market and non-market outputs, namely the economic performance of cereal farms (i.e. market production value) and the associated positive environmental impacts of production (e.g. positive environmental externalities). The composite indicator integrates three different indicators for the provision of environmental goods into a stochastic frontier analysis: a) agri-environmental payments; b) the ratio of rough grassland and permanent pasture area to total utilised agricultural area; and c) land use diversity, as measured by the Shannon Index. We apply this approach to a panel of data for 106 cereal farms in England and Wales during the period 2010–2012. Results indicate that farm rankings on the indicator vary substantially depending on the weight given to the different environmental aspects/indicators, suggesting that single indicators of the provision of environmental goods may not provide a true reflection of the environmental performance of farms. We illustrate a simple approach that captures the aspects of sustainable intensification of farms in a much more holistic way, i.e. by producing a distribution of sustainable intensification scores for each farm reflecting different weightings of evaluation criteria. To reduce the dimensionality of this distribution farms are classified into four distinct groups according to the shape of this distribution, with some farms found to perform well under all combinations of weights for evaluation criteria, while others always perform poorly. This distribution-based analysis provides a greater depth of information than traditional approaches based on the generation of a single sustainable intensification score.

Do climate change adaptation practices improve technical efficiency of smallholder farmers? Evidence from Nepal

This paper provides one of the first empirical studies that examine the impact of climate change adaptation practices on technical efficiency (TE) among smallholder farmers in Nepal. An adaptation index is used to explore the impact of farmers’ adaptation on TE using the stochastic frontier analysis framework. Data for six districts of Nepal representing all three agro-ecological regions (terai, hill, and mountain) were collected from a focus group discussion, a stakeholder workshop and a household survey. The survey shows that about 91% of the farming households have adopted at least one practice to minimize the adverse impacts of climate change. Empirical results reveal that adaptation is an important factor explaining efficiency differentials among farming households. Those adopting a greater number of adaptation practices on a larger scale are, on average, found to be 13% more technically efficient than those adopting fewer practices on smaller scale. The empirical results also show that average TE is only 0.72, indicating that there are opportunities for farming households in Nepal to further improve productive efficiency, on average by 28%. Other important factors that explain variations in the productive efficiency across farming households include farmer’s education level, irrigation facilities, market access, and social capital such as farmer’s participations in relevant agricultural organizations and clubs. This study provides empirical evidence to policy makers that small scale adjustments made by farmers in response to climate change impacts are effective in improving farmers’ efficiency in agriculture production. This indicates a need for farmers’ involvement in climate change adaptation planning.

Efficiency ranking method using SFA and TOPSIS (ERM-ST): case of Indian banks

PurposeThe purpose of this paper is to propose a performance evaluation framework using an integrated approach of stochastic frontier analysis (SFA) and technique of order preference with similarity to ideal solution (TOPSIS) called efficiency ranking method using SFA and TOPSIS (ERM-ST) specifically in the banking sector where service excellence is of prime importance for business growth.Design/methodology/approachThe proposed approach ERM-ST measures the performance of a DMU in the SFA framework by considering multiple outputs and multiple inputs. It is a non-parametric tool which does not need any prior model assumptions which enhances its applicability in real-life business scenarios. Moreover, the efficiency score obtained using the proposed model ERM-ST lies between 0 and 1, unlike in case of super efficiency data envelopment analysis (DEA) which may go well above 1.FindingsThe proposed framework is evaluated for its applicability using two various data sets and is further used to evaluate the performance of a group of 26 public sector banks in India. The results obtained by the proposed method ERM-ST are compared with those obtained by super efficiency DEA using Friedman’s test.Originality/valueThe proposed approach ERM-ST is developed to evaluate the performance of a service unit with multiple outputs and multiple inputs in the SFA framework.

Technical efficiency with multi-output, heterogeneous production: a latent class, distance function model of english football

This study combines the output distance function approach with a latent class model to estimate technical efficiency in English football in the presence of productive heterogeneity within a stochastic frontier analysis framework. The distance function approach allows the researcher to estimate technical efficiency including both on-field and off-field production, which is important in the case of English football where clubs are generally thought to maximize something other than profit. On-field production is measured using total league points, and off-field production is measured using total revenue. The data set consists of 2177 club-level observations on 88 clubs that competed in the four divisions of professional football in England over the 29-season period from 1981/82 to 2009/10. The results show evidence of three separate productivity classes in English football. As might be expected, technical efficiency estimated using the latent class model is, on average, higher than technical efficiency using an alternative method which confines heterogeneity to the intercept coefficient. Specifically, average efficiency for the sample is 87.3 and 93.2% for the random-intercept model and the latent class model respectively.

Sand dredging and environmental efficiency of artisanal fishermen in Lagos state, Nigeria.

Environmentally detrimental input (water turbidity) and conventional production inputs were considered within the framework of stochastic frontier analysis to estimate technical and environmental efficiencies of fishermen in sand dredging and non-dredging areas. Environmental efficiency was low among fishermen in the sand dredging areas. Educational status and experience in fishing and sand dredging were the factors influencing environmental efficiency in the sand dredging areas. Average quantity of fish caught per labour- hour was higher among fishermen in the non-dredging areas. Fishermen in the fishing community around the dredging areas travelled long distance in order to reduce the negative effect of sand dredging on their fishing activity. The study affirmed large household size among fishermen. The need to regulate the activities of sand dredgers by restricting license for sand dredging to non-fishing communities as well as intensifying family planning campaign in fishing communities to reduce the negative effect of high household size on fishing is imperative for the sustainability of artisanal fishing.

Does modernization improve performance: evidence from Indian police

This paper aims to measure the role of police modernization scheme in its performance in crime repression. We use output distance function as an analytical tool and estimate it using stochastic frontier analysis framework in a ‘single stage’. We find that the police modernization scheme is helping the state police departments in enhancing their performance, i.e., the police departments which have more modern communication equipments and which are spending more money on the training of their police personnel are doing better. The police density is found to be one of the major determinants of its efficiency along with the factors that creates more social cohesion. The total factor productivity is governed by the catch-up effect which is worsening over time though the technological progress has been observed in most of the states.

Effects of substituting energy with capital on China's aggregated energy and environmental efficiency

Substituting energy with capital (SEC) in economic productions has become a common practice both for business owners and policy-makers to improve their energy and environmental efficiency. However, seldom previous studies on energy efficiency and/or environmental performance evaluation took this role into account. This paper aims to shed some light on the effects of SEC on China's aggregated energy and environmental efficiency (AEEE) within a parametric stochastic frontier analysis framework. Moreover, influencing factors of regional efficiency score are also discussed using a pooled regression model. The results indicate that SEC poses significant effects on improving China's AEEE, and this impact appears obvious regional variation that regions with lower efficiency scores hold more extensive potential to improve their AEEE by means of SEC. Furthermore, upgrading industrial structure and decreasing the proportion of coal in energy consumption make great sense to improve China's AEEE.

Measuring consumption efficiency with utility theory and stochastic frontier analysis

The concept of production efficiency has been studied since the 1960s, but consumption activity as well may be inefficient for various reasons, such as product complexity, lack of information, the bounded rationality of the consumer and imperfect markets, to name a few. This study proposes a conceptual framework for measuring the consumption efficiency of differentiated products, based on traditional utility theory. It employs stochastic frontier analysis (SFA) in an empirical analysis. It makes use of hedonic price theory to link traditional utility theory and the SFA framework. When the developed model is applied to the Korean personal computer market, empirical results indicate the levels and distribution of consumption efficiency in that market. The findings afford us a better understanding of the characteristics of the innovation process in that market.

Access to credit, plot size and cost inefficiency among smallholder tobacco cultivators in Malawi

AbstractUsing data from the Malawi Financial Markets and Household Food Security Survey, this paper examines the effect of access to credit from formal sources, and tobacco plot size, on cost inefficiency among Malawian smallholder tobacco cultivators. Farm‐specific cost inefficiency is estimated within the framework of stochastic frontier analysis. Access to credit is measured as the sum of household members' self‐reported credit limits at credit organisations, arguably a truer measure of an exogenous credit constraint than credit program participation or actual loan uptake. It is found that tobacco cultivation is significantly less cost inefficient per acre on larger plots. While access to credit by itself has no statistically discernible effect on cost inefficiency, it reduces the gain in cost efficiency from a larger plot size.