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Critics opine that full expensing of research and development (R&D) depresses near-term profits and incentivizes myopic managers to under-invest in R&D, compromising firm efficiency. Advocates of the expensing rule argue that little rigorous research evidence supports the claimed adverse consequences. We examine the impact of the R&D expensing rule on firm efficiency by exploiting an exogenous shock: a shift in the accounting regime in Germany from full expensing to partial capitalization of R&D when it mandated International Financial Reporting Standard (IFRS) adoption in 2005. We employ Stochastic Frontier Analysis and Data Envelopment Analysis to estimate efficiency for the same German firms before and after the IFRS adoption. We find robust evidence of efficiency improvement in the post-period relative to the pre-period for German R&D firms that report R&D expenditures, and for both early adopters and timely adopters. We also document that financially constrained firms and firms experiencing rapid R&D growth prior to the IFRS adoption show greater efficiency improvement. Moreover, we conduct three falsification tests to make sure our results are not attributable to other accounting changes associated with the IFRS adoption, and find no efficiency improvement for the three control groups (German "no-R&D" sample, U.K. firms, and Australian firms), respectively. We conclude that the change in the R&D reporting rule is the likely catalyst for improvements in efficiency of German R&D firms. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Association of Southeast Asian Nations (ASEAN) heavily relies on fossil fuels to drive economic growth, making it one of the world's largest greenhouse gas emitters. Promoting energy efficiency has been proposed as a solution to mitigate this issue. However, the potential negative impact of energy efficiency on economic growth remains unclear. Therefore, this study aims to re‐evaluate the dynamic impact of overall energy efficiency on economic growth in ASEAN countries, considering climate change factors. Unlike prior studies, this research measures overall efficiency based on both persistent and transient components of energy efficiency. This study employs two key techniques: stochastic frontier analysis (SFA) to estimate the overall energy efficiency and panel vector autoregression (PVAR) to analyze the dynamic causal effects of determinants' shocks. The findings suggest that enhancing ASEAN's overall energy efficiency could result in an 85.9% reduction in total energy consumption, indicating high levels of inefficiency in the region. While extensive energy efficiency measures might induce a temporary economic contraction in ASEAN countries, the rate of decline seems to abate over the long term. This implies that the impact of the energy efficiency shock will be most prominent during initial growth stages, progressively waning over time. Additionally, this study confirms the presence of the Environmental Kuznets Curve (EKC) for climate change and economic growth. [ABSTRACT FROM AUTHOR]

Innovation is a key driver of productivity growth. This paper proposes a novel methodology in order to explore the impact of farm-level innovations on farm productivity and its components (i.e. technology, efficiency and scale) using representative data from Irish dairy farms. We measure innovation by an index based on employed production practices, continuous innovation activity and knowledge weighted by expert opinions. The results suggest that more innovative Irish dairy farmers are more productive. Specifically, all farmers improve their production technology and efficiency through their use of innovations, but farmers at specific levels of innovativeness may experience a decrease in productivity due to the small scale at which they operate. This indicates that innovation has a non-linear effect on productivity. We discuss the policy implications for reducing the unequal gains of innovation across farmers. [ABSTRACT FROM AUTHOR]

We measure the cost of technical inefficiency for local electricity distribution firms in Sweden using Stochastic Frontier Analysis, and explore how small-scale generation, the number of electric vehicles and the introduction of dynamic pricing schemes affects the transient inefficiency and efficiency scores. Our results show little to no effect of these environmental variables on the cost of technical inefficiency of electricity distribution grids in Sweden. [ABSTRACT FROM AUTHOR]

To investigate the impact of smart city construction (SCC) on destination tourism efficiency (TE), this study analyzed the impact paths and mechanisms of SCC on destination TE from 3 aspects: technological innovation, informatization, and industrial structure upgrading. Based on panel data of Chinese prefecture-level cities from 2004–2019, we combined a stochastic frontier analysis model with a difference-in-differences model to conduct an empirical analysis to assess the policy effects of SCC on destination TE and validate the impact paths and mechanisms. The results show that the tourism of 153 sample cities show a low TE level overall, an increasing trend year by year, a distribution pattern of high in the east, and low in the middle and west. SCC can significantly improve destination TE, and the impact of SCC on destination TE has spatially heterogeneous. [ABSTRACT FROM AUTHOR]

Optimizing resource efficiency and mitigating climate change have become consensuses of human society. However, there is still a gap in assessing the carbon emission efficiency (CEE) and identifying the influence of various factors, especially in rapid urbanizing regions. In this paper, we built a stochastic frontier analysis model to assess CEE and conducted a case study in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA), a typical area of collaborative development in China. A comprehensive influencing factor index was constructed to analyze and identify the key influencing factors of CEE. The results revealed that the average CEE among the 13 cities increased in volatility from 2000 to 2019. The average CEE in Langfang was lowest, while that in Tangshan was highest. The input-related factors had a negative effect on CEE, including carbon emissions per capita, employment per ten thousand people, total assets per capita, and energy intensity. GDP per capita, the urbanization level, and the proportion of the tertiary sector's GDP had positive impacts on CEE. Future policy formulation should focus on the transition from labor- and material-intensive industries to knowledge- and technology-intensive industries. All the results can contribute to achieving high-quality development and dual-carbon target of rapid-urbanizing areas. [ABSTRACT FROM AUTHOR]

Introduction: The unique characteristics of pineapples as a perennial plant, which guarantee their quick proliferation and adoption in both the tropics and subtropics, readily justify their economic significance. Although pineapple is a popular tropical fruit among Bangladeshi citizens, they continue to produce fewer pineapples than other international producers with limited export offerings. Hence, the study aimed to estimate the technological efficiency, prospects, and policies of pineapple growers in the northeastern district of Bangladesh. Methods: One hundred respondent growers were surveyed directly to gather cross-sectional data using a multistage sampling technique. The technical efficiency scores of individual farms were calculated using the stochastic frontier model with the technical inefficiency model for identifying factors responsible for inefficiency. Results: The technical efficiency scores range from about two-thirds to the absolute efficiency level, with a mean technical efficiency above the ninety percent level. The technical inefficiency effect model interpreted that farmers' age and education had a significant positive impact, whereas credit, training, and family size had a significant negative impact on inefficiency. Discussion: Findings indicated that sampled farmers may use inputs more efficiently and raise their yield by nearly one-twentieth. Therefore, the study suggests that the government should concentrate on strategies to attract young growers, as they are more capable of managing resources effectively and willing to accept technological breakthroughs. The study's conclusions have significant policy ramifications specifically in the areas of finance, education and skills, and rural development that the Government should consider to increase farmer's productivity and overcome various challenges while upholding national interests and ensuring the farming sector's continued prosperity. To commercialize pineapple production and establish Bangladesh as a prominent production zone, more research and development are needed. [ABSTRACT FROM AUTHOR]

There is an increasing emphasis on creating healthier living spaces and improving quality of life, making the planning and establishment of healthy cities a pivotal policy and a developmental goal worldwide. This study adopted WHO-recommended indicators for healthy cities and employed stochastic frontier analysis to estimate the correlation between influencing factors and efficiency in developing healthy cities across 22 counties and cities in Taiwan from 2001 to 2022. This study yielded several key findings: (1) there was significant room for improvement in the development of healthy cities in Taiwan; (2) western metropolitan areas demonstrated higher efficiency compared to eastern counties, cities, and outlying islands; and (3) key indicators of a healthy city included nursing manpower, air quality, employment rates, income levels, and the availability of kindergartens. Developing healthy cities requires integrating various factors including policy, environmental conditions, societal aspects, and economic considerations. Collaboration between the public and private sectors is essential for fostering sustainable, healthy cities. [ABSTRACT FROM AUTHOR]

This article is the first in the literature to discuss in detail how to conduct various types of inference in the stochastic frontier model when it is estimated using nonparametric methods. We discuss a general and versatile inferential technique that allows for a range of practical hypotheses of interest to be tested. We also discuss several challenges that currently exist in this framework in an effort to alert researchers to potential pitfalls. Namely, it appears that when one wishes to estimate a stochastic frontier in a fully nonparametric framework, separability between inputs and determinants of inefficiency is an essential ingredient for the correct empirical size of a test. We showcase the performance of the test with a variety of Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

With increasing pressures on big businesses to expand performance objectives beyond financial metrics and to include social and environmental objectives, business organizations experience rising tension in balancing these various objectives. Oftentimes, subjective narratives can weigh in on the relative importance of competing objectives. This subjectivity is a contributing factor to findings of inconsistent and mixed results for the financial impact of an organization's environmental performance in the prior literature. Our research effort seeks to provide a positivist perspective on the relationship between environmental performance and financial performance of companies. Also, given the importance of efficient operations for corporate success, we examine the influence of operational productivity on the environmental and financial performance relationship. Using a global dataset compiled from reputable sources, including 1738 unique firms spanning between the years 2011 and 2020, we find statistically significant results that indicate that lower carbon emissions are associated with higher profitability when a firm has competitively high operational productivity. Companies with operational productivity that is competitively low do not perform well financially when carbon emissions are low. Thus, our study fills a research gap in this domain by relying exclusively on a broad set of purely objective data and illuminating the importance of operational efficiency on the relationship between the environmental performance and financial performance of firms. [ABSTRACT FROM AUTHOR]

In this paper, we incorporate spatial analysis to estimate industry-level productivity in the presence of inter-sectoral linkages. Since each industry plays a role in providing intermediate goods to other sectors, the interdependence of economic activities across industries is inevitable. We exploit the linkage patterns from the input-output relationship to define cross-industry dependencies in economic space. We propose a spatial stochastic frontier model, which extends the stochastic frontier model to a spatially dependent specification. The models are estimated using quasi-maximum likelihood methods. Applying the approach to U.S. industry-level data from 1947 to 2010, we find that sectoral dependencies are the consequences of indirect effects via the supply chain network of industries resulting in larger output elasticities as well as scale effects for the networked production processes. However, productivity growth is estimated comparably across different spatial and non-spatial model specifications. [ABSTRACT FROM AUTHOR]

Fixed-effects modeling has become the method of choice in several panel data settings, including models for stochastic frontier analysis. A notable instance of stochastic frontier panel data models is the true fixed-effects model, which allows disentangling unit heterogeneity from efficiency evaluations. While such a model is theoretically appealing, its estimation is hampered by incidental parameters. This note proposes a simple and rather general estimation approach where the unit-specific intercepts are integrated out of the likelihood function. We apply the theory of composite group families to the model of interest and demonstrate that the resulting integrated likelihood is a marginal likelihood with desirable inferential properties. The derivation of the result is provided in full, along with some connections with the existing literature and computational details. The method is illustrated for three notable models, given by the normal-half normal model, the heteroscedastic exponential model, and the normal-gamma model. The results of simulation experiments highlight the properties of the methodology. [ABSTRACT FROM AUTHOR]

Sustainability requires that policy makers be able to use market signals to implement energy and environmental policy and that energy consumers respond rationally to these signals. Therefore, it is essential to understand how consumers' responses to market signals are formed. We propose a new model to measure behavioral efficiency in residential electricity consumption derived from the individual householder indirect utility function. This leads to a pair of simultaneous stochastic demand frontiers for electricity consumption (kWh) and power demand (kVA). Each is a function of power demand (standing) charges and energy demand (running) charges together with the net income after demand charges, the stock of appliances and household characteristics. We estimate the model using two samples of household responses, each of which represents around one percent of the total national population available, and we also pool these samples using pseudo-panel data procedures. We demonstrate how the resulting elasticity and efficiency estimates are related to the theory of behavioral agents from recent developments in behavioral economics. These developments also use the individual indirect utility function to derive propositions based on internality and hyperbolic discounting. The econometric estimates permit the calibration of the individual welfare effects of policy initiatives using carbon tax and price incentives with behavioral agents. [ABSTRACT FROM AUTHOR]

The outbreak of the COVID-19 pandemic seriously affected railway businesses. The motivation of this study is to provide vital information to railway company management and policymakers by quantitatively assessing the cost efficiency of railway operations. We examine the efficiency of Japanese listed railway companies by applying stochastic frontier analysis to their operational and financial data from 2005 to 2020. Then, we classify the companies into four groups by cost efficiency levels and identify the characteristics of the best-practice companies. Furthermore, we analyze the factors influencing cost efficiency before and during the pandemic. Finally, we discuss the sustainable business practices and measures of digital transformation (DX) that can be applied to improve efficiency and survive severe events like the pandemic. From the results, we reveal that cost-efficient companies succeeded in securing profits through the creation of new services by proactive DX investments. The practical contributions of this study are threefold: quantifying the deterioration in efficiency due to the pandemic; identifying characteristics of best-practice companies; and examining the relationship between cost efficiency levels and concrete measures and investments for sustainable business practices. This study proposes a new analytical framework that combines conventional methods. [ABSTRACT FROM AUTHOR]

This paper presents a conceptual framework aimed at exploring the connections between integration within the food supply chain and the three pillars of sustainability: economic, environmental, and social. The analysis combines theoretical insights with empirical research, specifically focusing on the economic aspect of sustainability, measured through efficiency. The study emphasizes the critical role of integrating participants across the food supply chain to achieve sustainability goals. It discusses methodologies for assessing integration levels within the chain, providing a theoretical and analytical basis for modeling integration and efficiency within the supply chain. To empirically validate these relationships, an extended stochastic frontier analysis (SFA) method was applied to selected sectors within the food processing industry. The results demonstrate that enhancing integration with suppliers and buyers can significantly improve efficiency within the food chain. In conclusion, through deductive reasoning, this study asserts that integration plays a pivotal role in advancing economic sustainability objectives within the food sector. This framework contributes to a deeper understanding of how integration influences sustainability outcomes, offering valuable insights for stakeholders aiming to enhance sustainability in food systems. [ABSTRACT FROM AUTHOR]

This study examines the current state of China's agricultural exports to ASEAN countries using a segmented export structure analysis via a stochastic frontier gravity model, based on panel data from 2007 to 2020. The results indicate that: (1) China's primary agricultural exports to ASEAN countries include plant products, food and beverages, and tobacco, with animal products mainly exported to Thailand, plant products mainly exported to Vietnam, and animal and plant fats, food, beverages, and tobacco mainly exported to Malaysia. (2) The economic scale and population size of China and ASEAN countries have differing impacts on various markets, while distance significantly negatively affects the exports of animal products, plant products, food, beverages, and tobacco. Additionally, ASEAN countries' per capita carbon emissions positively influence the exports of these product categories. (3) The liner shipping connectivity index is significantly negatively correlated with trade inefficiency. The influences of financial freedom, trade freedom, investment freedom, and government expenditure on trade inefficiency vary across ASEAN countries. (4) China's export efficiency for animal products, plant products, food, beverages, and tobacco has increased rapidly to Thailand and Vietnam, with Malaysia and Singapore showing high export efficiency, while that to Cambodia lags. (5) China exhibits significant export potential to Thailand, Indonesia, and Vietnam, with substantial expansion opportunities in Indonesia. Moreover, China's export potential and opportunities in Cambodia are steadily increasing. [ABSTRACT FROM AUTHOR]

In the face of climate change, it becomes crucial to motivate action and policies within water companies towards achieving carbon neutrality. Estimating the economic consequences of inaction can be a compelling catalyst for change. In this study, the carbon inefficiency and overuse of energy among a selection of English and Welsh water companies were assessed, along with their impact on the operational costs of producing and delivering drinking water over the period from 2010 to 2019. In doing so, a stochastic frontier analysis primal system was employed. The findings revealed that, on average, water companies exhibited a carbon inefficiency of 0.699. The overuse of energy relative to other inputs was estimated to be 71.4%. Consequently, water companies incurred a production cost increase of 0.089 £/m3. This research demonstrates that transitioning towards a low‐carbon urban water cycle is not merely an environmental beneficial endeavor; it also involves significant economic advantages. [ABSTRACT FROM AUTHOR]

This paper estimates feasible water savings for a sample of nine urban water districts in California during the height of the 2012-16 drought, just prior to the implementation of mandatory water use reductions, using household production theory and stochastic frontier analysis. Estimates of feasible savings are compared to mandated reductions and actual reductions in each district. Although the mandated reductions were generally feasible, our results show that they had asymmetric impacts across districts and tended to impose larger burdens on some disadvantaged groups.

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.

This study contributes to the existing literature on the influence of public subsidies on farmers' technical efficiency by highlighting the importance of separating persistent and transient inefficiency. Using data from a sample of French mixed (crop-livestock) farms, and relying on recent developments in stochastic frontier analysis, we find that public subsidies are positively associated with both persistent and transient technical inefficiency. The effect of public subsidies on persistent technical inefficiency suggests that they induce sluggish adjustments (restructuring) in farm management practices. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper innovatively defines the structure of human capital based on existing theories and use the heterogeneous stochastic frontier model to test the relationship between various types of human capital and innovation. It is found that with the progress of technology, the structure of human capital and the mechanism of promoting innovation have undergone profound changes. Together with commercial leasing human capital, financial human capital, and entrepreneurs, information human capital and transportation human capital participate in innovation activities and create a new collaborative space, which in turn helps to spread the value of innovation and influence the effectiveness of the entire innovation system. This study enriches the theoretical research on the mechanism of human capital promoting innovation in the information age and provides new insight to explain the imbalance between human capital input and innovation output. Based on the theory of innovation chain value and flow space, this study redefines the connotation of innovative human capital structure by distinguishing the nature of innovation activities. This study also reveals the difference in the influence of human capital structure on different types of innovation activities. This study partly explains the problem of increasing human capital input but decreasing innovation efficiency in developing countries. Therefore, from a macro perspective, our research provides guidance for understanding the transformation of innovation under the background of technological progress and formulating effective urban innovation strategies for managers. Plain language summary: Existing studies show that human capital is the core element of innovation activities, and the more human capital investment a country has, the stronger its innovation ability will be. However, there is still no consistent explanation of who promotes innovation and how. This makes it difficult for researchers to explain the problem of increasing human capital investment but decreasing innovation efficiency in some developing countries. This paper innovatively considers the impact of technological progress on innovation activities, and holds that technological progress changes the structure of human capital for innovation, thus affecting the efficiency of innovation. The analysis based on stochastic frontier model proves this view. The conclusion of empirical analysis shows that the total human capital input is not the more the better, but must pay attention to the structure, especially the information human capital and transportation human capital in innovation activities. But at the same time, this paper also believes that whether these two types of human capital will have a threshold effect on other types of human capital needs to be further discussed beyond this paper. This paper provides an enlightening perspective to explain the profound changes of innovation mechanism under the background of technological progress and promote the improvement of regional innovation efficiency. [ABSTRACT FROM AUTHOR]

Unique challenges have been elicited by climate change, demanding the utilisation of effective adaptation strategies that are both environmentally and economically sustainable. Regrettably, the agricultural sector has not been spared from the effects of climate change, but it is among the largest employers and the primary source of food security globally. The situation is worse in Pakistan, where poverty, hunger, and malnutrition are reported to be prevalent. The complexity of risks posed by climate change has called for climate-smart agriculture (CSA) technologies, which potentially could augment cost efficiency and yield in wheat production. Surprisingly, previous studies have largely overlooked this crucial aspect. Therefore, our research seeks to address two fundamental questions: What is the comparative cost efficiency between adopters and non-adopters of CSA practices in wheat production? And what are the yield effects associated with CSA adoption, particularly compared to non-adopters? To this end, a multi-stage sampling technique was employed to randomly select 400 farm households in a climate risk hotspot province in Pakistan, on which the stochastic frontier analysis (SFA) and endogenous switching regression (ESR) were applied. The results revealed that CSA adoption was associated with improved cost efficiency and yield. Interestingly, if non-adopters decided to adopt CSA, they would increase their wheat yield by about 20%. Given the importance of wheat for food security, this would contribute to poverty and hunger eradication. Therefore, our study conforms to the aspirations of the 2030 agenda by promoting rethinking food production through possible improvement in cost efficiency and yield in the face of a changing climate. [ABSTRACT FROM AUTHOR]

This work assesses the technical efficiency (TE) in agricultural production under irrigation of corn, alfalfa, sorghum, and plantain; the analysis is conducted for three hydrological subregions of Mexico: Río San Juan (north), Valley of Mexico (center) and Valle Bajo de Grijalva (South). The measurement was carried out by agricultural cycle (spring-summer, autumn-winter and perennial), and by land size. We use stochastic frontier analysis to corroborate whether the farmer’s skills favor efficiency, with a production function that relates irrigated land as a basic element, and a set of explanatory socioeconomic variables. Despite limitations in the data, the results contribute to the knowledge of TE in Mexican agriculture. Indirectly, the contribution of irrigation is recognized, so identifying their economic relevance could help define strategies to improve agricultural production and support water management in agriculture. [ABSTRACT FROM AUTHOR]

Innovation and green development are important aspects of a country's economic and social development. Exploring the impact of innovation on green development from a spatial perspective can help local governments suggest measures to promote green development. The super-efficiency slack-based measure model and stochastic frontier analysis model were used separately to measure green development and innovation. The coupling coordination degree model was used to measure the interaction of "double efficiency." Based on the spatial panel Durbin model, the spatial impact of innovation behavior on green development was studied, and regional heterogeneity was further studied. The study found that in the eastern region, provinces with a high degree of innovation and a developed financial industry have a negative effect on the green development of their neighboring provinces. In the central and western regions, the higher the innovation level of a region, the more negative the green development of neighboring regions is. A high-level financial industry promotes the green development of neighboring regions. [ABSTRACT FROM AUTHOR]

Rice is a crucial agricultural product, and enhancing its productivity is essential for increasing production. This study aims to analyze the total factor productivity growth of rice production in Iran from 2000 to 2020. Using parametric (stochastic frontier analysis) approaches, the research evaluated the rice productivity growth and its components, including scale and technological changes. Based on the estimated Translog Cost Function, the annual total factor productivity growth was 2.1%, with positive technological change as the primary driver of these improvements. To further enhance productivity, the study recommends utilizing improved seeds, modern machinery, fertilizers, and nutritional solutions during rice cultivation. Additionally, the research suggests the application of parametric approaches in future studies to assess the impact of technological changes on crop yields. [ABSTRACT FROM AUTHOR]

This article provides a large dataset on PSE using a parametric approach, and covering 158 countries of all income levels, over the period 1990–2017. The analysis includes four sectors: education, health, infrastructure, and public administration. We further consider three efficiency indicators regarding the 'Musgravian' tasks for government: allocation, distribution, and stabilization. After computing the efficiency scores for our sample countries, we examine their determinants using a wide range of economic and institutional factors. Our key findings are that trade globalization, factor productivity, and institutional quality seem to be important determinants of total PSE. The results remain robust to alternative specifications and methods. Finally, we provide additional evidence by exploring the sensitivity of the main determinants to different country groups, considering the level of economic development, geographical regions, and fragile states. [ABSTRACT FROM AUTHOR]

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The increase in market concentration and market power in the food supply chain is an issue of concern globally. This study focuses on an analysis of market imperfections in the Italian processed tomato food supply chain by considering changes in its supply chain governance from 2006–2018. The identification of the degree of non‐competitive behavior is based on the derived mark‐down and mark‐up models using the latest developments in stochastic frontier methodology. The estimated models reveal some degree of non‐competitive behavior in the input as well as in the output processing market. However, in consideration of the results on the supply chain governance during the study period, we argue that the establishment of an Interbranch Organization (IBO) could create fairly stable long‐term food supply chain relationships benefitting all IBO members and in particular farmers despite the significant change in concentration levels in the Italian tomato processing sector after 2015. [ABSTRACT FROM AUTHOR]

Stochastic frontier models commonly assume positive skewness for the inefficiency term. However, when this assumption is violated, efficiency scores converge to unity. The potential endogeneity of model regressors introduces another empirical challenge, impeding the identification of causal relationships. This paper tackles these issues by employing an instrument-free estimation method that extends joint estimation through copulas to handle endogenous regressors and skewness issues. The method relies on the Gaussian copula function to capture dependence between endogenous regressors and composite errors with a simultaneous consideration of positively or negatively skewed inefficiency. Model parameters are estimated through maximum likelihood, and Monte Carlo simulations are employed to evaluate the performance of the proposed estimation procedures in finite samples. This research contributes to the stochastic frontier models and production economics literature by presenting a flexible and parsimonious method capable of addressing wrong skewness of inefficiency and endogenous regressors simultaneously. The applicability of the method is demonstrated through an empirical example. [ABSTRACT FROM AUTHOR]

This study analyzes the economic efficiency of soybean production under contract and non-contract farming systems in the Northern region of Ghana. Using survey data from 374 soybean farmers, comprised of 200 contract farmers and 174 non-contract farmers, a stochastic frontier analysis and fractional regression models were employed to estimate technical, allocative, and economic efficiencies. The results reveal that contract farmers had a mean technical efficiency of 0.92, allocative efficiency of 0.869, and economic efficiency of 0.943, while non-contract farmers had mean technical efficiency of 0.973, allocative efficiency of 0.734, and economic efficiency of 0.866. Positive determinants of efficiency included education, farming experience, access to extension services, and participation in soybean contract farming. Off-farm activities and crop diversification negatively impacted efficiency. Contract farmers exhibited increasing returns to scale, while decreasing returns to scale prevailed among non-contract farmers. Factors influencing soybean output and production costs were also analyzed. The study highlights opportunities for enhancing soybean productivity and reducing production costs through improved resource allocation, adoption of training and extension services, and promoting contract farming arrangements that provide access to inputs, credit and technical support. [ABSTRACT FROM AUTHOR]

Understanding the effect of the relationship between timber harvesting attributes on loggers' productivity and efficiency is crucial for the feasibility and expansion of sustainable forest management and logging. We applied a stochastic production frontier model to firm-level operational data collected from 202 loggers in Virginia, United States, in 2019. Logging equipment value, physiographic region, tract area, number of workers and crews in the woods, college education level, and harvest type statistically increase harvesting productivity. Harvesting productivity in the Coastal Plain was the greatest of all physiographic regions, and pine clearcut productivity was statistically greater than that of hardwood thinning. On the other hand, manual felling reduces harvesting productivity. We found an average efficiency rate of 67% among firms in our sample, which is similar to that found in the literature. The estimated values can show factors that improve forest harvest productivity through better planning and investments while improving the sustainable use of inputs and resources. Study Implications: We empirically analyzed factors affecting logging productivity and efficiency in the southern US state of Virginia. Increased productivity was associated with working in the Coastal Plain physiographic region, investing in logging equipment, increasing the number of workers and crews in the woods, increasing pine clearcut as opposed to hardwood thinning, choosing optimal harvesting tract size, and having a college education as opposed to no high school degree. Manual felling reduces harvesting productivity, and average BMP implementation time does not affect harvesting productivity. Our results can be used as a guide in planning future decisions to increase logging productivity. [ABSTRACT FROM AUTHOR]

Given the complex managerial tasks and the risks and uncertainties involved in agricultural production, it is expected that personality traits may play an integral role in shaping farmers' performance. This study uses a large rural household survey dataset collected in three rice-producing provinces in China to examine this proposition. We find that openness to experience and internal locus of control have favourable effects on technical efficiency (TE), while agreeableness and neuroticism are associated with lower TE. Cognitive skills, as measured by years of education, do not contribute to higher TE of the interviewed farmers. These results imply that the motivational component of human capital (i.e. personality traits) is of greater importance for a farmer's managerial performance than cognitive skills attained through current formal education. The effectiveness of policies aimed at improving rural welfare may be enhanced by adapting agricultural training programmes to include fostering entrepreneurial and social skills, especially for those with unfavourable personality traits for agricultural production, in addition to improving agricultural knowledge. [ABSTRACT FROM AUTHOR]

Debt is a fundamental component of modern economic systems. It serves as a source of financing for government, business, and individual projects. Many earlier studies concentrated on the direct relationship between debt and economic performance using different econometric methodologies. This work investigates the effect of debt on production efficiency, extracted from the estimated production function. Unlike previous econometric approaches, we employ a production stochastic frontier analysis (SFA) on data for 18 OECD countries spanning from Quarter 1, 2015, to Quarter 3, 2021, to capture the short-run effect of debt on the production efficiency and, thus, output growth. The results show that, in the short run, as debt increases by $1 billion, efficiency increases by 0.04%. Additionally, we found that the most indebted countries are the most efficient countries. In our sample, those were the UK and France. Furthermore, the average efficiency for the 18 OECD countries was 70.07. [ABSTRACT FROM AUTHOR]

To obtain a consistent estimate of the impact of digital economy on the carbon total factor productivity (CTFP) is important not only in the academic field but also for the policymakers. However, the existence of endogeneity issue makes it challenging. This paper constructs a novel analysis framework that can measure the CTFP as well as the impact of digital economy simultaneously after addressing the endogeneity. By employing the endogenous stochastic frontier analysis method, the findings indicate that digital economy has a positive and significant effect on CTFP, which persists when different production functions and instrumental variables are employed. Mechanism analysis reveals that the positive impact is facilitated by changes in production methods and improvements in urban environmental regulatory governance. Moreover, the effect of digital economy on CTFP is more pronounced in regions with higher environmental awareness among residents, lower resource abundance, and higher levels of human capital. The results provide valuable policy insights into the utilization of the digital economy to achieve green and high-quality development in China, including to promote the regional balanced development of digital economy and so on. [ABSTRACT FROM AUTHOR]

The implementation of the policy of 'grain to feed' has a great impact on Chinese mutton sheep breeding industry. Based on the macro statistical data of domestic mutton sheep breeding cost-benefit, combined with the field survey data of 10 typical provinces from 2017 to 2022, this paper compares and analyzes the cost-efficiency changes and influencing factors of mutton sheep breeding in various scales in 2017 before the implementation of 'grain to feed' and in 2022 after the full implementation, so as to explore an effective way to improve the cost-efficiency of mutton sheep breeding in China under the background of 'grain to feed'. It is found that after the implementation of the policy of 'grain to feed', the cost efficiency of mutton sheep breeding in China has improved significantly. There is a positive correlation between the cost efficiency of farming and the scale of farming, and the cost efficiency of small-scale farming increases most obviously. Increasing technical guidance investment can steadily improve the cost efficiency of mutton sheep breeding. There are obvious regional differences in cost efficiency of mutton sheep breeding in different scales. The study indicates that under the background of the continuous release of the policy dividend of 'grain to feed', a technical guidance center for mutton sheep breeding should be established, the whole industrial chain of differentiated mutton sheep should be built, and the large-scale breeding project of 'grain to feed' should be implemented to provide a useful reference for improving the cost efficiency of mutton sheep breeding. [ABSTRACT FROM AUTHOR]

We study a semiparametric panel stochastic frontier model with nonseparable unobserved heterogeneity, which allows for time-varying conditional heteroskedastic productivity components. It does not require distributional assumptions on random noise except conditional symmetry. We utilize conditional characteristic functions from Kotlarski's Lemma to derive new moment conditions that yield the identification of the heteroskedastic variance parameters of inefficiency and random noise. Identification only requires a panel with three periods for serially correlated inefficiency. A nonparametric estimation procedure is also developed for the conditional variance of inefficiency, and its convergence rate is established. Monte Carlo simulation shows that the estimator is robust to misspecification of inefficiency distributions. [ABSTRACT FROM AUTHOR]

Based on the perspective of industry productivity, this article measures the sensitivities of different industries to external public security risks using stochastic frontier analysis, focusing on the relationship between the changes in industries' production line positions triggered by terrorist attacks and the industries' security risk sensitivities. We provide evidence that terrorist attacks have a significant adverse impact on the production line positions of global industries, and the strength of those positions' reactions to terrorist attacks is determined by the degree of the industries' security risk sensitivities. The reactions to terrorist attacks are nonmonotonic across industries' security risk sensitivities, with the largest effects in industries near the seventy-fifth percentile of the distribution. This phenomenon is particularly pronounced in high-income and upper-middle-income countries, and also in regions with economic and trade cooperation agreements. A further decomposition analysis of the different production stages shows that complex global value chain (GVC) activities, especially those that involve domestic value-added re-exports to third countries, are more vulnerable to negative shocks from terrorist attacks. [ABSTRACT FROM AUTHOR]

The biopharmaceutical industry in Korea is considered a key strategic industry following the semiconductor industry. However, success in the biopharmaceutical industry depends on the outcome of research and development processes that require long periods and substantial investment, resulting in a success rate of only around 2.5%–4% for new drug development. Consequently, rational strategic choices, such as determining key capabilities to pursue business, deciding where to position within the value chain and identifying collaboration partners and strategies, are more crucial in the biopharmaceutical industry compared to other industries. In this study, we divided Korean biopharmaceutical companies into research and development groups and Integrated groups, which perform both research and production, and compared their productivity using the meta-frontier methodology to verify the significance of technology gap ratio (TGR) values between groups. We also investigated the influence of open innovation activities, including the type, partners and timing, on the TGR of each group with Tobit analysis. The investigation revealed that productivity and its influencing elements varied depending on the business model. This finding suggests that this information can be utilised to develop efficient industrial policies. [ABSTRACT FROM AUTHOR]

Currently, COVID-19 is the most lethal menace in the world. Due to its health and economic consequences, it becomes a serious challenge for the economy. The present article aims to explore India's interstate disparities of efficiency in combating COVID-19 based on secondary data. Besides, an attempt has been made to pinpoint the factors responsible for the inefficiency of resisting this deadly virus. The interstate efficiency measurement is facilitated by applying stochastic production frontier analysis. The empirical result divulges that among the Indian states, Bihar is the most efficient in combating COVID-19. The empirical estimation of the frontier model discloses that the number of doctors, nurses, police force, isolation beds and hotspots positively and significantly influence the recovery rate from COVID-19 in Indian states. The empirical results of the inefficiency effects model suggest that the share of elderly and urbanisation reversely influence the efficiency in combating the virus, while favourable sex ratio, literacy rate, regular salaried employment, digitalisation and ruralisation stimulate the efficiency of the concerned state. The study concludes that efficient utilisation, coupled with the advancement of the existing health infrastructure, is imperative for the acceleration of the recovery rate from this pandemic. [ABSTRACT FROM AUTHOR]

This study examines the impact of farmers' professional cooperatives (FPCs) on agricultural technical efficiency (TE), using panel data from 30 provinces of China from 2015 to 2020 and the stochastic frontier function (SFF) method. The number of members of each cooperative, the proportion of demonstration cooperatives, and the proportion of standard cooperatives are introduced as proxy variables for the development level of FPCs. The results show that although the development of FPCs is imperfect, its development has a significant positive impact on improving China's agricultural TE. Through the continuous increase in the number of cooperative members and the vigorous promotion of standardized production, agricultural TE has been significantly improved. However, the construction of model cooperatives has not played a positive role but inhibited the growth of agricultural TE. It is suggested to expand the cooperative membership and promote standardized production. The government and policymakers should focus on improving the standardization level of cooperatives and the development quality of FPCs from the aspects of innovating cooperation models, standardizing internal governance, and giving full play to the synergistic effect of agricultural science and technology. [ABSTRACT FROM AUTHOR]