Production Function Research Articles

The Spatial–Temporal Evolution of the Trade-Offs and Synergy between the Suburban Rural Landscape’s Production–Living–Ecological Functions: A Case Study of Jiashan in the Yangtze River Delta Eco-Green Integrated Development Demonstration Zone, China

The Yangtze River Delta is one of China’s most economically developed regions and includes parts of Jiangsu, Zhejiang, and Shanghai. The economic development of the Yangtze River Delta region is in a stage of rapid growth. As a unique intersection of urban and rural functions, contradictions are prominent. The production, life, and ecological functions of suburban rural landscapes are forming new trade-off and synergistic relationships. Therefore, it is of great significance to study the production–living–ecological function of the suburban rural landscape in the Yangtze River Delta region. Jiashan County is located in Jiaxing City, Zhejiang Province, and is an important part of the Yangtze River Delta region. Jiashan County, which has location advantages and economic development, can be used as a representative area to study the relationship between the production–living–ecological function of the suburban rural landscape in the Yangtze River Delta region. To evaluate the current status of the production–living–ecological functions of suburban rural areas in the Yangtze River Delta region and provide data support for future planning decisions in the Yangtze River Delta region, this study selected the suburban rural landscape of Jiashan as the research object and used temporal rank correlation analysis and spatial bivariate autocorrelation analysis to explore the evolution characteristics of the suburban rural landscape of Jiashan from 2000 to 2020. The results show that (1) the linear increase in the production and life functions of Jiashan rural areas has led to a decline in ecological functions, and life functions has been dominant. (2) There are trade-offs and synergistic relationships between the different functions of the suburban rural landscape of Jiashan, showing a temporal change pattern dominated by trade-offs. (3) The multifunctional trade-offs and synergistic relationships for the suburban rural landscape in Jiashan County exhibited obvious spatial pattern variability, and there were differences in how the streets and towns evolved. The relevant policies for the construction of ecological green comprehensive demonstration areas affect the economic, social, and ecological development of the Yangtze River Delta region, resulting in substantial differences in the types of and trends in the spatiotemporal evolution of the functional trade-off and synergistic relationships of the suburban rural landscape. Targeted measures should be taken according to the local conditions to guide the coordinated development of landscape functions.

Pan-European Water Use Efficiency and Sustainability Evaluation Based on Stochastic Meta-frontier Analysis

In 2007, the European Union (EU) intended to become a water-efficient community. Yet, despite the EU’s commitment to the United Nations (UN) sustainable development goals (SDGs), relevant insights based on scientific research are still sparse. This study presents a pan-European water use performance evaluation, considering differences in production technologies and potential efficiency determinants. The empirical results are obtained by analysing country-level panel data from 2011 to 2020. Our paper provides more instructive and encompassing findings to inform holistic policy formulation and management practices than prior studies that have typically relied on partial-factor indicators with limited explanatory power. We find that European countries are subject to technological and efficiency heterogeneity, and our production function and inefficiency equation estimations attest to the existence of divergent cause-effect relationships, calling for decentralised, customised solutions. Arguably, our comparative benchmarking analysis constitutes the first comprehensive cross-country investigation for Europe of its kind, underscoring the importance of impactful science in fostering the preservation of high civilisation in line with the theme of this special issue.

Inhibit or promote: Spatial impacts of multifunctional farmland use transition on grain production from the perspective of major function-oriented zoning

Ensuring global sustainable development depends on achieving food security, a goal intrinsically linked to the farmland's grain production capacity. Despite its critical importance, the comprehensive spatial effects of multifunctional farmland use transition (MFFUT) on grain production, particularly from a production-living-ecology perspective, remain insufficiently explored. Addressing this gap, this study employs geospatial analysis techniques and spatial econometric models to examine the spatial impacts of MFFUT on grain production in the Huang-Huai-Hai Plain (HHHP), North China, from the perspective of Major Function-oriented Zoning (MFZ) during 2000–2020. The findings reveal an overall upward trend in grain production in HHHP, with main agricultural production zones emerging as significant grain bases. MFFUT considerably enhances local grain production while suppressing production in neighbouring areas. Specifically, Production Function Farmland Use Transition (PFFUT) and Living Function Farmland Use Transition (LFFUT) stimulate grain production in both local and neighbouring areas, whereas Ecological Function Farmland Use Transition (EFFUT) negatively impacts neighbouring areas while simultaneously bolstering local production. The heterogeneous analysis demonstrates that MFFUT promotes grain production in different MFZs but adversely affects neighbouring regions within main agricultural production zones. Further analysis indicates that PFFUT, LFFUT, and EFFUT considerably enhance grain production across various MFZs. However, PFFUT and LFFUT detrimentally affect neighbouring grain production in main agricultural production zones. This research provides valuable insights for policymakers to formulate optimised land use allocation schemes, implement differentiated land use measures, and safeguard food security.

Management on Transfer Pricing of Farmland Based on the Supply–Demand Mismatches for Multifunction: A Case Study from China

Realizing the multifunctional value of farmland is essential for regulating the pricing of farmland transfers and stabilizing the rural land market. However, in China, the mismatch between supply and demand leads to improper resource allocation, weakens the explicit value of farmland, and causes unreasonable transfer pricing mechanisms that threaten agricultural production and food security. This study develops an analytical framework to examine the relationship between farmland multifunction and transfer pricing from a supply–demand perspective. An evaluation index system is constructed, considering the physical, value, and material quantities. This study uses the matching index method and bivariate spatial autocorrelation to analyze the supply–demand match of farmland multifunction from 2014 to 2021 and its relationship with transfer prices. Additionally, management methods and strategies for dynamic zoning-based pricing under multifunctional matching trade-offs are proposed. The results show that: (1) There is significant heterogeneity in the supply and demand matching degree of different farmland functions in both space and time. The production and ecological functions of farmland are oversupplied, while the living functions are undersupplied. (2) Different spatial autocorrelation relationships exist between the degree of supply and demand matching of farmland functions and farmland transfer prices. Specifically, the supply and demand matching degrees of the production and living functions show a significant negative spatial correlation with farmland transfer prices. In contrast, the ecological function shows a significant positive spatial correlation with farmland transfer prices, which are continuously strengthening over time. (3) Based on the supply and demand matching situation of different farmland functions and the spatial autocorrelation of farmland transfer prices, nine types of regions are delineated for farmland functions. Among them, the surplus-coordinated development areas have the most cities, accounting for about 40%, with a wide distribution range. This study proposes zoning-based pricing instruments and management strategies. This research provides valuable insights for developing countries seeking to alleviate conflicts in multifunctional land use, enhance the sustainable protection of land resources, and improve land resource assessment frameworks.

Capital Inflow and Technical Efficiency: A Comparative Analysis Between India and China

This article empirically investigates the impact of foreign direct investment (FDI) on the technical efficiency of manufacturing firms in India and China. We apply the first-stage, stochastic frontier analysis (SFA), to the translog production frontier. The first-stage method estimates simultaneously consider exogenous technical efficiency determinants and translog production function factors. We take foreign ownership and foreign inputs as exogenous determinants of technical efficiency with control variables and foreign technology input in the production frontier. Empirical results find that foreign technology shifts the production frontier by enhancing productivity for Chinese firms, not for Indian firms. Furthermore, domestic firms which use foreign inputs and foreign firms are more efficient. JEL Classification: F14, O31, O32

Production Risk of Hybrid Maize in Sugihmanik Village, Tanggungharjo Subdistrict, Grobogan Regency (Case Study: Faisal Tani Store)

This study aims to examine the impact of production factors on hybrid corn production and to assess the level of production risk in Sugihmanik Village, Tanggungharjo District, Grobogan Regency (Case Study: Faisal Tani Store). The research adopts a quantitative approach with a sample of 69 hybrid corn farmers. The data analysis method utilized the Cobb-Douglas production function with multiple linear regression and coefficient of variation analysis. Data processing was conducted using SPSS 25. The results indicated that capital, land area, and labor factors collectively influence hybrid corn production. In addition, the land area and labor variables were found to have a significant effect on hybrid corn production, while the capital variable did not show a significant effect. The coefficient of variation (CV) for production risk in hybrid corn farming in Sugihmanik Village, Tanggungharjo District, Grobogan Regency (Case Study: Faisal Tani Store) was 0.33, indicating a low level of production risk.

Skill intensity in manufacturing exports: Do basic, technology-intensive or differentiated exports cause growth in Kuwait?

This study examines the causality between basic, technology-intensive, and differentiated manufacturing exports and economic growth in Kuwait using data from 1970 to 2021 and two augmented production function models: one with natural resource exports (Model 1) and the other without on both sides of the model (Model 2). The Johansen cointegration and the autoregressive distributed lag model (ARDL) bound tests are conducted to examine the long-run relationship between the variables. In addition, the Granger causality test in a vector autoregressive framework (VAR) and the Toda–Yamamoto test are employed to explore the directions of the short- and long-run causality between variables, respectively. The empirical results of Model 1 indicate that neither of the decomposed manufacturing exports directly causes economic growth in the short or long run at any conventional significance level, whereas natural resource exports cause economic growth, basic and technology-intensive manufactured exports in the short-run at the 5% level. Model 2 estimations confirm the absence of direct causality between decomposed manufacturing exports and economic growth, whereas a long-run causality runs from output net of natural resource exports to basic manufactured exports at the 10% level. Both model estimations indicate that all the variables jointly cause economic growth and basic manufactured exports in the short and long run, directly or indirectly through imports, confirming the existence of a circular causation. These findings can serve as the basis for designing specific export–import policies to foster diversification and a sustainable economic growth in line with Kuwait’s Vision 2035.

Green innovation for a sustainable environment: Modeling the new green knowledge production function for OECD countries

AbstractThe world community faces serious challenges such as climate change, biological loss, and environmental degradation. Developing ecological technologies is vital for coping with these unreversible crises. This study proposed a modified green knowledge production function to achieve sustainable development goals and generate policies for promoting environmental technologies. It examined the impact of market demands, environmental research and development expenditures, human capital, and environmental protection policies on the production of green environment technologies. Panel data included 16 OECD countries from 1990 to 2019. Data analysis strategies included the Gengenbach, Urbain, and Westerlund panel co‐integration test, fully modified least squares, mean group dynamic least squares, and estimators such as feasible generalized least squares and panel‐corrected standard errors for robust checks. A novel panel causality test via a half‐panel jackknife estimator was also applied for causality analyses. The findings showed that human capital, market size, and environmental policy stringency played significant roles in producing environmental technologies and innovations. Although environmental expenditures made by the government positively affected the supply of green innovation, no statistically significant results were observed. The study highlights the importance of enhancing environmental innovation factors by promoting policies, including human capital development, environmental sanctions, and market demands for a sustainable environment.

Modeling Tomato Yield and Quality Responses to Water and Nitrogen Deficits with a Modified Crop Water Production Function

Increasingly severe crises, such as climate change, water scarcity and environmental pollution, pose significant challenges to global food security and sustainable agricultural development. For efficient and sustainable tomato cultivation management under resource constraints, quantitatively describing the relationship between yield-quality harvest and water-nitrogen application is practically beneficial. Two successive greenhouse experiments with three irrigation levels (1/3 FI, 2/3 FI, and full irrigation (FI)) and four nitrogen fertilizer treatments (0 FN, 1/3 FN, 2/3 FN, and full nitrogen (FN)) were conducted on tomatoes during the whole phenological stage. The tomato evapotranspiration and nitrogen application amount, yield, comprehensive quality, solid–acid ratio, and lycopene content were measured. Based on crop water production functions, three equation forms of water-nitrogen production functions containing 20 models were established and evaluated to predict tomato harvest parameters. The results show that water increased tomato yield while decreasing fruit quality, and the effect of nitrogen was primarily contrary. Water most significantly impacted tomato formation, and the interaction of water and nitrogen changed among different harvest parameters. Tomato yield and quality formation was more sensitive to water and nitrogen at the flowering and fruit maturation stages. Model Singh-2 outweighed other models for yield estimates, with an R2 of 0.71 and an RMSE of 0.11. Singh-Log, Singh-sigmoid and Rao-Root models were effective models for comprehensive quality, solid–acid ratio, and lycopene content prediction, with an R2 of 0.41, 0.62, and 0.42, and an RMSE of 0.33, 0.50, and 0.16, respectively. Finally, models in the form of f(ETi)·f(N) were ideal for tomato harvest prevision and are recommended for water and nitrogen management in tomato cultivation.

Energy substitution possibilities and technological progress in Pakistan's industrial sector

Considered high-energy intensive, Pakistan's industrial sector has seen an upwelling in its energy use, reaching 19.74 million tons of oil equivalents in 2021, which is about 37% of Pakistan's total energy consumption. This has made the industry a major contributor to CO2 emissions and related contaminants. This research has tried to analyze the possibilities for factor substitution between energy and non-energy factors in the industrial sector by applying a trans-log production function. For the multicollinearity problem, ridge regression was used. The results show that (i) all the inputs are increasing return to scale; (ii) the measured substitution elasticity between gas-coal and oil-gas is about 0.901 and 0.953, while capital-oil, capital-gas, capital-coal, and labor-oil stands at 1.231, 1.088, 1.045, and 1.404. This is a strong sign that allocating more capital and labor to Pakistan's industrial sector instead of energy will be dynamic for sustainable development. (iii) oil-electricity consumption and electricity add to only a little share of energy by 0.378 because oil import has declined (about 15%) as a whole and imported electricity increased (5.53%), which gives the potential for primary interest, and (iv) technological progress is estimated between −0.051 and + 0.03 between energy inputs. The input of coal vs gas is a faster substitute with their relative difference in technological progress, while coal vs electricity also presents evidence of convergence. Our findings recommend robust policies, technological advancements, and industrial engagement for fostering energy efficiency towards a sustainable production system and contributing to an environmentally aware and efficient economy.

Narrative production and executive functions in post-stroke agrammatic aphasia

ABSTRACT Background Narrative production has been widely characterized as providing an ecologically valid way to assess language skills in post-stroke aphasia. Although narrative tasks have been instrumental in delineating patterns of lexical and syntactic production in individuals with agrammatic aphasia, our knowledge of how narrative skills are affected in agrammatic aphasia is still limited. Aims The study’s aims were to (a) compare narrative performance between individuals with agrammatic aphasia and a language-unimpaired group, (b) investigate the contribution of lexical and syntactic skills in each group’s narrative organizational skills, and (c) explore the effects of executive functions on each group’s narrative performance. Methods & Procedures The study included 14 individuals with agrammatic aphasia and 14 age- and education-matched language unimpaired individuals as the control group. Both groups told the Cinderella story, and their narrative production was analyzed in terms of microstructure (lexical diversity, syntactic complexity, clause length) and macrostructure (story grammar, story structure complexity). Each group’s executive functions were evaluated through the One-Touch Stockings of Cambridge test that assesses working memory, and the Intra-Extra Dimensional Set Shift test that assesses cognitive flexibility. Outcomes & Results Regarding narrative microstructure, the individuals with agrammatism scored significantly lower than controls in syntactic complexity and clause length, but not in lexical diversity, but they performed lower than controls in both narrative macrostructural measurements. Also, the agrammatic group scored lower than controls in both executive function tasks. A series of linear regression models showed that microstructural skills significantly affected narrative macrostructural abilities in the cohort with agrammatic aphasia, while controls’ macrostructure was affected by both narrative microstructure and executive function skills. Conclusions The individuals with agrammatic aphasia exhibited impairment in both low-level language features of narrative production, such as syntactic complexity and narrative length, and global measures of narrative organization. Their macrostructural performance critically relied on their language resources, while controls’ narrative macrostructure seemed to also draw on domain-general cognitive skills. These findings suggest that both low-level language and high-level discourse organizational skills are vulnerable in narrative production in agrammatic aphasia, and that macrostructural skills are mainly related to the individuals’ microstructural skills.

Specification of the health production function and its behavioral implications.

The health production function of the canonical health-capital model is generalized to allow the state of health to affect the total and marginal products of health investment. If the total and marginal products of health investment are nonincreasing functions of the state of health, then the solution of the generalized model is locally qualitatively identical to that of the canonical model. Moreover, and in contrast to the canonical model, the generalized model is able to rationalize the cycling of the state of health and health investment observed in some individuals. The necessary conditions on the health production function for cyclical behavior are identified as well.

Analysis of Allocative Efficiency of Watermelon Farming in Kapuas Regency, Central Kalimantan Province

The objective of this research is to analyze the costs, revenues, and profits of watermelon farming, to examine the impact of the use of production factors in watermelon farming, and to evaluate the allocative efficiency level of watermelon farming in Kapuas Regency, Central Kalimantan Province. The population of this research consists of 113 farmers, from which 55 were selected using simple random sampling techniques. The data processing method used to analyze the costs, revenues, and profits of watermelon farming includes using a multiple linear regression model, specifically the Cobb-Douglas function type. Additionally, to analyze the allocative efficiency of production factors used by farmers in watermelon farming, the comparison of a production factor’s Marginal Product Value (MPVx) with the price of the production factor (Px) is set to be equal to 1. Based on the results of the research and data processing, the average revenue obtained from watermelon farming in Kapuas Regency is IDR 75,619,181.82 per farm, and the average profit earned by watermelon farmers is IDR 45,541,259 per farm. The statistical test results of the Cobb-Douglas production function show that collectively (simultaneously), the production factors (land area, number of seeds, organic fertilizer, inorganic fertilizer, pesticides, and labor) significantly affect watermelon production. However, the partial test results indicate that the production factors of land area, seeds, organic fertilizer, inorganic fertilizer, and labor significantly affect watermelon production, except for the production factor of pesticides. The statistical test results for allocative efficiency (price efficiency) show that three production factors, namely organic fertilizer, labor, and pesticides, are used efficiently, meaning the marginal product equals the price of the production factor. The use of land area, seeds, and inorganic fertilizer is not yet efficient and needs to be increased to reach an efficient point.

Estimating the Ideas' Production Function Using Macro‐Economic Persistence

AbstractIf productivity stems from the accumulation of ideas, then the ideas' production function can cause productivity and macro‐economic aggregates to be persistent. We use this insight to estimate the parameters of the ideas' production function in a general equilibrium model. We find that ideas become harder to produce as they accumulate. We quantitatively explore the propagation of different kinds of shocks through the ideas' production function, finding that nonpersistent shocks that affect R&D decisions may lead to persistent productivity changes as a result. The use of capital in R&D is important for propagation.

Recent CO2 emission and projections in Chinese provinces: New drivers and ensemble forecasting

Although extensive studies focused on the driver of changing CO2 emission, the roles of labor and capital were largely ignored in shaping spatiotemporal change in CO2 emission and forecasting differences on CO2 emission was few considered, hindering relevant policymaking towards sustainable development in both climate change mitigation and economic growth for developing countries in particular. To fill the gap above, the study explored the roles of capital and labor in contributing to recent CO2 emission in a case of China over 2010–2019 and projecting provincial CO2 emissions to 2030, by proposing two new spatiotemporal logarithmic mean Divisia index models with Cobb-Douglas production function and developing an ensemble forecasting model including machine learning. We found, first, the effects of capital and labor inputs and carbon factor were the positive drivers affecting aggregate CO2 emissions, while the effects of the total-factor productivity and energy intensity were negative drivers. Second, the effects of capital and labor inputs were the negative drivers for narrowing the emission gap. Third, the ensemble forecasting model can improve the generalization ability of CO2 emission predictions. Therefore, we recommend that policymakers focus on optimizing the carbon reduction effects of capital and labor inputs while promoting the development of a circular economy to achieve sustainable economic growth.

Sustainable utilization of cultivated land resources based on "element coupling-function synergy" analytical framework: A case study of Guangdong, China

Solely focusing on the agricultural production function of cultivated land resources is not conducive to the various demands for meeting the UN's Sustainable Development Goals. Recognizing the multifunctionality of cultivated land and understanding the interrelationships between individual functions are crucial for the rational planning and utilization of resources. This paper introduces an "element coupling-function synergy" analytical framework for the sustainable utilization of cultivated land resources. The proposed framework is based on the causal relationships between elements and functions within the cultivated land system. Subsequently, a causal Bayesian belief network was constructed to identify trade-offs and synergies among multiple functions of cultivated land resources in Guangdong, China. The findings reveal trade-offs between food cleanliness and food production/social security, and synergistic relationships among food production, social security, and ecological regulation, as well as among ecological regulation, habitat maintenance and landscape culture. The study area was divided into eight functional zones: Green Agricultural Zone, Agro-inputs Control Zone, Urban Agricultural Zone, Major Grain-producing Zone, Modern Agricultural Zone, Agro-ecological Preservation Zone, Agro-ecological Tourism Zone, Quality Improvement Zone. Multi-objective management plans were formulated for optimizing multifunctional relationships within each zone. The analysis result reveals the importance of nutrient conditions and ecological environments for the sustainable management of cultivated land. Consequently, specific policy recommendations are proposed accordingly. This paper may not only advance understanding of the multifunctionality of cultivated land but can also provide valuable insights for land-use planning to ensure the judicious and sustainable management of cultivated land resources.

Returns to scale, technical and efficiency changes in the Spanish hotel industry using technological heterogeneity models

This paper analyses returns to scale, productivity growth and its decomposition in the Spanish hotel industry (period 1997–2019). To do so, we consider that hotels can have technological heterogeneity and, therefore, parameters in their production function can differ between them. Also, we use a multiple input and output production function based on an output distance stochastic frontier approach with random parameters in a Bayesian framework. Results indicate that the percentage of hotels working under increasing returns to scale decreased during the period considered. Furthermore, productivity growth was low, indicating signs of stagnation. Efficiency change appears to be the main driving force behind productivity growth, although technical change had a positive effect on productivity after the start of the global financial crisis. Several practical implications are proposed based on these results.

Benefit and risk: Keystone biomes in maize rhizosphere associated with crop yield under different fertilizations

The highly diverse beneficial and deleterious microbes in the rhizosphere influence plant growth and crop production in agricultural ecosystems. However, our understanding of the relationships between beneficial and risky phylotypes in the rhizosphere, and plant growth, in addition to their potentially varied response to different fertilization treatments in black soils, remains poor. Here, we investigated variations in multitrophic (e.g., bacteria, fungi, invertebrates, and protists) community composition and diversity under different five-year fertilization treatments, and identified the potential beneficial and potential risky keystone multitrophic biota in maize rhizosphere and bulk soils based on ecological networks and soil food web structure. Bacteria and protist community compositions exhibited greater variations under different fertilization regimes when compared with those of fungi and invertebrates. In addition, two keystone phylotype groups associated with crop yield and soil function were detected, and the potential beneficial keystone phylotypes exhibited higher relative abundances in C-fixation, N-fixation, and P-mineralization genes; conversely, the potential risky keystone phylotypes were associated with denitrification and nitrate reduction genes, and included more potential fungal pathogens. Furthermore, structural equation modeling results indicated that organic amendments, particularly cow manure, could improve crop yield by enriching beneficial keystone phylotypes and suppressing risky keystone phylotypes. Altogether, the results of the present study highlight the critical roles of rhizosphere biota in food production, and identify keystone phylotypes that are beneficial or harmful to crop production and soil function, which could facilitate the conservation of beneficial biota and the early detection of potential pathogens, as well as the exploitation of beneficial biota to increase crop yield.

Analyzing the impact of precision farming on the yield of grain crops based on production functions

Analyzing the impact of precision farming on the yield of grain crops based on production functions

Does The Consumption of Energy, Renewable Energy, Natural Resources and Emissions Affect Gross Domestic Product?: The Study of Southeast Asia

We face the challenges of economic growth productivity which still uses dirty energy and minimal efforts to cleaner energy transition. The debate on efforts to increase productivity by diverting dirty energy into clean energy while still preserving nature has long been discused. Southeast Asia is a region that has massive development potential with valuable natural resources facing regional threats in addition to decreasing environmental quality but also prosperity. This study aims to identify initial steps are needed to control energy consumption, which is still considered dirty, the extent of the scope of Southeast Asia's current clean energy transition and how emissions can be a determinant of the decline in regional economic produtivity. This is the first study to combine the Cobb-Douglass production function model with three models that focus on (1) energy consumption, (2) renewable energy and natural resources, and (3) emissions. The data used is secondary data for the period 2004-2018 sourced from the World Bank Development Indicator and ourworlddata.org. Panel data regression was used as an analytical technique. This study was conducted in the Southeast Asia region (with selected countries with developing economies and insutries, namely Indonesia, Malaysia, Thailand, the Philippines and Vietnam). The results of this study show that in the energy consumption model, only labor has a significant effect on GDP, in model B there is renewable energy consumption and the labor force which significantly affects GDP and in model C there are CO2 emissions and GHC emissions that affect GDP in the Southeast Asia region. This research will provide input to policy makers and growth analysts to form policies for sustainable economic development in Southeast Asia.