Capital Inputs Research Articles

Environmental regulation stringency and allocation between R&D and physical capital: A two-engine growth model

Many studies have identified the negative effect of environmental regulation on capital accumulation and the positive effect on innovation, but this observed capital-innovation tradeoff due to environmental regulation lacks theoretical underpinning. We fill this gap by developing a unified two-engine endogenous growth model with environmental regulation, and show that a stringent environmental policy (in terms of pollution tax) leads to a sectoral reallocation from dirty inputs to clean final-good sectors, which increases the demand for R&D and activates the innovation engine. The capital engine depends on the elasticity of substitution between polluting and capital inputs. If both are sufficiently complementary, capital accumulation slows down. Another novelty of our model is that the contrasting responses of the two growth engines can lead to an inverted-U relation between overall GDP growth and environmental taxation. Our calibration shows that a well-designed environmental regulation can achieve a “double dividend”: both improving the environment and enhancing economic growth and social welfare. Our empirical analysis provides macro-level evidence to justify our model prediction by using cross-country panel data.

Trauma Patient Transitions From Critical Care: A Survey of U.S. Trauma Centers.

Transitions between clinical units are vulnerable periods for patients. A significant body of evidence describes the importance of structured transitions, but there is limited reporting of what happens. Describing transitions within a conceptual model will characterize the salient forces that interact during a patient transition and, perhaps, lead to improved outcomes. To describe the processes and resources that trauma centers use to transition patients from critical care to nonintensive care units. This cross-sectional study surveyed all Level I and II trauma centers listed in the American Trauma Society database from September 2020 to November 2020. Data were merged from the American Hospital Association 2018 Hospital Survey. A total of 567 surveys were distributed, of which 152 responded for a (27%) response rate. Results were organized in categories: capital input, organizational facets, employee behavior, employee terms/scope, and labor inputs. Resources and processes varied; the most important opportunities for transition improvement included: (1) handoff instruments were only reported at 36% (n = 27) of trauma centers, (2) mandatory resident education about transitions was only reported at 70% (n = 16) of trauma centers, and (3) only 6% (n = 4) of trauma centers reported electronic medical record applications that enact features to influence employee behavior. After years of focusing on transitions as a high-stake period, there remain many opportunities to develop resources and enact effective processes to address the variability in transition practice across trauma centers.

Public Investment in a Production Network: Aggregate and Sectoral Implications

Abstract Aggregate and sectoral effects of public investment crucially depend on the interaction between the output elasticity to public capital and intermediate inputs. We uncover this fact through the lens of a New Keynesian production network. This setting doubles the socially optimal amount of public capital relative to the one-sector model without intermediate inputs, leading to a substantial amplification of the public-investment multiplier. We also document novel sectoral implications of public investment. Although public investment is concentrated in far fewer sectors than public consumption, its effects are relatively more evenly distributed across industries. We validate this model implication in the data.

Joan Robinson’s intelligible Marxism and The Accumulation of Capital: a generalisation of the two-sector reproduction scheme

Abstract Joan Robinson sought to make Marx’s economics intelligible to both academic colleagues and followers of Marx, in a twofold approach. First, she adopted Kalecki’s antipathy to the labour theory of value and his insights (following Rosa Luxemburg) into realisation problems in the schemes of reproduction; second, following Sraffa’s reading of Ricardo, she recognised the importance of surplus production as an alternative to neoclassical theory: both culminating in a stripped down two-sector scheme her mature work, The Accumulation of Capital. This scheme is recast here as an input–output framework, providing a generalisation that addresses some of its limitations: the need for an interface with the Kahn/Keynes employment multiplier, the absence of circulating capital inputs, and the lack of a systematic treatment of prices. Furthermore, a somewhat surprising result is the derivation of a core role for Marx’s category of surplus value in the employment multiplier derived from Robinson’s system.

Financial Transparency, Labor Productivity, and Real Wages: Evidence from Mandatory IFRS Adoption

ABSTRACT Financial transparency can affect labor markets directly by mitigating information asymmetries and optimizing the matching of heterogeneous firms and employees (matching efficiency channel) and indirectly through the effect of transparency on firms’ capital inputs (capital utilization channel). Exploiting the increase in financial transparency following the mandatory International Financial Reporting Standards (IFRS) adoption by European Union countries, we perform a battery of tests that indicate subsequent increases in labor productivity and real wages for manufacturing industries in member countries. More importantly, we find evidence that both channels are economically relevant in explaining gains in labor productivity and real wages following the mandatory IFRS adoption. Collectively, our results underscore that the benefits of an increase in transparency go beyond the effects on capital markets and corporate investments, with implications for the allocation of human resources across corporations.

Operating Hedge and Gross Profitability Premium

ABSTRACTWe show theoretically that variable production costs reduce systematic risk of firms' cash flows if capital and variable inputs are complementary in firms' production and input prices are procyclical. In our dynamic model, this operating hedge effect is weaker for more profitable firms, giving rise to a gross profitability premium. Moreover, gross profitability and value factors are distinct and negatively correlated, and their premia are not captured by the capital asset pricing model (CAPM). We estimate the model by simulated method of moments, and find that its main implications for stock returns and cash flow dynamics are quantitatively consistent with the data.

Rural Tourism Households Adapting to Seasonality: An Exploratory Sequential Mixed-Methods Study

The inherent vulnerability of tourism poses a substantial challenge to maintaining the productivity and stability of livelihoods among rural tourism households. Although tourism seasonality significantly influences the livelihood activities of rural tourism households, research exploring how they adapt their livelihood strategies to achieve optimal outcomes is limited. Employing an exploratory sequential mixed-methods design that combines thematic analysis and fuzzy-set Qualitative Comparative Analysis (fsQCA), we investigated the relationship between the livelihood strategies and outcomes of rural tourism households under the influence of tourism seasonality in the Lijiang scenic spot of China. The results indicate that livelihood strategies adopted by rural tourism households include “Tourism Persistence”, “Seasonal Employment”, and “Seasonal Farming” during the off-season and “Extending Working Hours”, “Increasing Staffing Input”, and “Increasing Capital Input” during the peak season. Furthermore, these strategies form flexible combinations to realize livelihood outcomes, with “Extending Working Hours” being a necessary condition. The findings also revealed that the four configurations of seasonal livelihood strategies in the two patterns significantly contributed to high livelihood outcomes. One is named “Peak-Season Driven Pattern”; the other is named “Peak-Off Blend-Driven Pattern”. These findings provide theoretical and practical insights for sustainable livelihood research.

Construction and Practice of Livelihood Efficiency Index System for Herders in Typical Steppe Area of Inner Mongolia Based on Super-Efficiency Slacks-Based Measure Model

Inner Mongolia is one of the main animal husbandry production bases in China, with herders being the main animal husbandry producers. A systematic analysis of the efficiency of herding households’ livelihoods and the influencing factors is of great importance to formulate effective policies to support herding households’ livelihoods, enhance their social adaptability, and alleviate the vulnerability of poor people in herding areas. This study used a typical steppe of Inner Mongolia as the research area. It used the interview data of herding households from 2021, constructed the evaluation index system of herding households’ livelihood efficiency, analyzed the redundancy of the inputs and outputs of herding households’ livelihoods, and examined the key factors affecting herding households’ livelihood efficiency. The results indicate that (1) the pure technical effectiveness of the livelihood efficiency of typical grassland herding households in Inner Mongolia is the highest; the comprehensive technical efficiency and scale efficiency are low. The scale return of most herders’ livelihoods shows a decreasing state. (2) According to the results of the model, under the premise of the output not being reduced, reducing the amount of social capital input can effectively save resources. Without increasing the input, the room for improvement in the living level is the most obvious. (3) The pasture area, the communication network, and the access to information have significant negative effects on the efficiency of herders’ livelihoods; infrastructure and water supply have significant positive impacts. In summary, we built a model for evaluating the livelihood efficiency of herders in typical grassland areas of Inner Mongolia, which can provide a reference for the revitalization work of pastoral areas and related research in the future.

Non-Linear Nexus of Technological Innovation and Carbon Total Factor Productivity in China

Scientific and technological innovation is the main driving force of the growth in the 14th Five-Year Plan with the aim of “carbon peaking and neutralization.” This research analyzes the carbon total factor productivity (CTFP) improvement mechanism induced by micro-subject technological innovation and macro-technological progress (TP). This research constructed the Malmquist index based on a relaxed nonparametric DEA model, measured the TP level and CTFP in China, and considered the non-strict externalization of technological progress. The endogenous dynamic threshold model was used to test the nonlinear dynamic effect of TP driving the increase in CTFP. Through the intertemporal distance DEA model, undesired output model, and dynamic threshold regression model, we found that science and technology innovation of the TP drive the function of the carbon total factor productivity; there was a threshold effect (−0.556) on the driving impact of TP caused by technological innovation on CTFP, and the lag period of TP and CTFP had a positive driving role for CTFP. The driving effect on the left side of the threshold value was better than that on the right side. Considering the reality of slowing down the growth of capital and labor factor input in the 14th Five-Year Plan, it is essential to take active policy measures to promote the growth rate of TP by promoting the speed of micro-scientific and technological innovation. It is crucial to promote green TP in micro renewable energy enterprises, which, in turn, drive the growth of CTFP, improve the performance of low-carbon development, and reduce the negative impact of the “two-carbon” target on economic growth while realizing low-carbon transition.

Digital Economy, Factor Allocation Efficiency of Dual-Economy and Urban-Rural Income Gap

The digital economy has significant economic structural transformation effects and income distribution effects. This article analyzed the impacts and mechanisms of digital economy development on the efficiency of dual-economic factor allocation and the urban–rural income gap from a theoretical perspective, empirically tested by using China’s provincial panel data from 2008 to 2017 and a bidirectional fixed effects model. It was found that the development of the digital economy has significantly improved the efficiency of factor allocation in the dual-economy, which has a significant improvement effect on the allocation efficiency of capital and labor. The development of the digital economy alleviates the problem of surplus labor factors and insufficient capital input in the agricultural sector by promoting nonagricultural employment and the flow of capital factors to the agricultural sector. The development of the digital economy can significantly reduce the urban–rural income gap by improving the efficiency of factor allocation in the dual-economy. The main contribution of this article is verifying that the flow of production factors triggered by the digital economy has a configuration efficiency improvement effect and further extending the economic structure effect of the digital economy to the field of distribution, examining the feasible path of optimizing the income distribution pattern of the digital economy.

Enacting people analytics: Exploring the direct and complementary effects of analytical and storytelling skills

AbstractAlthough research identifies analytical and storytelling skills as the two broad human capital inputs required to perform people analytics, further research is required to better understand how People Analysts that is, the enactors of people analytics, perceive the impact of these skills on their performance. Accordingly, this study draws on the human capital resource (HCR) and HCR complementarity frameworks to investigate the individual and collective impact of analytical and storytelling skills on People Analysts perceived job performance. A mixed‐method sequential explanatory research design is adopted, finding mixed results. Consistent with existing research, results from Phase 1 find People Analysts perceive storytelling skills to be positively associated with their job performance. However, contrary to existing claims, the findings reveal that analytical skills are only perceived to be significant in influencing People Analysts job performance when combined with storytelling skills, supporting a complementarity HCR relationship. To further explain the findings from Phase 1, Phase 2 involved collecting data from 50 people analytics professionals via semi‐structured interviews. Results from the thematic analysis reinforce the survey findings while also illustrating that People Analysts perceive the complementarity relationship between analytical and storytelling skills as important for improving job performance. Accordingly, we argue that debate in this area should be reframed to acknowledge the necessity of complementarities in building people analytics capabilities.

뉴노멀 시대 물류효율화가 경제성장에 미치는 영향

Purpose - The purpose of this study is to analyze the impact of logistics efficiency in G-7 countries on economic growth. In other words, it quantitatively evaluates the correlation between the alternative variable of logistics performance index (LPI), representing logistics efficiency, and economic growth, providing an in-depth analysis of how logistics efficiency in G-7 countries significantly influences economic growth.
 Design/Methodology/Approach - In this study, a Cobb-Douglas production function is employed as the basis for the research model. The Cobb-Douglas production function is an economic model that explains output obtained through the efficient combination of factors involved in production. Through this model, the influence of logistics efficiency on economic growth can be estimated.
 Findings - The estimated results using a fixed-effects model are as follows. Both the amount of capital input (K) and labor input (L) have significant effects on economic growth. On the other hand, the logistics performance index (LPI), representing an alternative measure of logistics efficiency, is not statistically significant in relation to the economic growth rate.
 Research Implications - This study holds significance in elucidating the relationship between logistics efficiency and economic growth in G-7 countries, and it also contributes to enhancing understanding and interest in the field of logistics.

China's carbon emissions peaking pathway in the post-COVID-19 era.

Several countries have weakened the carbon emission objectives to immediately revive the economy in the post-COVID-19 era. Therefore, it is a challenge worth addressing to readjust the economic development and carbon emissions after the COVID-19 pandemic. From the perspective of China's carbon emissions, this study shapes a multi-objective dynamic optimization model based on the material capital input and R&D support aspects. The proposed model imitates China's economic development, energy consumption, and carbon dioxide (CO2) emissions. The model provides theoretical suggestion for the government to revive economic development and reduce carbon emissions. In addition, this research paper compares the evolutionary path of carbon peak under the two scenarios. The first scenario requires maintaining the pre-epidemic development state and pace of carbon emission reduction, referred to as the baseline scenario (BS). The second scenario is termed the optimal scenario (OS) based on the model calculation. The study findings exhibit that China is not able to accomplish the 2030 CO2 emission peak objective, under the BS. However, China under the OS shall expectedly accomplish the 2030 carbon peak objective ahead of schedule, while the peak CO2 emissions shall be around 11.28 billion tons. Reportedly, at least 788 million tons of CO2 reduction contrasted with the BS. Furthermore, there is an 80.35% decline in energy intensity as compared to 2005. Consequently, the study results contribute theoretical guidance for the "green recovery" of China's economy and the adjustment of carbon emission reduction's path after the COVID-19 epidemic. Consistent with this, the research method also contributes to the theoretical research on carbon emissions at the national level while extending a new research perspective for the economic and environmental fields.

The influencing factors of carrying capacity of urban electricity infrastructure: Case study of six Chinese mega-cities

As one of important urban infrastructures, urban electricity infrastructure provides electrical resources, which people need in urban daily production and life. Its carrying capacity is vital to the normal operation of urban economic and social systems and affected by many different factors. Investigating the influencing factors of carrying capacity of urban electricity infrastructure is beneficial for grasping its operational status and improving its service level. This paper takes six Chinese mega-cities as examples to analyze the influencing factors of carrying capacity of urban electricity infrastructure by constructing panel regression model. This model is helpful for judging the impact degrees of different factors and finding the main influencing factors. It is an important method of grasping the common reasons of levels of carrying capacity of urban electricity infrastructure of different cities, which provides a major way for obtaining scientific and objective results. The results show that urban industrial structure has the most significant impact on carrying capacity of urban electricity infrastructure; per capita disposable income, per capita output, population density, proportion of non-agricultural population and capital input of urban electricity infrastructure also have significant influences to it. The carrying capacity of urban electricity infrastructure is mainly affected by urban economic and population factors. According to the research results, three policy implications are put forward to raise carrying capacity of urban electricity infrastructure.

Sustainable development in China? A nonparametric decomposition of economic growth

China has undergone significant deviations from the command economy established in 1949, achieving unprecedented success in sustaining high growth. Consequently, numerous scholars have devoted their attention to studying China's economic development. In this study, we contribute to this literature using a new technique to examine China's economic development. This technique utilizes nonparametric directional distance function in the framework of neoclassical growth theory. It avoids the assumptions imposed on parametric production functions that are often short of practical justifications. Our analysis shows that capital and energy inputs account for 75.7% and 20.8% of China's GDP growth during 1985–2020. These figures characterize a capital-driven growth model that is unlikely to be sustainable by conventional wisdom. However, our empirical evidence, obtained through an interactive-fixed effects model, indicates that it is not unreasonable to say that growth in China is government-led rather than capital-driven; the former could be sustained by desirable reforms under strong national leadership while the latter is not.

How to Break the Bottleneck of Potato Production Sustainable Growth—A Survey from Potato Main Producing Areas in China

China is the world’s largest potato producer, and the potato’s role in ensuring food security and rural development is irreplaceable. Therefore, how to achieve sustainable growth in potato production has attracted widespread attention from academia. However, few existing studies have analyzed how to achieve sustainable growth in main potato-producing areas based on farmers’ micro perspectives in terms of both technical efficiency and output elasticity of input factor. This paper investigates the output elasticities of input factors, technical efficiency, and its influencing factors among 398 potato farmers from China’s main potato-producing regions in 2021 to fill this knowledge gap. The stochastic frontier production is applied to calculate the technical efficiency and elasticities of input factors in main potato-producing areas. The Tobit model is utilized to analyze influencing factors of technical efficiency. Our findings indicate that the technical efficiency of the main potato production regions is 0.67, with an efficiency loss of 0.33. And, the output elasticity of land input and labor input is negative, and the output elasticity of capital input is positive. Moreover, the factors that affect the technical efficiency in main potato-producing areas include age, whether to be a village leader, income from other crops, labor input, potato price, and disaster impact. Our findings suggest that the agricultural authorities should strengthen the cultivation of potato producers, control the scale of potato production, and optimize the allocation of input factors.

Analysis of spatial and temporal carbon emission efficiency in Yangtze River Delta city cluster — Based on nighttime lighting data and machine learning

Improving carbon emission efficiency(CEE) is crucial to reducing CO2 emissions. Most studies on CO2 emission are conducted at national and industrial scales, and city-scale studies still need to be included. In order to collect more consistent city- and county-scale CO2 emission data, the sparrow search neural network is trained to fit the energy consumption CO2 emissions with nighttime light in this study. Additionally, using the SBM-DEA model and spatial econometric techniques, the CEE values of 27 cities in the Yangtze River Delta region (YRDR) from 2000 to 2020 were examined from the perspective of total factor inputs. The findings demonstrate that CEE's general trend is erratic and uneven. The CEE value of the YRDR decreases from 0.720 in 2000 to 0.628 by 2020, which means that the YRDR has redundant capital and labour inputs and insufficient economic output. The low value carbon efficiency areas are mainly concentrated in the western part of the YRDR, i.e. the Anhui Province region. Shanghai, Wuxi and Suzhou have high carbon efficiency values of 1.21, 2.08 and 1.00 respectively, and are exemplary cities in terms of carbon efficiency, while the rest of the cities have varying degrees of efficiency loss. Taking Chizhou-Jiaxing as the middle line, the CEE pattern in the YRDR presents a state of “low in the middle and high at each end,” and center of gravity for CEE generally shifts southward. Additionally, the cold-spot areas of CEE are concentrated in the southern part of Anhui Province, and develop a low-efficiency zone with Chizhou, Anqing, and Xuancheng as clusters and spreading outwards. Overall, this paper significantly narrows the spatial scale of carbon accounting studies and the findings can be applied to the formulation of customized carbon reduction policies.

Research on the Influencing Factors and Decoupling State of Carbon Emissions in China’s Transportation Industry

To help achieve the dual-carbon target, based on the LMDI model and C-D production function, this study decomposed the influencing factors of CO2 emissions in China’s transportation industry from 2000 to 2020, then combined the Tapio model to explore the decoupling state. The results showed that (1) from 2000 to 2020, CO2 emissions increased from 263.88 million tons to 957.59 million tons in China’s transportation industry. (2) The transportation intensity effect was the most significant factor to curb the growth in carbon emissions, and the total carbon emissions were reduced by about 364.84 million tons. The capital input effect was the primary factor promoting the carbon emissions, increasing the total carbon emissions by about 899.78 million tons. The effect of energy structure is the factor with the most potential to restrain the increase in carbon emissions in the future. (3) The decoupling state of the transportation industry mainly consists of expansive coupling and weak decoupling. Especially after 2010, the decoupling state remained a weak decoupling and continued to improve. The results can provide lessons for the establishment of policies in China’s transportation industry.

Circular economy in agriculture: unleashing the potential of integrated organic farming for food security and sustainable development

Food is a basic human requirement which sustains the dynamics of the Earth's inhabitants by satisfying hunger, providing nutrition and health, and catering to culture, tradition, and lifestyle. However, the rising global population coupled with climate change including calamities, diseases, conflicts, as well as poor agricultural practices put a huge constraint on the quantity and quality of food. Modern agriculture propelled by the green revolution has somehow been able to meet the food requirements of the ever-increasing population and is heavily dependent on chemical fertilizers, pesticides, and machinery, reducing the quality of food, and simultaneously posing a great risk of environmental quality degradation and genetic diversity reduction. The Integrated Organic Farming System (IOFS) is a novel approach that holds the potential in addressing the challenge of reconciling food production with environmental preservation. As this approach embraces zero or minimal chemical use, adopting the reprocessing and reuse of agricultural residues has led to a sustainable system that can be viewed as the closest approach to nature and a circular economy. However, certain constraints need to be addressed, such as ascertaining the effectiveness of organic fertilizers, the complexities associated with weed management, and the inadequacy of proficiency, financial resources, and technical expertise required to implement the IOFS. Therefore, this study emphasizes the comprehensive benefits that could be derived from IOFS, particularly agroforestry, including efficient food production, improved food quality, biodiversification of crops by the adoption of lesser-known crops to cater to cultural requirements and minimal capital input to achieve environmental sustainability and a carbon neutral economy.

How Do Higher Educated Employees Affect Firms’ Investment Efficiency in China?

ABSTRACT China’s higher education expansion increases firms’ human capital input in terms of the number of educated employees, while its quality undergoes questioning. It is unknown what employees with higher education bring to the firm in China. Considering that investment decision is one of the most important drivers of firm value, we examine how employees with higher education affect firms’ investment efficiency in this paper. We document that the number of employees with higher education increases by 89% from 2008 to 2021. We further find that more employees with higher education are associated with higher investment efficiency through mitigating over- and underinvestment. This association is stronger for firms with high product market competition, low customer concentration, state-owned enterprises, and high senior manager education. Collectively, the results suggest that the information inputs channel, monitoring channel and up-and-down communications channel are likely underlying mechanisms through which higher educated employees affect firms’ investment decisions. Overall, our paper sheds light on the real effect of higher educated employees on firms’ investment efficiency.