High Levels Of Human Capital Research Articles

Exploring the relationship between digital infrastructure and carbon emission efficiency: New insights from the resource curse and green technology innovation in China

Resource-rich regions can fall prey to the resource curse, leading to a decline in carbon emissions efficiency (CEE). But amid this challenge, building digital infrastructure offers an opportunity to find solutions that will pave the way for sustainable development. An indicator evaluation system was constructed to measure the level of digital infrastructure (DI) using panel data for 275 Chinese cities from 2010 to 2020. The impact of DI on CEE is validated using several econometric models. As an innovation, the time lag effect and spatial spillover effects are considered in the analysis. The study found that DI significantly improves CEE, and this effect is more effective in central and resource-based cities, but only significant in southern cities, cities with high levels of marketization, and cities with high levels of human capital. Reducing the resource curse and increasing green technological innovation are important transmission pathways, which are considered to be the key role of DI. Further, the third period of lagged DI has the most significant effect, and there is a positive spatial spillover effect of DI on the CEE of neighboring cities, which is most prominent around 600 km. Policymakers are advised to improve the level of construction of DI, focus on digital management, and utilize the role of DI at the optimal time and distance.

Digital development and rural financial inclusion: Evidence from China

Digital technology has profoundly influenced the development of the financial sector and is of great importance to financial inclusion. This paper employs sub-provincial panel data from 2005 to 2019 to analyse the impact mechanisms of digital economy development on rural finance, exploring the impact of digitalization and overall digital literacy on rural finance. Our findings verify that digitalization has a positive contribution to rural finance, while digital literacy has a significant inhibitory effect on rural finance. This still holds after a series of robustness tests. Subsequent mechanism analysis reveals that digital technology benefits rural finance by optimizing industrial structure and promoting technological progress, while digital literacy accelerates urbanization, leading to the loss of rural labor and thus inhibiting rural finance. Heterogeneity analysis shows that the role of the digital economy in rural inclusive finance is more pronounced in the eastern and central regions. Additionally, higher levels of human capital, economic development, entrepreneurship, and digitalization will further enhance the impact of the digital economy on rural inclusive finance. This study offers a new pathway for the realization of financial inclusion and a theoretical reference for financial development in rural areas. Our empirical analysis also provides new perspectives and insights for the formulation of policies and measures to coordinate the development of various elements of digital finance and cope with the impact of the digital economy on rural finance.

Flattening of government hierarchies and growth of farmers’ income

Continuously raising farmers’ income is important for poverty reduction. In a multilevel government system, institutional arrangements can influence the role of grassroots governments in economic and social development. Based on the rural statistical data of 743 townships in Province A in central China from 2001 to 2012, we use the difference-in-differences (DID) approach to investigate the effect of the reform of flattening governmental hierarchy at the township level on increasing farmers’ income. We find that the reform of grassroots flattening hierarchies significantly promotes the growth of farmers’ income. Specifically, in the face of economic-assessment pressure from the higher-level government and the incentives of fiscal excess revenue in the reform, the township government will make full use of the greater administrative power and resources endowed by the reform to vigorously attract investment to increase the number of enterprises and provide farmers with more non-agricultural employment opportunities, thus raising their wage income. Moreover, this reform’s income-increasing effect is more obvious in townships that are closer to the county seat and have more convenient transportation, a higher level of human capital, and a stronger ability to exercise administrative power.

Smarter and Cleaner? The Carbon Reduction Effect of Smart Cities: A Perspective on Green Technology Progress

In the context of the global climate change problem intensifying due to a dramatic increase in carbon emissions, smart cities, as a topical application of digitalization and intelligence, have become a new urban governance mode for countries, which helps to achieve sustainable development. This research studies the relationship between smart city construction (SCC) and carbon dioxide emissions based on the differences-in-differences model (DID) and propensity score matching (PSM) to promote China to achieve dual carbon goals and high-quality development. The findings are as follows: (a) SCC could promote carbon emission reduction by reducing urban carbon dioxide emissions by an average of 11.4%, which also has significant long-term dynamic effects. Specifically, SCC has more obvious emission reduction effects on activities, such as industrial production and waste treatment. (b) Mechanism verification shows that green technology progress is a significant booster for the carbon reduction effect in SCC. The pilot project can increase output of green patents, which helps transfer production mode and consumption patterns in an environmentally friendly manner. SCC could increase the total factor productivity (TFP) through the rational allocation and efficient use of resources, and thus reducing carbon emissions. (c) Research on city heterogeneity shows that a high level of human capital, material, and financial resources can provide support for smart cities to better achieve the carbon reduction effect. Among them, material resources have the best carbon reduction effect in the process of SCC, which could reduce carbon dioxide emissions by about 6.6–17.7%. This study is useful for policymakers to continuously and dynamically adjust urban development strategies in the future, to achieve a balance between socioeconomic prosperity and environmental sustainability.

Child Labor, Corruption, and Development

Abstract Employing an overlapping generations model with endogenous education choice and corruption, we investigate how child labor and corruption influence human capital accumulation and development. We show that multiple steady states exist in the economy. One steady state has a high level of human capital, while the other has a low level of human capital. In the steady state with a low level of human capital, child labor and corruption exist, fertility and child mortality rates are high, and the welfare level is low. Conversely, in the steady state with a high level of human capital, child labor and corruption are diminished, fertility and child mortality rates are low, and welfare is high. In addition, we show that it is difficult to steer an economy away from a poverty trap with child labor and corruption because bureaucrats of the current generation are opposed to policy changes, such as the reinforcement of monitoring and penal regulations. However, we highlight the possibility for the government to develop the economy in the poverty trap by implementing an education policy, which is Pareto improving.

Digital economy as a catalyst for low-carbon transformation in China: new analytical insights

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.

The impact of new digital infrastructure on green total factor productivity

As a new engine driving economic development, new digital infrastructure plays a significant role in enhancing green total factor productivity. Based on 2011–2020 panel data covering 30 Chinese provinces, this study empirically investigates the effects and mechanisms of new digital infrastructure on green total factor productivity. The results show that new digital infrastructure can significantly improve regional green total factor productivity, and this conclusion remains valid after a series of robustness tests and regressions of instrumental variables. Further mechanism research shows that new digital infrastructure indirectly promotes the growth of green total factor productivity by improving capital misallocation and driving technological innovation, while there is no mediating mechanism of labor misallocation. In addition, there is significant heterogeneity in the impact of new digital infrastructure on green total factor productivity. Especially during periods of high government attention, in the eastern regions, and in areas with higher levels of human capital, the positive incentive effect of new digital infrastructure is more significant. This study provides empirical evidence and policy references for promoting and amplifying the green growth effects of new digital infrastructure.

Bicycle use in the university community: Empirical analysis using MobiCampus-UdL data (Lyon, France)

Promoting sustainable mobility systems by encouraging the use of the bicycle as a transport mode is now a public policy objective. This political will is also pursued in France where the modal share of cycling is relatively low. However, young people and those with a high level of human capital, such as members of the university community, are observed to be more advanced in their adoption of cycling. An understanding of how cycling is used by university students and staff would therefore help to inform public decision-making and support more efficient targeted policies to develop this mode of transport. Using original data from the MobiCampus-UdL project, the aim of this article is to analyze the determinants of bicycle use by the university community at the University of Lyon, France. Two multivariate logistic regression models are estimated on the subsamples of students and staff: one explaining the probability of using the bicycle as an exclusive mode of transport to get to the campus and the other explaining the probability of using the bicycle in combination with other modes. Our results suggest that while socio-demographic characteristics have little influence within our two relatively homogeneous subsamples, access to mobility resources and the spatial characteristics of the campus and place of residence are crucial. We also find that access to bicycles is an important determinant of the utilization of cycling. Given that the adoption of cycling is still very low, our findings justify policies to increase the availability of bicycles and subsidize their purchase. More specifically, our results suggest that access to a shared bike station on campus encourages the exclusive use of bicycles by students and staff but has no effect when used in combination with other modes. On the other hand, good accessibility to public transport, whether from home or from campus, does not reduce the use of bicycles by either sub-population, either exclusively or in combination. Furthermore, while living far from the city center is an obstacle to the exclusive use of the bicycles, especially for staff, it does not in any way prevent their use in combination with other modes, such as the train. These results open up new avenues for anticipating the development of intermodality between public transport and cycling.

The Impact of Artificial Intelligence Development on Urban Energy Efficiency—Based on the Perspective of Smart City Policy

China’s economy is stepping into a new stage of high-quality development. The shift not only marks the optimization and upgrading of the economic structure, but also reflects the in-depth implementation of the concept of sustainable development. In this context, the development of AI technology is playing an important role in balancing economic growth and ecological protection with its unique advantages. This paper empirically studied the impact of AI development on urban energy efficiency by constructing panel data for 282 prefecture-level cities from 2006 to 2019 and then using the super-efficiency SBM model based on non-expected outputs to evaluate the urban energy efficiency indicators of prefecture-level cities. It was discovered that the development of AI had a key influence on increasing urban energy efficiency and the optimization of the energy structure by speeding up green technology innovation and digital economy development, which in turn improved urban energy efficiency. In terms of heterogeneity analysis, AI development had a greater impact on urban energy efficiency in the eastern region, which has higher levels of human capital, financial independence, and government intervention. This study combined the smart city pilot policy with a multi-period DID model, based on the treatment of endogeneity issues, in order to perform a parallel trend test and investigate further the effects of policy implementation on the advancement of AI in the context of improving urban energy efficiency. Accordingly, to achieve green and sustainable urban development, the relevant government departments should increase funding for AI research and development, pay attention to the introduction and cultivation of professionals, establish a platform for international exchanges and cooperation between AI and energy management, and continue to advocate for the pilot development of smart cities to increase urban energy efficiency.

Return Migration and Entrepreneurship: Does Human Capital Matter?

Return migration is a topic of considerable interest in scholarly literature, with many studies suggesting that returning migrants can impact the economic development of their home country through capital accumulation and entrepreneurship. This study seeks to examine the entrepreneurial intentions of return migrants and the influence of formal education and training on their entrepreneurial tendencies. Utilizing data from the National Workforce Survey (Sakernas) in 2020 and employing logistic regression analysis, the study revealed that formal education tends to steer returning migrants towards the formal sector rather than entrepreneurship upon their return. Conversely, while training was found to potentially increase the likelihood of entrepreneurship, the effect was not statistically significant. Additionally, individual characteristics such as age, gender, and marital status were found to significantly influence entrepreneurial intentions, with older individuals, females, and married individuals exhibiting a higher propensity for entrepreneurship among return migrants. These findings contribute to the existing literature by highlighting that, on average, return migrants in Indonesia tend to have relatively low levels of education, and higher levels of human capital may diminish their interest in entrepreneurship.

Effects of foreign direct investment in services on input imports of manufacturing firms: Evidence from China

AbstractThis study investigates the causal effects of foreign direct investment (FDI) in services on the input imports of manufacturing firms. We exploit a plausibly exogenous policy of FDI liberalization in services in China to construct an instrumental variable for FDI in services and address endogeneity concerns. The results demonstrate that FDI in services positively impacts both the value and sophistication of input imports for manufacturing firms. Mechanism analysis reveals that FDI in services enhances firms' input imports through reductions in production costs, relief from financial constraints, and decreased remote coordination costs. The positive effects of FDI in services are particularly pronounced for firms with lower initial productivity and higher levels of human capital.

Combining or Separating Management and Control: Effects on the Performance of French Listed Companies with Monist Structures

This study of the determinants of the choice to combine management and control functions, and then the impact of this choice on the performance of large French companies with monistic structures, relies on agency, entrenchment, stewardship, and substitution theories. The results, based on data from 2011–2021, show that the decision to combine functions depends on the human capital of the board of directors and the CEO’s seniority; independent directors and the proportion of capital held by the executive instead favor separation. This choice has no influence on the company's financial performance. However, when the proportion of independent directors is high or the board possesses a high level of human capital, combining the management and control functions benefits the company's financial performance.

Doğrudan Yabancı Yatırım-Gelir Eşitsizliği Bağlamı ve Özümseme Kapasitesinin Rolü: Bir Sonlu Karışım Model Yaklaşımı

The income inequality-FDI nexus is ambiguous on theoretical grounds, as several opposing mechanisms relating FDI to inequality are put forward in the theoretical literature. Empirical studies also produce mixed results. It might suggest a heterogeneous response of income inequality to FDI inflows conditional on distinct characteristics in recipient countries. Although unobserved country-specific characteristics are considered by fixed or random effects modeling in panel regression applications, some studies incorporate observable country-specific factors such as absorptive capacity as a conditioning factor to explain the reasons for conflicting findings. Therefore, the existing studies employ threshold panel regression models that split the sample based on the outcome (supervised learning). Differently from the previous ones, this study takes a distinct empirical strategy by adopting a finite mixture model (FMM) as an unsupervised model-based clustering technique to scrutinize distributional heterogeneity in the linkage between FDI and income inequality. The study then questions the role of absorptive capacity as a conditioning factor with varying effects on the inequality of FDI. Our empirical results, based on panel data from 26 developing countries between 2004-2019, explain the varying effects of FDI on income inequality according to three different country clusters. FDI improves income inequality in the first cluster, while it does not significantly affect income inequality in the second and deteriorates income inequality in the third cluster. Furthermore, our empirical findings reveal that a country's high absorptive capacity, especially its high level of human capital, prevents the negative impact of FDI on income distribution.

Управление человеческим капиталом промышленного предприятия

Effective management of a modern industrial enterprise involves solving complex technological problems, competent management of financial flows, work with innovations, their implementation and movement, which is possible only if the intellectual resource component of the enterprise's activities and the availability of high-level human capital are included. The high level of human capital of an industrial enterprise contributes to a rapid response to changes, the spread of innovations, the growth of added value, increased labor productivity, a high culture of communication and active communications. There is a lack of sufficient research in Russia on the application of the concept of human capital in the practice of managing industrial enterprises, the subsystem of human capital management has not been allocated and structured in enterprise management systems, employers do not always recognize the expediency of investing in human capital. The solution of these problems is facilitated by the awareness of the expediency of investments in human capital and the allocation of their main directions – investments in additional professional education, the creation of comfortable working conditions, maintaining the physical health of employees, the formation and development of corporate spirit. Human capital management at an industrial enterprise at the individual and corporate levels can be carried out using the proposed management tools. The construction of the human capital management system of an industrial enterprise is facilitated by the allocation of human capital characteristics and human capital management subsystems. An example of the adaptation of the proposed human capital management system to the activities of a specific industrial enterprise (Astrakhan Gas Processing Plant LLC). As s a result the structuring of human resource management functions aimed at formation and increment of human capital is presented.

Ecosystems of doing business and living standards: a configurational analysis based on Chinese cities

Purpose This paper aims to explain the causal complexity between ecosystems of doing business and living standards based on the theoretical model of the ecosystem of doing business proposed by Li (2019) and Du et al. (2020). By integrating ecological theory, transaction cost theory and institutional logics theory, this study explored effective ecosystems of doing business that achieve high living standards and explained the interpretive mechanisms behind different ecosystems of doing business. Moreover, this study also analyzed whether there were any necessary elements that lead to high living standards and discussed how the interactions between these elements influence carrying capacity and transaction costs from government logic and market logic, thus affecting living standards. Design/methodology/approach In this study, fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) were combined to analyze the data from the 2020 China City Statistical Yearbook, covering the main socioeconomic statistical data of cities at all levels in 2019. Findings This study found that no individual factor of the ecosystems of doing business was necessary to achieve high living standards, but the high level of human capital, innovation capacity, financial access and market demand play a significant role in achieving high living standards. Furthermore, two effective types of ecosystems of doing business lead to high living standards, namely, market dominance (government’s “invisible hand” or “nudging hand”) and government–market logic mutualism/symbiosis (government’s “helping hand”). Originality/value First, this work found that individual elements were not a necessary condition for high living standards, not only in kind but also in degree, complementing fsQCA with NCA, which indicates that environmental elements can be substituted by others. Second, this study considered the complex effects and explained the mechanisms behind different ecosystems of doing business, drawing on ecological theory, transaction cost theory and institutional logics theory from a configurational perspective. This study deepened the theories’ applications in the field of living standards and further discussed the elements interactions. Third, this study introduced configurational perspective and QCA into living standards research and adopted a mixed method that combines fsQCA and NCA to analyze the causal complexity between ecosystems of doing business and people’s living standards.

Numeracy selectivity of Spanish migrants in colonial America (sixteenth–eighteenth centuries)

AbstractSince the arrival of Christopher Columbus in the so‐called New World in 1492, hundreds of thousands of Spaniards settled in Central and South America. This paper assesses the skill selectivity of Spanish migrants who went to Hispanic America during the sixteenth to eighteenth centuries for the first time. The age‐heaping method is employed to estimate numeracy levels as a proxy for human capital. With a database of 33 929 individual observations, the findings show that Spaniards who left the country to settle in the Spanish territories were positively self‐selected. Additionally, differences are observed in the human capital of those who chose to settle in Mexico, who had a higher level of numeracy, than those who chose Peru. These differences might be due to the viceroyalty structure and educational institutions that encouraged the emigration of people with greater human capital to Mexico. Finally, when the level of numeracy of Spaniards in Hispanic America is compared with the numeracy of the total population, emigrants still had higher levels of human capital.

The Energy-Saving Effect of E-Commerce Development—A Quasi-Natural Experiment in China

This study provides a viable path to save energy by means of e-commerce development. Taking the national e-commerce demonstration cities (NEDC) pilots policy implemented in China as a quasi-natural experiment, based on the city panel data from 2006 to 2019, this study applies the multi-period difference-in-difference (DID) method to evaluate the effect of NEDC on energy saving in pilot cities. The empirical results suggest that the NEDC policy obviously contributes to energy conservation. The treated cities reduced energy consumption by 14.2% as a result of the implementation of NEDC, relative to the untreated cities. The conclusions remain valid after conducting robustness tests such as placebo test, instrumental variables regression, propensity score matching-difference-in-difference (PSM-DID), and synthetic difference-in-difference (SDID). The NEDC achieves energy-saving effects through technological innovation, industrial restructuring, and economic agglomeration. Furthermore, the heterogeneity analysis indicates that, in cities with high levels of human capital, well-developed information infrastructure, non-resource-based cities, and favorable business environments, the impact of NEDC on energy saving is more significant. Analysis of spatial effects shows that the implementation of NEDC has negative externalities, increasing energy consumption in the surrounding area. In the context of the digital economy, this paper presents new insights on the relationship between e-commerce and energy consumption and provides policy direction for countries looking for energy-saving solutions.

The Impact of Rural Enterprise Park Policy on the Income of Rural Residents: Evidence from China

Improving the income of rural residents plays an important part in sustainable rural development. Using a difference-in-difference (DID) approach and Chinese counties’ data from 2014 to 2019, this paper evaluates the effects of the rural enterprise park policy on the income of rural residents. We find that the policy significantly promotes rural residents’ income, and a series of additional tests suggest that the effects appear robust. We also find that stimulating entrepreneurial activities serves as a channel through which the policy affects rural incomes. Finally, the policy effects are mainly significant for counties with a higher level of human capital, a younger demographic age structure, and a higher level of financial development.

Do foreign and domestic venture capital firms differ in replacing CEOs of portfolio companies?

ABSTRACT Using a sample of 5,383 investment events of venture capital firms (VCs) investing in Chinese companies between 1997 and 2017, we investigate how levels of human capital of chief executive officers (CEOs) of portfolio companies affect tendencies of foreign and domestic VCs to replace CEOs. We find that domestic and foreign VCs are similar in that they are both less likely to replace CEOs of their portfolio companies if CEOs have higher levels of human capital. Furthermore, we find that domestic and foreign VCs exhibit significant differences in CEO replacement when not considering CEO human capital or when CEOs have lower levels of human capital. Results are consistent with our hypotheses that foreign VCs rely on CEO human capital as a stronger quality signal than domestic VCs, because they have more difficulty monitoring CEOs’ post-investment performance. On the contrary, the geographical and cultural proximity of domestic VCs enables them to obtain information other than CEO human capital, such as CEOs’ social skills, potential, entrepreneurial passion, and charisma, to make replacement decisions. The study advances our understanding of the behavioral differences between domestic and foreign VCs in the post-investment management process.

Robotization, employment, and income: regional asymmetries and long-run policies in the Euro area.

This work correlates the impact of robotization on employment and households' income at the regional scale with the level of investment in R&D and education policies. This kind of policy, by raising the qualitative and quantitative levels of human capital, contributes to improving the complementarity effect between humans and robots, thus mitigating the substitution effect. To this end, we compute the Adjusted Penetration of Robots (APR) (a metric used to measure the extent to which robots are being used in a particular industry or sector) at the sectoral level, combining the International Federation of Robotics database for the stock of robots, EUROSTAT Regional database, and the STructural ANalysis database on 150 NUTS-2 regions of the Euro area. We then perform a spatial stacked-panel analysis on the investment in R&D and education level. Results supports the idea that regions that invest more in R&D and have higher levels of human capital can turn the risk of robotization into an increase in both income and "quantity of work," by enhancing complementarity between robots and the labor force. On the contrary, regions investing less in R&D and having lower levels of human capital may suffer a reduction in households' disposable income.