Dynamic Panel Threshold Model Research Articles

International Trade as a Double-Edged Sword: The Perspective of Carbon Emissions

Due to the rapid growth of fossil energy consumption, countries worldwide have paid considerable attention to reducing carbon emissions. Moreover, with economic globalization and trade liberalization, exploring the relationship between foreign trade and carbon emission reduction has become increasingly critical. Exploring this relationship can aid in establishing suitable recommendations for global carbon emission reductions. This paper uses a spatial econometric model and a dynamic panel threshold model to empirically test the spatial effect, nonlinear effect, and heterogeneous effect of foreign trade on global carbon emissions. All the above models are based on the construction of the economic weight matrix of different countries. The results reveal that 1) carbon emissions in various countries exhibit with significant spatial spillover in the overall spatial context; 2) foreign trade has a significant role in promoting carbon emissions in local and similar economic areas, but it has an apparent dual-threshold effect on economic development; and 3) there are significant differences in the impact of foreign trade on carbon emissions in different regions and different periods. Therefore, in the process of global economic integration, based on their development stages and comparative advantages, countries can focus on overall planning and coordination to promote the optimal allocation of resources and reduce carbon emissions.

Towards the environmentally friendly manufacturing industry–the role of infrastructure

Infrastructure development and the green transition of manufacturing are two crucial issues concerning the national economy and people's livelihood. However, not many literatures discuss the influencing mechanism connecting the two. This paper starts from a new research perspective of infrastructure development and explores the potential ways to improve manufacturing's ETFP. The empirical results indicate that the infrastructure development has indeed improved the green development level (GDL) of manufacturing. This impact is heterogeneous in terms of different infrastructure types and planning periods. Besides, the completed infrastructure helps the formation of an environmentally friendly development model, while the new infrastructure investment could generate negative environmental externalities. Through mechanism analysis, we found that infrastructure mainly promotes the GDL through the two tracks: scale effect and energy structure adjustment. The technological progress and industrial structure adjustment did not play the expected mediating impact. The dynamic panel threshold model results proved that with the expansion of the scale effect and the optimization of energy consumption structure, the role of infrastructure in promoting the manufacturing's GDL could be stronger. Some policy recommendations are proposed to provide a reference for the infrastructure programming and the green transformation in the manufacturing industry.

Asymmetric effects of China’s tourism on the economy at the city level: a moderating role of spatial disparities in top level tourist attractions

ABSTRACT This study complements the tourism literature by proposing an asymmetrical effect of the tourism-led growth hypothesis on the city-level economy using panel data from 331 cities in China from 2004 to 2015 (3,972 observations). The results, based on an augmented Solow model and the system-generalized method of moments (GMM), reveal that the impact of tourism on city-level economic growth is indeed asymmetric and heterogeneous, depending on the presence of top-level attractions (TL), which are proxied by the World Heritage Sites or AAAAA (5A) scenic spots. The dynamic panel threshold model’s results also corroborate the asymmetric threshold effect of tourism on city-level economic growth. Tourism, in particular, has facilitated positive and significant economic growth in cities with TL but has had an uncertain and statistically insignificant impact on cities without it. The findings indicate that the validity of tourism-led growth depends on the availability and number of TL in each city, which serve as a moderator. As a result, we confirm tourism’s asymmetric effect and spatial heterogeneity on urban economic growth.

The impact of R & D elements flow and government intervention on China’s hi-tech industry innovation ability

ABSTRACT Despite the established correlation between research and development (R&D) investment and innovation capability, the correlation between China’s hi-tech industry R&D elements flow and its innovation capability remains unclear. This thesis aims to investigate the correlation between R&D elements flow and China’s hi-tech industries’ innovation ability by using appropriate spatial econometric methods and dynamic threshold panel model on account of the panel data of 30 hi-tech industries in Mainland China during 2004–2016. The estimation results of the spatial autoregressive model revealed that China’s hi-tech industry innovation capability exerted significant spatial correlation and spatial spillover effects. However, the hi-tech industry innovation capability in the surrounding areas exerted a significant reverse spatial spillover effect on this area. Both R&D personnel flow and R&D capital flow have significantly promoted China’s hi-tech industry innovation capabilities in recent years. Government intervention exerted a significant opposite regulatory impact on the correlation between R&D factor flow and innovation capability of China’s hi-tech industries. Furthermore, the estimation results of the dynamic threshold panel model revealed that nonlinear impacts of R&D personnel flow and R&D capital flow on innovation ability of China’s hi-tech industries depended on the specific level of government intervention.

Is there a nonlinear relationship between financial development and income inequality in Africa? Evidence from dynamic panel threshold

Using dynamic panel threshold model, this work examines the nonlinear relationship between financial development and inequality in Africa. The study introduces a robust measure of financial development into the literature. Using 40 African countries selected from high-income, middle-low and low-income countries, the study tests the new financial development indicator. The empirical results validate the existence of threshold levels of financial development that addresses inequality among African countries. Aggregately, financial development tends to promote inequality in high-income countries and reduces the same in low and middle-income countries. Hence, policymakers, in African countries, should be aware of the threshold level of financial development that imparts income inequality. Also, for financial development to have an enormous impact on inequality, all financial development pillars of depth, stability, access and efficiency must be simultaneously accorded a due place in policymaking by practitioners.

Nonlinear impacts of information and communications technology investment on industrial structure upgrading: the role of marketization

ABSTRACT This paper employs the dynamic panel threshold model to estimate the industrial upgrading effect of information and communications technology (ICT) investment in view of the role of marketization. Based on provincial-level data from 2008 to 2016 in China, the empirical results show that under a better institutional environment of marketization, ICT investment has an increasing marginal effect on the upgrading of the industrial structure. This implies that the diminishing marginal effect of ICT investment is compensated by the promotion of marketization. Overall, with higher-quality development of the market economy, ICT investment will play a more active role in upgrading the industrial structure.

Trade openness and green total factor productivity: testing the role of environment regulation based on dynamic panel threshold model

Trade openness and green total factor productivity: testing the role of environment regulation based on dynamic panel threshold model

The effect of energy patents on China's carbon emissions: Evidence from the STIRPAT model

China has been the world's largest carbon emitter since 2009. Thus, there is considerable pressure on it to control its carbon emissions. Technological progress is a factor that most influences the reduction of carbon emissions. Unlike existing literature, this study narrows the technological progress to the energy field and focuses specifically on energy patents. Additionally, as there is significant heterogeneity among different types of energy patents, we classify them based on performers and purposes. Conventional estimators including Driscoll and Kraay, fixed effects with instrumental variables, and difference generalised method of moments are applied to estimate the effect of energy patents on carbon emissions which was based on the stochastic impact by regression on population, affluence, and technology (STIRPAT) model. The results indicate that energy patents are not a powerful instrument for controlling carbon emissions. However, energy patents originating from enterprises and scientific institutions exert a positive effect in reducing carbon emissions, and energy patents originating from higher education institutions enhance these effects. The utility type of energy patents significantly reduces carbon emissions, but the creation type offsets this positive effect. Further, the dynamic panel threshold model is employed in which human capital is incorporated as the threshold variable. The estimates indicate that carbon emissions can be positively reduced by increasing the level of human capital.

Does too much finance suppress a country’s participation in the global value chains?

ABSTRACT Using a dynamic panel threshold model, we find a nonlinear effect of financial development on participation in the global value chains for 92 countries. The effect is positive below a threshold and turns negative above it. We provide evidence supporting our explanation that when a country’s financial system develops to a certain level, it serves foreign buyers by engaging more in outward foreign direct investments instead of enhancing its participation in the global value chains.

Polycentric or monocentric, which kind of spatial structure is better for promoting the green economy? Evidence from Chinese urban agglomerations.

The green economy has gained worldwide attention, especially in the urban agglomerations where population and economic activities are highly concentrated. However, what kind of urban agglomeration spatial structure is more conducive to promoting the green economy? No clear conclusions have been made. To bridge this gap, by employing the data of 16 urban agglomerations in China in 2003-2017 and a comprehensive analytic framework including dynamic panel threshold model, this paper studies the impact of urban agglomeration spatial structure on the green economy and the three subsystems of green economy to shed light on which kind of urban agglomeration spatial structure better drives the green economy. The main findings are shown below: (1) urban agglomeration spatial structural evolution is closely related to green economy, while in the research period, most urban agglomerations are not located in the optimal range of the spatial structure that drives the green economy. (2) Towards polycentric spatial structure is contributive to green economic growth; however, the excessively polycentric could not benefit green economy. (3) The evolution of urban agglomeration spatial structure exerts heterogeneous impacts on the three subsystems when green economy is decomposed into economic subsystem, resources subsystem, and environmental subsystem. Towards polycentric is more conducive to the improvement of economic subsystem and resource subsystem, while the tendency to monocentric drives the environmental subsystem. (4) Lastly, the conclusions enlighten the urban agglomeration development planning and spatial mode for approaching a better performance in green economy.

Technological progress and metal resource consumption in the electricity industry—A cross-country panel threshold data analysis

This paper introduces a dynamic panel threshold model to empirically investigate whether the effects of technological progress on metal consumption in the electricity industry differs by the change of industrial structure upgrading level (INSTRU). We consider a panel data set including 41 countries over the period 2000–2016. The estimated results suggests 2.72, 2.39 and 2.84 as the average threshold parameters of INSTRU for basic ferrous metals (Iron and Chromium), basic non-ferrous metals (Aluminium, Copper and Nickel) and critical metals (Indium, Neodymium and Dysprosium) respectively. When INSTRU is lower than the corresponding threshold, domestic technological progress (LnSRD) and foreign technological spillover progress (LnSIM) significantly promote the consumption of the above-mentioned metals. However, when INSTRU is higher than the corresponding threshold, LnSRD and LnSRD will reduce the consumption of basic ferrous metals such as Iron and Chromium, but will continue to increase the consumption of critical metals such as Indium, Neodymium and Dysprosium. Last, we confirm that LnSRD play a more important role in changing metal consumption structure in the electricity industry than that of LnSIM. These findings are of great significance to government policies that ensure the transition to low-carbon electricity systems.

Does environmental pollution promote China's crime rate? A new perspective through government official corruption

Environmental pollution and its effects have attracted increasing attention, but few studies have examined the impact of environmental pollution on the crime rate. This study adopted panel data of 30 provinces in China for the period 2005 to 2016 to examine the relationship between environmental pollution and the crime rate. In addition, a mediating effect model is used to study the mechanism through which environmental pollution influences the crime rate. This study considers the threshold effect of government official corruption on the link between environmental pollution and the crime rate. The generalized method of moments and a newly developed dynamic threshold panel model are employed to manage potential endogeneity problems. The estimation results indicate that environmental pollution significantly promotes China's crime rate. Environmental pollution can indirectly affect the crime rate through residents' health level, education level and inequality. The magnitude of the effect of environmental pollution on the crime rate will be greater after corruption reaches the threshold value. Regional heterogeneity analysis shows that a significant positive impact of environmental pollution on the crime rate exists in the eastern and western regions of China but not in the middle region. Based on the findings, we propose a series of policy implications to reduce criminal activities in China from the perspective of environmental pollution.

Does Environmental Pollution Promote China’s Crime Rate? A New Perspective Through Government Official Corruption

Environmental pollution and its effects have attracted increasing attention, but few studies have examined the impact of environmental pollution on the crime rate. This study adopted panel data of 30 provinces in China for the period 2005 to 2016 to examine the relationship between environmental pollution and the crime rate. In addition, a mediating effect model is used to study the mechanism through which environmental pollution influences the crime rate. This study considers the threshold effect of government official corruption on the link between environmental pollution and the crime rate. The generalized method of moments and a newly developed dynamic threshold panel model are employed to manage potential endogeneity problems. The estimation results indicate that environmental pollution significantly promotes China’s crime rate. Environmental pollution can indirectly affect the crime rate through residents' health level, education level and inequality. The magnitude of the effect of environmental pollution on the crime rate will be greater after corruption reaches the threshold value. Regional heterogeneity analysis shows that a significant positive impact of environmental pollution on the crime rate exists in the eastern and western regions of China but not in the middle region. Based on the findings, we propose a series of policy implications to reduce criminal activities in China from the perspective of environmental pollution.

Institutional Quality and Income Inequality in Developing Countries: A Dynamic Panel Threshold Analysis

This study investigates whether there is an institutional quality threshold effect on income distribution. We employ the dynamic panel threshold model developed by Kremer et al. (2013: Empirical Economics 44(2): 861–878) and a panel of both developing and advanced countries from 1995 to 2017. Our findings suggest the inequality-reducing effect of institutional quality is disproportionate. More specifically, we find two-pronged results: (i) when institutional quality is measured by World Governance Indicators, we find quadratic effect for advanced countries, but a monotonic negative effect for developing countries; (ii) when the International Country Risk Guide-based measure of institutional quality is used as the threshold variable, we find a Kuznets inverted U-shaped relationship between institutions and income inequality for both advanced and developing countries. The results also show a higher threshold value for developing countries compared to advanced economies. These results are robust to both measurement and endogeneity issues. The results have interesting policy implications for income inequality in developing economies.

Does internet development improve green total factor energy efficiency? Evidence from China

Information and communication technology supported by the internet has become an important driving force that promotes the intelligent development of environmental governance in China. Using Chinese provincial panel data for the period 2006–2017, this study investigates whether the internet has improved China's green total factor energy efficiency (GTFEE) using a dynamic spatial Durbin model, mediation effect model and dynamic threshold panel model. The empirical results indicate that the GTFEE has a significant positive spatial correlation. Internet development can not only directly improve local GTFEE but also improve GTFEE in neighboring regions. After accounting for potential endogeneity, this conclusion is still valid. Meanwhile, internet development can indirectly improve regional GTFEE by reducing the degree of resource mismatch while enhancing GTFEE by improving regional innovation capabilities and promoting industrial structure upgrades. In addition, the regression results of the dynamic threshold model show that there is a nonlinear relationship between the influence of the internet development and GTFEE. Specifically, due to an increase in the degree of labor resource mismatch and capital resource mismatch, the impact of the internet on GTFEE has gradually decreased, and this effect has gradually increased with the improvement of regional innovation capabilities and the industrial structure.

Energy-saving R&D and carbon intensity in China

China's domestic research and development (R&D), an important source of technological progress, is considered one of its most effective implements for cutting carbon intensity. However, few studies have yet focused on R&D in the energy field, or even explored the heterogeneity within energy-saving R&D. Considering its potential significance in yielding more effective environmental policies, this work focuses particularly on energy-saving R&D, which is representative of energy-saving technological progress, and categorizes these R&D activities according to actors and purposes to identify their heterogeneity. A series of estimators, including instrumental variable estimators, a propensity score matching and difference-in-differences estimator, and the generalized method of moments, are applied first. To obtain more detail on how energy-saving R&D influences carbon intensity, a two-step analysis and dynamic panel threshold model are then employed. Since enterprises' motivation for technological change arises from a profit-maximizing purpose, we hypothesize that the activities of enterprises, as opposed to universities or individuals, could produce more noticeable impacts on carbon intensity reduction. We further hypothesize that utility-type R&D activities are, in practice, more useful in cutting carbon intensity than invention-type R&D and that the technology absorptive capacity plays an important role in the effectiveness of energy-saving R&D activities on carbon intensity. Empirical results based on a Chinese provincial dataset (2000–2016) validate all our hypotheses, which enables us to provide policy suggestions for carbon intensity reduction in China.

The impact of outward foreign direct investment on green innovation: the threshold effect of environmental regulation.

Outward foreign direct investment (OFDI) in an open economy has gradually become an important source of green innovation (GI). With the rapid development of China's OFDI, this research studies the impact of OFDI on the country's GI, employing panel data of 30 provinces from 2006 to 2017. We first use the Super-SBM model to measure GI performance and then test the impact of OFDI on GI with the system GMM model. Evidence finds that the negative impact of OFDI on GI is not significant on the whole, but the results of regional regression show that impact of OFDI on GI exhibits obvious regional differences. We then utilize the dynamic threshold panel model to determine the non-linear relationship between OFDI and GI through the perspective of environmental regulation in order to avoid the bias caused by ignoring the impact of institutional factors and time dynamic change. After dividing environmental regulations into command control environmental regulation and market incentive environmental regulation, the research results show that the double threshold effects of both environmental regulations are significant. Command control environmental regulation does not play a role in promoting the effect of OFDI on GI. When the intensity of market incentive environmental regulation is low, OFDI negatively affects GI. Moreover, only when the market incentive regulation shows high intensity can OFDI significantly promote GI. With the continuous growth of China's OFDI, it is therefore necessary to determine the appropriate environmental regulation to improve the reverse spillover effect of OFDI enterprises on the country's GI.

How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China

Green development is critical for China's economic transformation. Enhancing green total factor energy efficiency (hereafterGTFEE) is vital to emission reduction and to win-win industrial development. This study uses the panel data of 30 Chinese provinces for the period 2005–2016 to investigate the relationship between environmental regulation and China's GTFEE. The spatial Durbin model is employed to control for the possible spatial spillover effect. A dynamic threshold panel model that can effectively address the endogeneity problem and regional heterogeneity is utilized to examine the potential non-linear relationship between environmental regulation and GTFEE under different conditions of environmental decentralization. The estimation results indicate that there is a significant U-shaped relationship between environmental regulation and China's GTFEE. With the further expansion of environmental decentralization, the local government's autonomous choice of pollution control is improved. The improvement of environmental decentralization can lead to negative moderating effect of environmental regulation on GTFEE. Additionally, the regression results of dynamic threshold model show that environmental decentralization can increase the negative influences of environmental regulation on GTFEE. Interestingly, the non-linear impact of environmental regulation on GTFEE is dependent on the specific type of environmental decentralization. Higher degree of environmental decentralization can lead to an increase in the restraining effect of environmental regulation on GTFEE. However, an improvement in the decentralization of environmental supervision and environmental monitoring can increase the negative influences of environmental regulation on GTFEE.

Does Internet Development Improve Green Total Factor Energy Efficiency? Evidence from China

Information and communication technology supported by the internet has become an important driving force that promotes the intelligent development of environmental governance in China. Using Chinese provincial panel data for the period 2006–2017, this study investigates whether the internet has improved China’s green total factor energy efficiency (GTFEE) using a dynamic spatial Durbin model, mediation effect model and dynamic threshold panel model. The empirical results indicate that the GTFEE has a significant positive spatial correlation. Internet development can not only directly improve local GTFEE but also improve GTFEE in neighboring regions. After accounting for potential endogeneity, this conclusion is still valid. Meanwhile, internet development can indirectly improve regional GTFEE by reducing the degree of resource mismatch while enhancing GTFEE by improving regional innovation capabilities and promoting industrial structure upgrades. In addition, the regression results of the dynamic threshold model show that there is a nonlinear relationship between the influence of the internet development and GTFEE. Specifically, due to an increase in the degree of labor resource mismatch and capital resource mismatch, the impact of the internet on GTFEE has gradually decreased, and this effect has gradually increased with the improvement of regional innovation capabilities and the industrial structure.

Threshold Effect of Inflation on Agricultural Growth: Evidence from Developing Countries

The paper examined the inflation-agricultural growth nexus in developing countries with the aim of identifying the inflation threshold that could benefit or harm the sector. We used panel data from 1970 to 2019 and the dynamic panel threshold model which accounts for endogeneity. Aside from inflation and agriculture GDP growth, we included the foreign direct investment (FDI), domestic credit to the private sector, and urbanization as control variables. The results show that credit has an enhancing effect on agriculture while urbanization has a diminishing effect. More importantly, we established that the inflation threshold is 5.997 %. Below this threshold, the effect of inflation on agricultural growth is positive, while the effect above the threshold is negative and stronger.