Dynamic Panel Threshold Model Research Articles

The impact of foreign direct investment on China's industrial carbon emissions based on the threshold model.

In recent years, the number of countries concerned about environmental protection continues to increase. With a continuous expansion of economic scale, many emerging markets are also sustainably enhancing their management for industrial carbon emissions in foreign direct investment (FDI). Therefore, the impact of FDI on the host country's industrial carbon emissions has been a hot topic of researches. This study selects panel data of 30 medium and large cities in China from 2006 to 2019. Combined with dynamic panel GMM estimation and panel threshold model, this study empirically analyzes the impact factors of FDI on the host country's industrial carbon emissions. This study is based on the perspective of dual environmental management systems. This study draws the following conclusions: When taking the dual environmental management system factors as threshold variables into the empirical research process, only the FDI in Beijing, Tianjin, and Shanghai shows a certain inhibitory effect on Chinese industrial carbon emissions. The FDI in other cities increases the scale of industrial carbon emissions. At the same time, in the formal environmental management system, FDI has no significant impact on China's industrial carbon emissions. It indicates that the formal environmental management system of each city is not effective in policy formulation or implementation. In addition, the corresponding role of environmental management systems, such as innovation compensation and mandatory emission reduction, is not played. With the exception of Beijing and Shanghai, informal environmental management systems in other cities help curb the scale of industrial carbon emissions brought by FDI.

Dynamic and threshold effects of energy transition and environmental governance on green growth in COP26 framework

Energy transition, green investment, and climate governance are core agendas of the COP26 framework. Therefore, this research explores the influence of energy transition and environmental governance by controlling the effects of renewable energy investments and human development in 37 IEA economies from 2010 to 2020. Notably, green growth and COP26 indicators are endogenous and may offer heterogeneous impacts subject to their implementation levels. Therefore, this study applies the dynamic panel threshold model (DPTM) to integrate threshold and endogenous effects of energy transition and environmental governance on green growth. Initially, this study constructed a composite energy transition index (ETI) using principal component analysis and applied DPTM to estimate threshold parameters. The results exhibit that ETI leads to lower green growth for those countries where its value is less than the threshold of 0.485. However, it turns highly significant and positive if ETI exceeds the threshold value. Moreover, environmental regulation shows a significant and positive influence on green growth; nevertheless, the marginal contribution towards green growth is more substantial if the environmental regulation score is higher than 0.604. Likewise, the moderating effect of ETI and environmental regulations report a more pronounced impact in stimulating green growth. Manifestly, the lagged effects of ETI and environmental regulations are more substantial and positive, which implies that a certain time lag is required to materialize the full benefits of green growth. These results suggest inclusive and long-term policy for energy transition and governance is imperative to achieve green growth agenda.

Business environment, technological innovation and government intervention: influences on high-quality economic development

PurposeThis paper aims to explore the impact of business environment on high-quality economic development (HQED) and clarify the role of technological innovation and government intervention in this relationship.Design/methodology/approachBased on China’s provincial panel data from 2010 to 2019, this paper adopts the system generalized method of moments to empirically analyze the influential mechanism and heterogeneity of the business environment on HQED. Furthermore, the authors construct a dynamic panel threshold model to test the threshold effect of government intervention.FindingsThe results indicate that optimizing the business environment can significantly promote HQED, technological innovation plays a partial mediating role in the impact of business environment on HQED, mainly by enhancing the intensity of innovation input and increasing innovation output to facilitate HQED. Government intervention can regulate the impact of business environment on HQED, and there is a double threshold effect, and it possesses an inverted U-shaped feature of first promoting and then inhibiting.Originality/valueThis paper examines the influence path of business environment on HQED from the perspective of technological innovation and government intervention, filling the gap in the study of provincial business environment. Moreover, the conclusions furnish a theoretical basis for optimizing the business environment and facilitating the HQED in China.

The energy-saving effect in the new transformation of urbanization

To cope with the severe challenges related to traditional economic-centered urbanization, the Chinese government has proposed a people-oriented new-type urbanization strategy, which focuses on promoting the coordination and sustainable development of the environment, economy, and society. The existing literature has studied the impact of traditional urbanization on energy use but has not yet revealed the mechanisms and effects of the new transformation of urbanization on energy efficiency. Based on socio-economic-natural complex ecosystem theory, this paper systematically explains how new-type urbanization affects energy efficiency. By adopting a newly developed dynamic panel threshold model, the paper examines the complex impact of new-type urbanization on energy efficiency using panel data of 285 cities in China from 2003 to 2017. The results show that new-type urbanization has a significant double-threshold effect on energy efficiency. As the new-type urbanization level increases, the improvement effect of new-type urbanization on energy efficiency presents the change features of “strong-weakened-stronger.” The heterogeneity analysis shows that under the constraints of multiple factors, such as new-type urbanization stages, geographic regions, economic development levels, and resource endowment, the impact of new-type urbanization on energy efficiency varies significantly. Targeted and differentiated policy recommendations for promoting new-type urbanization and energy efficiency are proposed.

The effectiveness of exchange rate regimes in controlling inflation: an econometric study using dynamic threshold panel models (Arabic)

This paper aims primarily at the economic measurement of the effect of exchange rate regimes on domestic inflation, in addition to other explanatory variables such as money supply and the inflation lags, imported inflation, wherein this latter is supposed to have a non-linear effect that varies according to the trade openness, the growth rate of the gross domestic product, and the oil price. We selected for the analysis the period from 1999 to 2019; By applying the Dynamic Panel Threshold models to a sample of 19 countries in the Middle East and North African region in addition to Turkey, Pakistan and Azerbaijan. The obtained results revealed that the exchange rate regimes have an important role in determining the levels of inflation, and the nature of relationship in the study sample doesn’t differ from what is in the developing countries, but it differs from the emerging and developed countries according to previous studies, where the fixed regimes achieved the best performance in term of inflation, followed by the intermediate and then the floating. Moreover, the imported inflation has a positive effect on the domestic, the trade openness and GDP incite the increase of this effect, the oil price is also important in noting the non-linearity of this relationship.

Internal mechanism analysis of the financial vanishing effect on green growth: Evidence from China

Using the panel data of 30 provinces in China from 2011 to 2018, this study examines the nonlinear relationship between financial development and green growth, as well as its internal generation mechanism by employing the Ordinary Least Square (OLS) method, Two-stage Least Squares (TSLS) method, System Two-step Generalized method of moments (System Two-step GMM) and dynamic panel threshold model of Seo et al. (2019). The empirical results reveal that, firstly, the scale of financial institutions (FDS) significantly inhibits green growth (GG), while the scale of the stock market (STO) significantly promotes green growth (GG). Secondly, there is a nonlinear relationship between financial development and green growth. There is an inverted U-shaped nonlinear relationship between the scale of financial institutions (FDS) and green growth (GG). That means when the ratio of the comprehensive level of financial development (FDCI) to the comprehensive level of technological innovation (TICI) is lower than a certain threshold, the development scale of financial institutions (FDS) will significantly promote green growth (GG). However, the scale of the stock market (STO) and green growth (GG) show an opposite linear relationship. This study proves that the financial vanishing effect differs in different proportions of the comprehensive level of financial development (FDCI) and the comprehensive level of technological innovation (TICI). This study also analyzes the differences between the impacts of technological innovation (TI) and green technology innovation (GI) on the financial vanishing effect. In addition, compared with the underdeveloped western regions, the scale of financial institutions (FDS) in the more developed eastern and central regions has a stronger inhibitory effect on green growth. Compared with the economically developed eastern and central regions, the scale of the stock market (STO) in the economically underdeveloped western regions has a stronger role in promoting green growth. Finally, financial development can affect green growth by affecting capital misallocation (ABK) and energy intensity (EDS). This study provides new policy suggestions for the country to improve the financial system reform and optimize the financial market structure. This study also offers a reference for policy makers to formulate financial risk early warning mechanisms and avoid the financial vanishing effects. In short, this study provides new evidence for the green development of China's economy.

How does financial development influence carbon emission intensity in the OECD countries: Some insights from the information and communication technology perspective

Based on an extended STIRPAT framework, this paper investigates the effects of financial development on carbon emission intensity in OECD countries from linear and non-linear perspectives, where financial development is proxied by three dimensions: financial deepening, financial deepening, and financial size, and financial efficiency. Fortunately, three types of financial development significantly alleviate carbon emission intensity. An extended moderation effect model is built to estimate the effect of financial development via information and communication technology on carbon emission intensity. The results reveal that internet-based information and communication technology and service-based information and communication technology are positively correlated with carbon emission intensity. To effectively handle the endogeneity issue triggered by causal relationships between variables and allow potential non-linear nexus, an advanced dynamic panel threshold model incorporating the generalised method of moments is employed to investigate how financial development affects carbon emission intensity under different types of information and communication technology. Empirical evidence demonstrates the significance of the non-linear nexus between financial development and carbon emission intensity. Lastly, heterogeneity analysis demonstrates the existence of heterogeneity associated with institutional quality, degree of economic development, and resource endowment concerning the effect of financial development on carbon emission intensity among the OECD countries.

Education puzzle, financial inclusion, and energy substitution: Growth Scales

Human capital is at the heart of new theories of growth through the intrinsic role of education. Economic growth, also called income effect or scale effect, is a crucial mechanism for education’s influence on energy. In line with Romer, maintaining increasing returns to scale is the result of a dynamic of growth on energy. Thus, in view of the urgency of the transition to renewable energies in Sub-Saharan Africa, this study examines the place of income in energy substitution. Controlling the dynamic nature of renewable energy, and the endogeneity both between the regressors and the threshold variable, the new generation of Seo and Shin's dynamic panel threshold model (DPTM) is performed. Including the quality of institutions, financial inclusion and industrialisation, the first-difference GMM approach is applied on a sample of 33 countries over 2005-2022. The findings show that the initial level of renewables affects the subsequent level of renewables consumption. Moreover, the transition from non-renewables to renewables is efficient when income stabilizes at a rate of 6.87%, human capital being involved in the process. It emerges that the contribution of growth to renewables follows the law of diminishing marginal returns with a stronger effect in Low-income than Middle-income countries.

Green finance and investment behavior of renewable energy enterprises: A case study of China

This study examines how the green finance facilitates the investment behavior of renewable energy enterprises. Considering the economic development level and financing constraints faced by the enterprises, a dynamic panel threshold model is applied using China as our experimental setting. The research finds that the development of green finance can improve the investment level of renewable energy enterprises. High-quality economic development can play a similar role as green finance in promoting investment in renewable energy enterprises. However, the promoting effect of green finance will be weakened or even offset by the excessive financing constraints of enterprises. The results advance our understanding of the mechanism of green finance on the investment behavior of renewable energy enterprises, and suggesting that maintaining high-quality economic development and alleviating the financing difficulties of enterprises will be more conducive to play the role of green finance in supporting the investment of renewable energy enterprises.

Outward foreign direct investment, green financial development, and green total factor productivity: evidence from China.

Prevailing research suggests reverse green technology spillovers from outward foreign direct investment (OFDI) significantly impact the green total factor productivity (GTFP) of the home country. However, the contribution of OFDI may depend on the home country's absorptive capacity. Based on panel data of 30 provinces in China from 2005 to 2019, this study constructs a generalized method of moments (GMM) model and a dynamic threshold panel model to empirically investigate how green financial development influences the impact of OFDI on the GTFP of the home country. We found that green financial development plays a positive moderating role in the impact of OFDI on GTFP in home country. The results also show the impact of OFDI on GTFP has a significant single-threshold effect on green financial development. Only when green financial development reaches a certain level can OFDI significantly promote GTFP of the home country. Moreover, regional heterogeneity exists in the moderating effect of green financial development. Given the ongoing growth of China's OFDI, it is vital to decide on a proper green financial development policy to improve the reverse spillover effect of OFDI firms on the nation's GTFP. The empirical analysis suggests that policymakers should build a multilevel green financial system to allocate financial resources and maximize the reverse spillover effect of OFDI.

Export Trade, Absorptive Capacity, and High-Quality Economic Development in China

Exports are a crucial driving force of China’s economic growth; however, researchers have yet to verify whether they can effectively improve the high-quality economic development. Based on interprovincial panel data from 2000 to 2019, in this study, we constructed a high-quality economic development indicator system through the entropy weight method, and we adopted the linear regression model and dynamic panel threshold model to empirically test the export trade effect on the high-quality economic development as well as its mechanism. We also probed the impact of the heterogeneous absorptive capacity on the high-quality economic development. According to our research findings, China’s export trade has substantially promoted the high-quality economic development level by, from the viewpoint of the action path, positively influencing the economic, open, and coordination subsystems. The influence of the export trade on the high-quality economic development has a substantial single-threshold effect on the heterogeneous absorptive capacity; that is, when the threshold variables that represent the regional absorptive capacity (the economic level, R&D intensity, and technological gap) are all higher than the threshold value, the export trade has a substantial positive impact on the high-quality economic development level. The research conclusions of this paper provide new ideas for the development of high-quality economic systems as well as a useful reference for China in its formulation of more targeted foreign trade policies.

The threshold effect of environmental regulation in the nexus between green finance and total factor carbon productivity: evidence from a dynamic panel threshold model.

This paper investigates whether the effect of regional green finance (GF) on total factor carbon productivity (TFCP) differs by the level of environmental regulation intensity. Using data of 30 provinces in China from 2008 to 2020, we measure green finance based on the entropy weight method. Then, we employ the Super-slacks-based measure (SBM) model that incorporates undesirable outputs to calculate TFCP. Further, based on a dynamic panel threshold model, we empirically investigate the relationship between GF and TFCP. The main conclusions are as follows: (1) a nonlinear relationship exists between GF and TFCP in China. Moreover, we are the first to take market-based environmental regulation (MER) and command-and-control environmental regulation (CER) as threshold variables. With MER and CER as threshold variables, there was a double-threshold effect between both GF and TFCP. Hence, when GF has a negative impact on TFCP, the government should consider reasonably adjusting environmental regulations to reap the full benefits of GF in terms of TFCP growth. (2) The heterogeneity analysis states that the nonlinear effect of GF on TFCP in different regions is still significant under the thresholds of MER and CER. Therefore, the government should implement flexible environmental regulation policies to make GF promote TFCP according to region's characteristics. This study provides a new perspective on the relationship between green finance and total factor carbon productivity.

The Threshold Level of Economic Growth in BRI and Non-BRI Developing Countries for Better Environmental Quality

This study investigates the nexus between economic growth and carbon dioxide (CO2) emissions. Specifically, this study employs a dynamic panel threshold model to identify and compare the threshold levels of economic growth between developing countries participating and not participating in the Belt and Road Initiative (BRI). The findings signify a nonlinear relationship between the sampled countries’ economic growth and their CO2 emissions in both categories. Furthermore, the result of dynamic panel threshold model reveals that the threshold level of economic growth, in the category of BRI developing countries, was lower (US$ 887.49) as compared to non-BRI developing countries (US$ 1358.57). This implies that the impact of economic growth in developing countries participating in the BRI was less harmful to the environment, and that these countries are more alert to environmental issues once the threshold of their gross domestic product per capita was achieved. Hence, Chinese authorities should put in more effort in facilitating sustainable infrastructure development to attract more developing countries to join the BRI to mitigate environmental degradation.

Only under good governance does public debt improve national income: Evidence from dynamic panel threshold model for Sub-Saharan African countries

This paper aims to explore the mediating role of governance in the relationship between per capita income and public debt in Sub-Saharan Africa. From a neoclassical production function and a dynamic panel threshold model, the paper estimates a model based on a sample of 39 countries in Sub-Saharan Africa over the period of 2002 to 2019. Our results indicate a non-linear relationship between per capita income and public debt, which is influenced by the quality of governance. In particular, the impact of public debt on per capita income depends on the level of governance quality. A governance threshold is identified, showing a minimum level of good quality of governance from which public debt has a positive effect on income. Moreover, the paper identified the most critical governance dimensions for optimizing the relationship between public debt and per capita income and provided policy suggestions.

Corporate governance and capital structure: dynamic panel threshold analysis

ABSTRACT This paper examines the nonlinear connection between corporate governance (CG) and corporate leverage. Our study applied the dynamic panel threshold model (DPTM) to facilitate the capture of the nonlinear effect of CG on a firm’s leverage for Japanese listed companies. Additionally, our study sought to demonstrate the linkage between CG and the speed of adjustment (SOA), particularly following the reforms in Japan’s CG system, to reach a targeted level of leverage. The empirical findings confirm the presence of the threshold influence of managerial ownership and board size, thus confirming their nonlinear impact on capital structure. Moreover, at a low level of managerial ownership, the SOA for firms to achieve the optimal level of leverage is faster than it is for firms with a high level of managerial ownership (MO), while firms with a larger board achieve their targeted level of leverage quicker than firms with a smaller board. Our findings indicate that recent reforms in Japan’s CG system seem to have been inefficient, with no positive effect on corporate leverage.

Macroeconomic implications of escalating stock of public debt: Evidence from sub‐Saharan African economies

AbstractThe study investigated the effect of public debts on macroeconomic indicators, such as inflation and the exchange rate, using a panel of 25 sub‐Saharan African (SSA) economies. The study contributed to extant studies by looking at the separate effect of domestic and foreign debts on inflation and exchange rate. We adopted a battery of econometric tools such as the Driscoll–Kraay standard errors and the dynamic panel threshold model. The results show that foreign debts worsen the inflation rate and expose the economy to unanticipated movements in the exchange rate, whereas domestic debts help to reduce the inflationary pressure. The study also found a nonlinear relationship between public debts and macroeconomic indicators of inflation and exchange rates. This implies the further accumulation of foreign debt will heighten the inflation rate and expose the region to unanticipated movements in the exchange rate. The study recommends that governments and policymakers in SSA should ensure that foreign debts are sufficiently hedged against currency and interest rate risks to reduce the exposure of SSA economies to exchange rate risks. The study also recommends that governments adhere strictly to the maximum debt limit of 60.59% (of gross domestic product), otherwise inflation and exchange rates may worsen.

The Impact of Science and Technology Finance on Regional Collaborative Innovation: The Threshold Effect of Absorptive Capacity

The collaborative innovation of Beijing-Tianjin-Hebei region is faced with prominent problems such as the large gap in innovation resources and capability. In addition, science and technology (S&T) finance provides the approach to promote the flow of regional capital, technology and talents, which can facilitate the coordinated development of Beijing-Tianjin-Hebei region. Therefore, this study takes the Beijing-Tianjin-Hebei region as an example to explore the mechanism of different S&T finance on regional S&T collaborative innovation. Based on the provincial panel data of Beijing-Tianjin-Hebei region from 2009 to 2020, this paper constructs a dynamic panel threshold model with different regional absorptive capacities (technology level and economic base) as threshold variables to analyze the impact of public and market S&T finance on regional collaborative innovation. The main findings of this paper are as follows: first, the overall level of regional collaborative innovation in Beijing, Tianjin and Hebei is low, and public and market S&T finance significantly affects regional collaborative innovation in Beijing, Tianjin and Hebei. Specifically, public S&T finance plays an inhibitory role on regional collaborative innovation, and market S&T finance positively affects regional collaborative innovation. Secondly, both types of S&T finance have obvious heterogeneous threshold characteristics of absorptive capacity on regional collaborative innovation. Once the absorptive capacity of both regions breaks through the critical scale, the inhibiting effect of public S&T finance on regional collaborative innovation shows a weakening trend; with the improvement of technology level, the positive influence of market S&T finance on regional collaborative innovation keeps increasing. With the improvement of economic base, it shows a shift from negative to positive. The research findings provide theoretical and practical guidance for accelerating the pace of S&T innovation and the implementation mechanism of regional coordinated development.

Modeling the dynamic influences of economic growth and financial development on energy consumption in emerging economies: Insights from dynamic nonlinear approaches

This article evaluates the dynamic impacts of economic growth and financial development on energy consumption in emerging economies from 1998 to 2019. The total financial development and its submeasures of financial institution and financial market development are applied in consideration of the different dimensions of financial development. In doing so, we apply a new dynamic semiparametric additive panel model to address potential dynamicity and nonlinearity. Moreover, the dynamic panel threshold model is recommended to explore the dynamic threshold effect of income growth on energy pressure under different financial development indicators, complementing the gap in the existing research on nonlinear mechanisms regarding this topic. Our findings do not indicate the presence of the EKC hypothesis but verify that income growth can reinforce energy pressure. Total financial improvement and financial market development both display an inverted “U-shaped” nonlinear influence on energy expenditure, while financial institution development can directly ease energy pressure. We also find that financial development performs a significant threshold effect in the linkage between income growth and energy expenditure. The higher the total financial development and financial market development levels are, the stronger the contribution of economic growth on energy pressure; however, the unfavorable influence of economic growth on energy pressure is receded with the increase in financial institution development. Some policy implications are provided for reducing energy poverty through optimizing economic and financial advancement.

Influence of research and development, environmental regulation, and consumption of energy on CO2 emissions in China-novel spatial Durbin model perspective.

Global warming continues to be an intimidating factor for environmental protection, and reducing carbon emissions is an effective way to deal with the phenomenon. However, the energy sector is a significant contributor to greenhouse gas emissions. Therefore, investment in environmental regulations and research and development (R&D), is critical for fostering a low-carbon growth model. This study focuses on 30 provinces in China from 2004 to 2019. We used the spatial Durbin model to investigate how the spatial spillover effect of R&D and environmental regulation impacts carbon emissions. In addition, we applied the dynamic threshold panel model to mitigate potential problems of endogeneity. The results reveal that carbon emissions have a considerable spatial correlation in both temporal and spatial dimensions, exhibiting high and low-value accumulation characteristics. Furthermore, the combined effect of R&D intensity, environmental regulation, and energy consumption were found to contribute to the increase in carbon emissions across China's provinces, and they also suggest different influencing mechanisms. The spillover effects of increased carbon emissions in neighboring regions also contribute to the increase in local carbon emissions. The study also found that R&D and stringent environmental regulations measures strongly moderate the link between energy consumption and carbon emissions. In promoting carbon reduction, by breaking the dynamic equilibrium in China, the provincial investment outflow on R&D intensity could be optimized, and the regional levels should focus more on tightening environmental regulatory measures and promoting the development of energy-conserving technologies.

How does artificial intelligence development affect green technology innovation in China? Evidence from dynamic panel data analysis.

As the global climate problem becomes increasingly serious, the green technology innovation to achieve "carbon peak and carbon neutral" has gradually become the global consensus of major countries, and how the rapid development of artificial intelligence (AI) technology affects green technology innovation (GTI) has received a great deal of attention in the field of economics. Therefore, based on China's inter-provincial panel data from 2006 to 2019, the system GMM, dynamic panel threshold model, and quantile regression model were constructed to examine various influences of AI development on GTI under different environmental regulation intensity, research and development (R&D) investment, and institutional environmental threshold conditions. The findings presented that AI development significantly contributes to GTI and GTFP, with an impact coefficient of 0.0122 and 0.0084, and this influence is mainly reflected in the western region of China and is more obvious in the 2006-2012 period. AI development mainly enhances green technological efficiency, and it has dampening effects on green technological progress during the period 2013-2019. Additionally, there are non-linear threshold effects in the relationship between the level of AI development and GTI when environmental regulatory intensity, R&D investment, and institutional environment are in different level intervals. AI development will boost GTI only when the intensity of environmental regulation and institutional environment is above a certain threshold value. However, the AI development represented by industrial robot applications still has no obvious effect on GTI even when the R&D investment exceeds a certain threshold. Furthermore, the growth effect of AI development on GTI indicates a decreasing nonlinear pattern as the GTI's quantile rises under the condition that R&D investment and institutional environment intensity cross the threshold, while this growth effect increases gradually with the rise of GTI's quantile when the environmental regulation is above the threshold.