Panel Smooth Transition Regression Model Research Articles

Modelling for disability: How does artificial intelligence affect unemployment among people with disability? An empirical analysis of linear and nonlinear effects

There is a growing debate among scholars regarding the impact of artificial intelligence (AI) on the employment opportunities and professional development of people with disability. Although there has been an increasing body of empirical research on the topic, it has generally yielded conflicting findings. This study contributes to the ongoing debate by examining the linear and nonlinear effects of AI on the unemployment of people with disability in 40 countries between 2007 and 2021. Using the system Generalized Methods of Moments and panel smooth transition regression, the main conclusions are as follows. First, AI reduces the unemployment of people with disability in the full sample. Second, upon disaggregating the sample based on income level (high income/non-high income) and gender (men/women), the linear model only detects an inverse correlation between AI and unemployment among people with disability in high-income countries and among men, whereas it does not influence unemployment in non-high-income countries and women. Third, the panel smooth transition regression model suggests that the effects of AI on the unemployment of people with disability and among women are only observed once artificial intelligence interest search exceeds a specific threshold level. The effects of AI in non-high-income economies and among women are not significant in the lower regime, which confirms the nonlinear association between AI and the unemployment rate of people with disability. These findings have important policy implications for facilitating the integration of people with disability into the labor market.

Non-linear relationship between FinTech, natural resources, green innovation and environmental sustainability: Evidence from panel smooth transition regression model

The rapid global economic growth has expressed worries regarding the depletion of natural resources and environmental sustainability. In such a situation, expanding FinTech, optimizing natural resource consumption, and escalating green innovation can serve as potential solutionsfor enhancing environmental sustainability. This research looks into the intricate relationship among FinTech, natural resources, green innovation, and environmental sustainability in the panel data comprised of G7 and G11 economies by employing the Panel Smooth Transition Regression Model, which assists inscrutinizing the asymmetric or non-linear association among the variables under consideration. Findings reveal the pivotal role of FinTech, Natural Resource Rent, and Green Innovation in shaping sustainable environment across bothG7 and G11 economies. FinTech demonstrates a momentous and affirmativeimpression on ecological quality, promoting digital transactions and reducing paper-based processes, which, in turn, lessens deforestation and carbon emissions from paper production. FinTech also enhances financial inclusion and fosters investment in eco-friendly projects. Natural Resource Rent, in contrast, significantly leads to the decline of the environment through its extensive use, resulting in elevated carbon emissions. Finally, Green innovation exhibits a remarkable and positive influence on carbon emissions, facilitating the shift from carbon-intensive resources to eco-friendly alternatives, thus reducing pollution and improving air quality. These findings underscore the importance of adopting less-carbon-emitting technologies to achieve carbon neutrality goals in both G7 and G11 countries. The research provides valuable insights for policymakers and offers recommendations for a more sustainable future.

Threshold effects of institutional quality on FDI-economic growth nexus: a panel smooth transition regression (PSTR) model

Threshold effects of institutional quality on FDI-economic growth nexus: a panel smooth transition regression (PSTR) model

Nonlinear effects of conservation reserve program rental rates on land enrollment under varying crop price regimes

AbstractWe use a panel smooth transition regression model to investigate the influence of Conservation Reserve Program (CRP) rental rates on land enrollment under different crop price regimes. We employ a flexible estimation technique, allowing the CRP rental rate incentives to vary with crop prices, and construct a Hausman‐type instrumental variable to address endogeneity. Simulations are conducted to assess the impact of varying crop prices on CRP acreage and its associated environmental effects. Results reveal a nonlinear relationship between rental rates and enrollment, with the impact diminishing as crop prices increase. A 10% rise in CRP rental rates corresponds to a 5.1% expansion in enrollment, reducing to 4.2% when crop prices reach a specific threshold. High crop prices lead to fewer acres enrolled, decreased carbon sequestration, increased phosphorus and nitrogen runoff, and increased sediment loss. Our findings highlight the importance of considering price fluctuations in conservation planning as it has significant implications for environmental conservation policies and programs.

The Role of Structural Reforms on the Price and Financial Stability: Evidence from a Multi-Country PSTR Model

This paper examines the effects of structural reforms on price and financial stability through the Panel Smooth Transition Regression model for 84 developed and developing countries in the period 2002-2018. Therefore, this paper aims to determine whether it is a matter of the impact of structural reforms in the real sectors on price stability; and in financial sectors on financial stability in the sampled countries, when output is given in the PSRT models. The results show that structural reforms have a significant impact on the price and financial stability, although the regimes shaped by the value of output gap threshold, differ in the sampled countries. These results present that structural reforms can help to improve the price and financial stability to the extent that they can eliminate supply-demand imbalances, prevent systemic risks and positively affect a deterioration in expectations by supporting new monetary policy designs.

Threshold effects of technology import on industrial employment: a panel smooth transition regression approach

The relationship between imported technology and employment is a controversial issue. This study aims to test the hypothesis that the relationship between imported technology and employment is non-linear and evolves with the level of technology imports. The study covers two groups of developed and developing countries over the period 2000–2019. The Panel Smooth Transition Regression (PSTR) model is used to estimate the technology import threshold and its impact on industrial employment. The study finds a positive relationship between imported technology and industrial employment for technology import rates above the 13.667% threshold, above which imported technology begins to improve industrial employment in developed countries. In contrast, for developing countries, the results showed a negative relationship between imported technology and industrial employment for technology import rates above the 3.44% threshold above which imported technology begins to reduce industrial employment. These results suggest that the threshold level of technology imports can be considered as an indicator for promoting innovation policies in both developed and developing countries to minimize the negative effect of process innovation resulting from imported technology.

The Impact of Artificial Intelligence on Unemployment among Educated People with Disabilities: An Empirical Analysis

The impact of artificial intelligence (AI) on unemployment is a subject of debate among researchers and policymakers. This study investigates how AI affects unemployment among educated people with disabilities in 33 countries from 2004 to 2021. Several conclusions have been reached. First, both static and dynamic panel data estimators show that AI reduces aggregate unemployment and unemployment among educated men with disabilities. In contrast, there is no significant impact on the unemployment of educated women with disabilities. Second, the panel smooth transition regression model provides compelling evidence for the existence of two regimes and a nonlinear impact of AI on unemployment among educated women with disabilities. The impact is not significant when AI is low (first regime), but the situation changes when AI exceeds a given threshold level (second regime). Therefore, educated women with disabilities may have more opportunities to integrate into the job market due to the increased adoption of AI. Countries are recommended to foster an employment-friendly environment that promotes inclusion and equitable opportunity for educated people with disabilities by developing and encouraging the adoption of AI technologies.

The influences of the US stock market on virtual currency price under us monetary policy threshold

This study uses a panel smooth transition regression model to investigate the nonlinear relationship between virtual currency and the stock market under the US monetary policy threshold from 7 August 2015 to 27 October 2020. A statistical test showed a threshold effect and confirmed that the relationship between the US stock market and virtual currency is nonlinear. Furthermore, virtual currency fluctuation has asymmetric responses to the US stock market?s fluctuation based on the threshold value. When the federal fund rate exceeds the threshold value, the changes in the S&P500 with a lag of one positively affect the fluctuation of virtual currency.

Searching for a Threshold effect in the Diversification-profitability Relationship. Evidence from the MENA Banks

This paper investigates the non-linear relationship between bank diversification and bank profitability in the MENA region. More specifically it checks whether there exists a threshold effect in the diversification-profitability relationship. To achieve this goal, we used a panel of 83 retail MENA banks during the period 2005-2020 and we performed the Panel Smooth Transition Regression (PSTR) model as empirical approach. The results confirm the existence of a threshold effect in the non-interest income and bank profitability relationship. To get benefit from bank diversification, the ratio of non-interest income in the MENA region should exceed 22% when profitability is ROA and 25.41% for ROE. Below these thresholds, bank diversification significantly decreases the level of bank profitability. The findings of this research have substantial implications for both policymakers and bankers. The MENA banks should be engaged in more diversified bank activities in order to enhance their overall revenues.

Coordinating economic growth and carbon emission reduction in China: evidence from the optimal levels of energy price distortions

Distorted energy prices cause resource mismatch and hinder the coordinated development of economic growth and carbon emission reduction (CDEC) in China. Therefore, it is essential to determine the optimal levels of energy price distortions. This paper first measures the price distortions of fossil and renewable energy sources and applies a panel smooth transition regression model to assess the optimal threshold values for the degree of energy price distortions. The results show that 1) Fossil energy price distortions are negative, and the price distortion for renewable energy is positive. 2) Energy price distortions inhibit CDEC, and this effect is regionally heterogeneous. 3) The panel smooth transformation model results indicate that distorted energy prices have a nonlinear impact on CDEC. CDEC is significantly hampered in the low regime by distorted fossil energy prices and facilitated in the high regime. In contrast, the distorted renewable energy price shows positive in the low regime and negative in the high regime. We also obtain the optimal intervals for the degree of energy price distortions that promote CDEC. With the target of “growth” and “carbon reduction,” this study provides a reference for improving the energy pricing mechanism and exploring the effective ways of CDEC.

Investigating the Effects of Environmental Regulation on Industrial Ecological Efficiency in China Using a Panel Smooth Transition Regression Model

Environmental regulation (ER) is a crucial tool used by governments to intervene in the environmental practices of enterprises, and it is recognized as a significant avenue to impact industrial ecological efficiency (IEE). This study uses the superefficiency SBM model to determine provincial IEE scores. Then, a panel smooth transition regression (PSTR) model is used to explore the effects of ER on IEE transition at different stages of economic growth. The main findings are as follows: Firstly, China’s IEE showed an overall upward trend, with small increments over the past two decades. Regions with higher IEE were mainly located in the east, while those with lower IEE were mostly in the less economically developed west. Secondly, the PSTR model revealed that ER had varying impacts on IEE at different stages of economic growth. ER positively influenced IEE in the early stages of economic growth. However, after surpassing the threshold of economic growth, ER began to contribute to reducing IEE scores. In addition to these findings, this study proposes a series of policy recommendations to strengthen IEE.

Complexity influence of societal development comprehensive indicators on building carbon emission: empirical evidence from China.

Carbon mitigation in the building sector is crucial for China to fulfill its commitments towards achieving a carbon peak and carbon neutrality. However, the impact of societal development and ecological indicators on building carbon emissions remains unclear. This study employs the panel smooth transition regression model to investigate the complex implications of societal development comprehensive indicators, characterized by harmonious development, decoupling, and technological advances, on buildings' total carbon emissions, based on the evidence from China's 30 provinces for the period between 2007 and 2020. Additionally, the robustness of the model confirms that the conclusion is still valid. The empirical results indicate a strongly non-linear relationship between societal development comprehensive indicators and building carbon emissions. Both the harmonious development and technological advances exhibit two transition functions, and decoupling features a single transition function. Harmonious development is more sensitive to the impact of building carbon emissions, while technological advances have tremendous emission reduction potential. From the time dimension, fluctuation trends and ranges are different. From the spatial dimension, the inhibiting and promoting effects on each province have regional heterogeneity. Our results entail suggestions for reduced building total carbon emissions and practical strategies for regional climate resilience and efficiency in mitigating climate change.

Nonlinear impact and spatial effect of tourism urbanization on human settlement environment: Evidence from the Yellow River Basin, China

The human settlement environment is the concrete embodiment of measuring the sustainable development of tourism urbanization. Previous studies have preliminarily verified that there is a coupling relationship between tourism urbanization and human settlement environment. However, whether tourism urbanization can effectively improve human settlement environment, especially in the most vulnerable watershed area in China, the Yellow River Basin, is still unclear. Therefore, the purpose of this study is to explore the degree and direction of the impact of tourism urbanization on human settlement environment in 78 prefecture-level cities in the Yellow River Basin from 2005 to 2019 under the influence of nonlinear and spatial spillover effects. This paper uses the PSTR (panel smooth transition regression) model SDM (spatial Durbin) model to reveal the following results: First, tourism urbanization can significantly improve human settlement environment in the Yellow River Basin. After crossing the second threshold (0.434), the nonlinear effect of tourism urbanization on human settlement environment is the strongest, but only a very small number of cities cross the threshold. Secondly, the improvement of the level of tourism urbanization has effectively improved production environment and living environment of the region, but it has had a significant negative impact on ecological environment of the region. Finally, the combined effect of regional geographical proximity and economic interaction is conducive to the positive spatial spillover effect of tourism urbanization on production environment and living environment of surrounding areas of the Yellow River Basin. The current empirical results reveal the key role of tourism urbanization in improving human settlement environment in the Yellow River Basin, and clearly outline that the development of tourism urbanization should be consistent with the national strategy of ecological protection and high-quality development in the Yellow River Basin.

Foreign direct investment, human capital and export diversification in Africa: A panel smooth transition regression (PSTR) model analysis

This paper investigates the role of local human capital in facilitating the export diversification improvement effect of foreign direct investment (FDI) in African countries. To this end, we use a panel smooth transition regression (PSTR) model which is able to deal with the heterogeneity issue associated with the cross-country data. Based on a sample of 30 African countries over the period 1996–2019, the results show that there is a minimum threshold of human capital beyond which the export diversification enhancing effect of FDI is unlocked in African countries. In other words, only countries located above a certain threshold of human capital benefit from the positive effect of FDI on export diversification. These results suggest that policymakers in African countries should focus on improving the conditions for acquiring local human capital (education and health) in order to extract economic gains from FDI.

Effects of digital global value chain participation on CO2 emissions embodied in digital exports: New evidence from PSTR approach

The technological revolution and industrial transformation led by digital technology is driving the transformation of global value chains (GVCs) to digital GVCs. To address global climate change issues while achieving economic growth, many countries prioritize practical energy-saving and emission-reduction measures while obtaining higher trade gains through participation in digital GVCs and the international division of labor. Using panel data for 60 countries and regions from 2007 to 2019, this study first measures the degree of participation in digital GVCs and the CO2 emissions embodied in digital exports. A panel smooth transition regression model is used to explore how the level of digitalization affects the impact of digital GVC participation on CO2 emissions embodied in digital exports. The empirical results show that actively participating in digital GVCs can reduce CO2 emissions embodied in digital exports, and the effect varies depending on the participation approach. Specifically, the impact of forward participation in digital GVCs (FDGVCs) on CO2 emissions exhibits an inverted U shape, indicating that the emission-reduction effect gradually appears only when the digitalization exceeds a threshold. However, backward participation in digital GVCs (BDGVCs) significantly reduces CO2 emissions, although this contribution weakens as digitalization increases. Overall, the impact strength of FDGVCs and BDGVCs on emission reduction shows a growth trend throughout the period, and the impact of FDGVCs was less than that of BDGVCs. Heterogeneity analysis reveals that Organization for Economic Cooperation and Development (OECD) and non-OECD countries have different relationships between digital GVC participation and CO2 emissions embodied in digital exports. Furthermore, the positive impact of participation in digital GVCs is consistent with CO2 emissions generated by digital export intermediates and final products. For nondigital exports, FDGVCs can significantly reduce CO2 emissions if digitalization is high. Finally, countries should actively participate in digital GVCs to promote global economic growth and sustainable development.

The dynamic effect of trading between China and Taiwan under exchange rate fluctuations

As an export-oriented economy, Taiwan’s export income can be easily influenced by internal and international economic factors, including the industrial production index (IPI) and the exchange rate. With China being Taiwan’s largest recipient, Taiwan’s export income from China is extremely important to Taiwan’s economy. Therefore, this research investigates the nonlinear relationship between the IPI of Taiwan and Taiwan’s export income from China with the application of a panel smooth transition regression (PSTR) model. In addition, the currency exchange rate of RMB to NTD, which is the transfer variable, is used to examine the dynamic effect. The research period is monthly data ranging from January 2001 to February 2022. The empirical results show that the effect of the IPI of Taiwan on Taiwan’s export income with China is dynamic. Moreover, with the existence of a threshold value, its influence changes as the currency exchange rate of RMB to NTD varies over time. Finally, regardless of whether the currency exchange rate of RMB to NTD is above or below the threshold value, as the IPI of Taiwan increases, Taiwan’s export income from China also increases, differing only in the degree of increase.

Threshold Effect in the Bank Lending Channel of Monetary Policy Transmission and the Role of Bank Portfolio Deterioration: A PSTR Specification in the WAEMU Zone

The objective of this paper is to analyse the influence of monetary policy on credit supply in the WAEMU zone over the period 1996-2017. The study focuses on the WAEMU countries, except for Guinea-Bissau, due to the unavailability of sufficient data. We apply the Panel Smooth Transition Regression (PSTR) model of Gonzalez et al. (2005). The results reveal the non-linearity of the link between monetary policy and credit supply. There is a threshold of credit risk exposure of 8.726% above which monetary policy loses its effectiveness. Indeed, monetary policy has a positive effect on the supply of credit when the value of the gross bank portfolio deterioration rate is less than or equal to the threshold of 8.726% and an insignificant effect above this threshold. Above this threshold, the link between monetary policy and bank credit supply is distended. In this case, it is the level of economic activity that stimulates the supply of bank credit in this area. These results indicate that the effectiveness of the monetary policy conducted by the Central Bank of West African States (BCEAO), through the bank credit channel, should take into account the level of credit risk attained by banks. Thus, the study recommends that the authorities further strengthen prudential supervision within the WAEMU.

Corporate social responsibility and firm performance: a threshold analysis of European firms

PurposeThis paper aims to investigate the reciprocal nonlinear relationship between corporate social responsibility (CSR) and firm performance (FP).Design/methodology/approachThe authors used a sample of 814 European firms over the period 2008–2017. The Panel Smooth Transition Regression (PSTR) model was performed as an econometric approach.FindingsFirstly, results show a threshold effect in the CSR–FP relationships within the two directions. More specifically, the authors found that firms are more likely to engage in CSR by surpassing a threshold of 1.231% for return on assets (ROA) and 0.821% for Tobin’s Q ratio. Secondly, the authors also found that the impact of CSR on FP is positive and significant only if the environment, social and governance score surpasses the threshold of 56.780% when the dependent variable is ROA and 41.02% when Tobin’s Q ratio measures performance.Research limitations/implicationsA significant part of the literature supports the linear relationship between CSR and FP from the unique direction (CSR → FP). This study comes to fill this gap by assessing the possible nonlinear relationship. In addition, this nonlinear relationship is tested under the two directions. Therefore, defining the threshold of FP that allows companies to engage in CSR, on the one hand, and the threshold of engagement in CSR that improves FP, on the other hand, could be an exciting topic.Practical implicationsTo get the full benefit from CSR effects, firms should be with better financial performance to be socially responsible.Originality/valueTo the best of our knowledge, few studies have explored the nonlinear relationship between CSR and FP. In addition, this study raises the question of whether this relation is causal. The authors assess the two nonlinear relationships between CSR ? FP and FP ? CSR by determining the optimal thresholds.

Research on digital intelligence business model based on artificial intelligence in post-epidemic era

PurposeThe 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.Design/methodology/approachThis work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.FindingsThe research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.Originality/valueThe finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

Economic Growth and Extreme Poverty in Sub-Saharan African Countries: Non-Linearity and Governance Threshold Effect

Over the last few decades, many economies in sub-Saharan Africa have experienced much faster economic growth than other parts of the world. However, many of these economies have not experienced significant poverty reduction. Several factors such as the quality of governance may limit the expected effects of economic growth on poverty. This paper examines the triangular relationship between extreme poverty, governance quality, and economic growth for the sub-Saharan African countries over the period 2010–2019. Compared to the work carried out until now, the novelty of this research lies in using the Panel Threshold Regression (PTR) and Panel Smooth Transition Regression (PSTR) models to determine the optimal level of governance index, which once attained, will make extreme poverty decrease with economic growth and governance quality. We found that the nexus between these three variables is nonlinear. Besides, results show that there exists a statistically negative relationship between governance and extreme poverty above the threshold level of 0.314 for the Global Governance Index (GGI) and 66.9 for the Ibrahim Index of African Governance (IIAG), above which governance quality decreases extreme poverty. The results showed that the economic growth would begin to reduce extreme poverty once governance reaches a threshold level of 0.367 for GGI and 63.2 for IIAG. Better performance of governance also appears to improve economic growth and reduces poverty.