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 Causal Relationship between Government Expenditure and Inflation in Nigeria: Smooth Transition Regression Approach

This paper revisits the nexus between government spending and inflation in Nigeria using a Smooth Transition Regression model (STR) to investigate both the linear and nonlinear effects of the former on the latter from 2000: 1 to 2023:6. The monthly data sourced from the Central Bank of Nigeria (CBN) Statistical Bulletin (2023) are used. The study reveals that linear approximation fails to adequately explain the non-linear effects of government spending on inflation, particularly in high-growth regimes financed by the central bank. It is suggested that in a low-growth regime where government spending is not financed by the central bank, avenue should be given to fiscal policy to stimulate and control inflation.

The impact of value-added taxes and inflation threshold on economic growth in the Kingdom of Saudi Arabia

The paper contributes to the literature by examining the effects of inflation on economic growth in Saudi Arabia between 2010Q1 and 2022Q4 and exploring whether the VAT impacted the inflation-growth nexus. The literature on the determinants of economic growth has expanded during the last few decades. The impact of inflation on economic growth has received much attention, with contradictory findings. The study employs the Logistic Smooth Transition Regression (LSTR) model to determine the optimal inflation rate and estimate the repercussions of inflation in each regime. The findings show that the optimal inflation rate is 2.47%. Inflation is demonstrated to improve growth if it remains below 2.47%. Nevertheless, as the inflation rate is beyond this threshold, the effect becomes negative. Subsequently, the study accounts for the influence of Value- Added Tax on the link between inflation and growth. According to the empirical estimation, the threshold level of the inflation rate is determined to be 2.88%. In addition, the adverse implications of inflation on growth are higher when we consider the implementation of VAT. Therefore, the study concludes that there are nonlinear effects of the inflation rate on economic growth in Saudi Arabia. The empirical results of the study have important policy implications for Saudi Arabia.

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 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 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.

Effect of Currency Devaluation in Pakistan: A Prospect of Short Term and Long Term

Currency devaluation is a standout amongst the most emotional even awful proportions of financial strategy that a legislature may attempt It generally creates cries of shocks and Sustainable economic growth and development is undoubtly, one of the most challenging development issue, nowadays, in the developing countries Therefore, this study investigates theoretically and empirically the impact of currency devaluation on economic growth of Pakistan The study finds evidence of non-linearity in this relationship and capture that through a smooth transition regression model. Using annual data for the period 1975-2018, employing ARDL bounds test. From an evaluation of the overall analysis and results, it is concluded that foreign exchange reserves have positive and significant short run effect for all the countries. Inflation has negative and significant effect on economic growth of all the countries while real exchange rate has also positive and significant effect on economic growth. The government spending on development has positive and significant effect in short run scenario for all the selected countries while the money growth have positive and negative but significant effect on different countries depending on the political situation and economy based on agrarian product or industrial products. The results of this study confirm the finding of most previous study, since the advent of the exogenous growth theory. The study suggests that all the variables e.g. inflation, foreign exchange reserves, real exchange rate, money growth and government spending could be effectual in these augmenting economies.

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.

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.

Smooth transition regression model relating inflation to economic growth in Tunisia

Since its independence, Tunisia has embarked on monetary and financial sector reforms aimed at boosting economic growth. However, these reforms have not been effective due to inflation pressures in this country. Thus, this paper examines the nature of the relationship between financial development and economic growth between 1965 and 2019, using the non-linear logistic smooth transition regression model and considering inflation as a threshold financial development. The results show the existence of a non-linear abrupt relationship with an inflation threshold equal to 3.63%. Specifically, when inflation is below 3.63%, all variables, including inflation, have a significant and positive impact on economic growth. However, when inflation exceeds the estimated threshold, inflation has a significant and negative impact with an elasticity equal to − 0.365. To effectively manage inflation, the Tunisian authorities are encouraged to set and embrace specific inflation targets as a goal. This approach aims to mitigate inflationary pressures and foster a favourable environment for financial development in Tunisia, thereby promoting economic growth. Hence, it becomes imperative to implement such measures that alleviate inflationary pressures and drive economic growth through the facilitation of development finance by the banking sector.

Globalization and inflation dynamics: evidence from emerging economies

ABSTRACT We test the impact of globalization on the inflation process (global slack hypothesis) for 15 emerging economies over the period (1996Q1-2019Q4). The novelty of this article lies in testing the impact of globalization on the inflation process. We introduce the smooth transition regression (STR) model of the Phillips curve to capture the gradual impacts of globalization on inflation dynamics. The main results are as follows. (i) The asymmetries in inflation exist that are not captured by the linear Phillips curve. (ii) The domestic output gap remains a main driving force of inflation. (iii) Globalization based on the trade weighted average of the domestic output gap does not affect the inflation process compared to other variables like the trade openness, import prices, real exchange rate and international oil prices. Our results yield important implications that the central banks of the emerging economies can stabilize inflation and output gap in an effective way, exploiting the inflation-output gap relationship. When economic expansion of the trading partners increases, the process of inflation dynamics changes in two economies (Brazil, and China).

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.

Investigating the dynamics of crude oil and clean energy markets in times of geopolitical tensions

This study examines how adverse geopolitical events influence the dynamics of crude oil and clean energy markets. A vector smooth transition regression model is implemented to capture the presence of regime shifts due to geopolitical conflicts. The impulse response analyses reveal that the crude oil market is non-responsive to all geopolitical events. A significant spike in oil prices arises only if risks associated with geopolitical tensions surpass a certain threshold level. The green equity market responds differently, showing an adverse reaction during episodes of higher geopolitical uncertainty. Moreover, our empirical results point out a decoupling between traditional and clean energy sectors in times of geopolitical stress. Our findings contrast with the conventional wisdom that a surge in oil prices would foster a shift toward alternative energies. While the observed disconnection would offer better diversification benefits, it is challenging for policymakers to encourage investors to maintain low-carbon portfolios.