Smooth Transition Regression Research Articles

Economic Growth and Income Inequality in Sub-Saharan Africa: Does Environmental Policy Matter?

The counter-intuitive correlation between economic growth and income inequality in sub-Saharan Africa in recent years and the lack of consensus in the literature on this relationship call for its re-examination, particularly in the context of sustainable development. This article analyses the effect of environmental policies on the relationship between economic growth and income inequality in sub-Saharan Africa. With its suitability for analyzing non-linear relationships, the panel smooth transition regression model (PSTR) of Gonzalès (2005) was applied to data covering the period 1999 to 2021 from the World Bank, the Yale Center for Environmental Law and Policy (YCELP), the World Governance Indicator (WGI) and the World Income Inequality Database WIID.In the presence of a strict application of environmental policies, the results show a U-inverted relationship between economic growth and income inequality in sub-Saharan Africa. The more a relatively wealthy country adopts a rigorous environmental policy, the more economic growth contributes to reduce income inequalities. Thus, the socially virtuous effect of a rigorous environmental policy only occurs in economically dynamic countries. In other words, environmental policies in sub-Saharan African countries can only be promoted in relation to their economic performance. Any standardisation of environmental policies on a continental or sub-regional scale for economically different countries should be reconsidered.

Is corruption useful in a context of weak democracy? Revisiting the relationship between financial development and economic growth in sub-Saharan Africa

The purpose of this study is to examine the role of corruption in a context of weak democracy on the relationship between financial development and growth. Using data from 28 sub-Saharan African countries covering the period from 1990 to 2017, we implemented two estimation methods: the smooth transition regression method for the static panel and the generalised method of moments for the dynamic panel model. The results of our estimations mainly validated the asymmetric moderating effect of democracy and corruption on the impact of financial development on economic growth. We demonstrated that financial development has a significant and positive effect on growth when the level of democracy increases. At the same time, financial development has a significant and positive effect on growth when the level of corruption increases. These results confirm the "grease the wheels" hypothesis in a context of weak democracy. Although our results show that corruption greases the wheels of growth in the short term, in the long term it can be detrimental to the economy. We therefore recommend that political decision-makers promote democracy and take the necessary measures to reduce corruption.

Threshold effects of financial inclusion on financial stability: Evidence from BRICS nations

This paper investigates the impact of financial inclusion on financial stability in BRICS countries from 2004 to 2020. Using a panel smooth transition regression model, the results reveal a U-shaped relationship between financial inclusion and financial stability. Financial inclusion reduces financial stability up to a threshold of 44.7%. Beyond this point, financial inclusion contributes to greater financial stability, through gradual transitions. Enhanced financial inclusion supports banks in stabilizing their deposit funding by facilitating access to more stable, long-term funds and alleviating the negative impacts of fluctuations in returns. Furthermore, the study examines the role of institutional quality in shaping the financial inclusion-financial stability nexus, indicating a significant positive effect, especially in the upper regime. These findings provide valuable insights for financial regulatory authorities, highlighting the importance of promoting financial inclusion in BRICS economies and adapting regulations to mitigate potential risks to global financial stability.

Are natural resource volatility curses or blessings for economic performance? Stories of resource-rich regions

This paper analyses the time-varying and non-linear effects of natural resource volatility on economic growth in 10 countries using the smooth transition regression (STR) model and further examines the long-run and short-run relationships using the autoregressive distributed lag (ARDL) cointegration approach. The conclusions exhibit that natural resource rents are linearly and non-linearly associated with economic growth in countries with different levels of economic development, and display long-term cointegration and short-term equilibrium state. This study provides guidance for policymakers to implement long-term and short-term management strategies when considering national development differences.

Does the material recycling rate matter in the effect of the generated waste on environmental pollution? Panel smooth transition regression approach

This study examined the effect of material recycling on the relationship between the waste amount and environmental pollution in EU-15 countries for the 1995-2019 period through panel smooth regression analysis by using the material recycling rate as the threshold variable. Based on the analysis results, the material recycling rate threshold level was estimated as 11.79. In these countries, if the material recycling rate is below the threshold level, the rise in the waste amount will increase environmental pollution. If the material recycling rate is above the threshold value, the rise in the waste amount will still increase environmental pollution, but the pollution increase rate will decrease. With the increase in the waste amount in the long term, environmental pollution can only be reduced by raising the material recycling rate. For the reduction of environmental pollution, which is one of the most prioritized issues in Europe in recent years, policy makers should take measures to increase the material recycling rate by taking the results of this study into consideration and pay attention to the implementation of these measures.

Nonlinearities in Economic Globalization Effects on the Environment: New Insights from a Panel Smooth Transition Regression Model

Abstract This study aimed to estimate the impact of economic globalization on environmental quality and examine the role of renewable energy production (REP) in this impact. For this purpose, the annual data of 1976–2021, which is the longest possible period, of the top 5 countries (Sweden, Switzerland, Norway, France, and Denmark) that show the best performance according to the Global Green Economy Index 2022 report, were used. These countries were chosen due to their high performance in green economy integration; and thus, it was considered that this research could provide reference results for other countries. In order to achieve this, the panel smooth transition regression model was applied to the dataset. This nonlinear approach divides the series into homogeneous regimes depending on the threshold variable and allows us to make regime-specific interpretations. As a result, this study, in which REP was defined as the threshold variable, has shown that there is a two-regime nonlinear relationship between environmental quality and economic globalization. According to the findings, economic globalization caused an increase in environmental degradation in the first regime, which had low REP. However, this impact was eliminated in the second regime, where REP was high.

The impact of the digital economy on carbon emission intensity from the environmental regulation perspective

ABSTRACT This study examines the nonlinear relationship between the digital economy and carbon emission intensity using Panel Smooth Transition Regression (PSTR) based on data from cities between 2010 and 2019. As environmental regulation intensity increases, the positive impact of the digital economy on carbon emission intensity gradually diminishes. This study offers a novel perspective on the interplay between the digital economy and carbon emission intensity within the context of environmental regulation.

The dark side of climate policy uncertainty: Hindering energy transition by shaping environmental taxes effectiveness

Climate policy uncertainty (CPU) may have an adverse impact on the environment by interfering with the effectiveness of environmental policies, but there is currently little evidence to support this indirect effect. By incorporating CPU into the transition function, this paper utilizes the panel smooth transition regression (PSTR) to dynamically analyze how CPU affects the relationship between environmental taxes (ETR) and energy transition. When CPU exceeds the threshold, the promoting effect of ETR on energy transition weakens or reverses. The robustness of the main conclusions is demonstrated by establishing a PSTR estimator with the instrumental variable. This paper also constructs a counterfactual scenario, showing that CPU reduces the positive impact of ETR on renewable energy consumption and generation by 7.6% and 3.5%, respectively. Further analysis indicates that this negative effect arises because CPU likely increases investment risk, particularly for long-term green projects, thereby inhibiting the clean energy market and energy-related green technological innovation. Heterogeneity analysis find that the weakening effect of CPU on the effectiveness of ETR is stronger in countries with low energy resource endowment, high energy intensity, and lower economic development levels, underscoring the need for tailored policy approaches. This research emphasizes that for countries with ambitious energy transition goals, climate policy stability is crucial for ensuring the healthy development of environmental taxes policy and renewable energy markets.

Threshold-based influence of currency devaluation on external debt sustainability: Insights from smooth transition regression and multiple thresholds nonlinear ARDL approaches

This study offers unique insights into the threshold-based influence of currency devaluation (CD) on external debt sustainability (EDS) in designated Sub-Saharan African (SSA) countries. The absence of evidence from this viewpoint, particularly in SSA, inspires this new assessment. On this premise, the study utilizes two innovative estimation procedures: smooth transition regression (STR) and multiple thresholds nonlinear ARDL (MTNARDL) to estimate the sign-based and magnitude-based asymmetric influence of CD on EDS. The outcomes indicate that first, an average CD threshold of 21.1% is consistent with EDS in the designated nations; second, a small CD significantly reduces the external debt–GDP ratio and improves sustainability, while a very high CD largely worsens the EDS problem; third, in the CD regime, devaluation has more detrimental effects on external debt burden; fourth, exceedingly large changes in exchange rate (whether positive or negative) essentially affect the countries’ EDS negatively; and fifth, the adverse effect of large depreciation on EDS is greater than that of large appreciation. The study recommends, amongst others, that heavily indebted countries with sizeable external debt denominated in foreign currency should, as a matter of urgency, avoid excessive and escalated large percentages of devaluation or exchange rate depreciation.

The role of governance and infrastructure in moderating the effect of resource rents on economic growth

AbstractThis study investigates how governance and infrastructure moderate the effect of natural resource rents on economic growth using a sample of 110 countries from 2000 to 2018. The empirical evidence is based on panel smooth transition regressions (PSTR). The nexus between economic growth and natural resources is not linear and the underlying non‐linearity is contingent on existing infrastructural and governance levels. Evidence of a “natural resource curse” is apparent in countries with extremely low levels of governance and infrastructural development. The favorable effect of natural resources on economic growth requires a governance threshold of −1.210 and an infrastructure threshold of 2.583, indicating that countries with governance and infrastructure levels higher than these values tend to benefit much more from the wealth of natural resources. Countries identified below the established thresholds are mainly from Africa. Policy implications are discussed with specific emphasis on African countries.Related ArticlesAli, Hamid E., and Shahjahan Bhuiyan. 2022. “Governance, Natural Resources Rent, and Infrastructure Development: Evidence from the Middle East and North Africa.” Politics & Policy 50(2): 408–40. https://doi.org/10.1111/polp.12451.Asiegbu, Martin F., Okey Marcellus Ikeanyibe, Pius Otu Abang, Okwudili Chukwuma Nwosu, and Chuka Eugene Ugwu. 2024. “Natural Resource Fund Governance and the Institutionalization of Rent Seeking in Nigeria's Oil Sector.” Politics & Policy 52(1): 169–95. https://doi.org/10.1111/polp.12579.Ikeanyibe, Okechukwu M. 2018. “Bureaucratic Politics and the Implementation of Liberalization Reforms in Nigeria: A Study of the Unbundling and Reorganization of the Nigerian National Petroleum Corporation.” Politics & Policy 46(2): 263–94. https://doi.org/10.1111/polp.12249.

How Does the Digital Economy Affect Carbon Emissions? Evidence from Panel Smooth Transition Regression Model

How Does the Digital Economy Affect Carbon Emissions? Evidence from Panel Smooth Transition Regression Model

Female top managers, female owners and corporate financial sustainability: new evidence from a panel smooth transition regression model

This study investigates the nonlinear link between gender diversity at various levels and business financial sustainability for a large sample of 54759 enterprises in 80 developing countries from 2015 to 2022. Previous studies have shown that female participation may bring both advantages and costs to businesses. The empirical evidence on whether it improves or degrades company results is inconclusive. This research attempts to improve our knowledge of the complicated link between gender diversity and company financial sustainability. It explains how female managers’ and female owners’ effects on business sustainability is dependent on their different levels of engagement in the firm. Results of the Panel Smooth Transition Regression model (PSTR) demonstrate a nonlinear relationship between gender diversity and firm sustainability. Depending on the measure of female participation, the model contains one threshold at 39% of female senior managers and 34% of female owners, as well as two extreme regimes. The results reveal that below these thresholds the relationship is negative. Misunderstandings and a lack of coherence between groups of different genders may affect decision-making and the capacity to come up with the best responses. However, increasing gender diversity has a favourable influence on firm sustainability above the projected thresholds. This research supports the theory that a critical mass condition is required before a minority group begins to alter organisational functioning. Our findings demonstrate that diversity has an influence on collective decision making and, hence, sustainability only when a critical mass is reached. These findings offer numerous managerial insights and policy recommendations for developing-country enterprises looking to improve their financial sustainability.

Corruption-inequality relationship in Sub-Saharan Africa

This paper investigates the effect of corruption on income inequality in Sub-Saharan Africa (SSA) over the period 1996–2022. Applying a threshold model approach notably the Panel Smooth Transition Regression (PSTR), two major results emerge from this analysis. First, the results reveal a U-shaped relationship between corruption and income inequality, with a different inflection point depending on the type of corruption. Second, we obtained strong evidence that corruption significantly increases income inequality in Sub-Saharan Africa only if the level of corruption is above a certain threshold, otherwise the effect of corruption is not detrimental. Furthermore, the results indicate that judicial corruption has the most detrimental effect on income inequality, followed by executive and legislative corruption. The paper suggests that public authorities promote transparency and good governance. Also, allocating resources to improving the education and healthcare systems will also help reduce inequalities.

Re-examining the curse of natural resources in SSA: New evidence from disaggregated natural resources and types of corruption

Understanding how corruption affects the relationship between natural resources and growth has profound implications for sustainable development goals in Sub-Saharan Africa (SSA). This study investigates the nexus between natural resources, economic growth, and corruption in SSA from 1985 to 2022, by employing a Panel Smooth Transition Regression model. Results indicate that corruption distorts natural resources and lowers economic growth. The magnitude of the effect of corruption depends on the type of corruption. The impact of political corruption is more relevant than the others form of corruption. In a low corruption regime, mineral, oil, and forest resources do not affect growth; (b) in a high corruption regime, oil and forest resources hinder growth whereas mineral resources lead to higher economic growth. The analysis highlights the need for policy measures that encourage sustainable economic development and promoting reinforcement of institutional quality.

Revisiting the resource curse: Does volatility matter?

AbstractCountries with abundant natural resources often possess greater wealth, yet the impact of these resources on economic growth remains unclear. This paper examines how natural‐resource abundance and its volatility impact economic growth. It questions whether natural resources themselves are a curse or if the negative growth effects are due to the volatility of natural‐resource revenues. The study also investigates how volatility of natural resources affects key economic growth channels, such as investment, human capital, and institutional quality. Using the standard panel model and panel smooth transition regression (PSTR), the paper analyzes data from 125 countries (1988–2020). Results show that natural‐resource abundance boosts economic growth, contradicting the resource‐curse theory. However, the growth impact is non‐linear and varies with natural‐resource volatility. Countries with high volatility face up to a 22 percentage point annual GDP growth loss compared with those with low volatility, suggesting that volatility and poor government responses drive the resource‐curse paradox, not the abundance of resources per se.

Estimation of the public debt threshold effects on economic growth in sub‐Saharan African countries

AbstractUsing data for 22 sub‐Saharan African (SSA) countries, this paper investigates the effects of public debt on economic growth in SSA countries covering the period 1990–2021. Relying upon the estimation of Panel Smooth Transition Regression and generalized method of moments method, our findings offer strong evidence that public debt nonlinearly impacts economic growth. More specifically, there exists a threshold beyond which public debt exerts a negative effect on growth. These results can be used to formulate economic recommendations that the public authorities could implement to improve public debt management and maintain stable economic growth.

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.

The nonlinear dynamic effect of government expenditure on income inequality: The case of macroprudential policy switching

A panel data analysis of nonlinear government expenditure and income inequality dynamics in a macroprudential policy regime was conducted on a panel of 15 emerging countries from 1985–2019, where there had been a non-prudential regime from 1985–1999 and a prudential regime from 2000–2019. The paper explored the validity of the nonlinearity between government expenditure and income inequality in the macroprudential policy regime as well as the threshold level at which excessive spending reduces income inequality using the Bayesian spatial lag panel smooth transition regression (BSPSTR) and fix effect models. The BSPSTR model was adopted due to its ability to address the problems of heterogeneity, endogeneity, and cross-section correlation in a nonlinear framework. Moreover, as the transition variable often varies across time and space, the effect of the independent variables can also be time- and space-varying. The results reveal evidence of a nonlinear effect between government spending and income inequality, where the minimum level of government spending is found to be 29.89 percent of GDP, above which expenditure reduces inequality in emerging countries. The findings confirmed an inverted U-shaped relationship. The focal policy recommendation is that fiscal policy decisions that will reinforce the need for more emphasis on education and public expenditure on education and health, as important tools for improving income inequality, are crucial for these economies. Caution is needed when introducing macroprudential policies, especially at a low level of government expenditure.

The complex relationship between credit and liquidity risks: a linear and non-linear analysis for the banking sector

This article explores the reciprocal link between credit risk and liquidity risk in Tunisia. To the best of our knowledge, no study has examined the linear and non-linear relationships between credit risk (CR) and liquidity risk (LR) taken in both directions. We utilized a sample of Tunisian banks from 2000 to 2018 to investigate this link in both causative directions and within a linear and non-linear framework. Unlike previous investigations, we used two empirical approaches. The linear link was assessed using the Seemingly Unrelated Regression (SUR) model, whilst the non-linear correlation was investigated using the Panel Smooth Transition Regression (PSTR) model.The results of the linear analysis show that credit and liquidity risks are positively related in both directions. The non-linear analysis proves that there is a threshold impact in both connections. More specifically, we discovered that the NPLs ratio, which measures credit risk, is 9.87%, while the LTD ratio measures liquidity risk, which is 102%. Below this threshold, there is a negative and significant relationship; beyond these thresholds, the effect is positive but only significant for the influence of credit risk on liquidity risk.

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.