Smooth Transition Regression Model Research Articles

Unlocking the poverty and hunger puzzle: Toward democratizing the natural resource for accomplishing SDGs 1&2

The objective of this paper is to investigate the substantial effect of natural resource abundance on poverty and hunger of the UN 2030th agenda. For this purpose, we use the panel smooth transition regression model (PSTR) technique and a sample of 20 African economies for the period 2001 to 2017, to explore the relationship between natural resource abundance and poverty and between natural resources and hunger. Besides, the principal component analysis method was used to develop two composite indices to reflect the institutional quality and hunger. The empirical highlights confirm the nonlinearity for both models, and the thresholds of poverty and hunger take the values of 18.16 and 19.24 in each model, correspondingly. We confirm the significant impact of natural resource abundance and induced opportunities as remedies to the SDGs 1&2 looming challenge and the UN agendas. Due to the obvious significance of our findings and their repercussions for decision-makers, a state of emergency in the natural resources sector should be proclaimed to address SDGs 1&2. Indeed, fair natural resource revenue management could be a critical component in addressing Africa's endless tales of poverty and hunger.

The Optimal Level of Financial Growth in View of a Nonlinear Macroprudential Policy Regime Model: A Bayesian Approach

A panel data analysis of nonlinear financial growth dynamics in a macroprudential policy regime was conducted on a panel of 10 African emerging countries from 1985–2021, where there had been a non-prudential regime from 1985–1999 and a prudential regime from 2000–2021. The paper explored the validity of the inverted U-shape hypothesis in the prudential policy regime as well as the threshold level at which excessive finance boosts growth using the Bayesian Spatial Lag Panel Smooth Transition Regression (BSPSTR) model. The BSPSTR model was adopted due to its ability to address the problems of endogeneity and heterogeneity 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 finance and growth, where the optimal level of financial development is found to be 92% of GDP, above which financial development decreases growth. The findings confirmed the Greenwood and Jovanovic hypothesis of an inverted U-shape relationship. Macroprudential policies were found to trigger the finance–growth relationship. The policy recommendation is that the financial sector should be given adequate consideration and recognition by, for example, implementing appropriate financial reforms, developing a suitable investment portfolio, and keeping spending on technological investment in Africa’s emerging countries below the threshold. Again, caution is needed when introducing macroprudential policies at a low level of the financial system.

Spillover Effects in the Presence of Structural Breaks, Persistence and Conditioned Heteroscedasticity

The intention of this article is to develop an instrument to overcome the limitations caused by traditional analyses and present a combined STR — Smooth Transition Regression model (EGARCH, STRIGARCH, and STR-FIEGARCH) to analyze the contagion effects of the 2008 financial crisis. The proposed instrument will aid the analysis of contagion and the impact of changes in long-term interest rates on the returns of international stock indices and forecasting, with special emphasis on the effects caused by structural breaks, persistence, and conditioned heteroscedasticity. The methodology begins with unit root tests with one and two structural breaks. In the second step, the asymmetry will be analyzed considering the STR models, which will determine the asymmetry relationship between interest rates and the long term, so that in a later step, these asymmetries will be used in the composition of a volatility estimation model, being based on the ARCH models: (i) EGARCH and (ii) FIEGARCH. This study provides a useful instrument based on modeling techniques to make the decision-making process more efficient and objective, providing a choice of instruments that assess the effect of changes in interest rates on stock market indices when influenced by falls, with structural data and better forecasting performance. The results show that the developed mixture models obtained better performance in predicting the effect or impact of changes in interest rates on stock market indices when influenced by structural breaks. STR and the ARCH family are useful instruments that make the decision-making process clearer and more objective when choosing instruments that assess the spillover effect of long-term interest rates on the profitability of international financial indices.

Corporate governance disclosure and annual reports quality: An investigation in Vietnam context

Corporate governance reports (CGR) and annual reports are two fundamental corporate documents disseminated to shareholders about the companies’ financial condition and operation. While the annual reports could be seen as outside appearance, the CGR reflects internal processes that an entity monitors the actions, policies, practices and decisions (Muttanachai and Thanyaorn, 2022; Ho and Taylor, 2014). Vietnam’s publicly traded companies are compulsory required to provide annual reports and CGR to shareholders. The purpose of this research is to investigate the link between the level of corporate governance disclosure (CGD) and the quality of annual reports in the context of Vietnam—an emerging and dynamic country in South East Asia. The existing literature review is developed by using a bibliometric analysis (via VOSviewer software) with Scopus database from 2002 to 2022 provides comprehensive evidence for mixed effects of the level of CGD on quality of annual reports, therefore, the paper attempts to contribute to the ongoing debate by examining whether the association between CGD and the quality of annual reports is nonlinear. Furthermore, the quality of annual reports and level of CGD are measured basing on scorecard of Vietnam Listed Company Awards (VLCA) reflect the typical research issues in the context of Vietnam. A panel smooth transition regression (PSTR) model is applied in order to test the relationship and calculate the value transition threshold of 356 Vietnamese listed companies from 2017 to 2022. Empirical findings indicate that there has been a nonlinear relationship between two tested variables. In addition, the quality of annual reports positively increases when the level of CGD exceeds the value transition threshold. Hence, the listed companies with high level of CGD (exceeds threshold value) have an incentive of preparing high quality annual reports.

Monetary policy uncertainty, monetary policy surprises and stock returns

We study the effects of monetary policy surprises on stock returns under low and high monetary policy uncertainty in the U.S. using the Panel Smooth Transition Regression (PSTR) model to identify the uncertainty regimes. Monetary policy surprises are unexpected changes in the Federal Funds Rate (FFR) on Federal Open Market Committee (FOMC) announcement days, where the mimicking portfolio method is used to obtain a regular time series with surprises since the announcements occur on an irregular basis. Using data for the period 1994–2008, we find a negative relationship between monetary policy surprises and stock returns under both uncertainty regimes but a less pronounced relationship between surprises and returns when uncertainty is low. Hence, it is more important to hedge against unexpected stock market volatility when the uncertainty in monetary policy is high compared to when uncertainty is low.

Environmental protection tax superseded pollution fees, does China effectively abate ecological footprints?

This paper constructs the ecological footprint accounts for 30 provinces in China, and explores the effects of environmental policies from the perspective of various ecological footprints. We innovatively focus on the impact which pollution fees superseded environmental protection tax on ecological footprints. The effects of these two environmental policies in China is compared with the panel smooth transition regression model (PSTR). In comparison with pollution fees, environmental protection tax has a stronger inhibition on ecological footprints. Pollution fees can lessen the cropland's ecological footprint, but this negative effect presents marginal diminishing. As for the ecological footprints of fishing grounds and fossil energy land, when pollution fees exceed 2.002 and 2.011 (‱ of GDP) respectively, there will be a restraining effect. Pollution fees has no effect on reducing the ecological footprints of grazing land, forest land, infrastructure, and the total. The environmental protection tax has a negative impact of linearity on the ecological footprints of fishing grounds and forest land. When environmental protection tax exceeds the corresponding thresholds (1.226, 3.482, 1.867 and 3.083), it will decrease the ecological footprints of grazing land, infrastructure, fossil energy land, and the total. The negative effect of environmental protection tax on cropland's ecological footprint is not obvious. Further, the change charts of influence coefficient on ecological footprints are drawn to directly reflect the optimal tax range for environmental protection tax to diminish ecological footprints. The heterogeneity analysis reveal that the current environmental protection tax only inhibits the total ecological footprint of eight provinces, mostly in northern China. These conclusions have reference significance for the government to adjust the appropriate environmental protection tax rate.

Nonlinear Relationship between Financial Development and CO2 Emissions—Based on a PSTR Model

The contradiction between financial development and environmental pollution has become increasingly prominent with economic development. The discovery of the link between financial development and carbon dioxide emissions will aid in the development of solutions to this problem. This paper uses a panel smooth transition regression (PSTR) model to examine the impact of financial development on carbon dioxide emissions using panel data from 28 Chinese provinces from 2005 to 2021. The PSTR model can solve the problem of minimizing potential outliers ignored in the previous literature, while taking into account the endogeneity and heterogeneity of the model and obtaining more reliable results. According to the findings, financial development has a nonlinear effect on carbon dioxide emissions. Furthermore, the positive effect of financial development on carbon dioxide emissions occurs via the scale and structural effects, while the negative effect occurs via the technological effect, which takes up more space. Moreover, financial added value and the financial scale demonstrate a smooth transition, while financial efficiency and foreign direct investment demonstrate a positive influence.

Corruption, imported innovation, and growth: Evidence using the panel smooth transition regression approach for developing countries

AbstractThis article investigates the nonlinear relationship between corruption, imported innovation (imports of high technology), and economic growth in developing countries from 2009 to 2018. We used a sample of 38 countries divided into two subsamples. The first covers 21 African countries, and the second covers 17 non‐African countries. The empirical results from the panel smooth transition regression model indicate that there is a threshold effect in the two relationships: corruption–imported innovation and corruption–growth. Specifically, we found that corruption exerts a significant effect only for non‐African countries. However, no significant effect was found for the whole sample and African countries. Furthermore, we found that below certain thresholds, corruption significantly decreases the level of growth for both the whole sample and the two subsamples. Above these thresholds, the effect of corruption becomes positive and significant.

Investigating the Role of Green Innovation in Economic Growth and Carbon Emissions Nexus for China: New Evidence Based on the PSTR Model

In the context of climate change and high-quality economic growth, the penetration of green innovation is crucial for attaining sustainable economic development. However, the economic growth and carbon emissions nexus has not been fully investigated from the green innovation perspective. Using green innovation as the transition variable, this research employs the panel smooth transition regression model to examine the influence of economic growth on carbon emissions in 30 Chinese provinces over the period 2000–2019. The empirical results indicate that economic growth and carbon emissions have a substantially nonlinear nexus. The promoting influence of economic growth on carbon emissions is offset and even transformed into an inhibiting effect as green innovation degree rises; that is, green innovation alters the economic growth and carbon emissions nexus and plays a considerable part in carbon reduction for China. Additionally, the temporal variations analysis indicates that the positive nexus economic growth effect exerted on carbon emissions decreases gradually as time goes on. In terms of spatial variations, economic growth in the eastern area with higher levels of green innovation exerts the least positive impacts on carbon emissions. The research findings indicate that it is crucial for the Chinese government to lay down effective environmental protection policies to stimulate the enthusiasm of green innovation for social entities.

The non-linear and interactive effects of meteorological factors on the transmission of COVID-19: A panel smooth transition regression model for cities across the globe

The ongoing pandemic created by COVID-19 has co-existed with humans for some time now, thus resulting in unprecedented disease burden. Previous studies have demonstrated the non-linear and single effects of meteorological factors on viral transmission and have a question of how to exclude the influence of unrelated confounding factors on the relationship. However, the interactions involved in such relationships remain unclear under complex weather conditions. Here, we used a panel smooth transition regression (PSTR) model to investigate the non-linear interactive impact of meteorological factors on daily new cases of COVID-19 based on a panel dataset of 58 global cities observed between Jul 1, 2020 and Jan 13, 2022. This new approach offers a possibility of assessing interactive effects of meteorological factors on daily new cases and uses fixed effects to control other unrelated confounding factors in a panel of cities. Our findings revealed that an optimal temperature range (0°C–20 °C) for the spread of COVID-19. The effect of RH (relative humidity) and DTR (diurnal temperature range) on infection became less positive (coefficient: 0.0427 to −0.0142; p < 0.05) and negative (coefficient: −0.0496 to −0.0248; p < 0.05) with increasing average temperature(T). The highest risk of infection occurred when the temperature was −10 °C and RH was >80% or when the temperature was 10 °C and DTR was 1 °C. Our findings highlight useful implications for policymakers and the general public.

Household indebtedness, financial frictions and the transmission of monetary policy to consumption: Evidence from China

This paper studies the impact of household indebtedness on the transmission of monetary policy to consumption using the Chinese household-level survey data. We employ a panel smooth transition regression model to investigate the non-linear role of indebtedness. We find that housing-related indebtedness weakens the monetary policy transmission, and this effect is non-linear as there is a much larger counteraction of consumption in response to monetary policy shocks when household indebtedness increases from a low level rather than from a high level. Moreover, the weakened monetary policy transmission from indebtedness is stronger in urban households than in rural households. This can be explained by the investment good characteristic of real estate in China.

Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model

Τhis paper presents new evidence on connectedness across cryptocurrencies in the era of the Covid-19 pandemic. The results from the TVP-VAR dynamic connectedness approach show that the degree of connectedness is time-varying, indicating a decline during the Covid-19 period. Next, this paper highlights the nonlinear characteristics of the relationship between connectedness and its explanatory variables. The results from the LSTR model indicate that the regression coefficients change smoothly between the low and the upper regimes as anxiety across Twitter users increases. As the latter changes smoothly from low to high values, the impact of higher Disease-based volatility or Twitter-based uncertainty on connectedness turns gradually from positive to negative. The upper regime is dominant during the Covid-19 pandemic. Important implications for investors and policy makers are derived.

Does globalization change the renewable energy consumption and CO2 emissions nexus for OECD countries? New evidence based on the nonlinear PSTR model

Renewable energy is preferred by most countries due to its clean and sustainable characteristic especially under the background of rapid rise in carbon emissions. However, the carbon reduction effect of renewable energy has not been thoroughly investigated in the context of rapid globalization. The panel smooth transition regression (PSTR) model is utilized in this study because it allows for smooth changes of the nexus when studying the dynamic linkage of the variables. Using globalization as the transition variable, this paper employs the PSTR model to investigate the effects of renewable energy consumption (REC) on CO2 emissions in 33 OECD countries for the period between 2000 and 2018. The empirical results demonstrate the existence of a strongly nonlinear relationship between REC and CO2 emissions. Although the renewable energy is always beneficial to carbon reduction, the carbon reduction effect of renewable energy becomes stronger as globalization level increases, that is globalization changes the REC and CO2 emissions nexus for OECD countries. Also, the individual country analysis indicates that the carbon reduction effects are more significant for the countries possessing less fossil energy and more advanced technologies. Our study emphasizes the effectiveness of globalization in encouraging the development of renewable energy and improving environmental quality. Based on this study, the significance of the global cooperation in renewables market and reducing CO2 emissions should be attached for policymakers.

Threshold Effect of Environmental Regulation on Eco-Friendly Productivity: Empirical Evidence From China

This paper identifies the existence of a significant nonlinear relationship between environmental regulation (ER) and eco-friendly efficiency (EFE) adopting the panel smooth transition regression model. It is interesting to find that ER has temporarily inhibited EFE growth in China. An initial downward trend is reversed and shows upward improvement from a distinct point, creating a V-shaped trend.

Crude Oil Price Shocks and Stock Market Volatility: Evidence From China

As the first international futures variety in China, crude oil futures, its price influence and function play has attracted much attention at home and abroad, from the perspective of market performance, crude oil futures have had a greater impact on the capital market since its launch, and what needs to be further studied is the quantitative degree and complexity of the impact of crude oil futures price fluctuations on stock market fluctuations. The daily data from March 26, 2018 to July 5, 2022 were selected to study the influence of domestic crude oil futures prices on domestic Shanghai and Shenzhen stock index by Granger causality, cointegration test and smooth transition regression model. The study shows that the price and yield of domestic crude oil futures have a one-way guiding effect on the domestic Shanghai and Shenzhen stock indexes and yields, but their guiding effect on the Shenzhen component index is greater than that of the Shanghai Composite Index. Domestic crude oil futures prices and Shanghai and Shenzhen stock indexes have a long-term similar negative cointegration relationship. The positive and negative impact of the domestic crude oil futures price yield on Shanghai and Shenzhen stock index yields is non-linear and asymmetrical, but the mechanism of impact on the two stock markets is different, for the Shanghai stock market, the negative impact of the crude oil futures price yield is greater than the positive shock impact, for the Shenzhen stock market, the positive impact of the crude oil futures price yield is greater than the negative shock impact, and the impact on both stock markets was limited .Therefore, for domestic crude oil futures to become the global crude oil price benchmark, they also need to be continuously improved in terms of national policies, industry supervision, exchange rules and market system construction.

Nonlinear relationship between financial inclusion and inclusive economic development in developed economies: evidence from panel smooth transition regression model

PurposeThe purpose of this study is to investigate the nonlinear association between financial inclusion and inclusive economic growth (IEG) in developed economies. A Block of G7 countries (Germany, Japan, Canada, France, Italy, the UK and the US) are considered in this study.Design/methodology/approachFor analysis, the authors have employed the “Panel Smooth Transition Regression model.” Annual data consists of the period from 1995 to 2019.FindingsThis research makes a unique contribution to literature with reference to G7 countries, being a pioneering attempt to apply the panel threshold regression model to analyze the relationship between financial inclusion and IEG by applying more rigorous and advanced econometric techniques.Originality/valueThe results indicate that total labor force available in a country, gross fixed capital formation and financial inclusion are positive and significant in lower regimes, but as it moves toward the higher regime, the labor force available in a country becomes less impactful. However, an increase has been observed in financial inclusion in the higher regime. The complete sample generally exhibits a positive yet significant relationship between financial inclusion and inclusive economic development.

Nonlinear Effect of Urbanization on the Gap between Urban and Rural Elementary Education in China

The urban-rural gap of elementary education seriously affects social fairness, so the study on the urban-rural gap of elementary education can help promote social fairness in China. China’s urbanization is an important variable affecting the social process, and its impact on the urban-rural gap of elementary education is worthy of further study. Based on China’s provincial panel data from 2006 to 2017, this paper uses the Theil index to measure the urban-rural gap in different aspects of elementary education and uses principal component analysis (PCA) to construct a comprehensive index to objectively measure the urban-rural gap of overall elementary education in China. Our results show that the gap between urban and rural areas in China’s elementary education showed an upward trend from 2006 to 2010, and the gap decreased year by year from 2010 to 2017. Then we used the panel smooth transition regression (PSTR) model to study the impact of urbanization on the urban-rural gap of elementary education in China and find evidence that urbanization has a nonlinear effect on the urban-rural gap of elementary education. That is, in economically underdeveloped areas, urbanization exacerbates the gap between urban and rural areas in elementary education, while in economically developed areas, urbanization narrows the gap between urban and rural areas in elementary education. Therefore, developing economy and continuing to promote urbanization are effective measures to narrow the gap between urban and rural areas in elementary education.

Exchange rate pass‐through to consumer prices in India – nonlinear evidence from a smooth transition model

AbstractUsing a backward‐looking Philips curve framework and a Logistic Smooth Transition Regression (STR) model, this article examined the exchange rate pass‐through (ERPT) to final consumer prices in the case of India. Specifically, the nonlinearity of ERPT has been investigated with respect to the level of economic activity and the rate of inflation by considering two alternative measures of exchange rate. For the first transition variable, results are markedly different between high and low‐activity regimes and signify the favourable impact of economic activity on the extent of pass‐through. In the short run, 1% exchange rate appreciation would decrease the price level by 0.244% when the economy is in a low‐activity regime; however, the same appreciation increases the price level by 0.485% when there is a boom in the economy. In the long run, ERPT in the low‐activity regime is −0.358, and in the high‐activity regime, it is 0.039. In both regimes, pass‐through coefficients differ from zero and one, implying that neither local currency pricing nor producer currency pricing characterizes the ERPT mechanism. The impact of other important determinants of inflation is also well according to theoretical expectations. Finally, for the rate of inflation, we did not report any evidence favouring the Taylor hypothesis in the case of India.

Nonlinear Impact of Inflation on Economic Growth in Nepal: A Smooth Transition Regression Approach

Macroeconomic stability is one of the most important macroeconomic goals for all countries. In recent years, the Nepalese economy has been experiencing inflation twice the economic growth rate, posing a threat to macroeconomic stability. Thus, careful investigation of the relationship between inflation and economic growth is required. This study assesses the existence of a nonlinear relationship between inflation and economic growth in the Nepalese context. The assessment is performed by considering the possibility of smoothly changing slope parameters to maximise economic growth or minimise growth losses and to determine the optimal inflation level along with the speed of inflation response to economic growth. The study applies a Logistic Smooth Transition Regression model that Terasvirta (1998, 2004) developed to estimate an optimal inflation rate using annual time-series data from 1976 to 2019. The study finds a nonlinear relationship between inflation and economic growth and estimates an optimal inflation threshold of 6.38±1.36 per cent for the Nepalese economy. It also shows that inflation positively correlates with economic growth up to the threshold level and that the association becomes negative beyond that level. This study suggests that inflation beyond the threshold level harms economic growth, while inflation below has a favourable effect. The findings assist policymakers in making an informed decision, providing leverage in inflation control and creating an atmosphere encouraging economic growth.

Artificial intelligence and unemployment:An international evidence

This paper examines the possible effect of artificial intelligence (AI) on unemployment using a broad database of AI-related patents in 40 developed and developing markets from 2000 to 2019. The study employs a panel smooth transition regression (PSTR) model to analyse the relationship between artificial intelligence and unemployment under various inflation levels. The study contributes to the existing literature with several findings. First, results from our analysis confirm the non-linear relationship between artificial intelligence and unemployment depending on the threshold of inflation. In general, artificial intelligence increases unemployment until a certain inflation threshold is attained, and then the effect reduces afterwards. Second, the smooth mechanism employed in this analysis can capture individual estimates varying amongst countries over time.