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1 – 10 of over 17000The threshold regression framework is used to examine the effect of foreign direct investment on growth in Sub-Saharan Africa (SSA). The growth literature is awash with divergent…
Abstract
Purpose
The threshold regression framework is used to examine the effect of foreign direct investment on growth in Sub-Saharan Africa (SSA). The growth literature is awash with divergent evidence on the role of foreign direct investment (FDI) on economic growth. Although the FDI–growth nexus has been studied in diverse ways, very few studies have examined the relationship within the framework of threshold analysis. Furthermore, even where this framework has been adopted, none of the previous studies has comprehensively examined the FDI–growth nexus in the broader SSA. In this paper, within the standard panel and threshold regression framework, the problem of determining the growth impact of FDI is revisited.
Design/methodology/approach
Six variables are used as thresholds – inflation, initial income, population growth, trade openness, financial market development and human capital, and the analysis is based on a large panel data set that comprises 45 SSA countries for the years 1985–2013.
Findings
The results of this study show that the direct impact of FDI on growth is largely ambiguous and inconsistent. However, under the threshold analysis, it is evident that FDI accelerates economic growth when SSA countries have achieved certain threshold levels of inflation, population growth and financial markets development. This evidence is largely invariant qualitatively and is robust to different empirical specifications. FDI enhances growth in SSA when inflation and private sector credit are below their threshold levels while human capital and population growth are above their threshold levels.
Originality/value
The contribution of this paper is twofold. First, the paper streamlines the threshold analysis of FDI–growth nexus to focus on countries in SSA – previous studies on FDI-growth nexus in SSA are country-specific and time series–based (see Tshepo, 2014; Raheem and Oyınlola, 2013 and Bende-Nabende, 2002). This paper provides a panel analysis and considers a broader set of up to 45 SSA countries. Such a broad set of SSA countries had never been considered in the literature. Second, the paper expands on available threshold variables to include two new important macroeconomic variables, population growth and inflation which, though are important absorptive capacities but, until now, had not been used as thresholds in the FDI–growth literature. The rationale for including these variables as thresholds stems from the evidence of an empirical relationship between population growth and economic growth, see Darrat and Al-Yousif (1999), and between inflation and economic growth, see Kremer et al. (2013).
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The purpose of this study is to seek to re-examine the threshold effects of public debt on economic growth in Africa.
Abstract
Purpose
The purpose of this study is to seek to re-examine the threshold effects of public debt on economic growth in Africa.
Design/methodology/approach
This study applies panel smooth transition regression approach advanced by González et al. (2017). The method allows for both heterogeneity as well as a smooth change of regression coefficients from one regime to another.
Findings
A debt threshold in the range of 62–66% is estimated for the whole sample. Low debt is found to be growth neutral but higher public debt is growth detrimental. For middle-income and resource-intensive countries, a debt threshold in the range of 58–63% is estimated. As part of robustness checks, a dynamic panel threshold model was also applied to deal with the endogeneity of debt, and a much higher debt threshold was estimated, at 74.3%. While low public debt is found to be either growth neutral or growth enhancing, high public debt is consistently detrimental to growth.
Research limitations/implications
The findings of this study show that there is no single debt threshold applicable to all African countries, and confirm that the debt threshold level is sensitive to modeling choices. While further analysis is still needed to suggest a policy, the findings of this study show that high debt is detrimental to growth.
Originality/value
The novelty of this study is twofold. Contrary to previous studies on Africa, this study applies a different estimation technique which allows for heterogeneity and a smooth change of regression coefficients from one regime to another. Another novelty distinct from the previous studies is that, for robustness checks, this study divides the sample into low- and middle-income countries, and into resource- and nonresource intensive countries, as debt experience can differ among country groups. Further, as part of robustness checks, another estimation method is also applied in which the threshold variable (debt) is allowed to be endogenous.
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Sachin Gupta and Anurag Saxena
The operational aspects of supply chain, when handled correctly, results in diminishing the impact of the bullwhip effect. The purpose of this study is to analyze the impact of…
Abstract
Purpose
The operational aspects of supply chain, when handled correctly, results in diminishing the impact of the bullwhip effect. The purpose of this study is to analyze the impact of operational and financial variables on the bullwhip effect. Various operational factors that contribute to the bullwhip effect in a supply chain are identified and their impact on variability in production is measured at manufacturer’s end in the supply chain.
Design/methodology/approach
Ten different sectors of the Indian economy are identified and analyzed on the basis of bullwhip effect. The ratio of change in production with respect to change in demand is taken as a metric to measure the bullwhip effect. Initially, the impact of identified variables on bullwhip effect is analyzed using the linear regression analysis and then to gain more insights, the threshold regression model is applied according to the change in bullwhip ratio.
Findings
The study identifies four threshold regions in which bullwhip ratio is changing its slope considerably. The operational and financial variables impacting bullwhip effect differently in these four regions provide useful insights about how the variables are impacting the bullwhip effect.
Research limitations/implications
Past 11 years of observations on identified operational and financial variables are studied for ten different sectors. The operational and financial variables are identified on basis of available literature but may not be exhaustive in nature.
Practical implications
The present study implies that the emphasis must be given to the magnitude of the bullwhip ratio. Strategies must be adopted that result in mitigation of bullwhip effect. Such mitigation strategies must not only be restricted on the basis of type of product or sector, perhaps they must be on the basis of threshold region of bullwhip ratio.
Originality/value
The study suggests a novel approach to study the bullwhip effect in supply chain management using the application of threshold regression considering the bullwhip ratio as a threshold variable.
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Xiaoxue Zhou, Yu Li and Yao Zhang
The purpose of this paper is to explore the threshold effect of firm size on technological innovation using panel data from 2007 to 2012 for listed enterprises in China's…
Abstract
Purpose
The purpose of this paper is to explore the threshold effect of firm size on technological innovation using panel data from 2007 to 2012 for listed enterprises in China's manufacturing sector.
Design/methodology/approach
Considering the aim of research question is to examine the nonlinear relationship, this paper utilizes the threshold regression proposed by Hansen's (2000).
Findings
Based on a threshold regression model using panel data from 2007 to 2012 for listed enterprises in China's manufacturing sector, we find a series of new results. This nonlinear relationship is under the restrictions and impacts of various factors, such as industry characteristics and government subsidies. The results suggest that the threshold regression model well explains the complicated nonlinear relationship and transition process, and it can also shed light on management practice and policy.
Originality/value
There are categorical arguments regarding why firm size is not as effective as before in explaining the monotonic principle of industrial innovation, especially for establishing an effective industrial policy in a particular situation. One of the important reasons is that we have begun to adopt a new perspective from the nonlinear view on the relationship between firm size and industrial innovation. In this study, we have examined the threshold effect of firm size on industrial technological innovation, which is the most representative nonlinear relationship.
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Eric B. Yiadom, Lord Mensah, Godfred A. Bokpin and Raymond K. Dziwornu
This research investigates the threshold effects of the interplay between finance, development and carbon emissions across 97 countries, including 50 low-income and 47 high-income…
Abstract
Purpose
This research investigates the threshold effects of the interplay between finance, development and carbon emissions across 97 countries, including 50 low-income and 47 high-income countries, during the period from 1991 to 2019.
Design/methodology/approach
Employing various econometric modeling techniques such as dynamic linear regression, dynamic panel threshold regression and in/out of sample splitting, this study analyzes the data obtained from the World Bank's world development indicators.
Findings
The results indicate that low-income countries require a minimum financial development threshold of 0.354 to effectively reduce carbon emissions. Conversely, high-income countries require a higher financial development threshold of 0.662 to mitigate finance-induced carbon emissions. These findings validate the presence of a finance-led Environmental Kuznet Curve (EKC). Furthermore, the study highlights those high-income countries exhibit greater environmental concern compared to their low-income counterparts. Additionally, a minimum GDP per capita of US$ 10,067 is necessary to facilitate economic development and subsequently reduce carbon emissions. Once GDP per capita surpasses this threshold, a rise in economic development by a certain percentage could lead to a 0.96% reduction in carbon emissions across all income levels.
Originality/value
This study provides a novel contribution by estimating practical financial and economic thresholds essential for reducing carbon emissions within countries at varying levels of development.
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Bin Xi and Pengyue Zhai
The purpose of this study is to explore the impact of environmental pollution and industrial structure upgrading on environmental pollution in different stages based on the…
Abstract
Purpose
The purpose of this study is to explore the impact of environmental pollution and industrial structure upgrading on environmental pollution in different stages based on the temporal and spatial heterogeneity of economic development level and industrial structure upgrading level in eastern, central and western regions of China and discuss whether there is adjustment effect and threshold effect in the process of economic growth affecting environmental pollution, and finally realizes sustainable economic development.
Design/methodology/approach
Based on panel data from 30 provincial-level administrative regions of China (excluding Tibet and Hong Kong, Macao and Taiwan) from 2000 to 2019, this paper uses the environmental Kuznets curve, regulating effect model and panel threshold model to analyze the impact of economic growth and industrial structure upgrading on environmental pollution.
Findings
The results present that the uneven distribution of natural resources leads to different levels of economic development and industrial structure upgrading in eastern and western regions, and its impact on environmental pollution is also different. Economic growth and industrial structure upgrading have a positive effect on environmental pollution, and the relationship between economic growth and environmental pollution is inverted U-shaped. At present, the eastern, central and western regions of China are at the right end of the inverted U-shaped relationship. In general, industrial structure upgrading in eastern, central and western regions has a significant inhibitory effect on environmental pollution. Industrial structure upgrading has a negative moderating effect on the relationship between economic growth and environmental pollution, and the regulating effect is most significant in the central region, followed by the eastern region, and not significant in the western region. The results of panel threshold model show that the industrial structure upgrading can slow down the positive impact of economic growth on environmental pollution and strengthen the negative moderating effect of industrial structure upgrading on economic growth and environmental pollution.
Originality/value
The innovation of this study is to bring economic growth, industrial structure upgrading and environmental pollution into a unified analytical framework, analyze the impact of economic development and industrial structure upgrading levels in different periods on environmental pollution, and select industrial structure upgrading as the moderating variable and threshold variable. It provides a thought for the influence mechanism of different levels of industrial structure upgrading on economic growth and environmental pollution. Based on the panel data in China, this study emphasizes the concept of sustainable development, adheres to green development and proposes relevant policies to improve environmental pollution. And this paper proposes relevant policies to improve environmental pollution from the perspective of transforming economic growth mode and optimizing industrial structure in China, which also has reference significance for developing countries to realize sustainable economic development.
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Ganli Liao, Xinshuai Hou, Yi Li and Jingyu Wang
Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of…
Abstract
Purpose
Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.
Design/methodology/approach
Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.
Findings
The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.
Originality/value
Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.
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Tobias Burggraf, Toan Luu Duc Huynh, Markus Rudolf and Mei Wang
This study examines the prediction power of investor sentiment on Bitcoin return.
Abstract
Purpose
This study examines the prediction power of investor sentiment on Bitcoin return.
Design/methodology/approach
We construct a Financial and Economic Attitudes Revealed by Search (FEARS) index using search volume from Google's search engine to reveal household-level (“bankruptcy”, “unemployment”, “job search”, etc.) and market-level sentiment (“bankruptcy”, “unemployment”, “job search”, etc.).
Findings
Using a variety of quantitative methodologies such as the transfer entropy model as well as threshold regression and OLS, GLS and 2SLS estimations, we find that (1) investor sentiment has strong predictive power on Bitcoin, (2) household-level sentiment has larger effects than market-level sentiment and (3) the impact of sentiment is greater in low sentiment regimes than in high sentiment regimes. Based on these information, we build a hypothetical trading strategy that outperforms a simple buy-and-hold strategy both on an absolute and risk-adjusted basis. The results are consistent across cryptocurrencies and regions.
Research limitations/implications
The findings contribute to the ongoing debate in the literature on the efficiency of cryptocurrency markets. The results reveal that the Bitcoin market is not efficient in the sense of the efficient market hypothesis – asset prices do not fully reflect all available information and we were able to “beat the market”. In addition, it sheds further light on the debate whether Bitcoin can be considered a medium of exchange, i.e. a currency or an investment product. Because investors are reallocating their Bitcoin holdings during times of increased market sentiment due to liquidity needs, they obviously consider bitcoin an investment product rather than a currency.
Originality/value
This study is the first to examine the impact of investor sentiment measured by FEARS on Bitcoin return.
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Striving to achieve the goal of carbon neutrality before 2060 indicates that China, as the most extensive power system in the world and a country based on coal power, is…
Abstract
Purpose
Striving to achieve the goal of carbon neutrality before 2060 indicates that China, as the most extensive power system in the world and a country based on coal power, is imperative to improve the technical level of electric power utilization. This paper aims to explore the nonlinear evolution mechanism of power technology progress under the constraints of net-zero carbon dioxide emissions in China.
Design/methodology/approach
This paper, first, based on China’s provincial panel data from 2000 to 2019, uses global direction distance function to measure power technological progress. Second, the threshold regression model is used to explore the nonlinear relationship between carbon emission reduction constraints on electric power technological progress.
Findings
There is a significant inverted U-shaped relationship between China’s provincial carbon emission reduction constraints and electric power technological progress. Meanwhile, the scale of regional economic development has a significant moderating effect on the relationship between carbon emission reduction constraints and power technological progress.
Research limitations/implications
This paper puts forward targeted suggestions for perfecting regional carbon emission reduction policy and improving electric power technological progress.
Originality/value
Based on the global directional distance function, this paper extracts power as a production factor in total factor productivity and calculates the total factor electric power technological progress. This paper objectively reveals the influence mechanism of carbon emission reduction constraints on electric power technology progress based on the threshold regression model.
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This study aims to examine the relationship between private capital inflows, financial development and economic growth in 28 sub-Saharan African (SSA) countries between the…
Abstract
Purpose
This study aims to examine the relationship between private capital inflows, financial development and economic growth in 28 sub-Saharan African (SSA) countries between the periods 1995 and 2017.
Design/methodology/approach
The study used a secondary source of data obtained from the world development indicator (WDI) and used the system generalized method of moments (SGMM) and dynamic panel threshold regression to analyze the data.
Findings
The study found that foreign direct investment has a negative and significant impact on the economic growth of SSA. The study also found that portfolio investment has a positive impact on economic growth but it is statistically insignificant. However, when portfolio investment interacted with financial development, it became positive and statistically significant presupposing that financial development is a necessary condition for portfolio investment to exert impact on economic growth. Further, the study showed that the interaction of foreign direct investment with financial development has a negative and significant effect on economic growth. Finally, the study found the minimum threshold of financial development at 42.66 per cent.
Practical implications
Policymakers in SSA should be cautious and critical in the kind of foreign direct investment they attract as the open door policy to attract all kinds of foreign direct investment would not bring about the desired result. Also, policymakers in the region should develop and implement policies that would deepen and strengthen the financial system to foster the development of the country’s financial sector and accelerate economic growth.
Originality/value
The contribution of the study lies in establishing a minimum threshold of financial development; thus, providing a clear-cut direction for policymakers in SSA countries in their pursuit of financial development and economic growth.
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