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The purpose of this study is to investigate the relationship between renewable energy consumption and economic growth, using the threshold variables of non-renewable energy consumption, urbanization level and per-capita income.

This study used a panel threshold regression model, on combined African countries and divided African countries into five regions (northern, western, central, southern and eastern Africa). The study used panel data from 54 African countries, from 1990 to 2018.

This study established a threshold interval where the significant negative impact of renewable energy consumption on the economic growth of combined African countries is different at each split asymmetric phase, meaning the relationship is negative and non-linear. Further, the study established the threshold effect of divided African countries into regions, revealed a negative effect of renewable energy consumption on economic growth and compared the differences of threshold effect and coefficient in the regions, which further highlight the varying resource and renewable energy development across African countries.

This study recommends strategies and investment priorities on energy transition, through optimizing renewable energy in Africa, hence aggressive investment in the renewable energy sector is highly encouraged especially for the oil-producing state to promote clean and sustainable energy.

The contribution of this study is the establishment of a non-linear panel threshold model to examine the asymmetric effect of renewable energy consumption on economic growth which to the best of the authors’ knowledge is pioneer research in Africa. Additionally, an in-depth analysis of renewable energy consumption’s effect on the economic growth of all the regions in Africa.

Most empirical papers on threshold effects between debt and growth focus on developed countries or a mix of developing and developed economies, often using public debt. Evidence for developing economies is inconclusive, as is the analysis of other threshold effects such as those probably caused by the level of relative development or the repayment capacity. The objective of this study was to examine threshold effects for developing economies, including external and total debt, and identify them in the debt-growth relation considering three determinants: debt itself, initial real Gross Domestic Product (GDP) per capita and debt to exports ratio.

We used a panel threshold regression model (PTRM) and a dynamic panel threshold model (DPTM) for a sample of 47 developing countries from 1970 to 2019.

We found (1) no evidence of threshold effects applying total debt as a threshold variable; (2) one critical value for external debt of 42.32% (using PTRM) and 67.11% (using DPTM), above which this factor is detrimental to growth; (3) two turning points for initial GDP as a threshold variable, where total and external debt positively affects growth at a very low initial GDP, it becomes nonsignificant between critical values, and it negatively influences growth above the second threshold; (4) one critical value for external debt to exports using PTRM and DPTM, below which external debt positively affects growth and negatively above it.

The outcome suggests that only poorer economies can leverage credits. The level of the threshold for the debt to exports ratio is higher than that found in previous literature, implying that the external restriction could be less relevant in recent periods. However, the threshold for the external debt-to-GDP ratio is lower compared to previous evidence.

A wide urban–rural income gap exists in China despite the implementation of pro-rural policies. Additionally, with the proliferation of the internet and information technology, the promotion effect of e-commerce on the economy has become apparent. Accordingly, China has been actively encouraging rural households to participate in e-commerce activities. This study aims to examine the effect of e-commerce on the urban–rural income gap.

In the study, linear and panel threshold models were applied to provincial-level panel data from 2002 to 2018.

The results of the linear model show that e-commerce contributes to narrowing the urban–rural income gap. Moreover, the panel threshold model results show that the narrowing effect exists in regions where the e-commerce intensity is at a medium-to-high level and urbanization is at a relatively low level; otherwise, e-commerce has no effect. In addition, in regions with a relatively high level of public expenditure and education, the income-gap-narrowing effect of e-commerce is more than double.

The urban–rural income gap can be reduced by promoting e-commerce and reducing the urban–rural divide in e-commerce use.

To determine how varying levels of e-commerce development affect the urban–rural income gap across regions, the study proposes four key causes of the digital divide in e-commerce: e-commerce intensity, public expenditure level, urbanization level and education level and applies the variables as threshold variables to examine the non-linear effect of e-commerce on the income gap.

This paper aims to seek the optimal proportion of female executives in corporate management teams, and to analyze the threshold effect of the proportion of female executives on the enterprise market value and enterprise management performance by using a panel threshold regression model. The purpose of this paper is to obtain the optimal interval, during which female executives exert positive effects on enterprise market value and enterprise management performance.

Based on the data of listed companies in SSE from 2003 to 2012, this paper conducts theoretical and empirical analysis by using a panel threshold regression model.

This paper proves that the proportion of female executives has a threshold effect on the enterprise market value and enterprise management performance. The results show that the proportion of female executives has an optimal interval. In other words, during the 53.8-68.4 percent interval, the proportion of female executives exerts the least negative effect on the enterprise market value and the most positive effect on the enterprise management performance.

In this paper, the non-linear relationship between female executives, enterprise market value and enterprise management performance has been verified, and the optimization interval of the female executives’ proportion has been figured out as well.

This study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the role of absorptive capacity as a moderating factor during this period.

Employing provincial panel data from China, this research measures agricultural TFP using the Stochastic Frontier Approach (SFA)-Malmquist method. The impact of FDI on agricultural productivity is further analyzed using a nondynamic panel threshold model.

The results highlight technological progress as the main driver of agricultural TFP growth in China. Agricultural FDI (AFDI) seems to impede TFP development, whereas nonagricultural FDI (NAFDI) shows a distinct positive spillover effect. The study reveals a threshold in absorptive capacity that affects both the direct and spillover impacts of FDI. Provinces with higher absorptive capacity are less negatively impacted by AFDI and more likely to benefit from FDI spillovers (FDISs).

This study provides new insights into the intricate relationship between FDI, absorptive capacity and agricultural productivity. It underscores the importance of optimizing technological progress and research and development (R&D) to enhance agricultural productivity in China.

The purpose of this study is to seek to re-examine the threshold effects of public debt on economic growth in Africa.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This monograph presents a thorough examination of the phenomena of “threshold” levels of advertising activity and the “wearout’ of advertisements and/or campaigns. These are seen as corresponding to the management questions “How little can we spend/How infrequently can we advertise?” and “How much is too much/How infrequently is too little?” In the first section the relevant literature on, or related to, the two issues is reviewed. Section 2 describes a survey aimed at establishing current beliefs in the existence of the phenomena, the practices resulting from these beliefs, and the data which support them. Finally, Section 3 offers an overview on the managerial issues involved in decisions concerning threshold or wearout risks in advertising. It is suggested that wasted expenditure may be occurring in advertising because the believed levels of threshold and wearout are both too high.

The purpose of this article is to investigate the asymmetric impact of exchange rate pass-through (ERPT) on employees' wages via consumer prices in 15 major oil-exporting countries from sub-Saharan Africa over the period 1996-2017 using the panel threshold regression model.

The methodology used in this article was built on non-linear panel threshold regression models developed by Hansen (1996, 1999) threshold regression. The authors first tested for the existence of threshold-effect in ERPT and wage nexus using 1,000 bootstrap replications and 400 grid searches to obtain an optimal threshold. We also estimated that asymmetric ERPT on employees' wages reacts differently when the inflation-threshold exceeds beyond a 15.12% threshold level.

Our findings showed that asymmetric ERPT is incomplete and indicates that an increase by one standard deviation in real exchange rate causes a decline in employees' wages by 2.69%.

The policy implications of our results are drawn from the significant threshold estimates. However, a significant threshold value of 15.12 is an inflation-threshold estimates that split our 330 observations into the lower (upper) regimes. Further, an inflation rate beyond the threshold value is likely to have an asymmetric ERPT on employees' wages in the 15 major oil-exporting sub-Saharan African (SSA) countries.

The practical implication of the study is when ERPT exceeds the threshold, the effect of real exchange rate variations is passed on to employees' wages. It is widely believed that labor productivity increase with increased minimum wages. Nevertheless, there is contention as regards the effects on employment and poverty. As rising goods prices make the minimum wage increased homogeneous of degree zero.

Considerable increased ERPT on imported goods reduces employees' wages purchasing ability from import-dependent countries through import prices. Once it has documented, this also reduces welfare via deteriorations of marginal propensity to consume (MPC) and marginal propensity to savings (MPS).

This article integrates labor purchasing power into the analysis of ERPT using non-linear dynamic panel heterogeneous threshold regression. It extends the Hansen (1996, 1999) dynamic panel threshold models to exchange rate pass-through in SSA economies.

This study aims to explore the relationship between the growth threshold effect on renewable energy consumption (REC) in the major oil-producing countries in sub-Saharan Africa (SSA) over the period 1990–2018.

This article used a dynamic panel threshold regression model introduced by Hansen (1996, 1999 and 2000) threshold (TR) models. The procedure is achieved using 5,000 bootstrapping replications and the grid search to obtain the asymptotic distribution and p-values. For the long-run relationship among our variables, the author followed the process in Pesaran et al. (1999) pooled mean group (PMG) for heterogeneous panels. Furthermore, for the robustness of our empirical results due to the sensitivity of the results to outliers, the author used the approach by Cook (1979) distance measure. The author applied quantile (QR) regression to explore the distribution of dependent variables following Bassett and Koenker (1982) and Koenker and Bassett (1978) approaches.

The results from the threshold effect test and threshold regression revealed a significant single threshold effect of growth level on REC. Furthermore, the result from the PMG estimation showed the growth of the variable, energy intensity, consumer prices and CO₂ emissions play a significant role in REC in major oil-producing countries in SSA. The growth threshold estimation results indicated one significant threshold value of 1.013% at one period lagged of real growth. The outlier’s sensitivity detention greatly influenced our empirical results.

The article filled the literature gap by applying a combined measure that is robustness to detect outliers in the data, which none of the studies in the literature addresses hitherto. Further, the article extends the quantile regression to growth – REC literature.