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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.

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.

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.

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).

The study examines whether the growth effect of government spending is contingent on the level of institutional environment prevalent in Economic Community of West African States (ECOWAS).

The study adopts the more refined and more appropriate dynamic threshold panel by Seo and Shin (2016) and made applicable be Seo et al. (2019). The technique models a nonlinear asymmetric dynamics and cross-sectional heterogeneity simultaneously in a dynamic threshold panel data framework.

The results show that there is a threshold effect in the government spending-growth relationship. Specifically, the authors found that the impact of government spending on economic growth is positive and statistically significant only above a certain threshold level of institutional development. Below that threshold, the effect of government spending on growth is insignificant and negative at best. The findings suggest that government spending-growth nexus is contingent on the level of Institutional quality.

Unlike previous studies that adopt the linear interaction model which pre-impose a priori conditional restrictions, this study adopts the dynamic threshold panel framework which allows the lagged dependent variable and endogenous covariates.

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.

This study aims to interrogate dynamic asymmetric relationships between public debt and economic growth in Southern African Developing Communities (SADC), over the period 2000–2018.

The study employed a panel smooth transition regression (PSTR) technique to analyse dynamic asymmetric relationships between public debt and economic growth, and the threshold effect at which public debt hampers economic growth.

The findings indicate that there is a significant nonlinear effect of debt on economic growth in SADC. The study discovered a debt threshold of 60% to GDP at which debt beyond this threshold deteriorates long-term growth. The low-debt regime was found to be positive and statistically significant, while the high-debt regime is detrimental for long-term growth. Fiscal policymakers ought to consider the adoption of well-coordinated debt policies that aims to strike a balance between sustainable public debt and economic growth, within a reasonable threshold target.

The study focusses on asymmetric and threshold analysis of public debt on economic growth in SADC using sophisticated panel smooth transition regression (STAR). This study provides rigorous empirical evidence within the SADC perspective in which previous studies have predominantly been confined in advanced economies.

The study's objective is to examine the relevance of globalization in affecting the size of the shadow economy in selected African nations.

To do this, the authors employ the KOF globalization index and implement both static and dynamic common correlated mean group estimators on a panel of 24 African nations from 1995–2017. This technique accommodates the issue of cross-sectional dependence, sample bias and endogenous regressors. Panel threshold analysis is also conducted to establish the nonlinearity between globalization and the shadow economy. To examine the causality between the variables, the study employs Dumitrescu and Hurlin's panel causality test.

The results show that globalization reduces the size of the shadow economy. The results of the nonlinear analysis suggest a U-shaped relationship. Overall globalization has a threshold impact of 48.837%, economic globalization has 45.615% and political globalization has 66.661% while social globalization has a threshold value of 35.744%. The results of the panel causality show that there is a bidirectional causality between the two variables.

The results suggest that the government and other relevant authorities need to introduce capital controls and other policy measures to moderate the degree of social, political and cultural diffusion. Appropriate policies should be formulated to monitor the extent of African economic openness to other continents to maximize the gains from globalization.

Apart from being the first study in the African region that evaluates the relevance of globalization in controlling the shadow economy, it also analyzes the dynamics and threshold analysis between the two variables using advanced panel econometrics which makes the study unique. The study suggests that globalization tools are useful for affecting the size of the shadow economy in Africa. This study provides fresh empirical evidence on the impact of globalization on the shadow economy in the case of Africa.

The purpose of this paper is to explore the effect of monetary policy on bank risk in the banking system in some MENA countries. It explores how some economic and credit indicators affect the level of risk in the banking sector. It combines many factors that could affect banks’ risk appetite such as macroeconomic conditions, banks’ credit size and lending growth. The authors use nonperforming loans as a proxy for banking sector risks. At first, the authors have analyzed the linear relationship between monetary policy and credit risk. As mentioned above, nonlinearity is expected in the underlying relationship, and, thus, they have investigated the nonlinear relationship to deeply analyse the relationship using the dynamic panel threshold model, as stimulated by Kremer et al. (2013). Threshold models have gained a great importance in economics and finance for modelling nonlinear behaviour. Threshold models are useful in showing the turning points in the behaviour of financial and economic indicators. This technique has been applied in this study to study the effect of monetary policy on credit risk.

This paper is divided into the following sections: Section 2 which previews the recent literature; Section 3 which includes some stylized facts about the relationship between credit risk and monetary policy; Section 4 which deals with the model and methodology; Section 5 which handles the data sources and discusses the results, and finally Section 6 which is the conclusion. The paper adopts dynamic panel threshold model of Kremer et al. (2013).

The results show that the relationship between monetary policy and credit risk is positive and significant to a certain threshold, 6.3. If the lending interest rate is higher than 6.3, this increases the credit risk in the banking sector, because increasing the lending interest rate imposes huge burdens on the borrowers, and, therefore, the bad loans and nonperforming loans become more likely. Thus, the MENA countries need to decrease the lending interest rate to be less than 6.3 to reduce the effect of monetary policy on credit risk. Further, these results are qualitatively robust regarding the inclusion of additional control variables, using alternative threshold variables and further endogeneity checks of the credit risk, such as Risk premium and the squared term of the lending interest rate. The results of taking the risk premium and the squared term of the lending interest rate as a threshold served the analysis and confirmed the positive relationship between monetary policy and credit risk above a certain threshold. As for the risk premium, the relationship below the threshold was negative and significant. Other related research points might be a good avenue for the future research such as applying this approach to micro data of banks from different MENA countries. Also, more sophisticated approaches like time-varying panel approach to assess the relationship over the time can be applied.

The importance of this paper lies in the fact that it does not only study the effect of time, but it also focuses on the panel data about some economic and credit indicators in the MENA region for the first time. This is because central banks in the MENA region have common characteristics and congruous level of economic growth. Therefore, to study how the monetary policy affects those countries’ credit risks in their lending policies, this requires careful analysis of how the central banks in this region might behave to control default risks.

Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. This study endeavors to systematically analyze the underlying mechanisms governing how negative reviews exert an influence on potential consumer decisions.

This paper constructs an “Aspect-based sentiment accumulation” index, a negative or positive affect load, reflecting the degree of consumer sentiment based on affect infusion model and aspect-based sentiment analysis. Initially, it verifies the causal relationship between aspect-based negative load and consumer decisions using ordinary least squares regression. Then, it analyzes the threshold effects of negative affect load on positive affect load and the threshold effects of positive affect load on negative affect load using a panel threshold regression model.

Aspect-based negative reviews significantly impact consumers’ decisions. Negative affect load and positive affect load exhibit threshold effects on each other, with threshold values varying according to the overall volume of reviews. As the total number of reviews increases, the impact of negative affect load diminishes. The threshold effects for positive affect load showed a predominantly U-shaped course of change. Hosts respond promptly and enthusiastically with detailed, lengthy text, which can aid in mitigating the impact of negative reviews.

The study extends the application of the affect infusion model and enriches the conditions for its theoretical scope. It addresses the research gap by focusing on the threshold effects of negative or positive review sentiment on decision-making in sharing accommodations.

Insurance companies play a significant role in every economy; hence, it is essential to investigate and understand the factors that propel their profitability. Unlike previous studies that present a linear relationship, this study provides initial evidence by exploring the non-linear impacts of the determinants of profitability amongst life insurers in South Africa.

The study uses a panel dataset of 62 life insurers in South Africa, covering 2013–2019. The generalised method of moments and the dynamic panel threshold estimation technique were used to estimate the relationship.

The empirical results from the direct relationship reveal that investment income and solvency significantly predict life insurance companies' profitability. On the other hand, underwriting risk, reinsurance and size reduce profitability. Further, the dynamic panel threshold analysis confirms non-linearities in the relationships. The results show that insurance size, investment income and solvency promote profitability beyond a threshold level, implying a propelling effect on life insurers' profitability at higher levels. Below the threshold, these factors have an adverse effect. The study further points to underwriting risk, reinsurance and leverage having a reduced effect on life insurers' profitability when they fall above the threshold level.

The findings suggest that insurers interested in boosting their profit position must commit more resources to maintain their solvency and manage their assets and returns on investment. The study further recommends that effective control of underwriting risk is critical to the profitability of the life insurance industry.

The study contributes to the literature by providing first-time evidence on the determinants of life insurance companies' profitability by way of exploring threshold effects in South Africa.

This study examines the linear and non-linear effects of enterprise risk management (ERM) and corporate governance (CG) on insurers’ risk-taking behaviour.

The study employed panel data of 63 insurers from South Africa over the period 2015 and 2019. The study used the generalised method of moments (GMM) to determine the direct relationship, while the dynamic panel threshold technique was utilised to discover whether there is non-linearity in the relationship and the threshold level at which ERM and CG stimulate insurance risk-taking.

The result from the GMM elicits a positive relationship between ERM and risk-taking, implying that insurers with a robust ERM system are more likely to pursue higher risks. The empirical evidence also suggests that board size and board independence improve insurers’ risk-taking. Contrarily, gender diversity shows an inverse relationship with risk-taking. The dynamic panel threshold regression confirms non-linearities between ERM, CG and risk-taking. The empirical evidence indicates a U-shaped relationship between ERM and risk-taking, implying that a robust ERM system increases insurers’ risk-taking and vice-versa. Further, board size and independence reveal an inverted U-shaped relationship, suggesting that larger boards and a higher proportion of independent directors exhibit lower risk-taking. However, gender diversity presents a negative relationship, demonstrating a strong impact at higher threshold levels. This tells that the presence of females on the board reduces insurers’ risk-taking preferences.

Due to the risk-bearing nature of the insurance business, it is required that they ensure a robust ERM system for prudent risk-taking decisions. This demands strict adherence to ERM principles and allocating sufficient resources for effective implementation. Also, there is a need for strong CG structures that pay more attention to diversity when selecting board members due to their influence in ensuring improved risk-taking choices.

This study contributes to the existing literature by providing insights into the under-researched role of ERM and CG in insurers’ risk-taking behaviour. The study further extends the literature by providing evidence on the non-linearity and threshold levels at which ERM and CG influence insurers’ risk-taking choices. The findings are unique and contribute to the growing body of literature documenting the need for strong ERM and CG systems in insurance companies.

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.