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South African public debt has recently increased significantly and has reached worrying levels. This study aims to examine the debt threshold effects on economic growth in South Africa, with an objective of suggesting a debt threshold as South African policymakers will seek to reduce debt to a sustainable level in the coming years.

The study applies a recent novel methodology advanced by Hansen (2017) that allows modelling a regression kink with an unknown threshold.

The findings of this study indicate a robust debt threshold of 37% of gross domestic product (GDP). Below this threshold, debt is growth-enhancing, but above 37% of GDP, debt is harmful to growth in South Africa.

Among other things, to reduce the debt-to-GDP ratio, South Africa will need a fiscal consolidation policy by undertaking reforms to state-owned companies to reduce their reliance on public funds, as well as putting in place economic measures to boost long-term growth. The country should also improve tax collection in order to realize additional tax revenue through enhancing compliance and other revenue collection measures.

Most of the existing studies on debt threshold effects in Africa are panel data studies, which assume parameter homogeneity, by determining a single debt threshold value applicable to all countries. This can be misleading as the debt-growth nexus is country-specific, being conditional on several factors, such as institutional quality. The present study applies a recent novel methodology, which allows to model a regression kink with an unknown threshold, for the case of South Africa. The methodology endogenously determines the debt threshold while also allowing a country-specific analysis.

Regression discontinuity (RD) models are commonly used to nonparametrically identify and estimate a local average treatment effect. Dong and Lewbel (2015) show how a derivative of this effect, called treatment effect derivative (TED) can be estimated. We argue here that TED should be employed in most RD applications, as a way to assess the stability and hence external validity of RD estimates. Closely related to TED, we define the complier probability derivative (CPD). Just as TED measures stability of the treatment effect, the CPD measures stability of the complier population in fuzzy designs. TED and CPD are numerically trivial to estimate. We provide relevant Stata code, and apply it to some real datasets.

A regression kink design (RKD or RK design) can be used to identify casual effects in settings where the regressor of interest is a kinked function of an assignment variable. In this chapter, we apply an RKD approach to study the effect of unemployment benefits on the duration of joblessness in Austria, and discuss implementation issues that may arise in similar settings, including the use of bandwidth selection algorithms and bias-correction procedures. Although recent developments in nonparametric estimation (Calonico, Cattaneo, & Farrell, 2014; Imbens & Kalyanaraman, 2012) are sometimes interpreted by practitioners as pointing to a default estimation procedure, we show that in any given application different procedures may perform better or worse. In particular, Monte Carlo simulations based on data-generating processes that closely resemble the data from our application show that some asymptotically dominant procedures may actually perform worse than “sub-optimal” alternatives in a given empirical application.

The authors derive a risk lower bound in estimating the threshold parameter without knowing whether the threshold regression model is continuous or not. The bound goes to zero as the sample size n grows only at the cube-root rate. Motivated by this finding, the authors develop a continuity test for the threshold regression model and a bootstrap to compute its p-values. The validity of the bootstrap is established, and its finite-sample property is explored through Monte Carlo simulations.

Higher replacement rates often imply higher levels of absenteeism, yet even in generous welfare economies, employers provide sick pay in addition to the public sick pay. Using comparative population-representative workplace data for Britain and Norway, we show that close to 50% of private sector employers in both countries provide sick pay in excess of statutory sick pay. However, the level of statutory sick pay is also much higher in Norway than in Britain. In both countries, private sick pay as well as other benefits provided by employers are chosen by employers in a way that maximizes profits having accounted for different dimensions of labor costs. Several health-related privately provided benefits are often bundled. In both countries easy-to-train workers, high turnover and risky work are linked to less extensive employer provision of extended sick leave and sick pay in excess of statutory sick pay. In contrast, the presence of a trade union agreement is strongly correlated with both the provision of private sick pay and extended sick leave in Britain but not in Norway. We show that the sickness absence rate is much higher in Norway than in Britain. However, the higher level of absenteeism in Norway compared to Britain relates to the threshold for statutory sick pay in the Norwegian public sick pay legislation. When we take this difference into account, no significant difference remains.

The purpose of this paper is to investigate the effect of government-led programs on the engagement of individuals in entrepreneurship.

The authors worked with government-led programs of 16 European countries between 2003 and 2014 and were able to benefit from the 2008 natural experiment (i.e. the global financial crisis) to produce a robust investigation using a regression kink design (RKD).

The work shows that government-led programs that are designed to include monitoring schemes can significantly increase individuals' engagement in opportunity-driven entrepreneurship. The authors found that monitoring schemes do not have the same relevance for necessity-driven entrepreneurship. Therefore, the authors believe the difference occurs because monitoring design avoids problems related to moral hazard and adverse selection when it comes to individuals choosing whether to participate (or not) in government-led programs.

While it is important for governments to provide an enabling environment for entrepreneurship, this study showed that not all types of public program have positive results. In fact, it has been demonstrated that poorly-designed programs can actually decrease the likelihood of individuals engaging in entrepreneurial activities. The efficiency of programs is substantially improved, however, when they are designed to include monitoring schemes.

Unemployment can negatively affect individuals, their families and communities in various ways. When individuals are out of work may experience mental and physical health problems, material deprivation and poverty. This study aims to examine the impact of unemployment benefits on health and living standards in Turkey.

The authors employ a structural equation modelling (SEM) to consider the simultaneous relationships among the unemployment benefits and the latent variables of health and Standard of Living (SoL). We propose a fuzzy Regression Discontinuity Design (FRDD) and a Regression Kink Design (RKD) within the SEM framework to infer causality. For the empirical analysis, the authors employ the panel Income and Living Conditions Survey (ILCS) in 2007–2015.

The authors’ findings suggest that those who receive these benefits are more likely to report higher levels of health and improve their living standards compared to the non-recipients. Furthermore, unemployment benefits replacement rates are associated with improved levels in health and living standards. The authors’ results indicate a substantial heterogeneity on the impact of unemployment benefits since males, low educated individuals and those belonging to the lower levels of income are affected more in terms of their health status and living standards.

The majority of earlier studies have focused on the impact of unemployment benefits on labor outcomes. The originality of this study is that we implement the FRDD and RKD within the SEM framework to explore, simultaneously, the impact of unemployment insurance on health and living standards. Moreover, future research studies can implement this framework to infer causality and explore the impact of related policies and reforms.

The purpose of this paper is to examine the relationship between the quality of different dimensions of institutional and economic growth in a panel of 15 member ECOWAS.

The study adopts Driscoll and Kraay′s nonparametric covariance matrix estimator, and the spatial error model to account for cross-section dependency, cross-country heterogeneity and spatial dependence inherent in empirical modelling, which has largely been ignored in previous studies. This is because, the likelihood that corruption and human capital cluster in space is very high because factors that affect these phenomena disperse across borders. Similarly, to test the threshold effect, the study adopts the more refined and more appropriate dynamic panel data which models a nonlinear asymmetric dynamics and cross-sectional heterogeneity, simultaneously, in a dynamic threshold panel data framework.

The empirical evidence supports findings by previous researchers that better-quality political and economic institutions can have positive effects on economic growth. Similarly, our results support a nonlinear relationship between political institutions and economic institution, confirming the “hierarchy of institution hypothesis” in ECOWAS. Specifically, the findings show that economic institutions will only have the desired economic outcome in ECOWAS, only when political institution is above a certain threshold.

Unlike previous studies which assume cross-sectional and spatial independence, the authors account for cross-section dependency and cross-country heterogeneity inherent in empirical modelling.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2019-0630