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The paper examines the differential impact of various firm characteristics on firm value across various threshold levels of foreign ownership.

Using a panel of 408 Indian publicly listed companies for the period during 2010–2018, a fixed-effect panel threshold regression model is adapted to study the threshold effects between foreign ownership and firm value. Tobin's Q is used as a proxy for firm value.

The study identifies three threshold levels, that is, four threshold regions in which foreign ownership changes its slope considerably. Various firm characteristics impact firm value differently in these four regions.

The study employs observations of the past nine years on variables identified as firm characteristics impacting firm value. Some variables are dropped due to the problem of multicollinearity. The employed variables may not be exhaustive in nature.

The present study implies that there exists no impact of foreign ownership on the value of the firm. Foreign investors invest for financial considerations and not with the objective of governing the firms. The governance effect of foreign investments is negligible, so their activism in the firms needs to be encouraged.

The study employs a novel approach to study the impact of foreign ownership on firm value applying fixed effect panel data threshold regression, considering foreign ownership as a proxy of corporate governance.

Most emerging economies have made conscious efforts through policy initiatives to attract foreign direct investment (FDI). However, a significant obstacle to FDI inflow has been the prevalence of corruption in the host country. This study, therefore, aims to examine whether there is an optimum corruption value that results in threshold effects of corruption on FDI.

To achieve this objective, this study used Hansen’s (1999) panel threshold regression (PTR) model by using a panel data of 30 sub-Saharan African (SSA) countries from 2000 to 2021.

This study finds that the nexus between corruption and FDI has a single threshold effect, with a 5.37% optimum corruption threshold value. At this threshold value, corruption affects FDI negatively. Any corruption value that is below the threshold value also elicits a negative corruption–FDI relationship. Despite having a negative relationship when the corruption value is above the optimum corruption threshold, it is not statistically significant.

The implication of the results is that it is deleterious to use corrupt practices to draw FDI to SSA nations.

To the best of the authors’ knowledge, this study is one of the first in the corruption–FDI nexus literature to use Hansen’s PTR model to estimate an optimal corruption threshold. The authors recommend that policymakers in the selected SSA countries reconsider the use of corruption to attract FDI because there is an optimal corruption threshold that could impact FDI in the host country.

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 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).

This paper aims to investigate how information and communication technology (ICT) services and digital finance affect the development of international tourism.

The two-way fixed effect panel regression model, spatial econometric model, panel threshold regression model and panel quantile regression model are used. Data on tourism, economic and social development in 198 Chinese cities from 2011 to 2020 are analyzed.

This study finds that digital economy including ICT services and digital finance has significantly promoted the development of international tourism industry, while there is a negative spatial spillover effect. The promotion effect of international tourism increases significantly after digital innovation reaches the threshold value. International tourism is benefiting more from digital economy with the development of international tourism industry.

The development quality of international tourism industry has not been analyzed due to data limitations, and the mechanism has not been tested.

This study creatively reveals the development of international tourism industry in the digital economy era from ICT services and digital finance perspectives. This study also shows the spatial, nonlinear and asymmetric relationship between digital economy and international tourism.

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.

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 purpose of this study is to examine the nonlinear relationship between financial constraints and the chief executive officer (CEO) stock options compensation and to analyze whether the impact of financial constraints on the CEO stock options compensation changes at certain level of financial constraints or not.

This study is based on a sample of 90 French firms for the period extending from 2008 to 2019. To deal with the non-linearity, the authors use a panel threshold method.

Using different measures of financial constraints [KZ index (Baker et al., 2003), SA index (Hadlock and Pierce, 2010) and FCP index (Schauer et al., 2019)], the results reveal that the impact of the financial constraints (SA index and FCP index) is positive below the threshold value and it becomes negative above.

The non-linearity between financial constraints and CEO stock options shows that the level of financial constraints can be a major determinant of the CEO compensation structure. More specifically, this study sheds light on the key role played by the level of financial constraints and how this latter influence management decisions.

This paper is the first to the best of the authors' knowledge to examine the nonlinear relationship between financial constraints and the CEO stock options compensation using a panel threshold model.

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.

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.

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.

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.

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.