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Responses to minimum income and minimum spending questions are used to produce economic well-being thresholds. Thresholds are estimated using a regression framework. Regression coefficients are based on U.S. Survey of Income and Program Participation (SIPP) data and then applied to U.S. Consumer Expenditure Survey (CE) data. Three different resource measures are compared to the estimated thresholds. The first resource measure is total before-tax money income, and the other two are expenditure based. The first of these two refers to expenditure outlays and the second to outlays adjusted for the value of the service flow of owner-occupied housing (rental equivalence). The income comparison is based on SIPP data while the outlays comparisons are based on CE data. Results using official poverty thresholds are shown for comparison. This is among the earliest work in the U.S. in which expenditure outlays have been used for economic well-being determinations in combination with personal assessments, and the first time rental equivalence has been used in such an exercise. Comparisons of expenditures for various bundles of commodities are compared to the CE derived thresholds to provide insight concerning what might be considered minimum or basic.

Results reveal that CE and SIPP MIQ thresholds are higher than MSQ thresholds, and resulting poverty rates are also higher with the MIQ. CE-based MSQ thresholds are not statistically different from average expenditure outlays for food, apparel, and shelter and utilities for primary residences. When reported rental equivalences for primary residences that are owner occupied are substituted for out-of-pocket shelter expenditures, single elderly are less likely to be as badly off as they would be with a strict outlays approach in defining resources.

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.

In this chapter, we examine the impact of pay-for-performance incentives on learning-by-doing. We exploit personnel data on fruit pickers paid under two distinct compensation contracts: a standard piece rate plan and one with an extra one-time bonus tied to output. Under the latter, we observe bunching of performance just above the bonus threshold, suggesting workers distort their behavior in response to the discrete bonus. Such bunching behavior increases as workers gain experience. At the same time, the bonus contract induces considerable learning-by-doing for workers throughout the productivity distribution who presumably hope to one day hit the target, and these improvements significantly outweigh the losses to the firm from the bunching. In contrast, under the standard piece rate contract, we find minimal evidence of bunching and only small performance improvements at the bottom of the productivity distribution. Our results suggest that contract design can help foster learning on the job, underscoring the importance of dynamic considerations in principle-agent models.

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.

We examine a central tenet of real option theory – whether real options influence managerial thresholds for investment. In contrast to prior studies that have focused on whether real options influence discrete investment decisions, our focus is on empirically isolating real options’ effects on thresholds. In particular, we examine the real options inherent in acquisition decisions. Our model posits that there are good reasons why we might expect there to be information asymmetry around the value of real options. Accordingly, if managers have unique information about growth options we might expect to observe them lowering their thresholds, perhaps to the point where they are willing to accept negative market returns. We further expect that the degree of information asymmetry for firm-specific growth options should be higher than for industry-specific growth options. Finally, we believe that managerial thresholds will be more prone to influence from growth options than deferment options. While thresholds are unobservable, we are able to isolate the effects of real options on acquisition thresholds by borrowing a method used originally in labor economics to isolate the determinants of reservation wages. Using a sample of over 28,000 acquisitions in the U.S., we find strong support for the model. These findings suggest that firms with low thresholds may choose to acquire despite comparatively low expected performance.

Owing to dual constraints including liability of foreignness and liability of origin when emerging multinationals internationalize, they inevitably face the challenge of overseas legitimation. However, few studies have explored how latecomers cross the threshold of legitimacy in the dynamic context of transnational operation. The purpose of this paper is to unravel the evolution process, triggers and specific strategies of overseas legitimacy threshold crossing of emerging multinationals.

Through the longitudinal case study of Haier Group and Goldwind Sci & Tech Co., Ltd, this study investigates the periodical characteristics of overseas legitimacy threshold crossings and the co-evolution among critical factors influencing the legitimation process in the host country.

First, it summarizes that the legitimacy threshold in the host country experiences a sequential process from pragmatic legitimacy to normative legitimacy, and finally cognitive legitimacy. It is an inevitable choice for emerging multinational enterprises to realize and sustain legitimation from passive adaptation to active creation. Second, it reveals that the triggers for crossing the threshold of overseas legitimacy include periodically dynamic factors – international network linkage and resource system reconfiguration, as well as cross-stage spiral interaction effects. Third, it determines the specific strategies for crossing the threshold of overseas legitimacy, namely, replacement, upgrading and reconstruction of organizational identity, and reveals the important role of insisting on the country-of-origin Facebook in promoting the legitimation.

This study enriches the legitimacy threshold crossing literature from an evolutional perspective, especially the traditional static legitimacy research. This study also reveals the key impacting factors – international network linkage and resource system reconfiguration – and their evolution process interacted with the legitimation process.

The emerging multinationals should break the stereotypes from developed markets in that only creating new cognitive patterns through active legitimate strategies can they truly cross the legitimacy threshold in the host country. The emerging multinationals also need to retain their own home country legitimacy traits – Facebook and balance the relation between the image of the home country and the image of host country.

This paper investigates the process of overseas legitimacy threshold crossing for emerging multinationals in a dynamic context of transnational operation, particularly with respect to the evolutionary role played by international network linkage and resource system reconfiguration.

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.

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.

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.

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.

This study examines the non-linear impact of financial development on income inequality and analyses the mediators through which financial development affects income inequality.

The study uses a dynamic panel threshold method with an endogeneous threshold variable on a comprehensive sample of 85 countries over the period of 1996-2015.

The author finds that financial development activities increase income inequality in developed countries. However, financial development promotes income equality in developing countries. Further, the study finds that education and institutional quality are the channels through which financial development has non-linear impacts on income inequality.

The study explores relatively new method to examine the nonlinear impact of financial development and also considers new dataset for the main explanatory variable.

The EU prudential regime for investment firms comprising the Directive (EU) 2019/2034 (IFD) and Regulation (EU) 2019/2033 (IFR) introduces a fit-for-purpose capital framework for investment firms. The capital impact on the practice of investment management can be material depending on firms’ specific business models and risk profiles, which may require them to take strategic decisions with respect to the services they provide. Despite the importance of this issue for the practice of investment management, there exists no study among the existing studies that focuses on this issue. This study aims to fill this gap in the literature.

This paper reviews the calibration approaches the European Banking Authority (EBA) has used by exploring the deficiencies of the regime with respect to the calibration of categorization thresholds and coefficients that are used by the EBA to calculate regulatory capital requirements.

This paper sets out that the choice of the relevant percentile for setting the firm categorization thresholds was not based on any theoretical rule. It also discusses that the calibration of the K-factors was subjective and lacked consistency. In addition, it criticizes the sample that the EBA used for business model coverage on the grounds that it was unbalanced, resulting in certain K-factors driving the overall capital impact.

Further research is needed on the calibration of thresholds as this will remain a crucial factor for the effectiveness of the new regime. In particular, a more data-driven and transparent approach would be necessary to ensure the accuracy and consistency of the thresholds.

This paper leads to the policy implication that, despite its merits that overweigh its shortcomings, potential market competition and financial stability issues that may stem from inconsistencies and a general lack of objectivity in certain aspects of the regime should not be underestimated by the EU policy makers.

The present paper contributes to the existing knowledge primarily by reviewing the EBA’s calibration approaches with respect to the K-factor coefficients and firm categorization thresholds, concluding that lack of objectivity and precision in the relevant methodologies could distort capital allocation decisions in the practice of investment management.

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.