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We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout.

A queuing framework that operates under two distinct regimes is formulated to analyze service rates that represent system capacity to vaccinate (under the first regime) and hesitancy-induced throughput (under the second regime). These supply- and hesitancy-constrained regimes form the focus of the present paper, as the former reflects the inherent ability of the nation in its various jurisdictions to mobilize, whereas the latter reflects a critical area for public policy to protect the population’s overall health and safety.

The two-regime framework analysis provides insights into the capacity to vaccinate and hesitancy-constrained demand, which is found to vary across the country primarily by politics and region. The framework also allows analysis of the end-to-end supply chain, where it is found that the ability to vaccinate was likely constrained by last-mile administration issues, rather than the capacity of the manufacturing and transportation steps of the supply chain.

This study presents a new framework to consider end-to-end supply chains as dynamic systems that exhibit different regimes because of unique supply- and demand-side characteristics and estimate rollout capacity and underlying determinants at the national, state and county levels.

This study aims to empirically examine how the Khmer Rouge regime (1975–1979) in Cambodia continues to affect the health of the second generation.

The 2000 and 2005 Cambodia Demographic and Health Surveys were used in the analysis. The study sample were women with a child/children in 2000/2005. The sample population was identified according to whether the person was in utero “91 months or earlier before the Khmer Rouge regime,” “46–90 months before the Khmer Rouge regime” and “1–45 months before the Khmer Rouge regime” and during the Khmer Rouge regime. The authors then regressed the size of babies of the targeted population on the timing of the mothers being in utero.

Mothers who were in utero during the regime had a higher likelihood of giving birth to smaller-than-average babies. Additionally, mothers born in the areas that had a higher probability of death of children aged five or under during the regime were at risk of giving birth to smaller-than-average babies if they were in utero during that time.

This is the first paper to assess the impact of the Khmer Rouge regime on the health of the second generation.

This study aims to present the climate change effect on soil moisture regimes in Mexico in a global 1.5°C warming scenario.

The soil moisture regimes were determined using the Newhall simulation model with the database of mean monthly precipitation and temperature at a scale of 1: 250,000 for the current scenario and with the climate change scenarios associated with a mean global temperature increase of 1.5°C, considering two Representative Concentration Pathways, 4.5 and 8.5 W/m² and three general models of atmospheric circulation, namely, GFDL, HADGEM and MPI. The different vegetation types of the country were related to the soil moisture regimes for current conditions and for climate change.

According to the HADGEM and MPI models, almost the entire country is predicted to undergo a considerable increase in soil moisture deficit, and part of the areas of each moisture regime will shift to the next drier regime. The GFDL model also predicts this trend but at smaller proportions.

The changes in soil moisture at the regional scale that reveal the impacts of climate change and indicate where these changes will occur are important elements of the knowledge concerning the vulnerability of soils to climate change. New cartography is available in Mexico.

The plethora of changes in the corporate governance landscape over the past two decades has the potential to tighten governance regimes and influence the preference of supervisory board members vis-à-vis the involved decision-making role of business unit (BU) controllers and their independent fiduciary role. Stricter financial reporting and compliance requirements may lead organizations to prioritize the latter role. However, recent studies support the need to balance these roles, inducing the potential for role conflict. The purpose of this study is to shed light on the influence of a tight and loose governance regime on this balance as preferred by supervisory board members.

This study uses a unique data set from an experiment among 73 supervisory board members. The authors take their perspective because compliance with governance codes and corporate policies are relevant topics for their function.

The authors find evidence for the preference of supervisory board members for “all-round” BU controllers who, irrespective of the governance regime, demonstrate substantial levels of fiduciary and decision-making qualities and deal with the resulting role conflict.

The outcomes of the experiment among supervisory board members provide evidence for their preferences concerning the balance of the two primary controller roles and for the potential of role conflict. The authors have not found studies that provide such empirical evidence.

Technology access, digital skills, and digital services are increasingly prerequisites for public life and accessing public services. The digital divide in contemporary societies matters for efforts to digitalize the welfare state. Research has already mapped individual determinants of digital exclusion and the existence of an age-related digital divide. However, far less attention has been paid to variations in digital inclusion between countries and to their potential explanations related to political systems. This study explores the influence of variations in welfare regimes on the digital divide among seniors (aged 65+) in Europe.

This article presents time-series cross-sectional analyses of the relationship between welfare state regimes and digital inclusion among seniors in European countries. The analyses are based on data from Eurostat, the World Bank, and the UN E-Government Survey.

The authors find extensive variation in the digital inclusion of citizens between welfare regimes and argue that considering regime differences improves the understanding of these variations. The findings indicate that the age-related digital divide seems to be least evident in countries with more universalistic welfare regimes and most evident in countries where seniors rely more on their families.

This is the first comparative study of the association between welfare state regimes and digital inclusion among seniors.

The purpose of this paper is to test whether financial analysts’ rationality in making stocks’ earnings forecasts is homogenous or not across different information regimes in stocks’ past returns.

By treating stocks’ past returns as the information variable in this study, the authors employ a threshold regression model to capture and test threshold effects of stocks’ past returns on financial analysts’ rationality in making earnings forecasts in different information regimes.

The results show that three significant structural breaks and four respective information regimes are identified in stocks’ past returns in the threshold regression model. Across the four different information regimes, financial analysts react to stocks’ past returns quite differently when making one-quarter ahead earnings forecasts. Furthermore, the authors find that financial analysts are only rational in a certain information regime of stocks’ past returns depending on a certain return-window such as one-quarter, two-quarter or four-quarter time period.

This study is different from those in the existing literature by arguing that there could exist heterogeneity in financial analysts’ rationality in making earnings forecasts when using stocks’ past returns information. The finding that financial analysts react to stocks’ past returns differently in the different information regimes of past returns adds value to the research on financial analysts’ rationality.

This study aims to generalize the following result of McDonald and Siegel (1986) on optimal investment: it is optimal for an investor to invest when project cash flows exceed a certain threshold. This study presents other results that refine or extend this one by integrating timing flexibility and changes in cash flows with time-varying transition probabilities for regime switching. This study emphasizes that optimal thresholds are either overvalued or undervalued in the absence of time-varying transition probabilities. Accordingly, the stochastic nature of transition probabilities has important implications to the search for optimal timing of investment.

This paper aims at examining the co-movement dependent regime and causality relationships between conventional and Islamic returns for emerging, frontier and developed markets from November 2008 to August 2020.

First, the authors used the Markov-switching autoregression (MS–AR) model to capture the regime-switching behavior in the stock market returns. Second, the authors applied the Markov-switching regression and vector autoregression (MS-VAR) models in order to study, respectively, the co-movement and causality relationship between returns of conventional and Islamic indexes across market states.

Results show the presence of two different regimes for the three studied markets, namely, stability and crisis periods. Also, the authors found evidence of a co-movement relationship between the conventional and Islamic indexes for the three studied markets whatever the regime. For the Granger causality, it is proved only for emerging and developed markets and only during the stability regime. Finally, the authors conclude that Islamic indexes can act as diversifiers, or safe-haven assets are not strongly supported.

This paper is the first study that examines the co-movement and the causal relationship between conventional and Islamic indexes not only across different financial markets' regimes but also during the COVID-19 period. The findings may help investors in making educated decisions about whether or not to add Islamic indexes to their portfolios especially during the recent outbreak.

This paper aims to investigate the pass-through (PT) effect in Turkey by using quarterly data for the period 1998: Q1-2019: Q2 to understand the dynamic potential effects of exchange rates on domestic prices.

The paper launches several nonlinear models in which the basic determinants of domestic prices in Turkey are determined through Markov regime-switching models (MSMs). Hence, this research follows the variables of the consumer price index (CPI), USD exchange rate, gross domestic product (GDP; demand side of the economy), industrial production index (production side of the economy), economic uncertainty and geopolitical risk index for Turkey.

This work explores that the exchange rate and demand side of the economy (GDP) follow a positive nonlinear relationship with CPI at both regimes. The production side of the economy (IP) affects negatively the CPI during regime 0. Economic uncertainty influences the CPI positively at Regime 1, while geopolitical risk has a negative association with CPI at Regime 0. Eventually, the paper provides some policy proposals associated with the impacts of GDP, IP, economic uncertainty and geopolitical risk on CPI in Turkey.

One may claim that any PT model, which does not observe the possible structural or regime shifts in estimated parameters, might fail to estimate the coefficients unbiasedly and efficiently. Hence, this work differs from available relevant works in the literature since this paper considers linearity or nonlinearity important and reveals that the relevant PT model follows a nonlinear path rather than a linear path, this nonlinear path is converged strongly by MSMs and estimates the significant regime shifts in the constant term and, in parameters of independent variables of PT by MSMs.