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The Epidemiologic Transition can help us understand a fundamental puzzle about aging. The puzzle stems from two seemingly contradictory facts. The first fact is that death rates from noninfectious degenerative maladies – the so-called diseases of aging – increase as people age. It seems to be at odds with the historical fact that for nearly a century in which people were aging more than ever before, the aggregate rates of such diseases have been decreasing. In what sense can both be true? Crucial to resolving the puzzle are the age-profiles of such diseases in cohorts that grew up in the different regimes of the Transition. For each cohort, noninfectious diseases had increased with age, resulting in an upward-sloping age profile, which affirms the first fact. As the regimes were transitioning from the Malthusian to the modern one, however, the profiles of successive cohorts had been shifting downward: death rates from noninfectious diseases were shrinking at each age, signifying the newer cohorts’ greater aging potentials. The shifting profiles had been renewing the cohort mix of the population, shaping the century-long descent of such diseases in aggregate, giving rise to the historical fact. The profiles had shifted early in the cohorts’ adult years, associating closely with the newer epidemiologic conditions in childhood. Those conditions appear to be a circumstance under which aging potentials of cohorts could be misgauged, including in one troubling episode in the first half of the nineteenth century when the potentials had reversed.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

This paper aims to study the asset pricing implications for stock and bond markets in a long-run risks (LRR) model with regime shifts. This general equilibrium framework can not only generate sign-switching stock-bond correlations and bond risk premium, but also quantitatively reproduce various other salient empirical features in stock and bond markets, including time-varying equity and bond return premia, regime shifts in real and nominal yield curves, the violation of the expectations hypothesis of bond returns.

The researchers study the joint determinants of stock and bond returns in a LRR model framework with regime shifts in consumption and inflation dynamics. In particular, the means, volatilities, and the correlation structure between consumption growth and inflation are regime-dependent.

The model shows that the term structure of interest rates and stock-bond correlation are intimately related to business cycles, while LRR play a more important role in accounting for high equity premium than do business cycle risks.

This paper studies the joint determinants of stock and bond returns in a Bansal and Yaron (2004) type of LRR framework. This rational expectations general equilibrium framework can (1) jointly match the dynamics of consumption, inflation and cash flow; (2) generate time-varying and sign-switching stock and bond correlations, as well as generating sign-switching bond risk premium; and (3) coherently explain another long list of salient empirical features in stock and bond markets, including time-varying equity and bond return premia, regime shifts in real and nominal yield curves, the violation of the expectations hypothesis of bond returns.

Following the reforms in monetary policy and shift in fiscal policies, it is logical to presume that these reforms may cause a significant structural change in the dynamic processes of inflation and hence affect the nature of inflation persistence. The purpose of this paper is to examine the persistence nature of the different inflation episodes while controlling for the effects of demand- and supply-side factors, which are modeled as regime-dependent.

This paper used the Markov-switching dynamic regression and annual time series data.

The results showed that high inflation regime is more persistent than low inflation regime, with a respective average duration of an escape of 3.5 and 2.57 years, which suggests that price stability achievements are less sustainable. In both regimes, demand- and supply-side factors play significant roles in driving inflation, but the effect of the latter dominates. Thus, on the argument of whether inflation in Ghana is structural or monetary, the results support the former. The roles of both structural and monetary factors have changed over time, but that of the former has been more significant and important in Ghana.

This study provides the first empirical attempt, in the case of Ghana, that examines the persistence nature of different inflation regimes, while modeling the effects of supply and demand factors as regime dependent. In the modeling sense, the authors also contribute by ruling out the assumption that the researcher knows the processes responsible for each observation at each point in time.

Compares the aggregate stock returns of five countries in order to understand their behaviour, bearing in mind shocks and regime shifts. Applies a Markov‐switching model to examine discrete shifts in regime in equity markets from 1976 to 1991 in Germany, Japan, USA, United Kingdom and Canada. Finds the German market takes by far the longest time to return to normality after a shock, and Canada the shortest, but that German stock return variance has the lowest mean return in the high‐volatility state. Detects an increase in volatility well before the stock market crash of 1987. Concludes that stock returns are time varying and the conditional variance is state‐dependent, and that markets vary widely in frequency of regime shifts and persistence.

To investigate, compare and document the magnitude and extent of intellectual capital disclosure to sustainability disclosure during a transition from a voluntary to mandated “comply or explain” sustainability reporting regime. And to empirically test if, during the regime transition period, changes in the magnitude (extent) of sustainability disclosure is a significant determinant of changes in the magnitude (extent) of intellectual capital disclosure.

Content analysis of 1,744 annual reports drawn from 436 Singapore listed firms spanning a four-year observation window (i.e. April 1, 2014 to March 31, 2018). The magnitude (number of sentences) and extent (number of items) of (1) intellectual capital disclosure measured using a 38-item index; (2) sustainability disclosure of a 105-item index; and (3) 15-item index to measure the magnitude and extent of joint sustainability/intellectual capital disclosure.

The average magnitude and extent of sustainability and the joint sustainability/intellectual capital disclosure increased whilst the average magnitude and extent of intellectual capital disclosure increased when regulatory discussion of a change to mandated sustainability reporting emerged. However, in the annual period the mandated sustainability reporting became effective while the average magnitude and extent of intellectual capital disclosure declined. Regression tests indicate a significant (insignificant) association between the change in the magnitude (extent) of sustainability disclosure and intellectual capital disclosure.

From a research perspective, the analysis implies researchers investigating the consequences of mandated sustainability disclosure should consider impact on alternative non-financial disclosure themes and develop theoretical frameworks to derive why and how management may shift non-financial reporting strategies and practices.

For regulators, findings suggest there may be a need to weigh spillover costs of reductions in transparency related to intellectual capital. For investors, declines in the magnitude and extent of intellectual capital disclosure following a transition to mandated sustainability reporting may limit future firm valuation particularly of heavy intangible asset-oriented firms.

Initial study empirically investigating the impact of the transition from a voluntary to mandated sustainability reporting regime on the magnitude and extent of intellectual capital disclosure.

This paper aims to investigate the dynamic linkage between stock prices and exchange rate changes for the Gulf Arab countries (Kuwait, Qatar, Saudi Arabia and United Arab Emirates [UAE]).

The author uses the Markov-switching autoregression to detect regime-shift behavior in the stock returns of the Gulf Arab countries and Markov-switching vector autoregressive (MS-VAR) model to capture the dynamic interrelatedness between exchange and stock returns over the period 2000–2018.

This study’s analysis finds evidence to support the persistence of two distinct regimes for all markets, namely, a low-volatility regime and a high-volatility regime. The low-volatility regime illustrates more persistence than the high-volatility regime. Specifically, exchange rate changes do not have an influence on the stock market returns of the Gulf Arab countries, regardless of the regimes. On the other hand, stock market returns have a substantial impact on exchange markets for all countries, except Saudi Arabia, and it is more noticeable during the regime of high volatility.

The findings shed light on the interconnectedness between two of the most important financial markets in the complex international financial environment. They are thus of particular interest for economic policymakers and portfolio investors.

The author distinguishes this study from previous studies in several ways. First, while previous empirical studies of the dynamic linkage between stock prices and foreign exchange markets are primarily devoted to developed markets or emerging markets, this study’s interest is concentrated on four Gulf Arab financial markets (Kuwait, Qatar, Saudi Arabia and UAE). Second, unlike most investigations in the literature that only estimate this link for the whole period, this study attempts to estimate during the good and bad period by using a two-regime MS-VAR model. To the best of the author’s knowledge, this is the first study of the Gulf Arab countries on the stock and foreign exchange markets to apply this model.

Introduction: Studies on the insurance sector/companies have, in recent years, taken their place in literature at an increasing rate. Especially after the 2008 global financial crisis, the need for people to ensure their assets has structurally changed both the transaction volume and the yield structure of insurance sector. The increase in demand for insurance has also increased the appetite of investors to make an investment on this sector. The transaction volume of the insurance sector has increased year by year coupled with the number of insurance companies traded on the stock exchanges has started to increase in the same direction.

Aim: This chapter aims to determine the return structure of the Borsa Istanbul Insurance Index (XSGRT) based on daily closing values.

Method: Markedly with similar studies in the literature review, the authors determined that the Markov Regime Switching (MRS) model is the best-suited model for the current research. It was applied for the data set of XSGRT Index from 1997 to 2020.

Results: The result shows that XSGRT has three regimes named as expansion regime, normal regime and recession regime. Subsequently, it has been determined that the index generally attends to transition from the recession regime to the expansion regime and normal regime. This outcome is statistically significant at a 5% significance level and confirmed by backtesting results. Likewise, the duration of the recession regime is longer than the normal and expansion regime.

Conclusion: Despite the fact that the XSGRT has not yet completed its development compared to other main and sectoral indices, it is one of the indices that offer attractive earnings for investors. To put it differently, the desire of insurance companies to stay longer totally in the normal and expansion period and their immediate exit from the recession period provides them with a significant competitive advantage in contrast to other indices.

Originality/Value: This research contributes to the literature by providing additional evidence for existing studies using the longer duration of data set and applying the MRS model for Insurance Index. Best of our knowledge, it is the first study that examines the return structure of XSGRT based on its daily closing values from 1997 to 2020. In essence, investors can use the result of this study and compare it with other stock indices to make the accurate investment decision to maximise their welfare and return on their equity investments. The authors suggest that not only the return but also the regime structures of the invested shares (indices) should be taken into account for investment decisions.

The potential impact of farmer's innovations for the development of food regimes is the topic of this chapter. Two case studies analysed from the perspective of strategic niche management show that there is niche formation visible as an alternative to the dominant modern food regime. These innovations are based upon the active rediscovery of marginalised and often forgotten knowledge and result in effective linkages between old and new knowledge. This retro side of innovations can have a large potential for developing viable alternatives for rural development. Social scientists play an important role in the understanding of the retro side of innovations and its potential and influence on the prevailing knowledge and information systems inside and outside of the scientific domain.

This paper provides some additional empirical evidence on the effect of exchange‐rate volatility on exports. The novelties of the study include: a regime‐switching model in conditional volatility is employed to better capture the exchange‐rate uncertainty; a 2SLS method as suggested by Hsiao is used to estimate a system of the dynamic export equations; and an attempt has been made to reconcile the empirical findings with existing theories. We find that the regime‐switching model captures the exchange‐rate risks better and the empirical evidence by and large is consistent with Viaene and Vries, who argued that the existence of the forward markets and current account positions of the country would determine the impact of the exchange uncertainty on trade.