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The author proposes analyzing the dynamics of income positions using dynamic panel ordered probit models. The author disentangles, simultaneously, the roles of state dependence and heterogeneity (observed and non-observed) in explaining income position persistence, such as poverty persistence and affluence persistence. The author applies the approach to Chile exploiting longitudinal data from the P-CASEN 2006–2009. First, the author finds that income position mobility at the bottom and the top of the income distribution is much higher than expected, showing signs that income mobility in the case of Chile might be connected to economic insecurity. Second, the observable individual characteristics have a much stronger impact than true state dependence to explain individuals’ current income position in the income distribution extremes.

This chapter examines the performance persistence evidences of pension fund managers who managed the constituent equity funds included in Hong Kong Mandatory Provident Fund (MPF) schemes over the period 2001–2004. Nonparametric two-way contingency table and parametric OLS regression analysis are employed to evaluate performance persistence. The evidence suggests that the raw returns, traditional Jensen alphas, and conditional Jensen alphas in the previous year possess predictive abilities. When the funds are classified into high-volatile and low-volatile samples, the high-volatile funds are found to possess stronger performance persistence. Neither hot-hand nor cold-hand phenomena are found in the equity funds managed by same investment manager.

The aim of this study is to compare volatility persistence with daily volatility and to analyze the asymmetry effect of volatilities in stock markets of emerging economies. Using daily observations of stock market indices of selected major emerging countries during the period of January 1, 2002 to December 31, 2018, the authors estimate the persistence, the half-life measure of volatility and the daily volatility of the return series using the GARCH model application. The authors also examine the leverage effect on stock market returns using the EGARCH model estimation. In addition, the authors investigate the impact of the 2008 global financial crisis on various volatility measures and the leverage effect of emerging stock market returns. The authors then examine and compare the different speeds of mean reversion, volatility persistence and leverage effects in the national stock market indices during the pre-crisis, crisis, and post-crisis periods. The authors hereby present evidence that the effects of negative shocks are significantly larger than those of positive shocks in emerging stock markets throughout their different sample periods.

Management has considerable discretion over how to present and announce earnings components that are either unusual or infrequent, but not both (hereafter referred to as special items). In this study, we study the independent and joint effects of the accounting presentation format of, and the level of announcement prominence given to income-decreasing special items on investors’ judgments about the persistence of declining earnings.

Our study uses a 3 (format) × 2 (prominence) between-subjects design. In the experiment, participants act as proxies for nonprofessional investors to assess the persistence of a hypothetical firm’s declining earnings and make investment decisions.

Our results suggest that investors’ judgments are influenced by accounting presentation format and the level of announcement prominence. With respect to format, both classification and disaggregation affect investors’ assessment of earnings persistence. In addition, the degree of prominence given to an income-decreasing special item, albeit self-serving and not audited, introduces additional influence beyond that of accounting presentation format. In particular, we find that announcement prominence has a greater effect when the special item is aggregated with other operating expenses than when the special item is presented under the two other alternatives.

Our study contributes to the literature by demonstrating that presentation format and announcement prominence both have significant impact on investors’ judgments and decisions, and that their effects are interactive. Our results also indicate that future research can possibly gain better insight if it considers the accounting attributes of the special items in addition to their economic attributes.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

To create and sustain a resource-based competitive advantage, managers acquire and develop specialized resources as they grow their firms. The authors argue that an important part of committing to a resource-based strategy is a willingness to keep spending on specialized resources during periods when sales and profits are down. The authors seek to validate this conjecture by examining whether such resource-based commitment to a customer-centered strategy results in improved customer satisfaction. The authors use the stickiness of selling, general, and administrative (SG&A) expenses to capture this commitment empirically. The authors first document that future customer satisfaction is positively associated with SG&A cost stickiness, consistent with the premise that the retention of specialized SG&A resources during low demand periods helps firms to build and maintain relationships with customers over time. Next, the authors test whether expected future benefits of customer satisfaction are enhanced when SG&A cost stickiness is higher. The authors find that the positive relation between Tobin’s Q and customer satisfaction is positively moderated by SG&A cost stickiness. Finally, the authors test whether earnings persistence, a quality of earnings associated with sustained performance over time, is positively associated with the interaction between customer satisfaction and SG&A cost stickiness. The authors find that it is. Their evidence supporting these predictions is consistent with the conjecture that resource-based commitment reflected in cost stickiness is an important dimension of creating and sustaining a resource-based competitive advantage.

This paper compares the out-of-sample forecasting performance of three long-memory volatility models (i.e., fractionally integrated (FI), break and regime switching) against three short-memory models (i.e., GARCH, GJR and volatility component). Using S&P 500 returns, we find that structural break models produced the best out-of-sample forecasts, if future volatility breaks are known. Without knowing the future breaks, GJR models produced the best short-horizon forecasts and FI models dominated for volatility forecasts of 10 days and beyond. The results suggest that S&P 500 volatility is non-stationary at least in some time periods. Controlling for extreme events (e.g., the 1987 crash) significantly improved forecasting performance.

The insurance industry often experiences criticism for unethical and frequently illegal activities. This document suggests that insurers operate in an uncompetitive environment and that the nature of insurer operations leads otherwise ethical individuals in the direction of questionable ethical decisions throughout the operations of an insurance company.

In this chapter, the authors ask two questions: (i) Is the conduct of monetary policy stable across time and similar across major economies? and (ii) Do policy decisions of major central banks have international spillover effects? To address these questions, the authors build on recent semi-parametric advances in time-varying parameter models that allow us to increase the vector autoregressive () dimension and to jointly model three advanced economies (USA, UK and the Euro Area). The main reduced-form finding of this chapter is an increased connectedness between and within countries during the recent financial crisis. In order to study policy spillovers, we jointly identify three economy-specific monetary policy shocks using a combination of sign and magnitude restrictions. The authors find that monetary policy shocks were larger in magnitude and more persistent in the early 1980s than in subsequent periods. The authors also uncover positive spillover effects of policy between countries in the 1980s and diminished, and sometimes negative ‘beggar-thy-neighbour’ effects in the second half of the sample. Moreover, during the 1980s, the authors find evidence for policy coordination between the Federal Reserve, the Bank of England and the European Central Bank.

We examine the role of structural breaks in forecasting stock return volatility. We begin by testing for structural breaks in the unconditional variance of daily returns for the S&P 500 market index and ten sectoral stock indices for 9/12/1989–1/19/2006 using an iterative cumulative sum of squares procedure. We find evidence of multiple variance breaks in almost all of the return series, indicating that structural breaks are an empirically relevant feature of return volatility. We then undertake an out-of-sample forecasting exercise to analyze how instabilities in unconditional variance affect the forecasting performance of asymmetric volatility models, focusing on procedures that employ a variety of estimation window sizes designed to accommodate potential structural breaks. The exercise demonstrates that structural breaks present important challenges to forecasting stock return volatility. We find that averaging across volatility forecasts generated by individual forecasting models estimated using different window sizes performs well in many cases and appears to offer a useful approach to forecasting stock return volatility in the presence of structural breaks.