Working sick and out of sorts: a cross-cultural approach on presenteeism climate,organizational justice and work–family conflict*

Abstract

A climate of presenteeism has important effects on employee well-being and the organization itself. Our study, based on surveys of health sector employees in six different countries (Brazil, Ecuador, Lebanon, Portugal, Russia and Spain) examines whether organizational justice plays a mediating role in the relationship between a presenteeism climate in the organization and work–family conflict (WFC). Our results indicate that the perception of organizational justice and the presenteeism climate do influence WFC. Moreover, higher levels of WFC were found in non-Latin countries. This study contributes to the work attendance and life balance field by providing cross-cultural empirical evidence corroborating the effect of justice and presenteeism climate on the WFC.     

Orthogonalized factors and systematic risk decomposition

In the context of linear multi-factor models, this study proposes an egalitarian, optimal and unique procedure to find orthogonalized factors, which also facilitates the decomposition of the coefficient of determination. Importantly, the new risk factors may diverge significantly from the original ones. The decomposition of risk allows one to explicitly examine the impact of individual factors on the return variation of risky assets, which provides discriminative power for factor selection. The procedure is experimentally robust even for small samples. Empirically we find that even though, on average, approximately eighty (sixty-five) percent of style (industry) portfolios’ volatility is explained by the market and size factors, other factors such as value, momentum and contrarian still play an important role for certain portfolios. The components of systematic risk, while dynamic over time, generally exhibit negative correlation between market, on one side, and size, value, momentum and contrarian, on the other side.     

A sectoral analysis of the financial instability hypothesis

Hyman Minsky's Financial Instability Hypothesis (FIH) is applied to various North American Industrial Classification System (NAICS) industry groups, and it is found that some sectors develop much more closely in accordance with the FIH than others. Minsky categorized firms based on the relationship between cash flow and debt service requirements: hedge finance units, whose operating revenues are adequate to service current interest and principal on their debt; speculative finance units, which can meet interest payments but cannot pay down principal; and Ponzi finance units, which cannot meet current interest payments. The FIH is related to, as well as supportive of, Austrian Business Cycle (ABC) theory, because interest rates are negatively correlated with the proportion and market value of speculative firms in several sectors.     

Legitimating Inequality: Fooling Most of the People All of the Time

Over the three decades leading up to the crisis of 2008, inequality dramatically increased in the United States and Great Britain. What stands out, but is seldom noted, is that this occurred within democracies where the relative losers—the overwhelming majority—could in principle have used the political system to block or reverse rising inequality. Why did they not do so? A glance at history reveals that peoples have only very infrequently contested inequality because they were led to believe that their inferior status in terms of income, wealth, and privilege was just, that it was not really so bad, or that it was necessary for their future well‐being. Ideological systems legitimated a status quo of inequality, or in more modern times even increasing inequality. This article surveys the manner in which inequality has been historically legitimated, first predominantly by religion, then predominately by economic thought. Attention is then focused on the manner in which contemporary economic science and its popular interpretations in the media have served to legitimate inequality in the U.S. since the mid‐1970s. The article concludes with a reflection on the unique conditions that enable the legitimation of inequality to be delegitimated.     

The effect of latency variables on repeated measures inference applied to the measurement of risk-taking as a function of psychopathy

In numerous psychology studies, subjects are asked to perform some task a number of times, T. The effect of the choice of T on the associated inference, however, is usually not assessed. We investigate the appropriate choice of T empirically by using data collected in a study on the relationship between psychopathy and risk-taking in 90 inner city drug users enrolled in a residential treatment program. We show that, when studying this relationship, the latency variable usually discarded from the analysis behaves exponentially allowing a natural division of the study period 1, . . . , T into two distinct subperiods. These subperiods yield significantly different results—in the early period only (which we call “reactive”), subjects with high psychopathy scores exhibit lower sensitivity to reward and punishment in our risk taking experiment. The later period (which we call “stable”) shows no relationship between sensitivity to reward and punishment and psychopathic tendencies.     

SEMIPARAMETRIC VECTOR MEM

Financial time series are often non‐negative‐valued (volumes, trades, durations, realized volatility, daily range) and exhibit clustering. When joint dynamics is of interest, the vector multiplicative error model (vMEM; the element‐by‐element product of a vector of conditionally autoregressive scale factors and a multivariate i.i.d. innovation process) is a suitable strategy. Its parameters can be estimated by generalized method of moments, bypassing the problem of specifying a multivariate distribution for the errors. Simulated results show the gains in efficiency relative to an equation‐by‐equation approach. A vMEM on several measures of volatility justifies a joint approach revealing full interdependence. Copyright © 2012 John Wiley & Sons, Ltd.     

Weekly scheduling models for traveling therapists

This paper presents a series of models that can be used to find weekly schedules for therapists who provide ongoing treatment to patients throughout a geographical region. In all cases, patient-appointment times and visit days are known prior to the beginning of the planning horizon. Variations in the models include single vs. multiple home bases, homogeneous vs. heterogeneous therapists, lunch break requirements, and a nonlinear cost structure for mileage reimbursement and overtime. The single home base and homogeneous therapist cases proved to be easy to solve and so were not thoroughly investigated. This left two cases of interest: the first included only lunch breaks while the second added nonlinear overtime and mileage reimbursement costs. For the first case, 40 data sets were solved, each consisting of either 15 or 20 therapists and between roughly 300 and 540 patient visits over five days. For each instance, we were able to obtain the minimum cost of providing residential healthcare services using a commercial solver. The results showed that CPU time increases more rapidly than total cost as the total number of visits grows. For the second case, which was much more difficult, it was necessary to develop heuristics to find good solutions quickly. Results for 5- through 20-therapist instances are presented and compared to the linear programming relaxation lower bounds. In the first of two parametric analyses, the tradeoff between the number of therapists on staff and the cost of providing service was examined. In the second, a similar tradeoff was explored between cost can the number of home bases used by the therapists.