Leaders' and subordinates' attachment orientations,emotion regulation capabilities and affect at work: A multilevel analysis

Two studies examined relationships between leaders' and subordinates' attachment orientations, emotion regulation capabilities, and affective experience and satisfaction at work. As expected, supervisors' and subordinates' insecure attachment orientations (higher anxiety and avoidance) were associated with own positive affect and satisfaction at work. Supervisors' anxious attachment orientation was associated with subordinates' lower positive affect and satisfaction at work. Contrary to hypotheses, supervisors' higher avoidance was associated with subordinates' lower negative affect and higher job satisfaction. Supervisors' emotion regulation capabilities did not mediate relationships between supervisors' insecure attachment orientations and supervisors' own or subordinates' affect and job satisfaction as expected. However, subordinates' emotion regulation capabilities interacted with supervisors' attachment orientations to predict subordinates' emotion experience at work. The results contribute to an understanding of attachment orientations' emotion dynamics in leader–follower interaction, pointing in particular to perceptual and affect-related processes at different levels of analysis.     

Estimation in a truncated bivariate poisson distribution using the EM algorithm

An EM algorithm (Dempster et al., 1977) is derived for the estimation of parameters of the truncated bivariate Poisson distribution with zeros rnissing from both margins. The observed inforrnation matrix is obtained and a numerical exarnple is given where the convergence of the EM algorithm is accelerated by the methods of Louis (1982) and conjugate gradients (Jamshidian antl Jennrich, 1993).     

The Implications of Using Messy Data to Estimate Production-Frontier-Based Technical Efficiency Measures

An empirical study of efficiency at the plant level, requiring production and financial data, was done using frontier function specifications. It is not evident from the implementation of the production-frontier models that different methodologies will consistently flag the same observations as being efficient or inefficient. As a result, outlier diagnostics for individual observations and for subsets of observations are used to achieve a relative index of influentiality within the spectrum of efficiency. These outlier diagnostic tests consistently flag the same subset of efficient and inefficient observations as the frontier models and additionally clarify ranking discrepancies among the frontier model specifications.     

Gender differences in life expectancy at birth in Greece 1994–2017

In this paper, we analyse the difference in life expectancy at birth between females and males in the Greek population between the years 1994–2017. After constructing life tables per gender, we used the method of Arriaga in order to decompose life expectancy’s differences by age and sex. We found that the gender gap increased until 2009 and decreased afterwards. Moreover, we estimated the differential contribution of the broad age groups of the population to the regulation of gender inequalities in longevity and studied the different effect of the causes of death. Besides age, the most important regulators are the neoplasms and the diseases of the circulatory system, followed by the external causes of morbidity and mortality, as well as the diseases of the respiratory system. All other causes of death play a marginal role. The results of the analysis indicate the need for the development and expansion of several public interventions and programs in order, not only to reduce the gender inequalities in longevity, but also to reduce the prevalence of several preventable diseases in the population.

     

A synaptic common sense? McLuhan’s tactility and electronic media rhythms

In Understanding Media, Marshall McLuhen proposed that tactility would eventually become a determining factor in electronic media, leading to the formation of a new kind of “common sense.” This article investigates whether by exploring this idea we are able to arrive at an alternative theoretical framework for understanding tactility, a framework that avoids the tactile-optic distinction and the understanding of tactility as a sensation primarily innervated through the bodily part of the hand. McLuhan’s notions of “acoustic space” and “contraction” are directly related to this breakthrough. It is further argued that the resulting theoretical framework can be enriched when considered in conjunction with social analyses of rhythms and used to account for the differentiation and customization or individualization of media use in the digital age. In this way, tactility is treated as embedded within rhythmic signals and fluctuations in media, allowing us to rethink McLuhan’s “common sense” in a singularly illuminating way.     

Axiomatizing bounded rationality: the priority heuristic

This paper presents an axiomatic framework for the priority heuristic, a model of bounded rationality in Selten’s (in: Gigerenzer and Selten (eds.) Bounded rationality: the adaptive toolbox, 2001) spirit of using empirical evidence on heuristics. The priority heuristic predicts actual human choices between risky gambles well. It implies violations of expected utility theory such as common consequence effects, common ratio effects, the fourfold pattern of risk taking and the reflection effect. We present an axiomatization of a parameterized version of the heuristic which generalizes the heuristic in order to account for individual differences and inconsistencies. The axiomatization uses semiorders (Luce, Econometrica 24:178–191, 1956), which have an intransitive indifference part and a transitive strict preference component. The axiomatization suggests new testable predictions of the priority heuristic and makes it easier for theorists to study the relation between heuristics and other axiomatic theories such as cumulative prospect theory.     

The Changing Transmission of Uncertainty Shocks in the U.S.

This article investigates if the impact of uncertainty shocks on the U.S. economy has changed over time. To this end, we develop an extended factor augmented vector autoregression (VAR) model that simultaneously allows the estimation of a measure of uncertainty and its time-varying impact on a range of variables. We find that the impact of uncertainty shocks on real activity and financial variables has declined systematically over time. In contrast, the response of inflation and the short-term interest rate to this shock has remained fairly stable. Simulations from a nonlinear dynamic stochastic general equilibrium (DSGE) model suggest that these empirical results are consistent with an increase in the monetary authorities’ antiinflation stance and a “flattening” of the Phillips curve. Supplementary materials for this article are available online.     

Determinants of Environmental Behavior in Societies in Transition: Evidence from Five European Countries

Countries of Central and East Europe are in a process of economic, social and political transition. This process provides a unique opportunity for cross-national studies in a context of social transformation and radical infrastructural changes. In the present study, we compared environmental behavior, and the factors affecting it, of citizens from five European countries with diverse economic and social status. Outcomes of the present survey suggest that people's attitudes towards environmental issues and economy-environment trade-offs can be considered reliable predictors, contrary to political attitudes which did not prove to be important determinants of environmental behavior. However, one should be aware of the differences in individual factors affecting citizens' environmental behavior, since the latter cannot be considered as a linear function of a country's development and modernization.     

Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations

We develop a framework that allows the use of the multi-level Monte Carlo (MLMC) methodology (Giles in Acta Numer. 24:259–328, 2015. https://doi.org/10.1017/S096249291500001X) to calculate expectations with respect to the invariant measure of an ergodic SDE. In that context, we study the (over-damped) Langevin equations with a strongly concave potential. We show that when appropriate contracting couplings for the numerical integrators are available, one can obtain a uniform-in-time estimate of the MLMC variance in contrast to the majority of the results in the MLMC literature. As a consequence, a root mean square error of $$\mathcal {O}(\varepsilon )$$ is achieved with $$\mathcal {O}(\varepsilon ^{-2})$$ complexity on par with Markov Chain Monte Carlo (MCMC) methods, which, however, can be computationally intensive when applied to large datasets. Finally, we present a multi-level version of the recently introduced stochastic gradient Langevin dynamics method (Welling and Teh, in: Proceedings of the 28th ICML, 2011) built for large datasets applications. We show that this is the first stochastic gradient MCMC method with complexity $$\mathcal {O}(\varepsilon ^{-2}|\log {\varepsilon }|^{3})$$, in contrast to the complexity $$\mathcal {O}(\varepsilon ^{-3})$$ of currently available methods. Numerical experiments confirm our theoretical findings.     

Impact of temporal aggregation on stock control performance of intermittent demand estimators: Empirical analysis

Intermittent demand is characterized by occasional demand arrivals interspersed by time intervals during which no demand occurs. These demand patterns pose considerable difficulties in terms of forecasting and stock control due to their compound nature, which implies variability both in terms of demand arrivals and demand sizes. An intuitively appealing strategy to deal with such patterns from a forecasting and stock control perspective is to aggregate demand in lower-frequency ‘time buckets’, thereby reducing the presence of zero observations. In this paper, we investigate the impact of forecasting aggregation on the stock control performance of intermittent demand patterns. The benefit of the forecasting aggregation approach is empirically assessed by means of analysis on a large demand dataset from the Royal Air Force (UK). The results show that the aggregation forecasting approach results in higher achieved service levels as compared to the classical forecasting approach. Moreover, when the combined service-cost performance is considered, the results also show that the former approach is more efficient than the latter, especially for high target service levels.