Legitimacy theory may explain the failure of global adoption of IFRS: the case of Europe and the U.S.

We investigate the reasons why “adoption” of one set of globally accepted accounting standards is presently unachievable. By “adoption” we mean that a jurisdiction incorporates IFRS instantly as its national accounting as issued by the IASB. We state that the IASB has used a Legitimacy Theory strategy to gain acceptance of its standards by more than 120 countries across the globe but it has only gained pseudo-“adoption” (not as published by the IASB) of its standards by many countries. We contend that achieving policing and enforcement of its standards globally has proven to be empirically illusive. This legitimacy deficit may explain why convergence between the IASB and FASB is currently idle. We offer a possible solution to bridging the legitimacy gap of global adoption of IFRS. We propose an internationally respected regulator and suggest the IOSCO for this role through its participation in the IFRS Foundation Monitoring Board for policing and enforcement of IFRS for cross-listed firms reporting in compliance with IFRS so that the IASB’s output legitimacy may be achieved globally.     

Digital technologies and power dynamics in the organization: A conceptual review of remote working and wearable technologies at work

In this article, we examine the kinds of control practices that emerge with the introduction of digital technologies, and how these technologies are employed to shape power within workplaces. We present a comparative conceptual review of work practices by contrasting remote work and the use of workplace wearables. We trace forms of power and control that have been enacted with the adoption of these work‐related technologies and associated practices. We find that the prevailing literature focuses on the practices enacted by management in order to control workers and exert power over them, and we propose that a more comprehensive approach be taken. In support of this view, we show how the concept of appropriation emerges from science and technology studies, and we argue that such a concept would be useful for exploring how workers use and incorporate digital technologies into their daily lives, thus reshaping power in organizations.     

On the estimation of non linear functions in stochastic volatility models

Abstract

This paper focuses on the inference of suitable generally non linear functions in stochastic volatility models. In this context, in order to estimate the variance of the proposed estimators, a moving block bootstrap (MBB) approach is suggested and discussed. Under mild assumptions, we show that the MBB procedure is weakly consistent. Moreover, a methodology to choose the optimal length block in the MBB is proposed. Some examples and simulations on the model are also made to show the performance of the proposed procedure.     

Constrained vs unconstrained labor supply: the economics of dual job holding

This paper develops a unified model of dual and unitary job holding based on a Stone-Geary utility function. The model incorporates both constrained and unconstrained labor supply. Panel data methods are adapted to accommodate unobserved heterogeneity and multinomial selection into six mutually exclusive labor supply regimes. We estimate the wage and income elasticities arising from selection and unobserved heterogeneity as well as from the Stone-Geary Slutsky equations. The labor supply model is estimated with data from the British Household Panel Survey 1991–2008. Among dual job holders, our study finds that the Stone-Geary income and wage elasticities are much larger for labor supply to the second job compared with the main job. When the effects of selection and unobserved heterogeneity are taken account of, the magnitudes of these elasticities on the second job tend to be significantly reduced.     

A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding

Floods are a natural hazard evolving in space and time according to meteorological and river basin dynamics, so that a single flood event can affect different regions over the event duration. This physical mechanism introduces spatio‐temporal relationships between flood records and losses at different locations over a given time window that should be taken into account for an effective assessment of the collective flood risk. However, since extreme floods are rare events, the limited number of historical records usually prevents a reliable frequency analysis. To overcome this limit, we move from the analysis of extreme events to the modeling of continuous stream flow records preserving spatio‐temporal correlation structures of the entire process, and making a more efficient use of the information provided by continuous flow records. The approach is based on the dynamic copula framework, which allows for splitting the modeling of spatio‐temporal properties by coupling suitable time series models accounting for temporal dynamics, and multivariate distributions describing spatial dependence. The model is applied to 490 stream flow sequences recorded across 10 of the largest river basins in central and eastern Europe (Danube, Rhine, Elbe, Oder, Waser, Meuse, Rhone, Seine, Loire, and Garonne). Using available proxy data to quantify local flood exposure and vulnerability, we show that the temporal dependence exerts a key role in reproducing interannual persistence, and thus magnitude and frequency of annual proxy flood losses aggregated at a basin‐wide scale, while copulas allow the preservation of the spatial dependence of losses at weekly and annual time scales.     

Malthus in the Bedroom: Birth Spacing as Birth Control in Pre-Transition England

We use duration models on a well-known historical data set of more than 15,000 families and 60,000 births in England for the period 1540–1850 to show that the sampled families adjusted the timing of their births in accordance with the economic conditions as well as their stock of dependent children. The effects were larger among the lower socioeconomic ranks. Our findings on the existence of parity-dependent as well as parity-independent birth spacing in England are consistent with the growing evidence that marital birth control was present in pre-transitional populations.     

Physical exercise,nutrition and hormones: three pillars to fight sarcopenia

Background: Sarcopenia is a pathophysiological condition diffused in elderly people; it represents a social issue due to the longer life expectancy and the growing aging population. It affects negatively quality of life and it represents a risk factor for other pathologies, such as diabetes, cardiovascular disease, and obesity. No silver bullet exists to hinder sarcopenia, but it may be counteracted by physical exercise, nutrition, and a proper endocrine milieu. Indeed, we aim to analyze the scientific literature to give to clinician effective advices to counteract sarcopenia.

Main text: Physical exercise, proper nutrition, optimized hormonal homeostasis represent the three pillars to fight sarcopenia. Physical exercise represents the most effective remedy to face sarcopenia, in particular if it is combined with a proper diet and with an adequate endocrine milieu. Consistency in training, adequate daily protein intake and eugonadism seems to be the keys to fight sarcopenia. The combination of these three pillars might act synergistically.

Conclusions: Optimization of these factors may increase their efficiency; however, scientific data may be sometimes confusing so far. Therefore, we aim to give practical advices to clinician to identify and to highlight the most important aspects in each of these three factors that should be addressed.     

Suspect community or suspect category? The impact of counter-terrorism as ‘policed multiculturalism’

How to think about the impact of counter-terrorism and counter-radicalisation on ethnic and religious accommodation? Much of the literature draws on the concept of ‘suspect community’, suggesting it has primarily alienated the Muslim community, favouring an assimilationist model of ‘muscular liberalism’. In this article, while I consider the merits of the ‘suspect community’ hypothesis, I argue that it only partially accounts for the effects of counter-terrorism and counter-radicalisation on multicultural societies. I contend that much of the literature has focused too narrowly on the discriminatory effects of counter-terrorist policies and has been unable to grasp the more insidious political effects of counter-terrorism policies based on the active participation and involvement of Muslims in their own policing. The main hypothesis of this paper is that rather than promoting ‘assimilation’, as the government would expect, or alienation, as the advocates of the ‘suspect community’ hypothesis would contend, counter-terrorist policies produce and reinforce a government of society in discrete and divided ethno-religious groups. Such ‘policed multiculturalism’—understood as the recognition and the management of diversity through a security perspective—has an important consequence in that it removes fundamental questions about pluralism from political debate, casting them instead in a depoliticised language of security.     

Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.