Tests for time series of counts based on the probability-generating function

We propose testing procedures for the hypothesis that a given set of discrete observations may be formulated as a particular time series of counts with a specific conditional law. The new test statistics incorporate the empirical probability-generating function computed from the observations. Special emphasis is given to the popular models of integer autoregression and Poisson autoregression. The asymptotic properties of the proposed test statistics are studied under the null hypothesis as well as under alternatives. A Monte Carlo power study on bootstrap versions of the new methods is included as well as real-data examples.     

Did Wars Make Nation‐States in the Balkans?: Nationalisms,Wars and States in the 19th and early 20th Century South East Europe

Nationalism and protracted warfare are often seen as the most important impediments to social advancement in the Balkans. In contrast to these popular perceptions I argue that for much of its history the Balkan region was characterised by limited inter‐state violence and by notable lack of nationalist ideologies. Furthermore by comparing the processes of state and nation formation and warfare in the South East Europe with those in the Western Europe the article aims to show that it is the weakness, not the strength, of nationalism and protracted warfare that historically have been the principal obstacles for social development. The general argument of the paper is developed in dialogue with Tilly's theory that ties state formation to proliferation of wars and Gellner's model that links the rise of nationalism to emergence of standardised educational systems and industrialisation. In an attempt to partially disprove Tilly and vindicate Gellner I argue that the experience of the Balkan region indicates that although wars can prove important catalysts of state formation they may not necessarily contribute to nation formation.     

Parental Leave Policies and Second Births: A Comparison of Czechia and Slovakia

Population Research and Policy Review - The paper investigates the transition to second births in Czechia and Slovakia in the context of the development of parental leave policies since the...     

Gender-related factors in family business succession: a systematic literature review

Review of Managerial Science - Succession is one of the most discussed topics in family business research. However, despite the changing professional and family roles of women and the growing...     

Large-scale commonness is the best predictor of bird species presence in European cities

Urban Ecosystems - Urban bird communities are homogenized across large spatial scales, suggesting that the urban environment acts as an environmental filter. We hypothesize that large scale...     

Housing of Seniors in the Czech Republic: Challenges for Social Services

The article focuses on the housing market, the behavior and motivations of senior households to move or to stay in place. Knowing if and why seniors decide to move at retirement is a critical factor for the establishment of social service policies in terms of their structure, location, and provision.

This study uses secondary data based on information about Czech households collected by the Czech Statistical Office (CSO). The data are annually collected via sample surveys of the income and living conditions of households (EU-SILC). The sample covers more than eight thousands of households. Analyzed data cover the period 2007–2012 when the abolishment of rent regulation in the Czech Republic took place. It is hypothesized that an impact like this might increase the willingness to move and reveal the factors which underlie the decisions of particular households.

The results indicated that most Czech households that decided to move during the study period were driven by the increased financial burden of housing. Other factors, including the availability of social services and public utilities within the current location, played only minor roles. It seems that Czech senior households act in a very pragmatic and rational manner when deciding whether to stay in place or move, with the majority of households preferring not to move. Social policies should, therefore, concentrate on providing services for the current locations rather than on the construction of new social housing.     

Promoting healthy transition to college through mindfulness training with first-year college students: Pilot randomized controlled trial

Objective: Given the importance of developmental transitions on young adults' lives and the high rates of mental health issues among U.S. college students, first-year college students can be particularly vulnerable to stress and adversity. This pilot study evaluated the effectiveness and feasibility of mindfulness training aiming to promote first-year college students' health and wellbeing. Participants: 109 freshmen were recruited from residential halls (50% Caucasian, 66% female). Data collection was completed in November 2014. Methods: A randomized control trial was conducted utilizing the Learning to BREATHE (L2B) program, a universal mindfulness program adapted to match the developmental tasks of college transition. Results: Participation in the pilot intervention was associated with significant increase in students' life satisfaction, and significant decrease in depression and anxiety. Marginally significant decrease was found for sleep issues and alcohol consequences. Conclusions: Mindfulness-based programs may be an effective strategy to enhance a healthy transition into college.     

Adaptive multiple importance sampling for Gaussian processes

In applications of Gaussian processes (GPs) where quantification of uncertainty is a strict requirement, it is necessary to accurately characterize the posterior distribution over Gaussian process covariance parameters. This is normally done by means of standard Markov chain Monte Carlo (MCMC) algorithms, which require repeated expensive calculations involving the marginal likelihood. Motivated by the desire to avoid the inefficiencies of MCMC algorithms rejecting a considerable amount of expensive proposals, this paper develops an alternative inference framework based on adaptive multiple importance sampling (AMIS). In particular, this paper studies the application of AMIS for GPs in the case of a Gaussian likelihood, and proposes a novel pseudo-marginal-based AMIS algorithm for non-Gaussian likelihoods, where the marginal likelihood is unbiasedly estimated. The results suggest that the proposed framework outperforms MCMC-based inference of covariance parameters in a wide range of scenarios.     

Tests for Structural Changes in Time Series of Counts

We propose methods for detecting structural changes in time series with discrete‐valued observations. The detector statistics come in familiar L2‐type formulations incorporating the empirical probability generating function. Special emphasis is given to the popular models of integer autoregression and Poisson autoregression. For both models, we study mainly structural changes due to a change in distribution, but we also comment for the classical problem of parameter change. The asymptotic properties of the proposed test statistics are studied under the null hypothesis as well as under alternatives. A Monte Carlo power study on bootstrap versions of the new methods is also included along with a real data example.     

A comparison of L-, LQ-, TL-moment and maximum likelihood high quantile estimates of the GPD and GEV distribution

In this article, L-moments, LQ-moments and TL-moments of the generalized Pareto and generalized extreme-value distributions are derived up to the fourth order. The first three L-, LQ- and TL-moments are used to obtain estimators of their parameters. Performing a simulation study, high-quantile estimates based on L-, LQ-, and TL-moments are compared to the maximum likelihood estimate with respect to their sample mean squared error. This consists of identifying an optimal combination of parameters α and p both considered in the range [0, 0.5] for estimating quantiles by LQ-moments. The results show L-moment and maximum likelihood methods outperform other methods.