Age Is But a Number? An Exploration of Age Differences in Episodic Volunteering

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Age has long been understood as a strong demographic determinant of volunteering. However, to date, limited literature...     

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.     

Demographic Shifts in the Czech Republic after 1989: A Second Demographic Transition View

A dramatic change in fertility,family formation and living arrangements tookplace in the Czech Republic over the 1990s. Theestablishment of democracy, profound socialtransformation and transition to the marketeconomy affected the values and demographicbehaviour of the young Czech generation. Thispaper examines whether these demographic shiftscan be interpreted within the framework of thesecond demographic transition. The theoreticalpart discusses the idea of the transition,outlining three distinctive conceptualisations.Two of them – the view of the transition as aprogression of characteristic interrelateddemographic changes and a broader viewstressing the importance of underlyingideational factors – fit the Czech situationvery well. A comparison with the Netherlandsreveals that the onset of the transition in theCzech Republic may be clearly located in thefirst half of the 1990s, lagging two decadesbehind the Netherlands.     

Dynamic reliability models with conditional proportional hazards

A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a jump from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution functions of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.     

Multilevel maximum likelihood estimation with application to covariance matrices

The asymptotic variance of the maximum likelihood estimate is proved to decrease when the maximization is restricted to a subspace that contains the true parameter value. Maximum likelihood estimation allows a systematic fitting of covariance models to the sample, which is important in data assimilation. The hierarchical maximum likelihood approach is applied to the spectral diagonal covariance model with different parameterizations of eigenvalue decay, and to the sparse inverse covariance model with specified parameter values on different sets of nonzero entries. It is shown computationally that using smaller sets of parameters can decrease the sampling noise in high dimension substantially.     

The Political Economy of Social Insurance: Towards a Fiscal‐Centred Framework

This article draws attention to social insurance (SI) as a revenue raising institution, and explores the potential merits of drawing on new fiscal sociology for studying the development of SI systems. This is done by revisiting previous research conducted in Germany, the USA, Finland and Israel and by offering a new reading of their findings. The reviewed cases support two interlocking claims drawn from new fiscal sociology to the study of SI. The first is that state actors may perceive SI as an extraction instrument and employ it to advance fiscal and/or economic interests other than covering the costs of SI schemes. The second is that the design and management of contribution policies for such purposes may have substantial ramifications for the development of SI schemes. In addition, while current understandings tend to associate fiscal concerns with welfare state retrenchment, this article shows that they can also play a major role in driving welfare state expansion.