A tutorial on adaptive MCMC

We review adaptive Markov chain Monte Carlo algorithms (MCMC) as a mean to optimise their performance. Using simple toy examples we review their theoretical underpinnings, and in particular show why adaptive MCMC algorithms might fail when some fundamental properties are not satisfied. This leads to guidelines concerning the design of correct algorithms. We then review criteria and the useful framework of stochastic approximation, which allows one to systematically optimise generally used criteria, but also analyse the properties of adaptive MCMC algorithms. We then propose a series of novel adaptive algorithms which prove to be robust and reliable in practice. These algorithms are applied to artificial and high dimensional scenarios, but also to the classic mine disaster dataset inference problem.     

Adaptive wavelet estimation of a density from mixtures under multiplicative censoring

In this paper, a mixture model under multiplicative censoring is considered. We investigate the estimation of a component of the mixture (a density) from the observations. A new adaptive estimator based on wavelets and a hard thresholding rule is constructed for this problem. Under mild assumptions on the model, we study its asymptotic properties by determining an upper bound of the mean integrated squared error over a wide range of Besov balls. We prove that the obtained upper bound is sharp.     

Spatial Patterns of Fertility Transition in Indian Districts

The article explores the dynamics of Indian fertility at the district level using a child‐woman index developed from the four Indian censuses, 1961 to 1991. It employs statistical and geostatistical techniques to assess fertility change across districts and periods. Fertility decline is evident in every region, but sizable regional differentials exist. A cluster analysis of fertility profiles indicates that a clear spatial pattern of fertility in India has emerged and the pattern intensified because of the process of fertility decline.     

The impact of education on third births. A multilevel discrete-time hazard analysis

We propose to use multilevel discrete-time hazard models to assess the impact of societal and individual level covariates on the timing and occurrence of third births. We focus mainly on the impact of educational attainment on third births across 15 European countries. From the analysis in this paper, the effect of education on the propensity to have a third child is found to be negative. This education effect is not significantly weakened by the Nordic countries, but living in Scandinavia does increase the hazard for a third birth.     

Optimizing the Collections Process in Consumer Credit

This paper builds a dynamic programming model to optimize the collections process in consumer credit. It determines which collections actions should be undertaken and how long they should be performed, including theoretical results about the form of the optimal policy under certain conditions. Finally, a case study is described based on data from the collections department of a European bank.     

Immigration,Growth, and Unemployment: Panel VAR Evidence from OECD Countries

This paper examines empirically the interaction between immigration and host country economic conditions. We employ panel vector autoregression (VAR) techniques for a large annual data set on 22 OECD countries over the period 1987–2009. The VAR approach addresses the endogeneity problem by allowing for endogenous interactions between the variables in the system. Our results provide evidence of migration contribution to host economic prosperity (positive impact on GDP per capita and negative impact on aggregate unemployment, native‐ and foreign‐born unemployment rates). We also find that migration is influenced by host economic conditions (migration responds positively to host GDP per capita and negatively to host total unemployment rate).     

Personal development plans supporting employee learning and perceived performance: the moderating role of self-directedness

Due to developments in the current dynamic business environment which is more global and competitive than ever, employees’ lifelong learning and the way organizations support their continuous development are pivotal. Many organizations introduce personal development plans (PDPs) to support employees’ learning, however, not always taking into account their personal characteristics. This study had a twofold purpose as it was designed to explore on the one hand the relationship between PDPs in the workplace with employee’s undertaking of learning activities and perceived performance, and on the other hand the possible moderating role of employee self-directedness on this relationship. For this study, data collected by means of a questionnaire at two different organizations were used, one organization foregoing profit and one non-profit activity. The results indicated significant positive relations between the individual supporting factor ‘employee learning and reflection’ and the undertaking of learning activities and perceived performance and between employee self-directedness and the undertaking of learning activities and perceived performance. The same accounted for the moderating effect of employee self-directedness on the interaction between learning and reflection and perceived performance. Some findings were surprising, nevertheless resulted in valuable insights and implications for practice.