The Patterns of Satisfaction Among Immigrants in Germany

Using the data from the German Socio-Economic Panel, the paper focuses on the analysis of life satisfaction and income satisfaction among immigrants in Germany. The results suggest that it cannot be argued that Germany’s immigrants are, ceteris paribus, more satisfied or less satisfied than natives, since some immigrant groups appear to be more satisfied, while others show lower satisfaction levels relative to natives. Separate estimations for natives and immigrants show that, even though the patterns of satisfaction for the two groups are largely similar, several notable differences emerge. The final goal was to take a closer look at the negative relationship between satisfaction and duration of stay in Germany. After constructing reference groups by the timing of arrival, the negative relationship between income satisfaction and years since migration is reduced substantially. On the other hand, the negative association between duration of stay and life satisfaction is persistent, regardless of the way the reference groups are defined.     

Refusal Bias in the Estimation of HIV Prevalence

In 2007, UNAIDS corrected estimates of global HIV prevalence downward from 40 million to 33 million based on a methodological shift from sentinel surveillance to population-based surveys. Since then, population-based surveys are considered the gold standard for estimating HIV prevalence. However, prevalence rates based on representative surveys may be biased because of nonresponse. This article investigates one potential source of nonresponse bias: refusal to participate in the HIV test. We use the identity of randomly assigned interviewers to identify the participation effect and estimate HIV prevalence rates corrected for unobservable characteristics with a Heckman selection model. The analysis is based on a survey of 1,992 individuals in urban Namibia, which included an HIV test. We find that the bias resulting from refusal is not significant for the overall sample. However, a detailed analysis using kernel density estimates shows that the bias is substantial for the younger and the poorer population. Nonparticipants in these subsamples are estimated to be three times more likely to be HIV-positive than participants. The difference is particularly pronounced for women. Prevalence rates that ignore this selection effect may be seriously biased for specific target groups, leading to misallocation of resources for prevention and treatment.     

Preference and choice

A theory of preference and choice based on that of von Wright is developed whereby the choice of a state of affairs is determined by preferences between pairs of them. The method used is letting preferences eliminate states of affairs from the choice set according to axiomatized rules. Formal properties of extensions of von Wright's preference logic are investigated.     

On Shifted Geometric INAR(1) Models Based on Geometric Counting Series

Two types of shifted geometric integer valued autoregressive models of order one (SGINAR(1)) are proposed. Both are based on the thinning operator generated by counting series of i.i.d. geometric random variables. Their correlation properties are derived and compared. Also, regression and conditional variance are considered. Nonparametric estimators of model parameters are obtained and their asymptotic characterizations are given. Finally, these two models are applied to a real-life data set and they are compared to some referent INAR(1) models.     

The Marshall-Olkin Fréchet Distribution

We introduce a new distribution, namely Marshall–Olkin Fréchet distribution. The probability density and hazard rate functions are derived and their shape properties are considered. Expressions for the nth moments are given. Various results with respect to quantiles, Rényi entropy and order statistics are obtained. The unknown parameters of the new distribution are estimated using the maximum likelihood estimation method adopting three different iterative procedures. The model is applied on a real data set on survival times.

[Supplementary materials are available for this article. Go to the publisher's online edition of Communications in Statistics—Theory and Methods for the following free supplemental resource: A file that will allow the random variables from MOF distribution to be generated.]     

Estimation in a bivariate integer-valued autoregressive process

ABSTRACT

A bivariate integer-valued autoregressive time series model is presented. The model structure is based on binomial thinning. The unconditional and conditional first and second moments are considered. Correlation structure of marginal processes is shown to be analogous to the ARMA(2, 1) model. Some estimation methods such as the Yule–Walker and conditional least squares are considered and the asymptotic distributions of the obtained estimators are derived. Comparison between bivariate model with binomial thinning and bivariate model with negative binomial thinning is given.     

Fast Random Number Generation Using 128-Bit Multimedia Extension Registers on Pentium Class Machines

In this article, it is shown how 128-bit SSE2 multimedia extension registers, present in Pentium IV class 32-bit processors, may be used to generate random numbers at several times greater speed then when regular general purpose registers are used. In particular, a 128-bit algorithm is presented for the Marsaglia MWC1616 generator from the DIEHARD battery of random number generator tests, and its performance is compared to that of the conventional approach.