On Estimation of the Bivariate Poisson INAR Process

In a recent article, Pedeli and Karlis (2010 Pedeli, X. and Karlis, D. 2010. A Bivariate INAR(1) Process with Application. Statistical Modelling: An international Journal, 11: 325–349. [Crossref], [Web of Science ®] , [Google Scholar]) examined the extension of the classical Integer–valued Autoregressive (INAR) model to the bivariate case. In the present article, we examine estimation methods for the case of bivariate Poisson innovations. This is a simple extension of the classical INAR model allowing for two discrete valued time series to be correlated. Properties of different estimators are given. We also compare their properties via a small simulation experiment. Extensions to incorporate covariate information is discussed. A real data application is also provided.     

LASSO order selection for sparse autoregression: a bootstrap approach

Autoregressive models are widely employed for predictions and other inferences in many scientific fields. While the determination of their order is in general a difficult and critical step, this task becomes more complicated and crucial when the time series under investigation is realization of a stochastic process characterized by sparsity. In this paper we present a method for order determination of a stationary AR model with a sparse structure, given a set of observations, based upon a bootstrapped version of MAICE procedure [Akaike H. Prediction and entropy. Springer; 1998], in conjunction with a LASSO-type constraining procedure for lag suppression of insignificant lags. Empirical results will be obtained via Monte Carlo simulations. The quality of our method is assessed by comparison with the commonly adopted cross-validation approach and the non bootstrap counterpart of the presented procedure.     

Institutions and structures as barriers? A comparison of native‐born and immigrant unemployment durations across 12 European countries

This study investigated the effect of institutions on the unemployment duration gap between non‐EU immigrants and native‐born in 12 European countries. Going further than the existing literature, our study encompassed unemployment duration, distinguishing between exits to inactivity, primary and secondary employment. Additionally, we have provided a stronger micro‐foundation to the comparative literature by introducing institutional measures for unemployment‐related benefits at the individual level rather than merely using aggregate proxies. Our analysis found no disincentive effects of benefits for immigrants. Furthermore, the employment prospects of immigrants were better when the demand for low‐skilled labour was high, and immigration policy was labour market‐oriented. In contrast, employment protection legislation did not affect the unemployment duration of immigrants.     

Muslim Immigrants in Greece: Religious Organization and Local Responses

Muslims are the second largest religious group in Greece. In this essay their migration process, numbers, settlement patterns and demographic characteristics are presented. It is shown that Muslims in Greece include not only economic migrants but also an indigenous population residing in the northern part of the country. The essay discusses mainly the immigrants' efforts to establish associations and prayer halls as well as the state's initiative to establish a central mosque in the suburbs of Athens. It argues that although Muslims are now an integral part of a multi-religious Greece, there is a long way to go to achieving their integration.     

Moment estimation for statistics from marked point processes

In spatial statistics the data typically consist of measurements of some quantity at irregularly scattered locations; in other words, the data form a realization of a marked point process. In this paper, we formulate subsampling estimators of the moments of general statistics computed from marked point process data, and we establish their L ₂-consistency. The variance estimator in particular can be used for the construction of confidence intervals for estimated parameters. A practical data-based method for choosing a subsampling parameter is given and illustrated on a data set. Finite sample simulation examples are also presented.     

Extrapolation of subsampling distribution estimators: The i.i.d. and strong mixing cases

Politis & Romano (1994) proposed a general subsampling methodology for the construction of large‐sample confidence regions for an arbitrary parameter under minimal conditions. Nevertheless, the subsampling distribution estimators may sometimes be inefficient (in the case of the sample mean of i.i.d. data, for instance) as compared to alternative estimators such as the bootstrap and/or the asymptotic normal distribution (with estimated variance). The authors investigate here the extent to which the performance of subsampling distribution estimators can be improved by interpolation and extrapolation techniques, while at the same time retaining the robustness property of consistent distribution estimation even in nonregular cases; both i.i.d. and weakly dependent (mixing) observations are considered.     

Improving the EM algorithm for mixtures

One of the estimating equations of the Maximum Likelihood Estimation method, for finite mixtures of the one parameter exponential family, is the first moment equation. This can help considerably in reducing the labor and the cost of calculating the Maximum Likelihood estimates. In this paper it is shown that the EM algorithm can be substantially improved by using this result when applied for mixture models. A short discussion about other methods proposed for the calculation of the Maximum Likelihood estimates are also reported showing that the above findings can help in this direction too.     

Information and Communication Technologies and the Opportunities of Disabled Persons in the Swedish Labour Market

This article attempts to outline the prospects of disabled persons to gain and retain employment within the Information Society by presenting and discussing the results of a labour market policy programme in Sweden based on information technology. The effects of Information and Communication Technologies (ICTs) for unemployed and employed persons with disabilities can be assessed on the micro, as well as on the macro levels. Technological optimism has given rise to expectations about the great potential of ICTs in creating employment opportunities for disabled persons. Technological optimism, however, derives from a deterministic point of view, i.e. ICTs are regarded as an independent variable. This article suggests that ICTs must be regarded as a variable dependent by the economic, social and cultural order. Its effects on disabled persons employment opportunities are not independent by the power relations at a given time.     

Prosodic cues of identity construction: Intensity in Greek young women's conversational narratives1

The present paper examines the discourse functions of intensity in the context of narrative direct speech quotations. We argue that differentiation in intensity functions as a contextualization cue signalling involvement as well as power negotiation. Intensity, therefore, seems to be an ambivalent signal acquiring its meaning in interaction with other contextual parameters. More specifically, we argue that a louder voice is preferred in in‐group talk representations as a contextualization cue of a high involvement style in conversations between intimate young peers. Lower intensity, on the other hand, is used by young female narrators in the representation of talk with authority‐out‐group figures, as a means of reducing the authority of the adult voices represented in their narratives. The qualitative analysis of our data is further supported by quantitative analysis. We conclude that intensity differentiation in the direct speech quotations of young female narrators functions as a contextualization cue signalling, on the one hand, their independence from adult authority and, on the other, their in‐group bonds.