Until work do us part: Labour migration and occupational stratification in non-cohabiting marriage

While recent decades have seen considerable research on cohabitation without marriage, the study of marriage without cohabitation has not fared as well. Prior work on the latter has emphasized the importance of occupational stratification, but ignored the social context around occupation, particularly regarding labour mobility and economic development. In this paper, we outline the significance of contemporary labour mobility and concomitant occupational stratification for the risk of non-cohabiting marriage, and use data from the IPUMS–International project to provide a cross-national accounting of non-cohabiting marriage. We focus on two issues: first, how does prevalence vary across countries, across time, and with respect to economic development? Second, how do the core dynamics of labour mobility—including migration, occupational status, and economic development—influence the probability of non-cohabiting marriage? Results indicate broad cross-national differences in prevalence, increasing risk over time, and a pattern of accumulating risk associated with multifaceted social disadvantage.     

A measure of interrater absolute agreement for ordinal categorical data

Statistical Methods & Applications - A measure of interrater absolute agreement for ordinal scales is proposed capitalizing on the dispersion index for ordinal variables proposed by Giuseppe...     

Estimation of General Stationary Processes by Variable Length Markov Chains

We develop new results about a sieve methodology for the estimation of minimal state spaces and probability laws in the class of stationary processes defined on finite categorical spaces. Using a sieve approximation with variable length Markov chains of increasing order, we show that an adapted version of the Context algorithm yields asymptotically correct estimates for the minimal state space and for the underlying probability distribution. As a side product, the method of sieves yields a nice graphical tree representation for the potentially infinite dimensional minimal state space of the data generating process, which is very useful for exploration of the memory.     

Beta Regression for Modelling Rates and Proportions

This paper proposes a regression model where the response is beta distributed using a parameterization of the beta law that is indexed by mean and dispersion parameters. The proposed model is useful for situations where the variable of interest is continuous and restricted to the interval (0, 1) and is related to other variables through a regression structure. The regression parameters of the beta regression model are interpretable in terms of the mean of the response and, when the logit link is used, of an odds ratio, unlike the parameters of a linear regression that employs a transformed response. Estimation is performed by maximum likelihood. We provide closed-form expressions for the score function, for Fisher's information matrix and its inverse. Hypothesis testing is performed using approximations obtained from the asymptotic normality of the maximum likelihood estimator. Some diagnostic measures are introduced. Finally, practical applications that employ real data are presented and discussed.     

An Assessment of the Italian 2007 Complementary Social Security Reform: A Simulation Approach

In this paper we aim at assessing the outcomes of the 2007 Italian reform of the complementary social security scheme and at identifying the determinants behind them. The reform provided workers with relevant incentives to switch the investment of about 7 per cent of their gross yearly wages from a firm‐managed scheme (which took the form of a termination indemnity payment, the Trattamento di Fine Rapporto scheme) to an external pension fund. We provide a theoretical framework to model the workers' problem of choosing between these two different forms of complementary social security schemes and we then perform an agent‐based simulation taking into account all the details of the reform. Differently from previous contributions, we stress the impact that the investment decision has on the financial health of firms and, consequently, on workers' employment stability. Our simulations are able to replicate the Italian data in terms of adhesion rates to complementary social security and also to identify some of the key determinants of that outcome, such as fiscal incentives, individual preferences, the working of both the Italian labour and the financial markets and the productive structure of the Italian economy.     

Multidimensional item response theory models for dichotomous data in customer satisfaction evaluation

In this paper, multidimensional item response theory models for dichotomous data, developed in the fields of psychometrics and ability assessment, are discussed in connection with the problem of evaluating customer satisfaction. These models allow us to take into account latent constructs at various degrees of complexity and provide interesting new perspectives for services quality assessment. Markov chain Monte Carlo techniques are considered for estimation. An application to a real data set is also presented.     

Weighting Elementary Prices in Consumer Price Index Construction Using Spatial Autocorrelation

The Consumer Price Indexes (CPI) are used in current economic systems to measure inflation. When constructing CPIs, however, official institutions have systematically overlooked the spatial dimension of elementary prices. Ignoring the fact that prices are collected at geographical locations implicitly implies considering prices as spatially independent, when in fact they are not. To solve this problem, this article proposes to weight basic price data by taking into account the spatial correlation they display. The weighted geometric and arithmetic means suggested generalize and improve the simple geometric and arithmetic means currently in use.     

Statistical Modeling of Temporal Dependence in Financial Data via a Copula Function

In financial analysis it is useful to study the dependence between two or more time series as well as the temporal dependence in a univariate time series. This article is concerned with the statistical modeling of the dependence structure in a univariate financial time series using the concept of copula. We treat the series of financial returns as a first order Markov process. The Archimedean two-parameter BB7 copula is adopted to describe the underlying dependence structure between two consecutive returns, while the log-Dagum distribution is employed to model the margins marked by skewness and kurtosis. A simulation study is carried out to evaluate the performance of the maximum likelihood estimates. Furthermore, we apply the model to the daily returns of four stocks and, finally, we illustrate how its fitting to data can be improved when the dependence between consecutive returns is described through a copula function.     

On Bayesian learning via loss functions

We provide a decision theoretic approach to the construction of a learning process in the presence of independent and identically distributed observations. Starting with a probability measure representing beliefs about a key parameter, the approach allows the measure to be updated via the solution to a well defined decision problem. While the learning process encompasses the Bayesian approach, a necessary asymptotic consideration then actually implies the Bayesian learning process is best. This conclusion is due to the requirement of posterior consistency for all models and of having standardized losses between probability distributions. This is shown considering a specific continuous model and a very general class of discrete models.     

Analysis of the ergonomic usage of the ARMflex in the odontological area

The aim of this paper is to analyze the importance and applicability of ARMflex in the odontological area and its influence in preventing or stopping the involuntary habit of improperly positioning the hand under the face or under the pillow. The ergonomic usage of ARMflex influences the design in odontological areas and innovates in the semi-immobilization of the patient to prevent future orthodontic problems.