Identification and Estimation of Stochastic Bargaining Models

Stochastic sequential bargaining models (Merlo and Wilson (1995, 1998)) have found wide applications in different fields including political economy and macroeconomics due to their flexibility in explaining delays in reaching an agreement. This paper presents new results in nonparametric identification and estimation of such models under different data scenarios.     

Sleep and behavioral correlates of napping among young adults: a survey of first-year university students in Madrid, Spain

Objective: Between November 2002 and March 2003, the authors assessed the prevalence and correlates of napping among Spanish university students. Participants: The sample comprised 1,276 first-year university students; the mean age was 18.74 +/- 1.24 years, and 35.45% were men. Methods: The study was cross-sectional, and the students completed self-report, anonymous questionnaires provided during an in-class survey. Results: Almost half (44%) of the sample reported napping (90% did so after lunch for longer than 1 hour). Multiple logistic regression analysis showed that experiencing an irregular sleep-wakefulness pattern, having a morning school schedule, and being male were significant predictor variables of napping. Further significant outcome variables related to napping were having excessive daytime sleepiness, missing classes because of tiredness, better ability to concentrate later in the afternoon, and a perception of deeper nighttime sleep. Conclusions: Habitual napping is common among Spanish university students and associated with an irregular sleep-wakefulness pattern. Taking long postlunch naps seems to be used by students to cope with insufficient sleep and daytime sleepiness.     

Belief system foundations of backward induction

Two justifications of backward induction (BI) in generic perfect information games are formulated using Bonanno's (1992; Theory and Decision 33, 153) belief systems. The first justification concerns the BI strategy profile and is based on selecting a set of rational belief systems from which players have to choose their belief functions. The second justification concerns the BI path of play and is based on a sequential deletion of nodes that are inconsistent with the choice of rational belief functions.     

Evaluating a Case of Parent Separation in Social Services Through a Text Analysis: Clinical and Health Implications

Abstract

The assessment of the family system is very complex, as several factors have to be taken into account: The number of people involved (one or more children), the involvement of other partners, and the presence of legal disputes. Although evaluation practices have increased considerably, it remains difficult for services to prove their effectiveness. The questions that have guided this work have concerned how much and how do the discourses (discursive repertoires) produced by the conflicting parents change as a result of an intervention by the Service? And how much is it possible to evaluate the change in short texts? We used the Methodology for the Analysis of Computerised Text Data (MADIT) methodology that makes it possible to analyze the texts produced by the parents after the Service consultancy. The text is acquired through 14 emails sent by each parent to the other. The results showed that it was possible to detect a change in the repertoires used by the two parents to make decisions regarding their child. This data could increase the use of evaluation in the Services, reducing costs and evaluating change also by email. Future research could apply this methodology in situations where the conflict has not yet exploded and has not had an impact on children.     

Image estimators based on marked bins

The problem of approximating an ‘image’ S?? ^d from a random sample of points is considered. If S is included in a grid of square bins, a plausible estimator of S is defined as the union of the ‘marked’ bins (those containing a sample point). We obtain convergence rates for this estimator and study its performance in the approximation of the border of S. The practical aspects of implementation are discussed, including some technical improvements on the estimator, whose performance is checked through a real data example.     

Chance-Corrected Measures of Reliability and Validity in 2 × 2 Tables

It is customary to use two groups of indices to evaluate a diagnostic method with a binary outcome: validity indices with a standard rater (sensitivity, specificity, and positive or negative predictive values) and reliability indices (positive, negative and overall agreements) without a standard rater. However neither of these classic indices is chance-corrected, and this may distort the analysis of the problem (especially in comparative studies). One way of chance-correcting these indices is by using the Delta model (an alternative to the Kappa model), but this means having to use a computer program to work out the calculations. This paper gives an asymptotic version of the Delta model, thus allowing simple expressions to be obtained for the estimator of each of the above-mentioned chance-corrected indices (as well as for its standard error).     

Fuzzy Autoregressive Rules: Towards Linguistic Time Series Modeling

Fuzzy rule–based models, a key element in soft computing (SC), have arisen as an alternative for time series analysis and modeling. One difference with preexisting models is their interpretability in terms of human language. Their interactions with other components have also contributed to a huge development in their identification and estimation procedures. In this article, we present fuzzy rule–based models, their links with some regime-switching autoregressive models, and how the use of soft computing concepts can help the practitioner to solve and gain a deeper insight into a given problem. An example on a realized volatility series is presented to show the forecasting abilities of a fuzzy rule–based model.     

A New Chart for Monitoring the Covariance Matrix of Bivariate Processes

In this article we consider a control chart based on the sample variances of two quality characteristics. The points plotted on the chart correspond to the maximum value of these two statistics. The main reason to consider the proposed chart instead of the generalized variance | S | chart is its better diagnostic feature, that is, with the new chart it is easier to relate an out-of-control signal to the variables whose parameters have moved away from their in-control values. We study the control chart efficiency considering different shifts in the covariance matrix. In this way, we obtain the average run length (ARL) that measures the effectiveness of a control chart in detecting process shifts. The proposed chart always detects process disturbances faster than the generalized variance | S | chart. The same is observed when the size of the samples is variable, except in a few cases in which the size of the samples switches between small size and very large size.     

Canonical correlation analysis in the definition of weight restrictions for data envelopment analysis

This work investigates the use of canonical correlation analysis (CCA) in the definition of weight restrictions for data envelopment analysis (DEA). With this purpose, CCA limits are introduced into Wong and Beasley's DEA model. An application of the method is made over data from hospitals in 27 Brazilian cities, producing as outputs average payment (average admission values) and percentage of hospital admissions according to disease groups (International Classification of Diseases, 9th Edition), and having as inputs mortality rates and average stay (length of stay after admission (days)). In this application, performance scores were calculated for both the (CCA) restricted and unrestricted DEA models. It can be concluded that the use of CCA-based weight limits for DEA models increases the consistency of the estimated DEA scores (more homogenous weights) and that these limits do not present mathematical infeasibility problems while avoiding the need for subjectively restricting weight variation in DEA.