Bayesian networks for imputation

Summary.  Bayesian networks are particularly useful for dealing with high dimensional statistical problems. They allow a reduction in the complexity of the phenomenon under study by representing joint relationships between a set of variables through conditional relationships between subsets of these variables. Following Thibaudeau and Winkler we use Bayesian networks for imputing missing values. This method is introduced to deal with the problem of the consistency of imputed values: preservation of statistical relationships between variables ( statistical consistency ) and preservation of logical constraints in data ( logical consistency ). We perform some experiments on a subset of anonymous individual records from the 1991 UK population census.     

The MIMIC–CUB Model for the Prediction of the Economic Public Opinions in Europe

Social Indicators Research - To study the Europeans’ perception on the economic conditions, a model that combine Multiple Indicators Multiple Causes (MIMIC) and Combination of Uniform and...     

Asymptotic relative efficiency of wald tests in measurement error models

In this paper, asymptotic relative efficiency (ARE) of Wald tests for the Tweedie class of models with log-linear mean, is considered when the aux¬iliary variable is measured with error. Wald test statistics based on the naive maximum likelihood estimator and on a consistent estimator which is obtained by using Nakarnura's (1990) corrected score function approach are defined. As shown analytically, the Wald statistics based on the naive and corrected score function estimators are asymptotically equivalents in terms of ARE. On the other hand, the asymptotic relative efficiency of the naive and corrected Wald statistic with respect to the Wald statistic based on the true covariate equals to the square of the correlation between the unobserved and the observed co-variate. A small scale numerical Monte Carlo study and an example illustrate the small sample size situation.     

Exploring the relationship between product-service system and profitability

Journal of Management and Governance - Over the last few decades there has been a significant change in the economic output worldwide, and services have become more and more important....     

Bayesian Conditional Mean Estimation in Log‐Normal Linear Regression Models with Finite Quadratic Expected Loss

Log‐normal linear regression models are popular in many fields of research. Bayesian estimation of the conditional mean of the dependent variable is problematic as many choices of the prior for the variance (on the log‐scale) lead to posterior distributions with no finite moments. We propose a generalized inverse Gaussian prior for this variance and derive the conditions on the prior parameters that yield posterior distributions of the conditional mean of the dependent variable with finite moments up to a pre‐specified order. The conditions depend on one of the three parameters of the suggested prior; the other two have an influence on inferences for small and medium sample sizes. A second goal of this paper is to discuss how to choose these parameters according to different criteria including the optimization of frequentist properties of posterior means.     

The Construction of a Synthetic Index Comparing Multidimensional Well-Being in the European Union

For many years, the quantification and measurement of level of well-being in a society has become an object of study by researchers, economists, international organizations and institutions. The purpose of these researches and applications is mainly the collection of data as accurate and complete as possible, dictating the paths of economic and social development policies, in order to help the economic problem of allocating scarce resources within a community, where not all individual needs can be fully met. The present work is intended as a part of that field. It will undertake the construction of a composite index of multidimensional well-being, through an aggregation of data, able to balance the trade-off between immediacy and completeness of information and to trespass the limits that characterize the commonly used income related measures. The method of factor analysis, which aims at detecting a statistically sufficient number of variables, is used to represent most of the explained variance of the phenomenon. Results are tested with different aggregative processes. This analysis is applied to the reality of the European Union, characterized by deep transformation and cultural, economic and social inequalities.     

Human Reliability Analysis by Fuzzy "CREAM"

This article proposes a systematic procedure for computing probabilities of operator action failure in the cognitive reliability and error analysis method (CREAM). The starting point for the quantification is a previously introduced fuzzy version of the CREAM paradigm that is here further extended to account for: (1) the ambiguity in the qualification of the conditions under which the action is performed (common performance conditions, CPCs) and (2) the fact that the effects of such conditions on human performance reliability may not all be equal.     

Eliciting decision weights by adapting de Finetti’s betting-odds method to prospect theory

This paper extends de Finetti’s betting-odds method for assessing subjective beliefs to ambiguous events. Thus, a tractable manner for measuring decision weights under ambiguity is obtained. De Finetti’s method is so transparent that decision makers can evaluate the relevant tradeoffs in complex situations. The resulting data can easily be analyzed, using nonparametric techniques. Our extension is implemented in an experiment on predicting next-day’s performance of the Dow Jones and Nikkei stock indexes, where we test the existence and nature of rank dependence, finding usual patterns. We also find violations of rank dependence.

Central bank credibility and monetary policy in Indonesia

This paper examines the role of central bank credibility in achieving an inflation target and proposes monetary policy rules for Indonesia. Towards that end, we construct and estimate a forward-looking small scale macroeconomic model (SSMM) of the Indonesian economy by adapting the theoretical underpinnings of the well-known Batini–Haldane model, along with the Taylor policy rule. Our results indicate that it is crucial for the Indonesian central bank to bolster its credibility in order to achieve a lower inflation rate. The inflation–output volatility trade-off frontier we derived from the SSMM shows that a monetary policy rule that targets both inflation and output gaps will result in less macroeconomic volatility. We also found that the inclusion of the exchange rate into the rule as an additional feedback variable warrants consideration in the future course of monetary policy management.     

A Small-Sample Estimator for the Sample-Selection Model

A semiparametric estimator for evaluating the parameters of data generated under a sample selection process is developed. This estimator is based on the generalized maximum entropy estimator and performs well for small and ill-posed samples. Theoretical and sampling comparisons with parametric and semiparametric estimators are given. This method and standard ones are applied to three small-sample empirical applications of the wage-participation model for female teenage heads of households, immigrants, and Native Americans.