Bivariate income distributions with lognormal conditionals

In this paper, the most general bivariate distribution with lognormal conditionals is fully characterized, using the methodology proposed by [3]. The properties of the new family are studied in detail, including marginal and conditional distributions, regression functions, dependence measures, moments and inequality measures. The new distribution is very broad, and contains as a particular case the classical bivariate lognormal distribution. Several subfamilies are studied and a generalization of the basic model is discussed. Finally, we present an empirical application. We estimate and compare the basic model proposed in the paper with a classical model, using data from the European Community Household Panel in different periods of time.     

Testing the Martingale Difference Hypothesis

In this paper we consider testing that an economic time series follows a martingale difference process. The martingale difference hypothesis has typically been tested using information contained in the second moments of a process, that is, using test statistics based on the sample autocovariances or periodograms. Tests based on these statistics are inconsistent since they cannot detect nonlinear alternatives. In this paper we consider tests that detect linear and nonlinear alternatives. Given that the asymptotic distributions of the considered tests statistics depend on the data generating process, we propose to implement the tests using a modified wild bootstrap procedure. The paper theoretically justifies the proposed tests and examines their finite sample behavior by means of Monte Carlo experiments.     

Dynamic evolution of alliance portfolios

This research advances in the conceptualization and the operationalization of the factors or microdynamics that determine the choice of partners. Most of the literature in this area of research has centered on the individual alliance without taking into account the set of alliances that a firm makes. This research applies a holistic approach, analyzing the set of alliances as a whole and points to the factors related to alliance portfolios that affect the choice of partners. The authors propose a longitudinal model that allows us to analyze the evolution of interorganizational networks. A Simulation Investigation for Empirical Network Analysis (SIENA) has been applied to a sample of 229 firms, analyzing 10,556 strategic alliances established between them over a 12 year period. The results show that certain factors over which managers exercise a degree of control (deliberate endogenous microdynamics) exert significant influences on the choice of partners by the focal actor and thereby on the dynamic configuration of alliance portfolios.     

Methodology for the Calculation of Annualized Incremental Risks in Systems of Dams

In the past few years, the field of dam safety has approached risk informed methodologies throughout the world and several methodologies and programs are appearing to aid in the systematization of the calculations. The most common way of implementing these calculations is through the use of event trees, computing event probabilities, and incremental consequences. This methodology is flexible enough for several situations, but its generalization to the case of systems of several dams is complex and its implementation in a completely general calculation methodology presents some problems. Retaining the event tree framework, a new methodology is proposed to calculate incremental risks. The main advantage of this proposed methodology is the ease with which it can be applied to systems of several dams: with a single risk model that describes the complete system and with a single calculation the incremental risks of the system can be obtained, being able to allocate the risk of each dam and of each failure mode. The article shows how both methodologies are equivalent and also applies them to a case study.     

The performance of the income protection system for older adults in Ecuador and future challenges

The objective of this article is to analyse the performance of Ecuador’s pension system and the challenges it will face in the future. Over the last 13 years, the pension system has made significant advances in terms of coverage and adequacy. However, demographic ageing is straining the financial sustainability of the contributory scheme. In this context, a number of public policy areas are identified, in terms of parameters and structures, which, together with the expansion of non-contributory coverage, could provide a more equitable and sustainable scheme.     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.     

The 3 F 2 with Complex Parameters as Generating Function of Discrete Distribution

A new discrete family of probability distributions that are generated by the ₃ F ₂ function with complex parameters is presented. Some of the properties of this new family are studied as well as methods of estimation for its parameters. It affords considerable flexibility of shape which turns the distribution into an appropriate candidate for modeling data that cannot be adequately fitted by classical families with fewer parameters. Finally, three examples in the fields of Agriculture and Education are included in order to show the versatility and utility of this distribution.     

A-optimal designs for heteroscedastic multifactor regression models

Abstract

This paper searches for A-optimal designs for Kronecker product and additive regression models when the errors are heteroscedastic. Sufficient conditions are given so that A-optimal designs for the multifactor models can be built from A-optimal designs for their sub-models with a single factor. The results of an efficiency study carried out to check the adequacy of the products of optimal designs for uni-factor marginal models when these are used to estimate different multi-factor models are also reported.     

An Exponential Model for Damage Accumulation

In this article, we present a general model for predicting the fatigue behavior for any stress level and amplitude using the exponential model. Based on the Wöhler field for fixed stress level, a compatibility functional equation enables us to derive the general model with eight parameters. The problem of parameter estimation is then discussed and some methods are described. Some examples are finally presented to illustrate the derived model and the proposed methods of estimation.     

Stages of change and engagement in a family intervention

Prochaska and DiClemente's stages of change model facilitate understanding of engagement difficulties in psychosocial intervention processes. We assessed the link between stages of family change and intervention dropout in a sample of 141 families with relational conflicts between parents and adolescent children. Each family member's stage of change was defined according to three criteria: seeing the conflict as a relational problem, assuming part of the responsibility for the dysfunctional relationship, and understanding one's own mental and emotional states and those of the other family members involved in the conflict (mentalization). Our dropout rate for the sample was 41.8% and was higher for immigrant families. We found a strong association between engagement and the contemplation stage of change, particularly the mother's. In family conflict interventions, participation of all the family members is essential so as raise awareness of the relational aspects of the conflict and the shared responsibility for the conflict and its resolution.