An Intertemporal Analysis of Development Policies in the EU

In this paper, we focus on the effects of EU structural transfer programs on the evolution of the EU less developed economies. We develop a two-sector endogenous growth model of private and public physical capital and human capital accumulation in which the public sector and the current account balances play a crucial role. This model is applied to Portugal. Simulation results suggest that structural programs will bring Portuguese GDP per capita to 63.7% of the EU average (up from around 54% in the last two decades), thereby greatly contributing to the process of real convergence of the Portuguese economy to EU standards. Additional transfers, primarily targeted at infrastructure development, are necessary, however, if a greater degree of real convergence is to be achieved. Furthermore, the impact of transfers on public deficits, the current account, and real exchange rates might adversely affect the long run requirements of nominal convergence and might exacerbate the need for budgetary restraint in Portugal. Accordingly, a relaxation of domestic matching fund requirements might be desirable.     

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.     

Lot sizing and scheduling: a survey of practices in Brazilian companies

The lot sizing and scheduling (LSS) problem has motivated much research in production planning and control. However, while there are many papers on modelling this problem, there is scant research on how it is addressed in the industry. We present a survey of Brazilian industry practices in LSS, intending to understand the problem faced by operations managers, drawing parallels with academic findings to identify gaps between theory and practice and opportunities for future research. We confirm that the main objective of practitioners in companies operating under MTS strategy is to maximise service level, followed by inventory reduction. Availability of raw material, demand uncertainty and safety stock levels, lack of decision support software and the impact of sequence-dependent set-up times are other major concerns highlighted by the practitioners. Lastly, we confirmed that despite the relevant body of research on this problem, there is still a large gap between theory and practice.     

Ambiguity in the Small and in the Large

This paper considers local and global multiple‐prior representations of ambiguity for preferences that are (i) monotonic, (ii) Bernoullian, that is, admit an affine utility representation when restricted to constant acts, and (iii) locally Lipschitz continuous. We do not require either certainty independence or uncertainty aversion. We show that the set of priors identified by Ghirardato, Maccheroni, and Marinacci's (2004) “unambiguous preference” relation can be characterized as a union of Clarke differentials. We then introduce a behavioral notion of “locally better deviation” at an act and show that it characterizes the Clarke differential of the preference representation at that act. These results suggest that the priors identified by these preference statements are directly related to (local) optimizing behavior.     

Modeling of soybean yield using symmetric,asymmetric and bimodal distributions: implications for crop insurance

Over the years, many papers used parametric distributions to model crop yields, such as: normal (N), Beta, Log-normal and the Skew-normal (SN). These models are well-defined, mathematically and also computationally, but its do not incorporate bimodality. Therefore, it is necessary to study distributions which are more flexible in modeling, since most of crop yield data in Brazil presents evidence of asymmetry or bimodality. Thus, the aim of this study was to model and forecast soybean yields for municipalities in the State of Paran, in the period from 1980 to 2014, using the Odd log normal logistic (OLLN) distribution for the bimodal data and the Beta, SN and Skew-t distributions for the symmetrical and asymmetrical series. The OLLN model was the one which best fit the data. The results were discussed in the context of crop insurance pricing.     

Male pressure in the decision to remain childfree

To examine the negotiations and resolutions of disagreement over childlessness (the childfree lifestyle), questionnaires were sent to 100 married couples drawn randomly from membership lists of the National Organization for Non-Parents (NON). Responses of 40 couples were analyzed, in a synthesized theoretical framework drawn from Thibaut and Kelley (1959) and sex role socialization theory. The pattern that emerged was: if it was the husband's decision to remain childfree and not the wife's at first, she was likely to come into agreement with him; if it was the wife's decision to remain childfree, only very rarely would the husband consent. The more likely result, if she remained adamant, was divorce. Because marital power was so much greater for the husbands, the childfree life-style as an alterntive marital form may not differ greatly from traditional marital patterns. Author's Note: An earlier draft of this paper was presented at the annual meetings of the American Sociological Association, Chicago, September 1977. I am indebted to Dr. Roger Libby for his helpful comments, and to the anonymous reviewers for their suggestions.     

Bayesian factor models for multivariate categorical data obtained from questionnaires

Factor analysis is a flexible technique for assessment of multivariate dependence and codependence. Besides being an exploratory tool used to reduce the dimensionality of multivariate data, it allows estimation of common factors that often have an interesting theoretical interpretation in real problems. However, standard factor analysis is only applicable when the variables are scaled, which is often inappropriate, for example, in data obtained from questionnaires in the field of psychology, where the variables are often categorical. In this framework, we propose a factor model for the analysis of multivariate ordered and non-ordered polychotomous data. The inference procedure is done under the Bayesian approach via Markov chain Monte Carlo methods. Two Monte Carlo simulation studies are presented to investigate the performance of this approach in terms of estimation bias, precision and assessment of the number of factors. We also illustrate the proposed method to analyze participants'' responses to the Motivational State Questionnaire dataset, developed to study emotions in laboratory and field settings.     

The overload at work and outside of work: the case of woman operators of blistering

The internationalization of labor is a prominent feature of the economy today, but is accompanied by adverse effects on operator health. In general, musculoskeletal diseases are the first to appear in this context. The open observations activity and interviews with operators and the hierarchy have been made to discover the organizational constraints. Other interviews were also conducted to account for the determinants of activity outside of work. The use of video has allowed the registration of work cycles, which helped to describe and quantify the postures and gestures to establish a possible link between musculoskeletal diseases and work activity. The collected data were processed using software Actogram Kronos. To understand the process of origin of these diseases, the analysis of the socioeconomic context is also essential because they in part determine the organization of certain companies. The objective of this paper was to discuss the activities of operators of blistering in both work and outside work. The goal is to determine the constraints presents in these two spheres of activity, that may increase the risk of developing musculoskeletal diseases and to define their interaction.     

The exponentiated exponential–geometric distribution: a distribution with decreasing,increasing and unimodal failure rate

In this paper, we proposed a new family of distributions namely exponentiated exponential–geometric (E2G) distribution. The E2G distribution is a straightforwardly generalization of the exponential–geometric (EG) distribution proposed by Adamidis and Loukas [A lifetime distribution with decreasing failure rate, Statist. Probab. Lett. 39 (1998), pp. 35–42], which accommodates increasing, decreasing and unimodal hazard functions. It arises on a latent competing risk scenarios, where the lifetime associated with a particular risk is not observable but only the minimum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its survival and hazard functions, moments, rth moment of the ith order statistic, mean residual lifetime and modal value. Maximum-likelihood inference is implemented straightforwardly. From a mis-specification simulation study performed in order to assess the extent of the mis-specification errors when testing the EG distribution against the E2G, and we observed that it is usually possible to discriminate between both distributions even for moderate samples with presence of censoring. The practical importance of the new distribution was demonstrated in three applications where we compare the E2G distribution with several lifetime distributions.