Do Marginal Employment Subsidies Increase Re-Employment Probabilities? Preliminary Results on the Experiment of the Agenzia del Lavoro of Trento (Italy)

ABSTRACT: The purpose of this paper is to test whether a Marginal Employment Subsidy program (MES) is effective in reducing the length of unemployment spells. Our test is constructed in such a way as to isolate the direct effect of the MES from the business cycle effect (i.e. the variation in unemployment that would have normally occurred in the absence of the program). Specifically, we estimate a Markov chain duration model with time-varying covariates and we test if eligibility for an MES increases the hazard rate of leaving unemployment. One of the time-varying covariates is an index of macro-economic performance that controls for the variation in the hazard rate due to business cycle fluctuations. The net effect of the MES offered by the Agenzia del Lavoro of Trento, Italy, is shown to be significantly positive: the Marginal Employment Subsidy program increases the re-employment probability and reduces the expected duration of unemployment by twenty one months.     

When money does not buy happiness: The case of “frustrated achievers”

An increase in real per capita income is generally expected to be associated with nonnegative variations in life satisfaction. The alternative (association with negative changes) is generally defined as “frustrated achievement” [Graham, C., Pettinato, S., 2002. Happiness and Hardship: Opportunity and Insecurity in New Market Economies. The Brookings Institution Press, Washington, D.C.].We investigate the determinants of “frustrated achievement” in the German socioeconomic panel on more than 30,000 individuals collected between 1992 and 2004. We observe a parallel reduction in self-declared life satisfaction corresponding to almost one-third of yearly increases in (equalised) real household income.Our econometric findings show that the lack of a full-time job, health deterioration, relative income effects, marital status shocks and poorer social life are the main factors associated with this phenomenon.     

Ergonomics, automation and logistics: practical and effective combination of working methods, a case study of a baking company

The aim of this study was to combine three different analytical methods from three different disciplines to diagnose the ergonomic conditions, manufacturing and supply chain operation of a baking company. The study explores a summary of comprehensive working methods that combines the ergonomics, automation and logistics study methods in the diagnosis of working conditions and productivity. The participatory approach of this type of study that involves the feelings and first-hand knowledge of workers of the operation are determining factors in defining points of action and ergonomic interventions, as well as defining opportunities in the automation of manufacturing and logistics, to cope with the needs of the company. The study identified an ergonomic situation (high prevalence of wrist-hand pain), and the combination of interdisciplinary techniques applied allowed to improve this condition in the company. This type of study allows a primary basis of the opportunities presented by the combination of specialized methods of different disciplines, for the definition of comprehensive action plans for the company. Additionally, it outlines opportunities for improvement and recommendations to mitigate the burden associated with occupational diseases and as an end result improve the quality of life and productivity of workers.     

Dynamic survival models with spatial frailty

In many survival studies, covariates effects are time-varying and there is presence of spatial effects. Dynamic models can be used to cope with the variations of the effects and spatial components are introduced to handle spatial variation. This paper proposes a methodology to simultaneously introduce these components into the model. A number of specifications for the spatial components are considered. Estimation is performed via a Bayesian approach through Markov chain Monte Carlo methods. Models are compared to assess relevance of their components. Analysis of a real data set is performed, showing the relevance of both time-varying covariate effects and spatial components. Extensions to the methodology are proposed along with concluding remarks.     

The use of geotechnologies for the identification of the urban flora in the city of Teresina,Brazil

Urban Ecosystems - Urban greenness is an element of vital importance for the population quality of life, and forest inventory is considered the most appropriate method for its assessment. Remote...     

POVERTY AND THE POLITICAL ECONOMY OF PUBLIC EDUCATION SPENDING: EVIDENCE FROM BRAZIL

A large body of literature has emphasized the elite capture of democratic institutions as the explanation for the low levels of spending on public education in many low‐income democracies. This paper provides an alternative to that longstanding hypothesis. Motivated by new cross‐country facts and evidence from Brazilian municipalities, we hypothesize that many democratic developing countries might invest less in public education spending because poor decisive voters prefer the government to allocate resources elsewhere. One possible explanation is that low‐income voters could instead favor redistributive programs that increase their incomes in the short run, such as cash transfers. To test for this possibility, we design and implement an experimental survey and an incentivized choice experiment in Brazil. The findings from both interventions support our hypothesis.     

Let's meet up! The role of relational goods in promoting cooperation

The present paper draws on data collected through a Traveler's Dilemma experiment where the possibility of consuming relational goods is introduced by allowing (or forcing) agents to meet after the experiment. It enriches the literature on social distance by comparing the effect of its reduction when it is a voluntary subject's choice and when it is compulsory.We show that the existing interpretations of the effect of social distance reduction cannot explain the differences in agents’ behavior across our experimental treatments. This allows us to give to the theory of social distance an original interpretation based on the concept of relational goods where the possibility to consume relational goods promotes non-selfish behavior.     

The random-effects proportional hazards model with grouped survival data: a comparison between the grouped continuous and continuation ratio versions

Summary.  When analysing grouped time survival data having a hierarchical structure it is often appropriate to assume a random-effects proportional hazards model for the latent continuous time and then to derive the corresponding grouped time model. There are two formally equivalent grouped time versions of the proportional hazards model obtained from different perspec-tives, known as the continuation ratio and the grouped continuous models. However, the two models require distinct estimation procedures and, more importantly, they differ substantially when extended to time-dependent covariates and/or non-proportional effects. The paper discusses these issues in the context of random-effects models, illustrating the main points with an application to a complex data set on job opportunities for a cohort of graduates.     

Predicting probabilities for the 2010 FIFA World Cup games using a Poisson-Gamma model

In this paper, we provide probabilistic predictions for soccer games of the 2010 FIFA World Cup modelling the number of goals scored in a game by each team. We use a Poisson distribution for the number of goals for each team in a game, where the scoring rate is considered unknown. We use a Gamma distribution for the scoring rate and the Gamma parameters are chosen using historical data and difference among teams defined by a strength factor for each team. The strength factor is a measure of discrimination among the national teams obtained from their memberships to fuzzy clusters. The clusters are obtained with the use of the Fuzzy C-means algorithm applied to a vector of variables, most of them available on the official FIFA website. Static and dynamic models were used to predict the World Cup outcomes and the performance of our predictions was evaluated using two comparison methods.