Macroeconomic Determinants of Equilibrium Unemployment Insurance

This paper proposes a new modeling strategy as regards the definition of an optimal level of unemployment benefits. While the traditional methodology privileges labor market equilibrium to derive optimal employment, wage and unemployment benefit levels, we present a model in which the optimal level of unemployment benefits is a function of the government’s macroeconomic objectives in terms of inflation and output fluctuations. In a second stage, the model allows for the investigation of unemployment insurance effects on labor market equilibrium.     

Comparison of Bayesian models for production efficiency

In this paper, we use Markov Chain Monte Carlo (MCMC) methods in order to estimate and compare stochastic production frontier models from a Bayesian perspective. We consider a number of competing models in terms of different production functions and the distribution of the asymmetric error term. All MCMC simulations are done using the package JAGS (Just Another Gibbs Sampler), a clone of the classic BUGS package which works closely with the R package where all the statistical computations and graphics are done.     

Development and Validation of a Self-Reported Measure of Job Performance

Social Indicators Research - The current turbulent context in which we live in requires, more and more, that organisations focus on improving the workers’ performance. Individual performance...     

On the trail of line managers as talent spotters

The deliberate identification of talent is a critical process in most organizations. Performance ratings and senior management recommendations are its main sources, revealing the importance of line managers in the process. Nevertheless, some managers do have a talent for talent spotting and little is known about their behaviours as effective talent spotters. We explore, through social cognition, as part of the social psychology framework, the practices required to execute the talent identification process (TIP). An exploratory and qualitative method was adopted for this study; 21 line managers of an Argentine holding describe their experiences as talent spotters through semi-structured interviews. Findings show that the identification process is a complex and iterative one, in which several behaviours come into play, interrelated among each other. This interaction involves talent identification and talent development behaviours, deployed in a synergetic way. The relationship building behaviours set the foundations for the identification process to bear fruit. Distinct skills are necessary at different stages of the identification process for line managers to fulfil the talent spotter role. Finally, a model of the TIP is proposed.     

Defective models induced by gamma frailty term for survival data with cured fraction

In this paper, we propose a defective model induced by a frailty term for modeling the proportion of cured. Unlike most of the cure rate models, defective models have advantage of modeling the cure rate without adding any extra parameter in model. The introduction of an unobserved heterogeneity among individuals has bring advantages for the estimated model. The influence of unobserved covariates is incorporated using a proportional hazard model. The frailty term assumed to follow a gamma distribution is introduced on the hazard rate to control the unobservable heterogeneity of the patients. We assume that the baseline distribution follows a Gompertz and inverse Gaussian defective distributions. Thus we propose and discuss two defective distributions: the defective gamma-Gompertz and gamma-inverse Gaussian regression models. Simulation studies are performed to verify the asymptotic properties of the maximum likelihood estimator. Lastly, in order to illustrate the proposed model, we present three applications in real data sets, in which one of them we are using for the first time, related to a study about breast cancer in the A.C.Camargo Cancer Center, São Paulo, Brazil.     

Discrete and continuous bivariate lifetime models in presence of cure rate: a comparative study under Bayesian approach

The modeling and analysis of lifetime data in which the main endpoints are the times when an event of interest occurs is of great interest in medical studies. In these studies, it is common that two or more lifetimes associated with the same unit such as the times to deterioration levels or the times to reaction to a treatment in pairs of organs like lungs, kidneys, eyes or ears. In medical applications, it is also possible that a cure rate is present and needed to be modeled with lifetime data with long-term survivors. This paper presented a comparative study under a Bayesian approach among some existing continuous and discrete bivariate distributions such as the bivariate exponential distributions and the bivariate geometric distributions in presence of cure rate, censored data and covariates. In presence of lifetimes related to cured patients, it is assumed standard mixture cure rate models in the data analysis. The posterior summaries of interest are obtained using Markov Chain Monte Carlo methods. To illustrate the proposed methodology two real medical data sets are considered.     

Aiming to keep poor Mexican families at the breadline (but no higher): The effects of minimum wage,tax, and social policy changes between 1994 and 2012

Welfare policy in Mexico has been transformed in recent decades. During the years of the import‐substitution industrialization economic strategy and the hegemonic party political regime, social policy was based on social insurance programs of limited coverage to urban formal sector workers and their families. In the mid‐1990s, an unprecedented expansion of social protection through social assistance programs was triggered, along with social insurance reform. This article assesses the effects at the household level of social policy changes, in combination with changes in taxes and the minimum wage, which also impact the welfare of the population. The research applies “model families” to establish effects of social, tax, and minimum wage policy changes across population groups, and their combined potential to combat poverty. Findings show that although taxation and social policy changes increased redistribution towards poor families, their capacity to lift and keep them above poverty thresholds was limited by the drop in the real value of the minimum wage and by strict targeting mechanisms, which exclude families that do not meet eligibility criteria but still fall below poverty lines. Social policy expansion merely subsidized the drop in real minimum wage, and poor families at best remained at similar income levels. Hence, the logic of the design of welfare policy changes can be characterized as aiming to keep poor families on the breadline, but no higher.     

Location estimators based on linear combinations of modified order statistics

Let Xj,…, X be i.i.d random variables with common distribution function F(x-0), and let a(u) be a function defined on [0,1], For each t$$$R define the t-order statistics as: X. (t) = X. if there in k exist exactly (i- 1) X. !s such that |X.-t|greater|X.-t| and define the variable T (t) = n 2. , a(i/n) X, (t) . We consider estimates of 8 defined as solutions of the eauaticn T (8) =6 , and     

Semiparametric Modeling of the Spatial Distribution of Occupational Accident Risk in the Casual Labor Market, Piracicaba, Southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.     

Population, Nomadic Pastoralism and the Environment in the Mongolian Plateau

The purpose of this paper is to examine the relationship between population, economic activity and the environment in the Mongolian Plateau. This analysis provides a valuable case study for several reasons. First, it elucidates a specific ecosystem—the steppe—that has not received much attention in the literature and a traditional economic activity consistent with such environment: nomadic pastoralism. Second, the Mongolian Plateau is shared by two entities, with two different economic and social organisation: the Republic of Mongolia and the Inner Mongolia Autonomous Region of the People's Republic of China. Third, these two entities have also experienced two different population dynamics that have resulted in different population densities and population pressure on natural resources. Fourth, environmental degradation does not seem to be a problem in the Republic of Mongolia, while in Inner Mongolia the quantity and quality of the grasslands are in decline.The argument discussed here is that the difference in resource depletion and environmental degradation between the two regions is mainly the result of different population dynamics, which has resulted in different human and animal population densities.