An analysis of quit and dismissal determinants between 1988 and 1999 using the bivariate probit model

Excessive labor turnover may be considered, to a great extent, an undesirable feature of a given economy. This follows from considerations such as underinvestment in human capital by firms. Understanding the determinants and the evolution of turnover in a particular labor market is therefore of paramount importance, including policy considerations. The present paper proposes an econometric analysis of turnover in the Brazilian labor market, based on a partial observability bivariate probit model. This model considers the interdependence of decisions taken by workers and firms, helping to elucidate the causes that lead each of them to end an employment relationship. The Employment and Unemployment Survey (PED) conducted by the State System of Data Analysis (SEADE) and by the Inter-Union Department of Statistics and Socioeconomic Studies (DIEESE) provides data at the individual worker level, allowing for the estimation of the joint probabilities of decisions to quit or stay on the job on the worker’s side, and to maintain or fire the employee on the firm’s side, during a given time period. The estimated parameters relate these estimated probabilities to the characteristics of workers, job contracts, and to the potential macroeconomic determinants in different time periods. The results confirm the theoretical prediction that the probability of termination of an employment relationship tends to be smaller as the worker acquires specific skills. The results also show that the establishment of a formal employment relationship reduces the probability of a quit decision by the worker, and also the firm’s firing decision in non-industrial sectors. With regard to the evolution of quit probability over time, the results show that an increase in the unemployment rate inhibits quitting, although this tends to wane as the unemployment rate rises.

Dinamicity and unpredictability of emerging markets: an implementation of Goetzamnn and Jorion (1999)

This research is to be considered as an implementation of Goetzmann and Jorion (1999). In order to provide a more realistic scenario, we have implemented a Garch (1,1) approach for the residuals of returns and a multifactor model thus to better replicate the systematic risk of a market. The new simulations reveal some new aspects of emerging markets’ expected returns: the unpredictability of the emerging markets’ returns with the global factor does not depend on the year of emergence and that the unsystematic risk explains the returns of emerging markets for a much larger period of time. The results also reveal the high impact of Exchange rate, Commodities index and of the Global factor in emerging markets’ expected return.

The influence of lifestyle and gender on sickness absence in brazilian workers

Background: Despite an increasing body of knowledge concerning gender and lifestyle factors as determinants of sickness absence in well-developed countries, the relationship between these variables has not been elucidated in emerging economic power countries, where the burden of non-communicable diseases is particularly high. This study aimed to analyze the relationships among lifestyle-related factors and sick leave and to examine whether gender differences in sickness absence can be explained by differences in socio-demographic, work and lifestyle-related factors among Brazilian workers. Methods: In this longitudinal study with a one year follow-up among 2.150 employees of a Brazilian airline company, sick leave was the primary outcome of interest. Independent variables collected by interview at enrolment in the study were gender, age, educational level, type of work, stress, and lifestyle-related factors (body mass index, physical activity and smoking). In addition, the risk for coronary heart disease was determined based on measurement of blood pressure, total cholesterol and glucose levels. The total number of days on sick leave during 12 months follow-up was available from the company register. Logistic regression analysis was used to determine the influence of socio-demographic, type of work and lifestyle-related factors on sick leave. Results: Younger employees, those with lower educational level, those who worked as air crew members and those with higher levels of stress were more likely to have sick leave. Body mass index and level of physical activity were not associated with sick leave. After adjustment by socio-demographic variables, increased odds for 10 or more days of sick leave were found in smokers (OR = 1.51, CI = 1.05-2.17), and ex-smokers (OR = 1.45, CI = 1.01-2.10). Women were more likely to have 10 or more days of sick leave. Gender differences were reduced mainly when adjusted for type of work (15%) and educational level (7%). Conclusions: The higher occurrence of sick leave among women than among men was partly explained by type of work and educational level. Our results suggest that type of work, a stressful life, and smoking are important targets for health promotion in this study population