Returns to education and experience in self-employment: Evidence from Germany

This paper compares the returns to human capital in the self-employed and wage-employed sectors of the economy. Using data from the former West German sample of the German Socioeconomic Panel survey for the 1984-1997 time period, we estimate returns to education and work experience from standard log-earnings equations for self-employed and wage-employed workers. Two key results are found. First, additional schooling has a smaller effect on earnings for the self-employed than for the wage-employed. Indeed, educational attainment has an insignificant effect on self-employment earnings. Second, prior self-employment experience receives a lower return in wage-employment than does prior wage-employment experience. These results are consistent across specifications controlling for education endogeneity and self-selection bias.

The Economic Returns to Multiple Language Usage in Western Europe

To what extent are there economic returns to learning a second or third language? Do the benefits differ according to country? This paper examines the return to multi-lingualism in the workplace. In particular, we estimate the effect that using an additional language in one’s job has on earnings for a sample of workers in the European Community Household Panel survey. Log-earnings regressions are estimated by country with controls for standard human capital, job, and personal characteristics. Preliminary results indicate that the use of a second language in the workplace raises earnings by about 5 to 10 percent, but the results are sensitive to the specification used and vary across countries, occupations, and gender.

A dynamic analysis of recent changes in the rate of part-time employment

The part-time employment rate has declined since the early 1980s, especially among females. This paper examines the decline over the 1980-1990 period, with a focus on the gender differential, using gross change data from the Bureau of Labor Statistics. Monthly transition rates between full-time employment, part-time employment, unemployment, and nonparticipation are estimated according to sex. Trend and cyclical analysis of the transition rates is conducted to identify the sources of part-time employment-rate trends and to explore gender differentials in them. The results suggest that the decline in the rate of part-time employment among females is not so much because unemployed females are more likely to move into full-time employment, but rather because females have become more likely to move from part-time to full-time employment and, most important, because they have become less likely to leave full-time employment once they get there.Labor supply ; Employment (Economic theory)

Gender Discrimination and Self-Employment Dynamics in Europe

This paper examines the effect that gender-based earnings discrimination has on self-employment dynamics among females, with a focus on four countries in Western Europe. Using data from the European Community Household Panel in the 1999-2001 time period, we test the hypothesis that the probability of moving into self-employment is positively related to prior earnings discrimination, as measured by unexplained deviations from expected (male) earnings. Our findings suggest that women who have lower than expected wage sector earnings relative to other women are more likely to leave wage employment in the following year. The results with respect to discrimination, however, are mixed.

White-and-blue-collar jobs in the recent recession and recovery: who's singing the blues?

An investigation of the 1990-91 recession's impact on blue- versus white-collar workers, showing that although blue-collar workers bore the brunt of the downturn, white-collar employment growth was unusually slow by historical standards.Employment (Economic theory) ; Recessions

A signal-to-noise ratio analysis of an autoradiographic image enhancement process

A signal-to-noise ratio(SNR) analysis of a S-35 thiourea autoradiographic image enhancement process incorporating subproportional bleaches is performed, with emphasis on diagnostic medical Imagery. Quantifying SNR through a spatial frequency definition of DQE and NEQ, these metrics were compared between donor and receiver-composite stages. While improvements in radiometric speed and gamma were noted in the receiver-composite, these gains were more than offset in a SNR sense by correspondingly lower MTF and higher Wiener spectrum values. As a result the donor\u27s DQF_max of .30 exceeded that of the receiver-composite\u27s DQE_max by 50%. Similarly, ImCXA the donor\u27s NEQ_max exceeded that of the receiver composite\u27s by 350%. The donor\u27s DQE and NEQ continued to exceed that of the receiver-composite even on an equi -exposure basis

On Nonregularized Estimation of Psychological Networks.

An important goal for psychological science is developing methods to characterize relationships between variables. Customary approaches use structural equation models to connect latent factors to a number of observed measurements, or test causal hypotheses between observed variables. More recently, regularized partial correlation networks have been proposed as an alternative approach for characterizing relationships among variables through off-diagonal elements in the precision matrix. While the graphical Lasso (glasso) has emerged as the default network estimation method, it was optimized in fields outside of psychology with very different needs, such as high dimensional data where the number of variables (p) exceeds the number of observations (n). In this article, we describe the glasso method in the context of the fields where it was developed, and then we demonstrate that the advantages of regularization diminish in settings where psychological networks are often fitted ( p≪n ). We first show that improved properties of the precision matrix, such as eigenvalue estimation, and predictive accuracy with cross-validation are not always appreciable. We then introduce nonregularized methods based on multiple regression and a nonparametric bootstrap strategy, after which we characterize performance with extensive simulations. Our results demonstrate that the nonregularized methods can be used to reduce the false-positive rate, compared to glasso, and they appear to provide consistent performance across sparsity levels, sample composition (p/n), and partial correlation size. We end by reviewing recent findings in the statistics literature that suggest alternative methods often have superior performance than glasso, as well as suggesting areas for future research in psychology. The nonregularized methods have been implemented in the R package GGMnonreg

Marketing and Survival Strategies of Gulf Seaports: A Preliminary Analysis

E. Cameron Williams is an Associate Professor of Marketing, Department of Marketing at Georgia Southern University and Donald R. Gibson is an Assistant Professor of Managment and Marketing at Texas A & I Universit