(Endogenous) occupational choices and job satisfaction among recent PhD recipients: evidence from Catalonia

Drawing on data from two successive cohorts of PhD graduates, this paper analyses differences in overall job satisfaction and specific job domain satisfaction among PhDs employed in different sectors four years after completing their doctorate degrees. Covariate-adjusted job satisfaction differentials suggest that, compared to faculty members, PhD holders employed outside traditional academic and research jobs are more satisfied with the pecuniary facets of their work (principally, because of higher earnings), but significantly less satisfied with the content of their job and with how well the job matches their skills (and, in the case of public sector workers, with their prospects of promotion). The evidence regarding the overall job satisfaction of the PhD holders indicates that working in the public or private sectors is associated with less work well-being, which cannot be fully compensated by the better pecuniary facets of the job. It also appears that being employed in academia or in research centres provides almost the same perceived degree of satisfaction with the job and with its four specific domains. We also take into account the endogenous sorting of PhD holders into different occupations based on latent personal traits that might be related to job satisfaction. The selectivity-corrected job satisfaction differentials reveal the importance of self-selection based on unobservable traits, and confirm the existence of a certain penalisation for working in occupations other than academia or research, which is especially marked in the case of satisfaction with job content and job-skills match. The paper presents additional interesting evidence about the determinants of occupational choice among PhD holders, highlighting the relevance of certain academic attributes (especially PhD funding and pre-and-post-doc research mobility) in affecting the likelihood of being employed in academia, in a research centre or in other public or private sector job four years after completing their doctorate programme.

Economic crisis and recovery: changes in second birth rates within occupational classes and educational groups

This study assesses the decline in second birth rates for men and women across different skill levels in transitional Russia. Changes within educational groups and occupational classes are observed over three distinct time periods: the Soviet era, economic crisis, and economic recovery. The most remarkable finding is the similarity in the extent second birth rates declined within educational groups and occupational classes during the economic crisis. Although further decline occurred in the recovery period, more variation emerged across groups.

Occupational choice and development

The rise in world trade since 1970 has been accompanied by a rise in the geographic span of control of management and, hence, also a rise in the e ective international mobility of labor services. We study the e ect of such a globalization of the world's labor markets. The world's welfare gains depend positively on the skill-heterogeneity of the world's labor force. We nd that when peoplecan choose between wage work and managerial work, the worldwide labor market raises output by more in the rich and the poor countries, and by less in the middle-income countries. This is because the middle-income countries experience the smallest change in the factor-price ratio, and where the option to choose between wage work and managerial work has the least value in the integratedeconomy. Our theory also establishes that after economic integration, the high skill countries see a disproportionate increase in managerial occupations. Using aggregate data on GDP, openness and occupations from 115 countries, we find evidence for these patterns of occupational choice.

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.