This paper provides robust estimates of the impact of both product and labor market regulations on unemployment using data from 24 European countries over the period 1998–2013. Controlling for country fixed effects, endogeneity, and a large set of covariates, results show that product market deregulation overall reduces the unemployment rate. This finding is robust across all specifications and in line with theoretical predictions. However, not all types of reforms have the same effect: deregulation of state controls and in particular involvement in business operations tend to push up the unemployment rate. Labor market deregulation, proxied by the employment protection legislation index, is detrimental to unemployment in the short run, while a positive impact (i.e., a reduction in the unemployment rate) occurs only in the long run. Analysis by sub-indicators shows that reducing protection against collective dismissals helps in reducing the unemployment rate. The unemployment rate equation is also estimated for different categories of workers. Although men and women are equally affected by product and labor market deregulations, workers distinguished by age and educational attainment are affected differently. In terms of employment protection, young workers are almost twice as strongly affected as older workers. Regarding product market deregulation, highly educated individuals are less impacted than low- and middle-educated workers.
Pablo de Pedraza, Stefano Visintin, Kea Tijdens and Gábor Kismihók
This paper studies the relationship between a vacancy population obtained from web crawling and vacancies in the economy inferred by a National Statistics Office (NSO) using a traditional method. We compare the time series properties of samples obtained between 2007 and 2014 by Statistics Netherlands and by a web scraping company. We find that the web and NSO vacancy data present similar time series properties, suggesting that both time series are generated by the same underlying phenomenon: the real number of new vacancies in the economy. We conclude that, in our case study, web-sourced data are able to capture aggregate economic activity in the labor market.
Economic research on labor migration in the developing world has traditionally focused on the role played by the remittances of overseas migrant labor in the sending country’s economy. Recently, due in no small part to the availability of rich microdata, more attention has been paid to the effects of migration on the lives of family members left behind. This paper examines how the temporary migration of parents for work affects the health outcomes of children left behind using the longitudinal data obtained from the Indonesia Family Life Survey. The anthropometric measure of the child health used, height-for-age, serves as a proxy for stunting. The evidence suggests that whether parental migration is beneficial or deleterious to the child health depends on which parent moved. In particular, migration of the mother has an adverse effect on the child’s height-for-age, reducing height-for-age Z-score by 0.5 standard deviations. This effect is not seen on the migration of the father.
This review article surveys the recent economic literature on diaspora networks, globalization, and development. Diasporas are shown to contribute to the economic and cultural integration of source (i.e., developing) countries into the global economy. I first review the effect of diaspora networks on core globalization outcomes such as trade, foreign investments, and the diffusion of knowledge and technology across borders. I then turn to the cultural and political sway of the diaspora, investigating the impact of emigration on the formation of political attitudes, fertility behavior, and other aspects of culture in the home country.
This study quantifies the economic effects of two major immigration policies aimed at legalizing undocumented individuals that entered the United States as children and completed high school: Deferred Action for Childhood Arrivals (DACA) and the DREAM Act. The former offers only temporary legal status to eligible individuals, whereas the latter provides a track to legal permanent residence. Our analysis is based on a general equilibrium model that allows for shifts in participation between work, college, and non-employment. The model is calibrated to account for productivity differences across workers of different skills and documentation status, and a rich pattern of complementarities across different types of workers. We estimate that DACA increased gross domestic product (GDP) by almost 0.02% (about $3.5 billion), or $7,454 per legalized worker. Passing the DREAM Act would increase GDP by around 0.08% (or $15.2 billion), which amounts to an average of $15,371 for each legalized worker. The larger effects of the DREAM Act stem from the expected larger take-up and the increased incentive to attend college among DREAMers with a high school degree. We also find substantial wage increases for individuals obtaining legal status, particularly those that increase their educational attainment. Because of the small size of the DREAMer population, and their skill distribution, legalization entails negligible effects on the wages of US-born workers.
The current wave of technological change based on advancements in artificial intelligence (AI) has created widespread fear of job loss and further rises in inequality. This paper discusses the rationale for these fears, highlighting the specific nature of AI and comparing previous waves of automation and robotization with the current advancements made possible by a widespread adoption of AI. It argues that large opportunities in terms of increases in productivity can ensue, including for developing countries, given the vastly reduced costs of capital that some applications have demonstrated and the potential for productivity increases, especially among the low skilled. At the same time, risks in the form of further increases in inequality need to be addressed if the benefits from AI-based technological progress are to be broadly shared. For this, skills policies are necessary but not sufficient. In addition, new forms of regulating the digital economy are called for that prevent further rises in market concentration, ensure proper data protection and privacy, and help share the benefits of productivity growth through the combination of profit sharing, (digital) capital taxation, and a reduction in working time. The paper calls for a moderately optimistic outlook on the opportunities and risks from AI, provided that policymakers and social partners take the particular characteristics of these new technologies into account.
The disruption of family life is one of the important legacies of South Africa’s colonial and apartheid history. Families were undermined by deliberate strategies implemented through the pass laws, forced removals, urban housing policy, and the creation of homelands. Despite the removal of legal restrictions on permanent urban settlement and family co-residence for Africans, patterns of internal and oscillating labor migration have endured, dual or stretched households continue to link urban and rural nodes, children have remained less urbanized than adults, and many grow up without coresident parents. Although children are clearly affected by adult labor migration, they have tended to be ignored in the migration discourse. In this study, we add to the literature by showing how a child lens advances our understanding of the complexities of household arrangements and migration processes for families. In a mixed-methods study, we use nationally representative panel data to describe persistence, and also change, in migration patterns in South Africa when viewed from the perspective of children. We then draw on a detailed case study to explore what factors constrain or permit families to migrate together, or children to join adults at migration destination areas.
Effrosyni Adamopoulou, Emmanuele Bobbio, Marta De Philippis and Federico Giorgi
Aggregate wages display little cyclicality compared to what a standard model would predict. Wage rigidities are an obvious candidate, but the existing literature has emphasized the need to take into account the growing importance of worker composition effects, especially during downturns. This paper seeks to understand the role of firm heterogeneity for aggregate wage dynamics with reference to the Italian case. Using a newly available dataset based on social security records covering the universe of Italian employers between 1990 and 2015, we document that firm composition effects increasingly matter in explaining aggregate wage growth and largely reflect shifts of labor from low-paying to high-paying firms, especially in the most recent years. We find that changes in reallocation of workers across firms accounted for approximately one-fourth of aggregate wage growth during the crisis.
This study investigates the incidence of overeducation among graduate workers in 21 European Union countries and its underlying factors based on the European Labor Force Survey 2016. Although controlling for a wide range of covariates, the particular interest lies in the role of fields of study for vertical educational mismatch. The study reveals country differences in the impact of these factors. Compared to Social sciences, male graduates from, for example, Education, Health and welfare, Engineering, and ICT (Information and Communication Technologies) are less and those from Services and Natural sciences are more at risk in a clear majority of countries. These findings are robust against changes of the standard education. Moreover, some fields show gender-specific risks. We suggest that occupational closure, productivity signals and gender stereotypes answer for these cross-field and cross-country differentials. Moreover, country fixed effects point to relevant structural differences between national labor markets and between educational systems.