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We briefly survey the literature which uses data for Gini coefficients of education. We update the Gini coefficients of education to include the year 2015, added to the Barro-Lee data set recently, and compare them to those of the earlier data set based on older Barro-Lee data. A panel analysis shows that every five years education inequality falls by 2.8 percentage points. A stable average value is predicted to be 0.22. Kernel density world distributions for education Ginis loose their twin peaks when going from 1955 to later years, and the right tail of the distribution with high inequality is losing mass over time.

We update the Gini coefficients of education to include the year 2015, added to the Barro-Lee data set recently. A panel analysis shows that every five years education inequality falls by 2.8 percentage points. A stable average value is predicted to be 0.22. Kernel densities loose their twin peaks when going from 1955 to later years.

We update the Gini coefficients of education to include the year 2015, added to the Barro-Lee data set recently. A panel analysis shows that every five years education inequality falls by 2.8 percentage points. A stable average value is predicted to be 0.22. Kernel densities loose their twin peaks when going from 1955 to later years.

We update the Gini coefficients of education to include the year 2015, added to the Barro-Lee data set recently. A panel analysis shows that every five years education inequality falls by 2.8 percentage points. A stable average value is predicted to be 0.22. Kernel densities loose their twin peaks when going from 1955 to later years.

Workers that become automated may transfer productivity gains to their co-workers or make it easier to automate their jobs too. In this paper, I empirically investigate how automatable jobs have diffused impacts to neighbouring jobs in North American cities between 2007 and 2016. Results indicate that jobs that share similarities with neighbouring high-risk jobs grew less, even when controlling for their own technical risk of automation. Conversely, jobs that share complementarities with neighbouring high-risk jobs grew faster, possibly indicating productivity gains from working with recently automated jobs. In addition to the analysis in this paper, I provide an adjusted index of job automation risk that accounts for local diffusion of impacts (negative and positive) in US cities.

Workers that become automated may transfer productivity gains to their co-workers or make it easier to automate their jobs too. In this paper, I empirically investigate how automatable jobs have diffused impacts to neighbouring jobs in North American cities between 2007 and 2016. Results indicate that jobs that share similarities with neighbouring high-risk jobs grew less, even when controlling for their own technical risk of automation. Conversely, jobs that share complementarities with neighbouring high-risk jobs grew faster, possibly indicating productivity gains from working with recently automated jobs. In addition to the analysis in this paper, I provide an adjusted index of job automation risk that accounts for local diffusion of impacts (negative and positive) in US cities.

Workers that become automated may transfer productivity gains to their co-workers or make it easier to automate their jobs too. In this paper, I empirically investigate how automatable jobs have diffused impacts to neighbouring jobs in North American cities between 2007 and 2016. Results indicate that jobs that share similarities with neighbouring high-risk jobs grew less, even when controlling for their own technical risk of automation. Conversely, jobs that share complementarities with neighbouring high-risk jobs grew faster, possibly indicating productivity gains from working with recently automated jobs. In addition to the analysis in this paper, I provide an adjusted index of job automation risk that accounts for local diffusion of impacts (negative and positive) in US cities.

This article empirically investigates the effect of structural transformation on wage inequality in Asia, using industry-level data for three skill groups of workers. While structural transformation, associated with technological progress, productivity catching-up, and capital deepening, has contributed to Asias sustained growth, its effect on income inequality remains uncertain. Our results show that the process of economic transformation has exacerbated inequality in the region by increasing the relative share of high-skilled workers in total compensation. This is mainly due to a shift toward more productiveand more intensive in the use of skilled laboractivities both within and between industries. However, we also find that policy responses, especially investments in education, mitigate the increase in inequality.

Using a unique firm-level database comprising the top European R&D investors over the period 2002-2013 and running LSDVC estimates, this study finds a significant labour-friendly impact of R&D expenditures. However, this positive employment effect appears limited in magnitude and entirely due to the medium-and high-tech sectors, while no effect can be detected in the low-tech industries. From a policy point of view, this outcome is supporting the EU2020 strategy, but - taking into account that most European economies are specialised in low-tech activities - is also worrying in terms of future perspectives of the European labour market.

Using a unique firm-level database comprising the top European R&D investors over the period 2002-2013 and running LSDVC estimates, this study finds a significant labour-friendly impact of R&D expenditures. However, this positive employment effect appears limited in magnitude and entirely due to the medium-and high-tech sectors, while no effect can be detected in the low-tech industries. From a policy point of view, this outcome is supporting the EU2020 strategy, but - taking into account that most European economies are specialised in low-tech activities - is also worrying in terms of future perspectives of the European labour market.

Using a unique firm-level database comprising the top European R&D investors over the period 2002-2013 and running LSDVC estimates, this study finds a significant labour-friendly impact of R&D expenditures. However, this positive employment effect appears limited in magnitude and entirely due to the medium-and high-tech sectors, while no effect can be detected in the low-tech industries. From a policy point of view, this outcome is supporting the EU2020 strategy, but - taking into account that most European economies are specialised in low-tech activities - is also worrying in terms of future perspectives of the European labour market.

Mankiw et al. (1992) have extended the Solow (1956) model by augmenting the production function with human capital. Its empirical success is impressive and it showed a procedure to improve the explanatory power of the neoclassical growth model. This article suggests an empirical procedure to further extend the neoclassical growth model to distinguish between the growth and level effects of shift variables like the human capital. We use time-series data from Guatemala to show that while the growth effects of education are small, they are significant and dominate the level effects.

article i nfo Article history: Informal self-employment is a major source of employment in developing countries. Its cyclical behavior is important to our understanding of the functioning of LDC labor markets, but turns out to be surprisingly complex. We develop a flexible model with two sectors: a formal salaried (tradable) sector that may be affected by wage rigidities, and an informal (non tradable) self-employment sector faced with liquidity constraints to entry. This labor market is then embedded in a standard small economy macro model. We show that different types of shocks interact with different institutional contexts to produce distinct patterns of comovement between key variables of the model: relative salaried/self-employed incomes, relative salaried/self-employed sector sizes and the real exchange rate. Model predictions are then tested empirically for Argentina, Brazil, Colombia and Mexico. We confirm episodes where the expansion of informal self- employment is consistent with the traditional segmentation views of informality. However, we also identify episodes where informal self-employment behaves "pro-cyclically"; here, informality is driven by relative demand or productivity shocks to the non tradable sector.

This paper studies the causes and consequences of informality and applies the analysis to Arab countries. It starts with a review of employment, labor informality and other labor market outcomes in the Arab world; and a discussion on the definition and measures of informality, as well as on the reasons why widespread informality should be of great concern. The paper also analyzes informality's main determinants, arguing that informality is not single-caused but results from the combination of poor public services, a burdensome regulatory regime, and weak monitoring and enforcement capacity by the state. This combination is especially explosive when the country suffers from low educational achievement and features demographic pressures and primary production structures. Finally, using cross-country regression analysis, the paper evaluates the empirical relevance of each determinant of informality. It then applies the estimated relationships to several Arab countries to assess the country-specific relevance of each proposed mechanism. Results suggest that informality has had negative marginal effects for Micro and Small Enterprises' (MSEs') performance in the Arab world. Moreover, informal establishments might have difficulty penetrating regional or international markets; instead, they are likely to specialize in producing for local markets.