Innovation and Top Income Inequality
The Review of Economic Studies,
In this article, we use cross-state panel and cross-U.S. commuting-zone data to look at the relationship between innovation, top income inequality and social mobility. We find positive correlations between measures of innovation and top income inequality. We also show that the correlations between innovation and broad measures of inequality are not significant. Next, using instrumental variable analysis, we argue that these correlations at least partly reflect a causality from innovation to top income shares. Finally, we show that innovation, particularly by new entrants, is positively associated with social mobility, but less so in local areas with more intense lobbying activities.
College Choice Allocation Mechanisms: Structural Estimates and Counterfactuals
IZA Discussion Paper, Heft 8550,
We evaluate a simple allocation mechanism of students to majors at college entry that was commonly used in universities in Brazil in the 1990s and 2000s. Students first chose a single major and then took exams that select them in or out of the chosen major. The literature analyzing student placement, points out that this decentralized mechanism is not stable and is not strategy-proof. This means that some pairs of major & students can be made better off and that students tend to disguise their preferences using such a mechanism. We build up a model of performance and school choices in which expectations are carefully specified and we estimate it using cross-section data reporting choices between two medical schools and grade performances at the entry exams. Given those estimates, we evaluate changes in selection and students’ expected utilities when other mechanisms are implemented. Results highlight the importance of strategic motives and redistributive effects of changes of the allocation mechanisms.
What Do We Learn from Schumpeterian Growth Theory?
P. Aghion, S. N. Durlauf (eds.), Handbook of Economic Growth, Volume 2B, Amsterdam: North Holland,
Schumpeterian growth theory has operationalized Schumpeter’s notion of creative destruction by developing models based on this concept. These models shed light on several aspects of the growth process that could not be properly addressed by alternative theories. In this survey, we focus on four important aspects, namely: (i) the role of competition and market structure; (ii) firm dynamics; (iii) the relationship between growth and development with the notion of appropriate growth institutions; and (iv) the emergence and impact of long-term technological waves. In each case, Schumpeterian growth theory delivers predictions that distinguish it from other growth models and which can be tested using micro data.
R&D Offshoring and the Productivity Growth of European Regions
CIRCLE Working Papers, No. 20,
The recent increase in R&D offshoring have raised fears that knowledge and competitiveness in advanced countries may be at risk of 'hollowing out'. At the same time, economic research has stressed that this process is also likely to allow some reverse technology transfer and foster growth at home. This paper addresses this issue by investigating the extent to which R&D offshoring is associated with productivity dynamics of European regions. We find that offshoring regions have higher productivity growth, but this positive effect fades down with the number of investment projects carried out abroad. A large and positive correlation emerge between the extent of R&D offshoring and the home region productivity growth, supporting the idea that carrying out R&D abroad strengthen European competitiveness.
Technology Clubs, R&D and Growth Patterns: Evidence from EU Manufacturing
European Economic Review,
This paper investigates the forces driving output change in a panel of EU manufacturing industries. A flexible modeling strategy is adopted that accounts for: (i) inefficient use of resources and (ii) differences in the production technology across industries. With our model we are able to identify technical, efficiency, and input growth for endogenously determined technology clubs. Technology club membership is modeled as a function of R&D intensity. This framework allows us to explore the components of output growth in each club, technology spillovers and catch-up issues across industries and countries.