Public funding of Higher Education: who gains, who loses?

This paper analyses the efects of public funding of higher education on the welfare of the diferent agents. It takes into account the hierarchical nature of the educational system and also the fact that parents always have the possibility to complement basic public education with private expenditures in individual tutoring. It is obtained that although public funding implies a larger access to higher education it is always the case that some of the agents that gain access lose in welfare terms. Moreover, it is shown that the marginal agent to access university would always prefer a pure private funding system. Thus, when studying the e¤ects of public funding of higher education, we can not identify gaining access to University with an increase in welfare. Finally, I consider a funding system where only those that send their o¤spring to university support the funding of higher education.higher education, public fundinghigher education, public funding. JEL codes: I22, I28

(Relative Price) Lessons from Taking an AK Model to the Data

Endogenous Growth, Technology Shocks, Investment Shocks.

Innovation and Environmental Policy: Clean vs. Dirty Technical Change

We study a two sector endogenous growth model with environmental quality with two goods and two factors of production, one clean and one dirty. Technological change creates clean or dirty innovations. We compare the laissez-faire equilibrium and the social optimum and study first- and second-best policies. Optimal policy encourages research toward clean technologies. In a second-best world, we claim that a portfolio that includes a tax on the polluting good combined with optimal innovation subsidy policies is less costly than increasing the price of the polluting good alone. Moreover, a discriminating innovation subsidy policy is preferable to a non-discriminating one. JEL codes: H23, O3, O41Pollution, Endogenous Growth, Innovation, Environmental Policy, Laissez-Faire Equilibrium, Optimal Equilibrium, Discriminating vs. Non-Discriminating Subsidies to R&D

More Lessons from Taking an AK Model to the Data

We take an AK model to the PWT data. In the model both technology (intratemporal) and investment (intertemporal) shocks determine the variation of the growth rate. In earlier work we looked at singular models where we extracted only the technology shock using the policy functions from dynamic optimality. Here we recover time series for both shocks for a panel of countries and we isolate what we believe are pervasive patterns in macroeconomic models and postwar data: a negative correlation between intra and intertemporal shocks, and a somewhat lesser role for the intertemporal shock