This paper develops a decomposition algorithm by which a market economy with many households may be solved through the computation of equilibria for a sequence of representative agent economies. The paper examines local and global convergence properties of the sequential recalibration (SR)...

We analyse long-term consumption paths in a dynamic two-sector economy with overlapping generations. Each young generation saves for the retirement age, both with private savings and pension funds. The productivity of each sector can be raised by sector-specific research while the essential use...

This paper studies the e¤ects of distortionary taxes and public in- vestment in an endogenous growth OLG model with knowledge trans- mission. Fiscal policy a¤ects growth in two respects: .rst, work time reacts to variations of prospective tax rates and modi.es knowledge formation; second,...

We study the general equilibrium properties of two growth models with overlapping generations, habit formation and endogenous fertility. In the neoclassical model, habits modify the economy's growth rate and generate transitional dynamics in fertility; station- ary income per capita is...

This paper analyzes overlapping-generations models where natural capital is owned by selfish agents. Transfers in favor of young agents reduce the rate of depletion and increase output growth. It is shown that intergenerational transfers may be preferred to laissez-faire by an indefinite...

We analyze the consequences of habit formation for income levels and long-term growth in an overlapping generations model with dynastic altruism and resource dependence. If the strength of habits is below a critical level, the competitive economy displays an altruistic (Ramsey-like) equilibrium...

The prevailing literature discusses intergenerational trade-offs predominantly in infinitely-lived agent models despite the finite lifetime of individuals. We discuss these trade-offs in a continuous time OLG framework and relate the results to the infinitely-lived agent setting. We identify...