Abstract:
Macroeconomic modeling in the context of a stochastic continuous-time environment has become more popular in recent years. Most of these models are based on stochastic differential equations to describe macroeconomic dynamics and stochastic uncertainty is mostly modeled by Brownian motions or Poisson processes. However, these assumptions neglect the statistical evidence of long-range dependence in macroeconomic time series such as inflation rates, GDP, unemployment rates and interest rates. Based on Brunnermeier and Sannikov's contribution to the Handbook of Macroeconomics 2016, we present a small and quite simple model where the uncertainty is modeled by an approximated Liouville fractional Brownian motion. With this approach we are able to consider the effects of correlated shocks as well as the impact of long-range dependence in capital stock on the rate of interest and the distribution of wealth.