This paper applies linear and neural network-based “thick” models for forecasting inflation based on Phillips–curve formulations in the USA, Japan and the euro area. Thick models represent “trimmed mean” forecasts from several neural network models. They outperform the best performing...

This paper examines how membership of a monetary union affects macroeconomic adjustment of Euro Area countries to sudden stops.We focus on a key difference between a standard peg and a monetary union: the availability of external financing from the common centralbank via the TARGET system. For...

This paper applies linear and neural network-based “thick” models for forecasting inflation based on Phillips–curve formulations in the USA, Japan and the euro area. Thick models represent “trimmed mean” forecasts from several neural network models. They outperform the best performing...

This paper compares alternative methods for approximating and solving the stochastic growth model with parameterized expectations. We compare polynomial and neural netowork specifications for expectations, and we employ both genetic algorithm and gradient-descent methods for solving the...

This paper compares three approximation methods for solving and simulating real business cycle models: linear quadratic (including log- linear quadratic) methods, the method of parameterized expectations, and the genetic algorithm. Linear quadratic (LQ), log-linear quadratic (log- LQ) and...

This paper is a simulation analysis of the stochastic growth model with heterogeneous agents. The environment is one of two agents, with a common technology for production, individual labor endowment shocks, constant relative risk aversion utility functions, and limited borrowing/lending...