This paper contributes a multivariate forecasting comparison between structural models and Machine-Learning-based tools. Specifically, a fully connected feed forward nonlinear autoregressive neural network (ANN) is contrasted to a well established dynamic stochastic general equilibrium (DSGE)...

This paper contributes a multivariate forecasting comparison between structural models and Machine-Learning-based tools. Specifically, a fully connected feed forward nonlinear autoregressive neural network (ANN) is contrasted to a well established dynamic stochastic general equilibrium (DSGE)...

This article aims to deepen the knowledge on consumer choices from the microeco-nomic perspective so as to better understand the behaviour of home buyers and its impact on the housing market. First, we provide an analysis of housing understood as a consumer and investment good. We then discuss...

The global economic development model has proved to be insufficiently reliable under the new economic crisis. As a result, the entire theoretical construction about the global economy needs rethinking and reorientation. In this context, it is quite clear that only through effective use of...

We generalize the classic Grossman and Laroque (1990) (GL) model of optimal portfolio choice with housing and transaction costs by introducing predictability in house prices. As in the GL model, agents only move to more expensive (cheaper) houses when their wealth-to-housing ratios reach an...

We generalize the classic Grossman and Laroque (1990) (GL) model of optimal portfolio choice with housing and transaction costs by introducing predictability in house prices. As in the GL model, agents only move to more expensive (cheaper) houses when their wealth-to-housing ratios reach an...