Building on the models of sticky information, we endogenize the probability of obtaining new information by introducing a switching mechanism allowing agents to choose between costly rational expectations and costless expectations under sticky information. Thereby, the share of agents with...

The DSGE model with endogenous and time-varying sticky information in Dräger (2010) is extended by allowing agents' recursive choice between forecasts under rational or sticky information to affect the model solution. Dynamic equilibrium paths generate highly persistent series for output,...

This paper assesses the probability method for quantifying EU consumer survey data on perceived and expected inflation. Based on household level data from the Swedish consumer survey that asks for both qualitative and quantitative responses, it is found that the theoretical assumptions of the...

We review and evaluate methods previously adopted in the applied literature of adaptive learning in order to initialize agents' beliefs. Previous methods are classified into three broad classes: equilibrium-related, training sample-based, and estimation-based. We conduct several simulations...

Adaptive learning under constant-gain allows persistent deviations of beliefs from equilibrium so as to more realistically reflect agents' attempt of tracking the continuous evolution of the economy. A characterization of these beliefs is therefore paramount to a proper understanding of the role...

Uncertainty shapes the trajectory of business cycles and remains a central research topic in Macroeconomics. When studying the impact of uncertainty on the economy, economists use different uncertainty measures. While all indicators approximate uncertainty along some certain dimension, none of...

In this paper, we evaluate the forecasting ability of 145 indicators and ten types of forecast combination schemes to predict housing prices and rents in 71 German cities. We are interested in whether local business confidence indicators facilitate substantial improvements of the forecasts,...

In this paper we extend the targeted-regressor approach suggested in Bai and Ng (2008) for variables sampled at the same frequency to mixed-frequency data. Our MIDASSO approach is a combination of the unrestricted MIxed-frequency DAta-Sampling approach (U-MIDAS) (see Foroni et al., 2015; Castle et...

We apply the novel approach of Siliverstovs (2015) to modelling data sampled at different frequencies in order to scrutinise the composition of one of the most influential economic indicators in Switzerland. The Purchasing Managers' Index consists of eight sub-indices out of which only five...

This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon lag polynomial scheme which is designed to reduce...