This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

We construct Bayesian vector autoregressive (BVAR) models optimized by the Posterior Information Criterion (PIC), in which hyper-parameters are data-determined in the same way as the lag length and trend order. We also assess the performance of the selected models by one-step ahead forecasts...

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

We use Bayesian factor regression models to construct a financial conditions index (FCI) for the U.S. Within this context we develop Bayesian model averaging methods that allow the data to select which variables should be included in the FCI or not. We also examine the importance of different...

We construct an empirical heterogeneous agent model which optimally combines forecasts from fundamentalist and chartists agents and evaluate its out-of-sample forecast performance using daily date covering the period from January 1999 to June 2014 for six of the most widely traded currencies. We...

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

An empirical small labor market model for the Czech Republic is estimated in the state-space framework. Its purpose is joint modeling of the labor force, employment, wages, hours worked, output, and the GDP deflator in a consistent “structural” framework suitable for short-run forecasting....

A small labour market model for the six largest euro area countries (Germany, France, Italy, Spain, the Netherlands, Belgium) is estimated in a state -space framework. The model entails, in the long run, four driving forces: a trend labour force component, a trend labour productivity component,...

We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR, bridge equations) and offers methods to manage data selection and adjust for Covid-19 observations. The toolbox aims at simplifying two key tasks: creating new nowcasting...