This paper presents a method to improve the one-step-ahead forecasts of the Spanish unemployment monthly series. To do so, we use numerous potential explanatory variables extracted from searches in Google (GoogleTrends tool).Two different dimension reduction techniques are implemented (PCA and...

This paper presents a method to improve the one-step-ahead forecasts of the Spanish unemployment monthly series. To do so, we use numerous potential explanatory variables extracted from searches in Google (GoogleTrends tool).Two different dimension reduction techniques are implemented (PCA and...

The goal of this paper is to estimate the impact of the 2008 and 2020 economic crises on the employment in Spain. We perform a counterfactual analysis, combining intervention (interrupted time series) analysis and conditional forecasting to estimate a “crisis-free” scenario. These...

This paper proposes a statistical model and a conceptual framework to estimate inflation volatility assuming rational inattention, where the decay in the level of attention reflects the arrival of news in the market. We estimate trend inflation and the conditional inflation volatility for...

This paper provides a new, uni¯ed, and °exible framework to measure and characterize convergence in prices. We formally de¯ne this notion and propose a model to represent a wide range of transition paths that converge to a common steady-state. Our framework enables the econometric measurement...

This paper discusses how to determine the order of a state-space model. To do so, we start by revising existing approaches and find in them three basic shortcomings: i) some of them have a poor performance in short samples, ii) most of them are not robust and iii) none of them can accommodate...