Short time series are fundamental in the foreign exchange market due to their ability to provide real-time information, allowing traders to react quickly to market movements, thus optimizing profits and mitigating risks. Economic transactions show a strong connection to foreign currencies,...

The TSpVARX model can be used in inflation and money outflow forecasting by accommodating the reciprocal relationship among endogenous variables, the influence of exogenous variables, inter-regional linkages, and the nonlinearity of the relationship between endogenous and predetermined...

The purpose of this study is to see if the Fisher's hypothesis validation is robust in year or/and countries dimensions. We investigate whether nominal or real stock market returns are hedged against inflation rate, so as to determine the appropriate time and markets to invest in (from the 32...

In this paper, tests for fractional cointegration that allow for structural breaks in the long-run equilibrium are proposed. Traditional cointegration tests cannot handle shifts in fractional cointegration relationships, a limitation addressed here by allowing for a time-dependent memory...

This paper introduces the family of Dynamic Kernel models. These models approximate the predictive density function of a time series through a weighted average of kernel densities possessing a dynamic bandwidth. A general specification is presented and several particular models are studied in...

This paper explores the evolution of non-working time in Spain over recent years by analysing the results of two surveys conducted by the National Statistics Institute: the Quarterly Survey on Labor Costs and the Labor Force Survey. Using time series models and intervention analysis, potential...

What drives the recent inflation surge? To answer this question, one must decompose inflation fluctuations into the contribution of structural shocks. We document how whimsical such a historical shock decomposition can be in standard vector autoregressive (VAR) models. We show that the...

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...