Antoni Espasa
Charles III University of Madrid
61 Papers
185 Citations
Antoni Espasa is an academic researcher from Charles III University of Madrid. The author has contributed to research in topics: Cointegration & Inflation. The author has an hindex of 12, co-authored 61 publications. Previous affiliations of Antoni Espasa include Complutense University of Madrid & Carlos III Health Institute.
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Papers
Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors
TL;DR: In this article, the authors show that the breakdown by group of markets improves the European inflation forecasts and constitutes a framework in which general and specific indicators can be introduced for further improvements.
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On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach
TL;DR: In this paper, a generalized profile likelihood approach is proposed to estimate a component model for the analysis of financial durations, which is based on the assumption either of a likelihood function for the model errors or that the error density belongs to the class of exponential densities.
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Forecasting aggregates and disaggregates with common features
Antoni Espasa,Iván Mayo-Burgos +1 more
TL;DR: In this article, a disaggregated approach based on single-equation models for the components, which take into account the stable features that some components share, such as a common trend and common serial correlation, is proposed.
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Semiparametric estimation for financial durations
Juan M. Rodriguez-Poo,David Veredas,David Veredas,Antoni Espasa +3 more
- 01 Jan 2008
TL;DR: In this paper, a semiparametric model for the analysis of time series of durations that show autocorrelation and deterministic patterns is proposed, based on generalized profile likelihood, which allows for joint estimation of the parametric and nonparametric components.
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Econometric modelling for short-term inflation forecasting in the emu.
Antoni Espasa,Rebeca Albacete +1 more
TL;DR: In this paper, the authors face the problem of forecasting monthly inflation in the euro zone by breaking down the HICP in different sectors through the different countries, grouping the eight smallest countries all together for the purpose of this work.