sample of publications

• articles 

  • Discovering specific common trends in a large set of disaggregates: statistical procedures, their properties, and an empirical application.  OXFORD BULLETIN OF ECONOMICS AND STATISTICS.  2020
  • Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis.  Econometrics Journal.  5:1-28. 2017
  • Geographical disaggregation of sectoral inflation. Econometric modelling of the Euro area and Spanish economies.  APPLIED ECONOMICS.  48:799-815. 2016
  • Quarterly Regional GDP Flash Estimates by Means of Benchmarking and Chain Linking.  Journal of Official Statistics.  31:627-647. 2015
  • Comments on: Short-term forecasting the daily load curve for residential electricity usage in the smart grid [book review].  APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY.  29:621-623. 2013
  • Forecasting aggregates and disaggregates with common features.  INTERNATIONAL JOURNAL OF FORECASTING.  29:718-732. 2013
  • Prediction intervals in conditionally heteroscedastic time series with stochastic components.  INTERNATIONAL JOURNAL OF FORECASTING.  27:308-319. 2011
  • Conditionally Heterocedastic Unobserved Component Models and their Reduced Form.  ECONOMICS LETTERS.  107:88-90. 2010
  • Forecasting Spanish Inflation using the Maximum Disaggregation Level by Sectors and Geographical Areas.  INTERNATIONAL REGIONAL SCIENCE REVIEW.  33:181-204. 2010
  • Energy Forecasting.  INTERNATIONAL JOURNAL OF FORECASTING.  24:561-565. 2008
  • Forecasting the Electricity Load from One Day to One Week Ahead for the Spanish System Operator.  INTERNATIONAL JOURNAL OF FORECASTING.  24:588-602. 2008

• book chapters 

  • Comentarios a "¿Brotes verdes? ¿Dónde, cuándo y cómo?" de Máximo Camacho, Gabriel Pérez-Quirós y Pilar Poncela. In: La crisis de la economía española: análisis económico de la Gran Recesión.  FUNDACION DE ESTUDIOS DE ECONOMIA APLICADA. 72-78. 2010
  • Implementing Business Intelligence in Electricity Markets. In: Business Intelligence in Economic Forecasting: Technologies and Techniques.  IGI GLOBAL. 283-295. 2010

• conference contributions 

  • Discovering common trends in a large set of disaggregates: statistical procedures and their properties 2016
  • The Spanish Economic Perspectives 2016
  • 22 years of forecasting experience at the Bulletin of Inflation and Macroeconomic Analysis 2015
  • Forecasting a large set of disaggregates with common trends and outliers 2015
  • The pairwise approach to model and forecast a large set of disaggregates with common trends 2015
  • A pairwise approach to model and forecast a large set of disaggregates with common trends 2014
  • Comments on "A powerful simple model of moving deasonality for model based seasonal adjustment by D.F.Findley and D.P. Lytras" 2014
  • Consideraciones sobre la economia española: situacion actual y cuestiones pendientes 2014
  • The pairwise approach to model and forecast a large set of disaggregates with common trends 2014
  • Forecasting disaggregates by sectors and regions: the case of inflation in the Euro area and in Spain 2013
  • Forecasting disaggregates by sectors and regions: the case of inflation in the Euro area and in Spain 2013
  • The disaggegation map approach to identify non-pervasive common features in a large set of disaggregates 2013
  • Estadístiques i prediccions macroeconòmiques en les comunitats autònomes 2012
  • Modeling Monthly Electricity Demand and Building MacroeconomiIc ndicators based on Electricity Consumption: Interaction between Monthly Econometric and Daily Time Series Models 2012
  • Modeling Monthly Electricity Demand: Interaction Between Monthly Econometric and Daily Time Series 2012
  • Combining Benchmarking and Chain-Linking for Short-Term Regional Forecasting 2011
  • Combining Benchmarking and Chain-Linking for Short-Term Regional Forecasting: An Application to Spanish GDP 2011
  • Forecasting Aggregate and Disaggregates with Common Features 2011
  • Forecasting GDP: Disaggregation, Indicators and Monthly Information 2011
  • ARIMA-GARCH and Unobserved Component Models with GARCH Disturbances: Are their Prediction Intervals Different? 2008
  • Ponencia 2008
  • The Relationship between ARIMA-GARCH and Unobserved Component Models with GARCH Disturbances 2008

• working papers 

  • Tall big data time series of high frequency: stylized facts and econometric modelling 2023
  • Discovering general and sectorial trends in a large set of time series 2020
  • Discovering pervasive and non-pervasive common cycles 2017
  • 22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis 2017
  • Discovering common trends in a large set of disaggregates: statistical procedures and their properties 2015
  • Forecasting a large set of disaggregates with common trends and outliers 2015
  • The pairwise approach to model a large set of disaggregates with common trends 2014
  • Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain 2013
  • Forecasting aggregates and disaggregates with common features 2012
  • Combining benchmarking and chain-linking for short-term regional forecasting 2011
  • El perfil de crecimiento de un fenómeno económico 2008
  • Forecasting Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas and Cointegration Relationships Between Regional and National Sectors: The Case of Spain 2008
  • Forecasting Spanish Inflation Using Information from Different Sectors and Geographical Areas 2008