Nowcasting Spanish GDP growth in real time: "One and a half months earlier"
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008.
"Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?,"
Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
- Reichlin, Lucrezia & Giannone, Domenico & De Mol, Christine, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
- De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank.
- Giannone, Domenico & Reichlin, Lucrezia & De Mol, Christine, 2006. "Forecasting using a large number of predictors: Is Bayesian regression a valid alternative to principal components?," Working Paper Series 700, European Central Bank.
- Garcia-Ferrer, Antonio, et al, 1987. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 53-67, January.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013.
"Now-Casting and the Real-Time Data Flow,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237,
Elsevier.
- Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
- Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta & Modugno, Michele, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
- Martha Banbura & Domenico Giannone & Michèle Modugno & Lucrezia Reichlin, 2012. "Now-Casting and the Real-Time Data Flow," Working Papers ECARES ECARES 2012-026, ULB -- Universite Libre de Bruxelles.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Caruso, Alberto & Reichlin, Lucrezia & Ricco, Giovanni, 2019.
"Financial and fiscal interaction in the Euro Area crisis: This time was different,"
European Economic Review, Elsevier, vol. 119(C), pages 333-355.
- Caruso, Alberto & Reichlin, Lucrezia & Ricco, Giovanni, 2018. "Financial and Fiscal Interaction in the Euro Area Crisis : This Time was Different," The Warwick Economics Research Paper Series (TWERPS) 1167, University of Warwick, Department of Economics.
- Alberto Caruso & Lucrezia Reichlin & Giovanni Ricco, 2019. "Financial and fiscal interaction in the euro area crisis: this time was different," SciencePo Working papers Main hal-03403269, HAL.
- Alberto Caruso & Lucrezia Reichlin & Giovanni Ricco, 2019. "Financial and fiscal interaction in the Euro Area crisis: This time was different," Post-Print hal-03403613, HAL.
- Reichlin, Lucrezia & Caruso, Alberto & Ricco, Giovanni, 2018. "Financial and Fiscal Interaction in the Euro Area Crisis: This Time was Different," CEPR Discussion Papers 13016, C.E.P.R. Discussion Papers.
- Albert Caruso & Lucrezia Reichlin & Giovanni Ricco, 2019. "Financial and fiscal interaction in the euro area crisis : this time was different," Documents de Travail de l'OFCE 2019-11, Observatoire Francais des Conjonctures Economiques (OFCE).
- Alberto Caruso & Lucrezia Reichlin & Giovanni Ricco, 2019. "Financial and fiscal interaction in the Euro Area crisis: This time was different," SciencePo Working papers Main hal-03403613, HAL.
- Alberto Caruso & Lucrezia Reichlin & Giovanni Ricco, 2019. "Financial and fiscal interaction in the euro area crisis: this time was different," Working Papers hal-03403269, HAL.
- Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018.
"Bayesian Vector Autoregressions,"
The Warwick Economics Research Paper Series (TWERPS)
1159, University of Warwick, Department of Economics.
- Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
- Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," SciencePo Working papers Main hal-03458277, HAL.
- Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Working Papers hal-03458277, HAL.
- Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," Bank of England working papers 756, Bank of England.
- Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Documents de Travail de l'OFCE 2018-18, Observatoire Francais des Conjonctures Economiques (OFCE).
- Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian Vector Autoregressions," Discussion Papers 1808, Centre for Macroeconomics (CFM).
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015.
"Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
- Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.
- Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021. "A Large Bayesian VAR of the United States Economy," Staff Reports 976, Federal Reserve Bank of New York.
- Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2011.
"Forecasting large datasets with Bayesian reduced rank multivariate models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 735-761, August.
- Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2009. "Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models," CEPR Discussion Papers 7446, C.E.P.R. Discussion Papers.
- Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2009. "Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models," Economics Working Papers ECO2009/31, European University Institute.
- Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021.
"Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR,"
International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
- Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2015. "Real-Time Forecasting and Scenario Analysis using a Large Mixed-Frequency Bayesian VAR," Working Papers 2015-030, Federal Reserve Bank of St. Louis, revised 10 Apr 2020.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022.
"How is machine learning useful for macroeconomic forecasting?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
- Julieta Fuentes & Pilar Poncela & Julio Rodríguez, 2015.
"Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 576-595, June.
- Fuentes, Julieta & Poncela, Pilar & Rodríguez, Julio, 2012. "Sparse partial least squares in time series for macroeconomic forecasting," DES - Working Papers. Statistics and Econometrics. WS ws122216, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Giannone, Domenico & Lenza, Michele & Momferatou, Daphne & Onorante, Luca, 2014.
"Short-term inflation projections: A Bayesian vector autoregressive approach,"
International Journal of Forecasting, Elsevier, vol. 30(3), pages 635-644.
- Domenico Giannone & Michèle Lenza & Daphné Momferatu & Luca Onorante, 2010. "Short-term inflation projections: a Bayesian vector autoregressive approach," Working Papers ECARES ECARES 2010-011, ULB -- Universite Libre de Bruxelles.
- Giannone, Domenico & Lenza, Michele & Onorante, Luca & Momferatou, Daphne, 2010. "Short-Term Inflation Projections: a Bayesian Vector Autoregressive approach," CEPR Discussion Papers 7746, C.E.P.R. Discussion Papers.
- Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011.
"Forecasting the US real house price index: Structural and non-structural models with and without fundamentals,"
Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 200927, University of Pretoria, Department of Economics.
- Rangan Gupta & Alan Kabundi & Stephen M. Miller, 2010. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 1001, University of Nevada, Las Vegas , Department of Economics.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working papers 2009-42, University of Connecticut, Department of Economics.
- Tomasz Woźniak, 2016. "Bayesian Vector Autoregressions," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 365-380, September.
- Matteo Barigozzi & Marc Hallin, 2023.
"Dynamic Factor Models: a Genealogy,"
Papers
2310.17278, arXiv.org, revised Jan 2024.
- Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Working Papers ECARES 2023-15, ULB -- Universite Libre de Bruxelles.
- Kazimi, Camilla & Brownstone, David, 1999.
"Bootstrap confidence bands for shrinkage estimators,"
Journal of Econometrics, Elsevier, vol. 90(1), pages 99-127, May.
- Kazimi, C. & Brownstone, D., 1994. "Bootstrap Confidence Bands for Shrinkage Estimators," Papers 94-95-5, California Irvine - School of Social Sciences.
- Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
- Marco Lombardi & Chiara Osbat & Bernd Schnatz, 2012.
"Global commodity cycles and linkages: a FAVAR approach,"
Empirical Economics, Springer, vol. 43(2), pages 651-670, October.
- Lombardi, Marco J. & Osbat, Chiara & Schnatz, Bernd, 2010. "Global commodity cycles and linkages a FAVAR approach," Working Paper Series 1170, European Central Bank.
- Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009.
"Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP,"
Economics Working Papers
ECO2009/13, European University Institute.
- Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
- Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "Pooling versus model selection for nowcasting with many predictors: An application to German GDP," CEPR Discussion Papers 7197, C.E.P.R. Discussion Papers.
- Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Chen, Sophia & Ranciere, Romain, 2019.
"Financial information and macroeconomic forecasts,"
International Journal of Forecasting, Elsevier, vol. 35(3), pages 1160-1174.
- Sophia Chen & Mr. Romain Ranciere, 2016. "Financial Information and Macroeconomic Forecasts," IMF Working Papers 2016/251, International Monetary Fund.
- Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2014. "Signals from the Government: Policy Uncertainty and the Transmission of Fiscal Shocks," MPRA Paper 56136, University Library of Munich, Germany.
- Červená, Marianna & Schneider, Martin, 2014.
"Short-term forecasting of GDP with a DSGE model augmented by monthly indicators,"
International Journal of Forecasting, Elsevier, vol. 30(3), pages 498-516.
- Marianna Cervená & Martin Schneider, 2010. "Short-term forecasting GDP with a DSGE model augmented by monthly indicators," Working Papers 163, Oesterreichische Nationalbank (Austrian Central Bank).
More about this item
Keywords
Minnesota priors; mixed estimation; forecasting;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
NEP fields
This paper has been announced in the following NEP Reports:- NEP-CBA-2011-01-03 (Central Banking)
- NEP-FOR-2011-01-03 (Forecasting)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bde:wpaper:1037. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ángel Rodríguez. Electronic Dissemination of Information Unit. Research Department. Banco de España (email available below). General contact details of provider: https://edirc.repec.org/data/bdegves.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.