Banco de España macroeconomic projections: comparison with an econometric model
Author
Abstract
Suggested Citation
Note: Analytical Articles
Download full text from publisher
References listed on IDEAS
- Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015.
"Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections,"
International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
- Giannone, Domenico & Bańbura, Marta & Lenza, Michele, 2014. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," Working Paper Series 1733, European Central Bank.
- Giannone, Domenico & Banbura, Marta & Lenza, Michele, 2014. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," CEPR Discussion Papers 9931, C.E.P.R. Discussion Papers.
- Marta Bañbura & Domenico Giannone & Michèle Lenza, 2014. "Conditional Forecasts and Scenario Analysis with Vector Autoregressions for Large Cross-Sections," Working Papers ECARES ECARES 2014-15, ULB -- Universite Libre de Bruxelles.
- Luis Julián Álvarez & Alberto Cabrero & Alberto Urtasun, 2014. "A procedure for short-term GDP forecasting," Economic Bulletin, Banco de España, issue OCT, pages 29-35, October.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, 2025. "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015.
"Prior Selection for Vector Autoregressions,"
The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," NBER Working Papers 18467, National Bureau of Economic Research, Inc.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2012. "Prior selection for vector autoregressions," Working Paper Series 1494, European Central Bank.
- Domenico Giannone & Michèle Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," Working Papers ECARES ECARES 2012-002, ULB -- Universite Libre de Bruxelles.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2012. "Prior Selection for Vector Autoregressions," CEPR Discussion Papers 8755, C.E.P.R. Discussion Papers.
- Maximo Camacho & Gabriel Perez Quiros, 2011. "Spain‐Sting: Spain Short‐Term Indicator Of Growth," Manchester School, University of Manchester, vol. 79(s1), pages 594-616, June.
- Ana Arencibia Pareja & Samuel Hurtado & Mercedes de Luis López & Eva Ortega, 2017. "New version of the quarterly model of Banco de España (MTBE)," Occasional Papers 1709, Banco de España.
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.- Michael W. McCracken & Joseph T. McGillicuddy, 2019.
"An empirical investigation of direct and iterated multistep conditional forecasts,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 181-204, March.
- Michael W. McCracken & Joseph McGillicuddy, 2017. "An Empirical Investigation of Direct and Iterated Multistep Conditional Forecasts," Working Papers 2017-40, Federal Reserve Bank of St. Louis.
- Ganics, Gergely & Odendahl, Florens, 2021.
"Bayesian VAR forecasts, survey information, and structural change in the euro area,"
International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
- Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers 733, Banque de France.
- Gergely Ganics & Florens Odendahl, 2019. "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers 1948, Banco de España.
- Todd E. Clark & Michael W. McCracken, 2014.
"Evaluating Conditional Forecasts from Vector Autoregressions,"
Working Papers (Old Series)
1413, Federal Reserve Bank of Cleveland.
- Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
- Tallman, Ellis W. & Zaman, Saeed, 2020.
"Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy,"
International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
- Ellis W. Tallman & Saeed Zaman, 2018. "Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy," Working Papers (Old Series) 1809, Federal Reserve Bank of Cleveland.
- Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016.
"Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts,"
International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
- Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
- Christian Glocker & Serguei Kaniovski, 2022.
"Macroeconometric forecasting using a cluster of dynamic factor models,"
Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
- Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
- Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019.
"Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
- Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
- Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
- 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," Sciences Po Economics Publications (main) hal-03458277, HAL.
- Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Working Papers hal-03458277, HAL.
- Silvia Miranda-Agrippino & Giovanni Ricco, 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).
- Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020.
"What's Up with the Phillips Curve?,"
Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 301-373.
- Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s up with the Phillips Curve?," NBER Working Papers 27003, National Bureau of Economic Research, Inc.
- Del Negro, Marco & Lenza, Michele & Primiceri, Giorgio E. & Tambalotti, Andrea, 2020. "What’s up with the Phillips Curve?," Working Paper Series 2435, European Central Bank.
- Primiceri, Giorgio & Del Negro, Marco & Lenza, Michele & Tambalotti, Andrea, 2020. "What's up with the Phillips Curve?," CEPR Discussion Papers 14583, C.E.P.R. Discussion Papers.
- William Chen & Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s Up with the Phillips Curve?," Liberty Street Economics 20200918a, Federal Reserve Bank of New York.
- 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.
- 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.
- Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
- Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017.
"Forecast Combinations in a DSGE‐VAR Lab,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
- Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2014. "Forecast combinations in a DSGE-VAR lab," Economics Series 309, Institute for Advanced Studies.
- Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, October.
- Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022.
"Common factors of commodity prices,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
- Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
- Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2017. "Common Factors of Commodity Prices," Working papers 645, Banque de France.
- Giannone, Domenico & Ferrara, Laurent & Delle Chiaie, Simona, 2018. "Common Factors of Commodity Prices," CEPR Discussion Papers 12767, C.E.P.R. Discussion Papers.
- Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017. "Common factors of commodity prices," Working Paper Series 2112, European Central Bank.
- Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023.
"Tail Forecasting With Multivariate Bayesian Additive Regression Trees,"
International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
- Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," Working Papers 21-08R, Federal Reserve Bank of Cleveland, revised 12 Jul 2022.
- Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
- Deryugina, Elena & Ponomarenko, Alexey, 2014.
"A large Bayesian vector autoregression model for Russia,"
BOFIT Discussion Papers
22/2014, Bank of Finland, Institute for Economies in Transition.
- Elena Deryugina & Alexey Ponomarenko, 2015. "A large Bayesian vector autoregression model for Russia," Bank of Russia Working Paper Series wps1, Bank of Russia.
- Berg, Tim O. & Henzel, Steffen R., 2015.
"Point and density forecasts for the euro area using Bayesian VARs,"
International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
- Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," ifo Working Paper Series 155, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
- Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
- Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
- Christiane Baumeister & Lutz Kilian, 2014.
"What Central Bankers Need To Know About Forecasting Oil Prices,"
International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.
- Kilian, Lutz & Baumeister, Christiane, 2012. "What Central Bankers Need to Know about Forecasting Oil Prices," CEPR Discussion Papers 9118, C.E.P.R. Discussion Papers.
- Christiane Baumeister & Lutz Kilian, 2013. "What Central Bankers Need to Know about Forecasting Oil Prices," Staff Working Papers 13-15, Bank of Canada.
More about this item
Keywords
; ; ;JEL classification:
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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:journl:y:2019:i:9:d:aa:n:26. 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.
Printed from https://ideas.repec.org/a/bde/journl/y2019i9daan26.html