The impact of the official statistics revision on the accuracy of the Russian macroeconomic indicators nowcasting models
Author
Abstract
Suggested Citation
Download full text from publisher
To our knowledge, this item is not available for download. To find whether it is available, there are three options:1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a for a similarly titled item that would be available.
References listed on IDEAS
- 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.
- Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008.
"Nowcasting: The real-time informational content of macroeconomic data,"
Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
- Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
- Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group.
- Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
- Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011.
"A two-step estimator for large approximate dynamic factor models based on Kalman filtering,"
Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2006. "A Two-step estimator for large approximate dynamic factor models based on Kalman filtering," THEMA Working Papers 2006-23, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," PSE-Ecole d'économie de Paris (Postprint) hal-00638009, HAL.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Post-Print hal-00638009, HAL.
- Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00638009, HAL.
- Catherine Doz & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Post-Print hal-00844811, HAL.
- Reichlin, Lucrezia & Doz, Catherine & Giannone, Domenico, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers.
- Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2023.
"Testing big data in a big crisis: Nowcasting under Covid-19,"
International Journal of Forecasting, Elsevier, vol. 39(4), pages 1548-1563.
- Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," JRC Working Papers in Economics and Finance 2022-06, Joint Research Centre, European Commission.
- Ekaterina Astafieva & Marina Turuntseva, 2021. "Revisions of GDP: Data and Assessment of Statistical Properties," HSE Economic Journal, National Research University Higher School of Economics, vol. 25(1), pages 65-101.
- N. M. Makeeva & I. P. Stankevich & N. S. Lyubaykin, 2024. "Nowcasting the Russian economy macroeconomic indicators under uncertainty: Does taking into account the news sentiment help?," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 3.
- Michael P. Clements & Ana Beatriz Galvao, 2009.
"Forecasting US output growth using leading indicators: an appraisal using MIDAS models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206.
- Michael P. Clements & Ana Beatriz Galvão, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206, November.
- Caroline Jardet & Baptiste Meunier, 2022.
"Nowcasting world GDP growth with high‐frequency data,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
- Caroline Jardet & Baptiste Meunier, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
- Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
- Evžen Kočenda & Karen Poghosyan, 2020.
"Nowcasting Real GDP Growth: Comparison between Old and New EU Countries,"
Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
- Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
- Evzen Kocenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Working Papers IES 2020/5, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2020.
- Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017.
"Nowcasting BRIC+M in real time,"
International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
- Tatjana Dahlhaus & Justin-Damien Guénette & Garima Vasishtha, 2015. "Nowcasting BRIC+M in Real Time," Staff Working Papers 15-38, Bank of Canada.
- Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
- repec:taf:jnlbes:v:30:y:2012:i:2:p:181-190 is not listed on IDEAS
- Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2014.
"Nowcasting GDP in Real Time: A Density Combination Approach,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(1), pages 48-68, January.
- Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in Real-Time: A Density Combination Approach," Working Papers No 1/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
- Berger, Tino & Morley, James & Wong, Benjamin, 2023.
"Nowcasting the output gap,"
Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
- Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the Output Gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Litterman, Robert B, 1986.
"Forecasting with Bayesian Vector Autoregressions-Five Years of Experience,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
- Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
- Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
- Robert Lehmann, 2024.
"A real-time regional accounts database for Germany with applications to GDP revisions and nowcasting,"
Empirical Economics, Springer, vol. 67(2), pages 817-838, August.
- Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
- Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
- Strohsal, Till & Wolf, Elias, 2020. "Data revisions to German national accounts: Are initial releases good nowcasts?," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1252-1259.
- Natalya Makeeva & Ivan Stankevich, 2022. "Nowcasting of the Components of Russian GDP," HSE Economic Journal, National Research University Higher School of Economics, vol. 26(4), pages 598-622.
- Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021.
"Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach,"
International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
- Alessandro Giovannelli & Tommaso Proietti & Ambra Citton & Ottavio Ricchi & Cristian Tegami & Cristina Tinti, 2020. "Nowcasting GDP and its Components in a Data-rich Environment: the Merits of the Indirect Approach," CEIS Research Paper 489, Tor Vergata University, CEIS, revised 30 May 2020.
- repec:hal:journl:peer-00844811 is not listed on IDEAS
- Ivan Stankevich, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
- M. Y. Gareev & A. V. Polbin, 2022. "Nowcasting Russia’s key macroeconomic variables using machine learning," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 8.
- Ghysels, Eric & Kvedaras, Virmantas & Zemlys, Vaidotas, 2016. "Mixed Frequency Data Sampling Regression Models: The R Package midasr," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(i04).
- Zubarev Andrey & Rybak Konstantin, 2021. "GDP Nowcasting: Dynamic Factor Model vs. Official Forecasts [Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
- Ivan Stankevich, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
- Galvão, Ana Beatriz, 2017. "Data revisions and DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 215-232.
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.- Alexander Eliseev, 2025. "Nowcasting Russian GDP in a Mixed-Frequency DSGE Model with a Panel of Non-Modelled Variables," Russian Journal of Money and Finance, Bank of Russia, vol. 84(3), pages 63-93, September.
- Ivan Stankevich, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
- Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
- Luke Hartigan & Tom Rosewall, 2024.
"Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator,"
Working Papers
2024-15, University of Sydney, School of Economics.
- Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," RBA Research Discussion Papers rdp2024-04, Reserve Bank of Australia.
- Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2024.
"Lessons from nowcasting GDP across the world,"
Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 8, pages 187-217,
Edward Elgar Publishing.
- Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
- Diakonova, Marina & Molina, Luis & Mueller, Hannes & Pérez, Javier J. & Rauh, Christopher, 2024.
"The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting,"
Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(4).
- Marina Diakonova & Luis Molina & Hannes Mueller & Javier J. Pérez & Cristopher Rauh, 2022. "The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting," Working Papers 2232, Banco de España.
- Diakonova, M. & Molina, L. & Mueller, H. & Pérez, J. J. & Rauh, C., 2024. "The Information Content of Conflict, Social Unrest and Policy Uncertainty Measures for Macroeconomic Forecasting," Cambridge Working Papers in Economics 2418, Faculty of Economics, University of Cambridge.
- Diakonova, M. & Molina, L. & Mueller, H. & Pérez, J. J. & Rauh, C., 2024. "The Information Content of Conflict, Social Unrest and Policy Uncertainty Measures for Macroeconomic Forecasting," Janeway Institute Working Papers 2413, Faculty of Economics, University of Cambridge.
- Claudia Foroni & Massimiliano Marcellino, 2013.
"A survey of econometric methods for mixed-frequency data,"
Economics Working Papers
ECO2013/02, European University Institute.
- Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
- Andrey Polbin & Andrei Shumilov, 2025. "Nowcasting and forecasting Russian GDP and its components using quantile models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 79, pages 5-26.
- 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.
- Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018.
"Uncertain Kingdom: Nowcasting GDP and its Revisions,"
Discussion Papers
1824, Centre for Macroeconomics (CFM).
- Nikoleta Anesti & Ana Galvão & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England.
- Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
- Götz, Thomas B. & Hecq, Alain & Urbain, Jean-Pierre, 2016. "Combining forecasts from successive data vintages: An application to U.S. growth," International Journal of Forecasting, Elsevier, vol. 32(1), pages 61-74.
- Ballarin, Giovanni & Dellaportas, Petros & Grigoryeva, Lyudmila & Hirt, Marcel & van Huellen, Sophie & Ortega, Juan-Pablo, 2024.
"Reservoir computing for macroeconomic forecasting with mixed-frequency data,"
International Journal of Forecasting, Elsevier, vol. 40(3), pages 1206-1237.
- Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
- Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
- 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.
- 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.
- Baumeister, Christiane & Guérin, Pierre, 2021.
"A comparison of monthly global indicators for forecasting growth,"
International Journal of Forecasting, Elsevier, vol. 37(3), pages 1276-1295.
- Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," NBER Working Papers 28014, National Bureau of Economic Research, Inc.
- Baumeister, Christiane & Guerin, Pierre, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CEPR Discussion Papers 15403, C.E.P.R. Discussion Papers.
- Christiane Baumeister & Pierre Guerin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CAMA Working Papers 2020-93, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
- Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
- Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018.
"Macroeconomic Nowcasting and Forecasting with Big Data,"
Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
- Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
- Giannone, Domenico & Tambalotti, Andrea & Sbordone, Argia & Bok, Brandyn & Caratelli, Daniele, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
- Deicy J. Cristiano & Manuel D. Hernández & José David Pulido, 2012. "Pronósticos de corto plazo en tiempo real para la actividad económica colombiana," Borradores de Economia 724, Banco de la Republica de Colombia.
- Katja Heinisch & Rolf Scheufele, 2018.
"Bottom-up or direct? Forecasting German GDP in a data-rich environment,"
Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
- Katja Drechsel & Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.
- Drechsel, Katja & Scheufele, Rolf, 2013. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," IWH Discussion Papers 7/2013, Halle Institute for Economic Research (IWH).
More about this item
Keywords
; ; ; ; ;JEL classification:
- 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
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:ris:apltrx:021520. 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: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/ris/apltrx/021520.html