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Marta Banbura

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models
    2. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
  2. 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.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models
    2. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.

    Mentioned in:

    1. Nowcasting (economics) in Wikipedia (English)
  2. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.

    Mentioned in:

    1. Large Bayesian vector auto regressions (Journal of Applied Econometrics 2011) in ReplicationWiki ()

Working papers

  1. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.

    Cited by:

    1. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2024. "The bias of the ECB inflation projections: A State-dependent analysis," Bank of Finland Research Discussion Papers 4/2024, Bank of Finland.

  2. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.

    Cited by:

    1. Boeck, Maximilian & Zörner, Thomas O., 2025. "Natural gas prices, inflation expectations, and the pass-through to euro area inflation," Energy Economics, Elsevier, vol. 141(C).
    2. Adolfsen, Jakob Feveile & Ferrari Minesso, Massimo & Mork, Jente Esther & Van Robays, Ine, 2024. "Gas price shocks and euro area inflation," Journal of International Money and Finance, Elsevier, vol. 149(C).
    3. Lukas Berend & Jan Pruser, 2025. "Large structural VARs with multiple linear shock and impact inequality restrictions," Papers 2505.19244, arXiv.org.
    4. Karol Szafranek & Grzegorz Szafrański & Agnieszka Leszczyńska-Paczesna, 2023. "Inflation returns. Revisiting the role of external and domestic shocks with Bayesian structural VAR," NBP Working Papers 357, Narodowy Bank Polski.
    5. Ferreira, Vicente & Abreu, Alexandre & Louçã, Francisco, 2025. "The rise and fall of inflation in the Euro Area (2021-2024): A heterodox perspective," Structural Change and Economic Dynamics, Elsevier, vol. 72(C), pages 103-110.
    6. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    7. Meg Tulloch, "undated". "Nowcasting and Forecasting Average Weekly Earnings in the United Kingdom," National Institute of Economic and Social Research (NIESR) Discussion Papers 565, National Institute of Economic and Social Research.
    8. Ascari, Guido & Bonam, Dennis & Smadu, Andra, 2024. "Global supply chain pressures, inflation, and implications for monetary policy," Journal of International Money and Finance, Elsevier, vol. 142(C).
    9. Lin, Xiang & Li, Xiaoying, 2025. "A study on anchoring Swedish inflation expectations in times of turbulence," Energy Economics, Elsevier, vol. 144(C).
    10. Bobeica, Elena & Holton, Sarah & Huber, Florian & Martínez Hernández, Catalina, 2025. "Beware of large shocks! A non-parametric structural inflation model," Working Paper Series 3052, European Central Bank.
    11. Daniele Colombo & Francesco Toni, 2025. "Understanding Gas Price Shocks: Elasticities, Volatilities, and Macroeconomic Transmission," LEM Papers Series 2025/20, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    12. Lukas Berend & Jan Pruser, 2024. "The Transmission of Monetary Policy via Common Cycles in the Euro Area," Papers 2410.05741, arXiv.org, revised Nov 2024.
    13. Daniele Colombo & Francesco Toni, 2025. "Understanding Gas Price Shocks: Elasticities, Volatility and Macroeconomic Transmission," GREDEG Working Papers 2025-20, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    14. Ko, Dong Gyun, 2025. "Did the American Rescue Plan cause inflation? A synthetic control approach," Economic Modelling, Elsevier, vol. 143(C).
    15. Jan Pruser, 2024. "A large non-Gaussian structural VAR with application to Monetary Policy," Papers 2412.17598, arXiv.org.
    16. Guido Ascari & Dennis Bonam & Lorenzo Mori & Andra Smadu, 2024. "Fiscal Policy and Inflation in the Euro Area," Working Papers 820, DNB.

  3. Marta Bañbura & Danilo Leiva-León & Jan-Oliver Menz, 2021. "Do inflation expectations improve model-based inflation Forecasts?," Working Papers 2138, Banco de España.

    Cited by:

    1. Huber, Florian & Onorante, Luca & Pfarrhofer, Michael, 2024. "Forecasting euro area inflation using a huge panel of survey expectations," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1042-1054.
    2. Burban, Valentin & De Backer, Bruno & Vladu, Andreea Liliana, 2024. "Inflation (de-)anchoring in the euro area," Working Paper Series 2964, European Central Bank.
    3. Baumann, Ursel & Darracq Pariès, Matthieu & Westermann, Thomas & Riggi, Marianna & Bobeica, Elena & Meyler, Aidan & Böninghausen, Benjamin & Fritzer, Friedrich & Trezzi, Riccardo & Jonckheere, Jana & , 2021. "Inflation expectations and their role in Eurosystem forecasting," Occasional Paper Series 264, European Central Bank.
    4. Martin, Ertl & Fortin, Ines & Hlouskova, Jaroslava & Koch, Sebastian P. & Kunst, Robert M. & Soegner, Leopold, 2024. "Inflation Forecasting in Turbulent Times," IHS Working Paper Series 56, Institute for Advanced Studies.
      • Martin Ertl & Ines Fortin & Jaroslava Hlouskova & Sebastian P. Koch & Robert M. Kunst & Leopold Sögner, 2025. "Inflation forecasting in turbulent times," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 52(1), pages 5-37, February.
    5. Heikkinen, Joni & Heimonen, Kari, 2024. "Media tone: The role of news and social media on heterogeneous inflation expectations," Bank of Finland Research Discussion Papers 8/2024, Bank of Finland.
    6. Giulio Galdi & Roberto Casarin & Davide Ferrari & Carlo Fezzi & Francesco Ravazzolo, 2022. "Nowcasting industrial production using linear and non-linear models of electricity demand," DEM Working Papers 2022/2, Department of Economics and Management.
    7. Douglas Kiarelly Godoy de Araujo & Nikola Bokan & Fabio Alberto Comazzi & Michele Lenza, 2025. "Word2Prices: embedding central bank communications for inflation prediction," BIS Working Papers 1253, Bank for International Settlements.
    8. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    9. Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2024. "Oil jump tail risk as a driver of inflation dynamics," Journal of Commodity Markets, Elsevier, vol. 36(C).
    10. Luigi Bonatti, & Andrea Fracasso & Roberto Tamborini, 2021. "What to expect from inflation expectations: theory, empirics and policy issues," DEM Working Papers 2022/1, Department of Economics and Management.
    11. Olivier de Bandt & Jean-Charles Bricongne & Julien Denes & Alexandre Dhenin & Annabelle De Gaye & Pierre-Antoine Robert, 2023. "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers 921, Banque de France.
    12. Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.

  4. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.

    Cited by:

    1. Huber, Florian & Onorante, Luca & Pfarrhofer, Michael, 2024. "Forecasting euro area inflation using a huge panel of survey expectations," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1042-1054.
    2. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    3. 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.
    4. Burban, Valentin & De Backer, Bruno & Vladu, Andreea Liliana, 2024. "Inflation (de-)anchoring in the euro area," Working Paper Series 2964, European Central Bank.
    5. Allayioti, Anastasia & Arioli, Rodolfo & Bates, Colm & Botelho, Vasco & Fagandini, Bruno & Fonseca, Luís & Healy, Peter & Meyler, Aidan & Minasian, Ryan & Zahrt, Octavia, 2024. "A look back at 25 years of the ECB SPF," Occasional Paper Series 364, European Central Bank.
    6. Baumann, Ursel & Darracq Pariès, Matthieu & Westermann, Thomas & Riggi, Marianna & Bobeica, Elena & Meyler, Aidan & Böninghausen, Benjamin & Fritzer, Friedrich & Trezzi, Riccardo & Jonckheere, Jana & , 2021. "Inflation expectations and their role in Eurosystem forecasting," Occasional Paper Series 264, European Central Bank.
    7. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    8. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    9. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    10. Bańbura, Marta & Bobeica, Elena & Giammaria, Alessandro & Porqueddu, Mario & van Spronsen, Josha, 2025. "A new model to forecast energy inflation in the euro area," Working Paper Series 3062, European Central Bank.
    11. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
    12. Adämmer, Philipp & Prüser, Jan & Schüssler, Rainer A., 2025. "Forecasting macroeconomic tail risk in real time: Do textual data add value?," International Journal of Forecasting, Elsevier, vol. 41(1), pages 307-320.

  5. Baumann, Ursel & Darracq Pariès, Matthieu & Westermann, Thomas & Riggi, Marianna & Bobeica, Elena & Meyler, Aidan & Böninghausen, Benjamin & Fritzer, Friedrich & Trezzi, Riccardo & Jonckheere, Jana & , 2021. "Inflation expectations and their role in Eurosystem forecasting," Occasional Paper Series 264, European Central Bank.

    Cited by:

    1. Baumann, Ursel & Ferrando, Annalisa & Georgarakos, Dimitris & Gorodnichenko, Yuriy & Reinelt, Timo, 2024. "SAFE to Update Inflation Expectations? New Survey Evidence on Euro Area Firms," CEPR Discussion Papers 19161, C.E.P.R. Discussion Papers.
    2. Glas, Alexander & Heinisch, Katja, 2023. "Conditional macroeconomic survey forecasts: Revisions and errors," Journal of International Money and Finance, Elsevier, vol. 138(C).
    3. Koester, Gerrit & Lis, Eliza & Nickel, Christiane & Osbat, Chiara & Smets, Frank, 2021. "Understanding low inflation in the euro area from 2013 to 2019: cyclical and structural drivers," Occasional Paper Series 280, European Central Bank.
    4. Ehrmann, Michael & Holton, Sarah & Kedan, Danielle & Phelan, Gillian, 2021. "Monetary policy communication: perspectives from former policy makers at the ECB," Working Paper Series 2627, European Central Bank.
    5. Andrejs Zlobins, 2022. "Into the Universe of Unconventional Monetary Policy: State-dependence, Interaction and Complementarities," Working Papers 2022/05, Latvijas Banka.
    6. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    7. Yury Perevyshin, 2024. "Analysts' Inflation Expectations vs Univariate Models of Inflation Forecasting in the Russian Economy," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 54-76, June.

  6. Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.

    Cited by:

    1. Luca Brugnolini & Giuseppe Ragusa, 2022. "Euro Area Deflationary Pressure Index," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 883-900, October.
    2. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    3. Joseph, Andreas & Potjagailo, Galina & Chakraborty, Chiranjit & Kapetanios, George, 2024. "Forecasting UK inflation bottom up," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1521-1538.
    4. Brand, Claus & Obstbaum, Meri & Coenen, Günter & Sondermann, David & Lydon, Reamonn & Ajevskis, Viktors & Hammermann, Felix & Angino, Siria & Hernborg, Nils & Basso, Henrique & Hertweck, Matthias & Bi, 2021. "Employment and the conduct of monetary policy in the euro area," Occasional Paper Series 275, European Central Bank.
    5. Fontanari, Claudia & Palumbo, Antonella & Salvatori, Chiara, 2022. "The updated Okun method for estimation of potential output with alternative measures of labor underutilization," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 158-178.
    6. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    7. Manuel M. F. Martins & Fabio Verona, 2024. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequencies Matter," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 811-832, August.
    8. Stephen G. Hall & George S. Tavlas & Yongli Wang & Deborah Gefang, 2024. "Inflation forecasting with rolling windows: An appraisal," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 827-851, July.
    9. Faria, Gonçalo & Verona, Fabio, 2024. "Enhancing forecast accuracy through frequencydomain combination: Applications to financial and economic indicators," Bank of Finland Research Discussion Papers 14/2024, Bank of Finland.
    10. Alberto Americo & Douglas Kiarelly Godoy de Araujo & Johannes Damp & Sjur Nilsen & Daniel Rees & Rafael Schmidt & Christian Schmieder, 2025. "Inflation cycles: evidence from international data," BIS Working Papers 1264, Bank for International Settlements.
    11. Panpan Zhu & Qingjie Zhou & Yinpeng Zhang, 2024. "Investor attention and consumer price index inflation rate: Evidence from the United States," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    12. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.
    13. Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
    14. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    15. Nicholas Apergis, 2024. "Eurozone inflation: fresh projections from global factors," Economics and Business Letters, Oviedo University Press, vol. 13(1), pages 39-47.
    16. Bobeica, Elena & Hartwig, Benny, 2021. "The COVID-19 shock and challenges for time series models," Working Paper Series 2558, European Central Bank.
    17. Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.
    18. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.

  7. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.

    Cited by:

    1. Bobeica Elena & Holton Sarah & Koester Gerrit, 2023. "Bringing Inflation Back Under Control," Intereconomics: Review of European Economic Policy, Sciendo, vol. 58(3), pages 136-141, June.
    2. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.
    3. Matthew Fontes Baptista & Stéphane Lhuissier & Matteo Mogliani, 2024. "Measuring the underlying component of inflation [Mesurer la composante sous-jacente de l’inflation]," Bulletin de la Banque de France, Banque de France, issue 253.
    4. Ampudia, Miguel & Ehrmann, Michael & Strasser, Georg, 2023. "The effect of monetary policy on inflation heterogeneity along the income distribution," CEPR Discussion Papers 18460, C.E.P.R. Discussion Papers.
    5. Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.

  8. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.

    Cited by:

    1. Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
    2. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    3. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    4. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    5. Barbara Rossi, 2021. "Forecasting in the Presence of Instabilities: How We Know Whether Models Predict Well and How to Improve Them," Journal of Economic Literature, American Economic Association, vol. 59(4), pages 1135-1190, December.
    6. Andrei Dubovik & Adam Elbourne & Bram Hendriks & Mark Kattenberg, 2022. "Forecasting World Trade Using Big Data and Machine Learning Techniques," CPB Discussion Paper 441, CPB Netherlands Bureau for Economic Policy Analysis.
    7. Arnoud Stevens & Joris Wauters, 2018. "Is euro area lowflation here to stay ? Insights from a time-varying parameter model with survey data," Working Paper Research 355, National Bank of Belgium.
    8. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    10. 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.
    11. 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, September.
    12. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    13. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    14. Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.

  9. Bańbura, Marta & Albani, Maria & Ambrocio, Gene & Bursian, Dirk & Buss, Ginters & de Winter, Jasper & Gavura, Miroslav & Giordano, Claire & Júlio, Paulo & Le Roux, Julien & Lozej, Matija & Malthe-Thag, 2018. "Business investment in EU countries," Occasional Paper Series 215, European Central Bank.

    Cited by:

    1. Azqueta-Gavaldón, Andrés & Hirschbühl, Dominik & Onorante, Luca & Saiz, Lorena, 2023. "Sources of Economic Policy Uncertainty in the euro area," European Economic Review, Elsevier, vol. 152(C).
    2. Hickey, Rónán & Lozej, Matija & Smyth, Diarmaid, 2020. "Financing government investment and its implications for public capital: A small open economy perspective," Economic Modelling, Elsevier, vol. 93(C), pages 620-641.

  10. 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.

    Cited by:

    1. Endong Wang, 2024. "Structural counterfactual analysis in macroeconomics: theory and inference," Papers 2409.09577, arXiv.org.
    2. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
    3. Olga Korotkikh, 2020. "A Multi-Country BVAR Model for the External Sector," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 98-112, December.
    4. Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
    5. Ekaterina Pirozhkova & Nicola Viegi, 2023. "Changing the inflation target in emerging markets: the reward of reducing risk," Economics Bulletin, AccessEcon, vol. 43(3), pages 1453-1457.
    6. Domenico Giannone & Michele Lenza & Lucrezia Reichlin, 2019. "Money, Credit, Monetary Policy, and the Business Cycle in the Euro Area: What Has Changed Since the Crisis?," International Journal of Central Banking, International Journal of Central Banking, vol. 15(5), pages 137-173, December.
    7. 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.
    8. Francesco Bianchi & Giovanni Nicolò & Dongho Song, 2023. "Inflation and Real Activity over the Business Cycle," NBER Working Papers 31075, National Bureau of Economic Research, Inc.
    9. Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
    10. 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.
    11. Danilo Leiva-Leon & Luis Uzeda, 2021. "Endogenous time variation in vector autoregressions," Working Papers 2108, Banco de España.
    12. Michele Lenza & Giorgio E. Primiceri, 2022. "How to estimate a vector autoregression after March 2020," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 688-699, June.
    13. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    14. Narcissa Balta & Bořek Vašíček, 2020. "Financial channels and economic activity in the euro area: a large-scale Bayesian VAR approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(2), pages 431-451, May.
    15. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    16. 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.
    17. Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Documents de Travail de l'OFCE 2018-18, Observatoire Francais des Conjonctures Economiques (OFCE).
    18. Máximo Camacho & Matías Pacce & Gabriel Pérez-Quirós, 2020. "Spillover effects in international business cycles," Working Papers 2034, Banco de España.
    19. Anastasios Evgenidis & Stephanos Papadamou, 2021. "The impact of unconventional monetary policy in the euro area. Structural and scenario analysis from a Bayesian VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5684-5703, October.
    20. Pagliari, Maria Sole, 2024. "Does one (unconventional) size fit all? Effects of the ECB’s unconventional monetary policies on the euro area economies," European Economic Review, Elsevier, vol. 168(C).
    21. D’Amuri, Francesco & De Philippis, Marta & Guglielminetti, Elisa & Lo Bello, Salvatore, 2022. "Slack and prices during Covid-19: Accounting for labor market participation," Labour Economics, Elsevier, vol. 75(C).
    22. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    23. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    24. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    25. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
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    62. 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.
    63. Guy P. Nason & James L. Wei, 2022. "Quantifying the economic response to COVID‐19 mitigations and death rates via forecasting purchasing managers' indices using generalised network autoregressive models with exogenous variables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1778-1792, October.
    64. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have standard VARs remained stable since the crisis?," Working Paper 2014/13, Norges Bank.
    65. Klaus-Heiner Röhl & Joachim Ragnitz & Ulrich Walwei & Timo Wollmershäuser & Justus Haucap & Jarko Fidrmuc & Florian Horky & Philipp Reichle & Fabian Reck & Birgit Felden, 2021. "Die Post-Covid-19-Wirtschaft: Welche unerwarteten Spuren hinterlässt die Krise in Branchen, Regionen und Strukturen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 74(03), pages 03-25, March.
    66. Stefan Laseen & Marzie Taheri Sanjani, 2016. "Did the Global Financial Crisis Break the U.S. Phillips Curve?," IMF Working Papers 2016/126, International Monetary Fund.
    67. Misha van Beek, 2020. "Consistent Calibration of Economic Scenario Generators: The Case for Conditional Simulation," Papers 2004.09042, arXiv.org.
    68. Petrella, Ivan & Antolin-Diaz, Juan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
    69. Rostagno, Massimo & Altavilla, Carlo & Carboni, Giacomo & Lemke, Wolfgang & Motto, Roberto & Saint Guilhem, Arthur & Yiangou, Jonathan, 2019. "A tale of two decades: the ECB’s monetary policy at 20," Working Paper Series 2346, European Central Bank.
    70. João Barata R.B. Barroso & Fernanda Nechio, 2020. "Financial market development, monetary policy and financial stability in Brazil," BIS Papers chapters, in: Bank for International Settlements (ed.), Financial market development, monetary policy and financial stability in emerging market economies, volume 113, pages 55-65, Bank for International Settlements.
    71. Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    72. Barroso, João Barata R.B. & da Silva, Luiz A. Pereira & Sales, Adriana Soares, 2016. "Quantitative easing and related capital flows into Brazil: Measuring its effects and transmission channels through a rigorous counterfactual evaluation," Journal of International Money and Finance, Elsevier, vol. 67(C), pages 102-122.
    73. Gustavo Adler & Sebastian Sosa, 2016. "External Factors in Debt Sustainability Analysis: An Application to Latin America?," Journal of Banking and Financial Economics, University of Warsaw, Faculty of Management, vol. 1(5), pages 81-120, June.
    74. Manuel González-Astudillo & Juan Guerra-Salas & Avi Lipton, 2024. "Fiscal Consolidations in Commodity-Exporting Countries: A DSGE Perspective," Working Papers Central Bank of Chile 1015, Central Bank of Chile.
    75. 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.
    76. 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.
    77. Salman Huseynov, 2021. "Long and short memory in dynamic term structure models," CREATES Research Papers 2021-15, Department of Economics and Business Economics, Aarhus University.
    78. Sakai Ando & Taehoon Kim, 2024. "Systematizing Macroframework Forecasting: High-Dimensional Conditional Forecasting with Accounting Identities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(4), pages 1386-1410, December.
    79. Conti, Antonio M., 2017. "Has the FED Fallen behind the Curve? Evidence from VAR models," Economics Letters, Elsevier, vol. 159(C), pages 164-168.
    80. Antonello D'Agostino & Michele Modugno & Chiara Osbat, 2015. "A Global Trade Model for the Euro Area," Finance and Economics Discussion Series 2015-13, Board of Governors of the Federal Reserve System (U.S.).
    81. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.
    82. Rodríguez, Aldo, 2020. "Estimación Bayesiana de un Modelo de Economía Abierta con Sector Bancario," Dynare Working Papers 52, CEPREMAP.
    83. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    84. Anastasios Evgenidis & Anastasios G. Malliaris, 2020. "To Lean Or Not To Lean Against An Asset Price Bubble? Empirical Evidence," Economic Inquiry, Western Economic Association International, vol. 58(4), pages 1958-1976, October.
    85. Liudmila Kitrar & Tamara Lipkind, 2021. "Assessment Of GDP Growth After The Corona Crisis Using The Results Of Business And Consumer Surveys," HSE Working papers WP BRP 118/STI/2021, National Research University Higher School of Economics.
    86. Deryugina, Elena & Ponomarenko, Alexey, 2014. "A large Bayesian vector autoregression model for Russia," BOFIT Discussion Papers 22/2014, Bank of Finland Institute for Emerging Economies (BOFIT).
    87. Hajer Ben Romdhane & Nahed Ben Tanfous, 2017. "Conditional FAVAR and scenario analysis for a large data: case of Tunisia," IHEID Working Papers 15-2017, Economics Section, The Graduate Institute of International Studies.
    88. Afanasyeva, Elena & Jerow, Sam & Lee, Seung Jung & Modugno, Michele, 2024. "Sowing the seeds of financial imbalances: The role of macroeconomic performance," Journal of Financial Stability, Elsevier, vol. 74(C).
    89. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
    90. Joshua C. C. Chan & Michael Pfarrhofer, 2025. "Large Bayesian VARs for Binary and Censored Variables," Papers 2506.01422, arXiv.org.
    91. Matteo Barigozzi & Luca Trapin, 2025. "Estimation of large approximate dynamic matrix factor models based on the EM algorithm and Kalman filtering," Papers 2502.04112, arXiv.org, revised May 2025.
    92. 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.
    93. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    94. Cristina Manteu & Sara Serra, 2017. "Impact of uncertainty measures on the Portuguese economy," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    95. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
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  11. Michele Modugno & Lucrezia Reichlin & Domenico Giannone & Marta Banbura, 2012. "Nowcasting with Daily Data," 2012 Meeting Papers 555, Society for Economic Dynamics.

    Cited by:

    1. Wieland, Volker & Wolters, Maik Hendrik, 2012. "Forecasting and policy making," IMFS Working Paper Series 62, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    2. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
    3. Davor Kunovac & Borna Špalat, 2014. "Nowcasting GDP Using Available Monthly Indicators," Working Papers 39, The Croatian National Bank, Croatia.
    4. Hecq, A.W. & Götz, T.B. & Urbain, J.R.Y.J., 2012. "Real-time forecast density combinations (forecasting US GDP growth using mixed-frequency data)," Research Memorandum 021, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    5. Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
    6. Park, Sungjun & Kim, Jinsoo, 2018. "The effect of interest in renewable energy on US household electricity consumption: An analysis using Google Trends data," Renewable Energy, Elsevier, vol. 127(C), pages 1004-1010.
    7. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.

  12. 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.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
    3. Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
    4. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    5. Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
    6. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    7. Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
    8. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    9. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
    10. Miroslav Klucik, 2019. "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers Working Paper No. 1/2019, Council for Budget Responsibility.
    11. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    12. Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
    13. Wieland, Volker & Wolters, Maik Hendrik, 2012. "Forecasting and policy making," IMFS Working Paper Series 62, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    14. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    15. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    16. 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.
    17. Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
    18. Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    19. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    20. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    21. Martyna Marczak & Víctor Gómez, 2017. "Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter," Empirical Economics, Springer, vol. 52(4), pages 1379-1408, June.
    22. Grant Allan & Gary Koop & Stuart McIntyre & Paul Smith, 2014. "Nowcasting Scottish GDP growth," Working Papers 1411, University of Strathclyde Business School, Department of Economics.
    23. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    24. Steven Trypsteen, 2014. "The Importance of a Time-Varying Variance and Cross-Country Interactions in Forecast Models," Discussion Papers 2014/15, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    25. Potjagailo, Galina & Wolters, Maik H, 2020. "Global financial cycles since 1880," Bank of England working papers 867, Bank of England.
    26. Bell, Venetia & Co, Lai Wah & Stone, Sophie & Wallis, gavin`, 2014. "Nowcasting UK GDP growth," Bank of England Quarterly Bulletin, Bank of England, vol. 54(1), pages 58-68.
    27. Eguren-Martin, Fernando & O’Neill, Cian & Sokol, Andrej & Berge, Lukas von dem, 2021. "Capital flows-at-risk: push, pull and the role of policy," Working Paper Series 2538, European Central Bank.
    28. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    29. Antonello D’Agostino & Jacopo Cimadomo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Papers 7, European Stability Mechanism.
    30. 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.
    31. Scott Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Realtime," Working Paper Series WP 2019-11, Federal Reserve Bank of Chicago.
    32. James H. Stock & Mark W. Watson, 2017. "Twenty Years of Time Series Econometrics in Ten Pictures," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 59-86, Spring.
    33. Thomas Gilbert & Chiara Scotti & Georg Strasser & Clara Vega, 2015. "Is the Intrinsic Value of Macroeconomic News Announcements Related to their Asset Price Impact?," Finance and Economics Discussion Series 2015-46, Board of Governors of the Federal Reserve System (U.S.).
    34. Pradeep Mishra & Khder Alakkari & Mostafa Abotaleb & Pankaj Kumar Singh & Shilpi Singh & Monika Ray & Soumitra Sankar Das & Umme Habibah Rahman & Ali J. Othman & Nazirya Alexandrovna Ibragimova & Gulf, 2021. "Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)," Data, MDPI, vol. 6(11), pages 1-15, November.
    35. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
    36. Edward P. Herbst & Fabian Winkler, 2021. "The Factor Structure of Disagreement," Finance and Economics Discussion Series 2021-046, Board of Governors of the Federal Reserve System (U.S.).
    37. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    38. Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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    180. Urasawa, Satoshi, 2014. "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 116-134.
    181. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    182. Fosten, Jack & Nandi, Shaoni, 2025. "Nowcasting U.S. state-level CO2 emissions and energy consumption," International Journal of Forecasting, Elsevier, vol. 41(1), pages 20-30.
    183. Christian Brownlees & Vladislav Morozov, 2022. "Unit Averaging for Heterogeneous Panels," Papers 2210.14205, arXiv.org, revised May 2024.
    184. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    185. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
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    187. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina, 2018. "Deutsche Konjunktur im Frühjahr 2018 - Deutsche Wirtschaft näher am Limit [German Economy Spring 2018 - German economy closer to its limit]," Kieler Konjunkturberichte 41, Kiel Institute for the World Economy (IfW Kiel).
    188. Michael Graff & Dominik Studer, 2018. "Konstruktion von Sammelindikatoren für den Konjunkturverlauf bei prekärer Datenlage am Beispiel Montenegros," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 12(3), pages 81-91, October.

  13. Reichlin, Lucrezia & Giannone, Domenico & Banbura, Marta, 2010. "Nowcasting," CEPR Discussion Papers 7883, C.E.P.R. Discussion Papers.

    Cited by:

    1. Martin Feldkircher & Florian Huber & Josef Schreiner & Marcel Tirpák & Peter Tóth & Julia Wörz, 2015. "Bridging the information gap: small-scale nowcasting models of GDP growth for selected CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 56-75.
    2. David Havrlant & Peter Tóth & Julia Wörz, 2016. "On the optimal number of indicators – nowcasting GDP growth in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 54-72.

  14. Bańbura, Marta & Modugno, Michele, 2010. "Maximum likelihood estimation of factor models on data sets with arbitrary pattern of missing data," Working Paper Series 1189, European Central Bank.

    Cited by:

    1. Baris Soybilgen & Ege Yazgan, 2017. "Nowcasting The New Turkish Gdp," Working Papers 1702, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    2. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
    3. Christina Anderl & Guglielmo Maria Caporale, 2023. "Shadow rates as a measure of the monetary policy stance: Some international evidence," Scottish Journal of Political Economy, Scottish Economic Society, vol. 70(5), pages 399-422, November.
    4. Evren Erdogan Cosar & Sevim Kosem & Cagri Sarikaya, 2013. "Do We Really Need Filters In Estimating Output Gap? : Evidence From Turkey," Working Papers 1333, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    5. Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
    6. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    7. Mr. Troy D Matheson, 2013. "The Global Financial Crisis: An Anatomy of Global Growth," IMF Working Papers 2013/076, International Monetary Fund.
    8. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation of Non-Stationary Large Approximate Dynamic Factor Models," Papers 1910.09841, arXiv.org.
    9. Maria A. Arias & Charles S. Gascon & David E. Rapach, 2014. "Metro Business Cycles," Working Papers 2014-46, Federal Reserve Bank of St. Louis.
    10. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
    11. Cleiton Guollo Taufemback, 2023. "Asymptotic Behavior of Temporal Aggregation in Mixed‐Frequency Datasets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 894-909, August.
    12. Florian Eckert & Philipp Kronenberg & Heiner Mikosch & Stefan Neuwirth, 2025. "Tracking Economic Activity With Alternative High‐Frequency Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(3), pages 270-290, April.
    13. 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.
    14. O'Rourke, Kevin & Ellison, Martin & Lee, Sang Seok, 2020. "The Ends of 27 Big Depressions," CEPR Discussion Papers 15061, C.E.P.R. Discussion Papers.
    15. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    16. Christian Bayer & Luis Calderon & Moritz Kuhn, 2025. "Distributional Dynamics," CRC TR 224 Discussion Paper Series crctr224_2025_625, University of Bonn and University of Mannheim, Germany.
    17. C. Thubin & Thomas Ferrière & Eric Monnet & Magali Marx & Vichett Oung, 2016. "The PRISME model: can disaggregation on the production side help to forecast GDP?," Working papers 596, Banque de France.
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    19. Miranda Gualdrón, Karen Alejandra & Poncela, Pilar & Ruiz Ortega, Esther, 2021. "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS 32210, Universidad Carlos III de Madrid. Departamento de Estadística.
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    24. 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.
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    42. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    43. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
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    45. Lahiri, Kajal & Yang, Cheng, 2022. "Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York," International Journal of Forecasting, Elsevier, vol. 38(2), pages 545-566.
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    47. Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
    48. 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.
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    Cited by:

    1. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2016. "Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 15-084/III, Tinbergen Institute, revised 03 Jul 2017.
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    8. Olga Korotkikh, 2020. "A Multi-Country BVAR Model for the External Sector," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 98-112, December.
    9. Rangan Gupta & Monique Reid, 2013. "Macroeconomic surprises and stock returns in South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 30(3), pages 266-282, July.
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    30. Koop, Gary & Korobilis, Dimitris, 2016. "Model uncertainty in Panel Vector Autoregressive models," European Economic Review, Elsevier, vol. 81(C), pages 115-131.
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    33. Rangan Gupta & Chi Keung Marco Lau & Vasilios Plakandaras & Wing-Keung Wong, 2019. "The role of housing sentiment in forecasting U.S. home sales growth: evidence from a Bayesian compressed vector autoregressive model," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 32(1), pages 2554-2567, January.
    34. Schreiber, Sven, 2014. "Anticipating business-cycle turning points in real time using density forecasts from a VAR," Discussion Papers 2014/2, Free University Berlin, School of Business & Economics.
    35. Haroon Mumtaz & Ahmed Pirzada & Konstantinos Theodoridis, 2018. "Non-linear effects of oil shocks on stock prices," Working Papers 865, Queen Mary University of London, School of Economics and Finance.
    36. Scheufele, Rolf & Bäurle, Gregor, 2015. "Credit cycles and real activity - the Swiss case," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112931, Verein für Socialpolitik / German Economic Association.
    37. Mehmet Balcilar & NICO KATZKE & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 15-05, Eastern Mediterranean University, Department of Economics.
    38. Tomáš Slacík & Katharina Steiner & Julia Wörz, 2014. "Can Trade Partners Help Better FORCEE the Future? Impact of Trade Linkages on Economic Growth Forecasts in Selected CESEE Countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 1, pages 36-56.
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    733. Shevelev A.A., 2017. "Bayesian approach to evaluate the impact of external shocks on Russian macroeconomics indicators," World of economics and management / Vestnik NSU. Series: Social and Economics Sciences, Socionet, vol. 17(1), pages 26-40.
    734. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    735. Olfa Kaabia & Ilyes Abid & Khaled Guesmi, 2012. "Does Bayesian Shrinkage Help to Better Reflect What Happened during the Subprime Crisis?," Working Papers hal-04141032, HAL.
    736. Heather Anderson & Giovanni Caggiano & Farshid Vahid & Benjamin Wong, 2020. "Sectoral Employment Dynamics in Australia and the COVID‐19 Pandemic," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 53(3), pages 402-414, September.
    737. Tino Berger & Lorenzo Pozzi, 2023. "Cyclical consumption," Tinbergen Institute Discussion Papers 23-064/VI, Tinbergen Institute.
    738. Farrukh Suvankulov, 2016. "Crude Oil Prices and Fixed-Asset Cash Spending in the Oil and Gas Industry: Findings from VAR Models," Staff Analytical Notes 16-8, Bank of Canada.
    739. Swamy, Vighneswara, 2020. "Macroeconomic transmission of Eurozone shocks to India—A mean-adjusted Bayesian VAR approach," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 126-150.
    740. Gupta, Rangan & Jurgilas, Marius & Kabundi, Alain, 2010. "The effect of monetary policy on real house price growth in South Africa: A factor-augmented vector autoregression (FAVAR) approach," Economic Modelling, Elsevier, vol. 27(1), pages 315-323, January.
    741. Paponpat Taveeapiradeecharoen & Popkarn Arwatchanakarn, 2025. "Forecasting Thai inflation from univariate Bayesian regression perspective," Papers 2505.05334, arXiv.org, revised May 2025.
    742. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
    743. Kexin Zhang & Simon Trimborn, 2024. "Influential assets in Large-Scale Vector AutoRegressive Models," Tinbergen Institute Discussion Papers 24-080/III, Tinbergen Institute.
    744. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    745. Petrevski, Goran & Exterkate, Peter & Tevdovski, Dragan & Bogoev, Jane, 2015. "The transmission of foreign shocks to South Eastern European economies: A Bayesian VAR approach," Economic Systems, Elsevier, vol. 39(4), pages 632-643.
    746. Felipe Leal & Carlos Molina & Eduardo Zilberman, 2020. "Proyección de la Inflación en Chile con Métodos de Machine Learning," Working Papers Central Bank of Chile 860, Central Bank of Chile.
    747. Mehdiyev, Mehdi & Ahmadov, Vugar & Huseynov, Salman & Mammadov, Fuad, 2015. "Ölkə iqtisadiyyatı üzrə göstəricilərin modelləşdirilməsi və proqnozlaşdırılması: problemlər və praktiki çətinliklər [Modeling and forecasting of macroeconomic variables of the national economy: pro," MPRA Paper 63517, University Library of Munich, Germany.
    748. Michele Campolieti & Deborah Gefang & Gary Koop, 2013. "Technical appendix to: a new look at variation in employment growth in Canada," Working Papers 26145533, Lancaster University Management School, Economics Department.
    749. Chai, Jian & Guo, Ju-E. & Meng, Lei & Wang, Shou-Yang, 2011. "Exploring the core factors and its dynamic effects on oil price: An application on path analysis and BVAR-TVP model," Energy Policy, Elsevier, vol. 39(12), pages 8022-8036.
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    751. Haruna, Issahaku, 2019. "Harnessing international remittances for financial development: The role of monetary policy," MPRA Paper 97004, University Library of Munich, Germany, revised 30 Jul 2019.
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    754. Rivolta, Giulia & Trecroci, Carmine, 2020. "Measuring the effects of U.S. uncertainty and monetary conditions on EMEs' macroeconomic dynamics," MPRA Paper 99403, University Library of Munich, Germany.
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    758. Prüser, Jan & Blagov, Boris, 2022. "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers 960, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    759. Bin Jiang & Anastasios Panagiotelis & George Athanasopoulos & Rob Hyndman & Farshid Vahid, 2016. "Bayesian Rank Selection in Multivariate Regression," Monash Econometrics and Business Statistics Working Papers 6/16, Monash University, Department of Econometrics and Business Statistics.

  16. Angelini, Elena & Rünstler, Gerhard & Bańbura, Marta, 2008. "Estimating and forecasting the euro area monthly national accounts from a dynamic factor model," Working Paper Series 953, European Central Bank.

    Cited by:

    1. Abdić Ademir & Resić Emina & Abdić Adem, 2020. "Modelling and forecasting GDP using factor model: An empirical study from Bosnia and Herzegovina," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 10-26, May.
    2. 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.
    3. Abdić Ademir & Resić Emina & Abdić Adem & Rovčanin Adnan, 2020. "Nowcasting GDP of Bosnia and Herzegovina: A Comparison of Forecast Accuracy Models," South East European Journal of Economics and Business, Sciendo, vol. 15(2), pages 1-14, December.
    4. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    5. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65, September.
    6. Gabe J. Bondt, 2019. "A PMI-Based Real GDP Tracker for the Euro Area," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(2), pages 147-170, December.
    7. Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta & Modugno, Michele, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
    8. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    9. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    10. Rünstler, Gerhard & Bańbura, Marta, 2007. "A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 751, European Central Bank.
    11. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2008. "Short-Term Forecasting of GDP Using Large Monthly Datasets: A Pseudo Real-Time Forecast Evaluation Exercise," Bank of Lithuania Working Paper Series 1, Bank of Lithuania.
    12. Pérez-Valbuena, Gerson Javier & Bonet-Morón, Jaime & Ricciulli-Marín, Diana & Barrios, Paula, 2024. "Reglas fiscales subnacionales en Colombia: desde su concepción hasta los resultados frente al COVID-19," Coyuntura Económica, Fedesarrollo, vol. 54, pages 83-142, December.
    13. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    14. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    15. Modugno, Michele, 2013. "Now-casting inflation using high frequency data," International Journal of Forecasting, Elsevier, vol. 29(4), pages 664-675.
    16. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
    17. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    18. Tretyakov, Dmitriy & Fokin, Nikita, 2020. "Помогают Ли Высокочастотные Данные В Прогнозировании Российской Инфляции? [Does the high-frequency data is helpful for forecasting Russian inflation?]," MPRA Paper 109556, University Library of Munich, Germany.
    19. Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo.
    20. Antonio José Orozco-Gallo & Pavel Vidal-Alejandro & Johana Sanabria-Domínguez & Jaime Andrés Collazos-Rodríguez, 2021. "Indicador coincidente de actividad económica en la recesión pandémica: el caso del Caribe colombiano," Documentos de Trabajo Sobre Economía Regional y Urbana 19285, Banco de la República, Economía Regional.
    21. Alain Kabundi & Elmarie Nel & Franz Ruch, 2016. "Nowcasting Real GDP growth in South Africa," Working Papers 7068, South African Reserve Bank.
    22. Katja Drechsel & Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.
    23. Lombardi, Marco J. & Godbout, Claudia, 2012. "Short-term forecasting of the Japanese economy using factor models," Working Paper Series 1428, European Central Bank.
    24. Rueben Ellul, 2016. "A real-time measure of business conditions in Malta," CBM Working Papers WP/04/2016, Central Bank of Malta.
    25. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?," ifo Working Paper Series 171, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    26. Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024. "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 3-25, June.
    27. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    28. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    29. Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
    30. Pavel Vidal Alejandro & Lya Paola Sierra Suárez & Johana Sanabria Dominguez & Jaime Andres Collazos Rodríguez, 2015. "Indicador mensual de actividad económica (IMAE) para el Valle del Cauca," Borradores de Economia 13610, Banco de la Republica.
    31. Danilo Cascaldi-Garcia & Thiago Revil T. Ferreira & Domenico Giannone & Michele Modugno, 2021. "Back to the Present: Learning about the Euro Area through a Now-casting Model," International Finance Discussion Papers 1313, Board of Governors of the Federal Reserve System (U.S.).
    32. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank, Research and Statistics Department.
    33. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    34. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    35. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    36. Knut Are Aastveit & Tørres G. Trovik, 2008. "Estimating the output gap in real time: A factor model approach," Working Paper 2008/23, Norges Bank.
    37. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    38. Muriel Nguiffo-Boyom, 2014. "2007-2013: This is what the indicator told us ? Evaluating the performance of real-time nowcasts from a dynamic factor model," BCL working papers 88, Central Bank of Luxembourg.
    39. Michele Modugno & Bariş Soybilgen & M. Ege Yazgan, 2016. "Nowcasting Turkish GDP and News Decomposition," Finance and Economics Discussion Series 2016-044, Board of Governors of the Federal Reserve System (U.S.).
    40. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    41. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    42. Boriss Siliverstovs & Konstantin A. Kholodilin, 2010. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Discussion Papers of DIW Berlin 970, DIW Berlin, German Institute for Economic Research.
    43. Lya Paola Sierra Suárez & Jaime Andrés Collazos-Rodríguez & Johana Sanabria-Domínguez & Pavel Vidal-Alejandro, 2017. "La construcción de indicadores de la actividad económica: una revisión bibliográfica," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, vol. 36(64), pages 79-107, October.
    44. Knut Aastveit & Tørres Trovik, 2012. "Nowcasting norwegian GDP: the role of asset prices in a small open economy," Empirical Economics, Springer, vol. 42(1), pages 95-119, February.
    45. Stéphanie Guichard & Elena Rusticelli, 2011. "A Dynamic Factor Model for World Trade Growth," OECD Economics Department Working Papers 874, OECD Publishing.
    46. Mahmut Günay, 2015. "Forecasting Turkish Industrial Production Growth With Static Factor Models," International Econometric Review (IER), Econometric Research Association, vol. 7(2), pages 64-78, September.
    47. Daniela Bobeva, 2021. "Nominal, Structural and Real Convergence of the EU Candidate Countries’ Economies," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(3), pages 59-78.

  17. Rünstler, Gerhard & Bańbura, Marta, 2007. "A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 751, European Central Bank.

    Cited by:

    1. Maurin, Laurent & Drechsel, Katja, 2008. "Flow of conjunctural information and forecast of euro area economic activity," Working Paper Series 925, European Central Bank.
    2. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
    3. 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.
    4. Evren Erdogan Cosar & Sevim Kosem & Cagri Sarikaya, 2013. "Do We Really Need Filters In Estimating Output Gap? : Evidence From Turkey," Working Papers 1333, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    5. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    6. Gabriele Fiorentini & Enrique Sentana, 2019. "Dynamic specification tests for dynamic factor models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 325-346, April.
    7. 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.
    8. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
    9. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    10. 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.
    11. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    12. Lamprou, Dimitra, 2016. "Nowcasting GDP in Greece: The impact of data revisions and forecast origin on model selection and performance," The Journal of Economic Asymmetries, Elsevier, vol. 14(PA), pages 93-102.
    13. Germán López, 2015. "Forecast Accuracy of Small and Large Scale Dynamic Factor Models in Developing Economies," Working Papers. Serie AD 2015-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    14. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    15. William A. Barnett & Marcelle Chauvet & Danilo Leiva-Leon & Liting Su, 2016. "Nowcasting Nominal GDP with the Credit-Card Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201605, University of Kansas, Department of Economics, revised Aug 2016.
    16. C. Thubin & Thomas Ferrière & Eric Monnet & Magali Marx & Vichett Oung, 2016. "The PRISME model: can disaggregation on the production side help to forecast GDP?," Working papers 596, Banque de France.
    17. Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta & Modugno, Michele, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
    18. Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
    19. Luke Mosley & Idris A. Eckley & Alex Gibberd, 2022. "Sparse temporal disaggregation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2203-2233, October.
    20. Lenza Michele & Warmedinger Thomas, 2011. "A Factor Model for Euro-area Short-term Inflation Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 50-62, February.
    21. 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.
    22. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2016. "Testing for Granger causality with mixed frequency data," Journal of Econometrics, Elsevier, vol. 192(1), pages 207-230.
    23. 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.
    24. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2008. "Short-Term Forecasting of GDP Using Large Monthly Datasets: A Pseudo Real-Time Forecast Evaluation Exercise," Bank of Lithuania Working Paper Series 1, Bank of Lithuania.
    25. Wanbo Lu & Yifu Wang & Xingjian Zhang, 2023. "Which news topics drive economic prosperity in China?," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-23, October.
    26. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    27. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2016. "Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 118-127, January.
    28. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2019. "Mixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland," International Journal of Central Banking, International Journal of Central Banking, vol. 15(2), pages 151-178, June.
    29. 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.
    30. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
    31. Pirschel, Inske, 2015. "Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113031, Verein für Socialpolitik / German Economic Association.
    32. Elena Angelini & Gonzalo Camba-Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2008. "Short-Term Forecasts of Euro Area GDP Growth," Working Papers ECARES ECARES 2008-035, ULB -- Universite Libre de Bruxelles.
    33. Poncela, Pilar & Ruiz Ortega, Esther, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
    34. Karim Barhoumi & V ronique Brunhes-Lesage & Olivier Darn & Laurent Ferrara & Bertrand Pluyaud & Rouvreau, B., 2008. "Monthly forecasting of French GDP: A revised version of the OPTIM model," Working papers 222, Banque de France.
    35. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
    36. Pérez-Quirós, Gabriel & Pérez, Javier J & Paredes, Joan, 2015. "Fiscal targets. A guide to forecasters?," CEPR Discussion Papers 10553, C.E.P.R. Discussion Papers.
    37. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    38. Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
    39. Liebermann, Joelle, 2010. "Real-time nowcasting of GDP: Factor model versus professional forecasters," MPRA Paper 28819, University Library of Munich, Germany.
    40. Andreou, Elena & Gagliardini, Patrick & Ghysels, Eric & Rubin, Mirco, 2017. "Is Industrial Production Still the Dominant Factor for the US Economy?," CEPR Discussion Papers 12219, C.E.P.R. Discussion Papers.
    41. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an Uncertain Economic Environment," Tinbergen Institute Discussion Papers 14-152/III, Tinbergen Institute.
    42. 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.
    43. Audrone Jakaitiene & Stephane Dees, 2012. "Forecasting the World Economy in the Short Term," The World Economy, Wiley Blackwell, vol. 35(3), pages 331-350, March.
    44. Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
    45. Döhrn, Roland & an de Meulen, Philipp & Barabas, György & Gebhardt, Heinz & Kitlinski, Tobias & Micheli, Martin & Schmidt, Torsten & Vosen, Simeon & Zimmermann, Lina, 2011. "Die wirtschaftliche Entwicklung im Inland: Zunehmende Risiken für die Konjunktur," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 62(2), pages 41-90.
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    757. Paponpat Taveeapiradeecharoen & Popkarn Arwatchanakarn, 2025. "Forecasting Thai inflation from univariate Bayesian regression perspective," Papers 2505.05334, arXiv.org, revised May 2025.
    758. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
    759. Kexin Zhang & Simon Trimborn, 2024. "Influential assets in Large-Scale Vector AutoRegressive Models," Tinbergen Institute Discussion Papers 24-080/III, Tinbergen Institute.
    760. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
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Articles

  1. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    See citations under working paper version above.
  2. Bańbura, Marta & Bobeica, Elena & Bodnár, Katalin & Fagandini, Bruno & Healy, Peter & Paredes, Joan, 2023. "Underlying inflation measures: an analytical guide for the euro area," Economic Bulletin Boxes, European Central Bank, vol. 5.

    Cited by:

    1. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.
    2. Martín Almuzara & Argia M. Sbordone, 2024. "Measurement and Theory of Core Inflation," Staff Reports 1115, Federal Reserve Bank of New York.
    3. Stefano Neri, 2024. "There has been an awakening. The rise (and fall) of inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 834, Bank of Italy, Economic Research and International Relations Area.

  3. Bańbura, Marta & Saiz, Lorena, 2020. "Short-term forecasting of euro area economic activity at the ECB," Economic Bulletin Articles, European Central Bank, vol. 2.

    Cited by:

    1. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    2. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.

  4. 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.
    See citations under working paper version above.
  5. Marta Bańbura & Michele Modugno, 2014. "Maximum Likelihood Estimation Of Factor Models On Datasets With Arbitrary Pattern Of Missing Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 133-160, January.
    See citations under working paper version above.
  6. Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
    See citations under working paper version above.
  7. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    See citations under working paper version above.
  8. Elena Angelini & Marta Banbura & Gerhard Rünstler, 2010. "Estimating and forecasting the euro area monthly national accounts from a dynamic factor model," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-22.
    See citations under working paper version above.

Chapters

  1. Marta Bańbura & Michele Lenza & Joan Paredes, 2024. "Forecasting inflation in the US and in the euro area," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 9, pages 218-245, Edward Elgar Publishing.

    Cited by:

    1. Bobeica, Elena & Holton, Sarah & Huber, Florian & Martínez Hernández, Catalina, 2025. "Beware of large shocks! A non-parametric structural inflation model," Working Paper Series 3052, European Central Bank.
    2. Bańbura, Marta & Bobeica, Elena & Giammaria, Alessandro & Porqueddu, Mario & van Spronsen, Josha, 2025. "A new model to forecast energy inflation in the euro area," Working Paper Series 3062, European Central Bank.

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