Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data
Author
Abstract
Suggested Citation
DOI: 10.1002/for.2944
Download full text from publisher
References listed on IDEAS
- 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.
- Marta Bańbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92, January.
- Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
- Gabriele Di Filippo, 2015. "Dynamic Model Averaging and CPI Inflation Forecasts: A Comparison between the Euro Area and the United States," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(8), pages 619-648, December.
- Massimiliano Marcellino, 2008. "A linear benchmark for forecasting GDP growth and inflation?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 305-340.
- Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
- Messner, Jakob W. & Pinson, Pierre, 2019. "Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1485-1498.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, 2025. "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Roberto S. Mariano & Yasutomo Murasawa, 2010. "A Coincident Index, Common Factors, and Monthly Real GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 27-46, February.
- Troy D. Matheson, 2014.
"New indicators for tracking growth in real time,"
OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 51-71.
- Mr. Troy D Matheson, 2011. "New Indicators for Tracking Growth in Real Time," IMF Working Papers 2011/043, International Monetary Fund.
- repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
- Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022.
"Nowcasting with large Bayesian vector autoregressions,"
Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
- Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2020. "Nowcasting with large Bayesian vector autoregressions," Working Paper Series 2453, European Central Bank.
- Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
- Francis X. Diebold, 2020.
"Real-Time Real Economic Activity:Exiting the Great Recession and Entering the Pandemic Recession,"
PIER Working Paper Archive
20-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold, 2020. "Real-Time Real Economic Activity: Exiting the Great Recession and Entering the Pandemic Recession," NBER Working Papers 27482, National Bureau of Economic Research, Inc.
- Patrick C. Higgins, 2014. "GDPNow: A Model for GDP \"Nowcasting\"," FRB Atlanta Working Paper 2014-7, Federal Reserve Bank of Atlanta.
- Mr. Jean-Francois Dauphin & Mr. Kamil Dybczak & Morgan Maneely & Marzie Taheri Sanjani & Mrs. Nujin Suphaphiphat & Yifei Wang & Hanqi Zhang, 2022. "Nowcasting GDP - A Scalable Approach Using DFM, Machine Learning and Novel Data, Applied to European Economies," IMF Working Papers 2022/052, International Monetary Fund.
- de Bondt, Gabe J. & Hahn, Elke & Zekaite, Zivile, 2021. "ALICE: Composite leading indicators for euro area inflation cycles," International Journal of Forecasting, Elsevier, vol. 37(2), pages 687-707.
- Jacopo Cimadomo & Antonello D'Agostino, 2016.
"Combining Time Variation and Mixed Frequencies: an Analysis of Government Spending Multipliers in Italy,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1276-1290, November.
- D'Agostino, Antonello & Cimadomo, Jacopo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Paper Series 1856, European Central Bank.
- 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.
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
- Fabio Canova & Filippo Ferroni, 2011.
"Multiple filtering devices for the estimation of cyclical DSGE models,"
Quantitative Economics, Econometric Society, vol. 2(1), pages 73-98, March.
- Fabio Canova & Filippo Ferroni, 2009. "Multiple filtering devices for the estimation of cyclical DSGE models," Economics Working Papers 1135, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2010.
- Filippo Ferroni & Fabio Canova, 2015. "Multiple Filtering Devices for the Estimation of Cyclical DSGE Models," Working Papers 498, Barcelona School of Economics.
- Jing Cynthia Wu & Fan Dora Xia, 2016.
"Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 253-291, March.
- Jing Cynthia Wu & Fan Dora Xia, 2014. "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," NBER Working Papers 20117, National Bureau of Economic Research, Inc.
- Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021.
"Nowcasting GDP using machine-learning algorithms: A real-time assessment,"
International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
- 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.
- Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP Using Machine Learning Algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting GDP using machine learning algorithms: A real-time assessment," Reserve Bank of New Zealand Discussion Paper Series DP2019/03, Reserve Bank of New Zealand.
- Claudia Foroni & Massimiliano Marcellino & Christian Schumacher, 2015. "Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 57-82, January.
- Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
- Jing Cynthia Wu & Fan Dora Xia, 2020.
"Negative interest rate policy and the yield curve,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 653-672, September.
- Jing Cynthia Wu & Fan Dora Xia, 2018. "Negative Interest Rate Policy and the Yield Curve," NBER Working Papers 25180, National Bureau of Economic Research, Inc.
- Dora Xia & Jing Cynthia Wu, 2018. "The negative interest rate policy and the yield curve," BIS Working Papers 703, Bank for International Settlements.
- Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
- Kirstin Hubrich & Frauke Skudelny, 2017.
"Forecast Combination for Euro Area Inflation: A Cure in Times of Crisis?,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 515-540, August.
- Kirstin Hubrich & Frauke Skudelny, 2016. "Forecast Combination for Euro Area Inflation - A Cure in Times of Crisis?," Finance and Economics Discussion Series 2016-104, Board of Governors of the Federal Reserve System (U.S.).
- Hubrich, Kirstin & Skudelny, Frauke, 2016. "Forecast combination for euro area inflation: a cure in times of crisis?," Working Paper Series 1972, European Central Bank.
- JÖrg Breitung & Christoph Roling, 2015. "Forecasting Inflation Rates Using Daily Data: A Nonparametric MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 588-603, November.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- 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.
- Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023.
"Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany,"
Discussion Papers
34/2023, Deutsche Bundesbank.
- Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2024. "Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany," Working Paper Series 2930, European Central Bank.
- Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
- Konstantin Boss & Luigi Longo & Luca Onorante, 2025. "Nowcasting the euro area with social media data," Papers 2506.10546, arXiv.org.
- Barış Soybilgen & M. Ege Yazgan & Hüseyin Kaya, 2023. "Nowcasting Turkish Food Inflation Using Daily Online Prices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 171-190, September.
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.- Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
- 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, July.
- Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
- Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
- Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
- Kuusela, Annika & Hännikäinen, Jari, 2017. "What do the shadow rates tell us about future inflation?," MPRA Paper 80542, University Library of Munich, Germany.
- Kaustubh, Kaustubh & Ranjan, Abhishek, 2025. "A multi-factor GDP nowcast model for India," Economic Modelling, Elsevier, vol. 147(C).
- Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
- Raul Ibarra & Luis M. Gomez-Zamudio, 2017.
"Are Daily Financial Data Useful for Forecasting GDP? Evidence from Mexico,"
Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 173-203.
- Gómez-Zamudio, Luis M. & Ibarra, Raúl, 2017. "Are daily financial data useful for forecasting GDP? Evidence from Mexico," LSE Research Online Documents on Economics 123310, London School of Economics and Political Science, LSE Library.
- Ibarra-Ramírez Raúl & Gómez-Zamudio Luis M., 2017. "Are daily financial data useful for forecasting GDP? Evidence from Mexico," Working Papers 2017-17, Banco de México.
- Bekiros Stelios & Paccagnini Alessia, 2015.
"Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
- Stelios D. Bekiros & Alessia Paccagnini, 2014. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Open Access publications 10197/7588, School of Economics, University College Dublin.
- 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).
- Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
- Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
- Cross, Jamie L. & Hou, Chenghan & Poon, Aubrey, 2020. "Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity," International Journal of Forecasting, Elsevier, vol. 36(3), pages 899-915.
- 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.
- Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022.
"How is machine learning useful for macroeconomic forecasting?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
- Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022.
"The global component of inflation volatility,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
- Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
- Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
- Gianluca Cubadda, 2025.
"VAR Models with an Index Structure: A Survey with New Results,"
Econometrics, MDPI, vol. 13(4), pages 1-17, October.
- Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org, revised Sep 2025.
- Gianluca Cubadda, 2025. "VAR Models With An Index Structure: A Survey With New Results," CEIS Research Paper 611, Tor Vergata University, CEIS, revised 22 Sep 2025.
- Grassi, Stefano & Proietti, Tommaso & Frale, Cecilia & Marcellino, Massimiliano & Mazzi, Gianluigi, 2015.
"EuroMInd-C: A disaggregate monthly indicator of economic activity for the Euro area and member countries,"
International Journal of Forecasting, Elsevier, vol. 31(3), pages 712-738.
- Cecilia Frale & Stefano Grassi & Massimiliano Marcellino & Gianluigi Mazzi & Tommaso Proietti, 2013. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries," CEIS Research Paper 287, Tor Vergata University, CEIS, revised 01 Oct 2013.
Corrections
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:wly:jforec:v:42:y:2023:i:3:p:464-480. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/wly/jforec/v42y2023i3p464-480.html