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Andrea Carriero

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. 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.

    Mentioned in:

    1. > Econometrics > Forecasting > Nowcasting
    2. > Econometrics > Time Series Models > VAR Models > Time Varying Parameters and Stochastic Volatility
  2. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.

    Mentioned in:

    1. > 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. Andrea Carriero & Sarah Mouabbi & Elisabetta Vangelista, 2018. "UK term structure decompositions at the zero lower bound," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 643-661, August.

    Mentioned in:

    1. UK term structure decompositions at the zero lower bound (Journal of Applied Econometrics 2018) in ReplicationWiki ()
  2. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2011. "Forecasting large datasets with Bayesian reduced rank multivariate models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 735-761, August.

    Mentioned in:

    1. Forecasting large datasets with Bayesian reduced rank multivariate models (Journal of Applied Econometrics 2011) in ReplicationWiki ()

Working papers

  1. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2024. "Specification Choices in Quantile Regression for Empirical Macroeconomics," CEPR Discussion Papers 18901, C.E.P.R. Discussion Papers.

    Cited by:

    1. 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.
    2. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    3. Kevin Moran & Dalibor Stevanovic & Stéphane Surprenant, 2025. "Risk Scenarios and Macroeconomic Forecasts," Staff Working Papers 25-28, Bank of Canada.

  2. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org, revised Sep 2025.

    Cited by:

    1. Byeungchun Kwon & Taejin Park & Phurichai Rungcharoenkitkul & Frank Smets, 2025. "Parsing the pulse: decomposing macroeconomic sentiment with LLMs," BIS Working Papers 1294, Bank for International Settlements.
    2. Umberto Collodel, 2025. "Interpreting the Interpreter: Can We Model post-ECB Conferences Volatility with LLM Agents?," Papers 2508.13635, arXiv.org, revised Oct 2025.

  3. Andrea Carriero & Massimiliano Marcellino & Tommaso Tornese, 2023. "Blended Identification in Structural VARs," BAFFI CAREFIN Working Papers 23200, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Robin Braun, 2023. "The importance of supply and demand for oil prices: Evidence from non‐Gaussianity," Quantitative Economics, Econometric Society, vol. 14(4), pages 1163-1198, November.
    2. Christiane Baumeister, 2025. "Comment on "Local Projections or VARs? A Primer for Macroeconomists"," NBER Chapters, in: NBER Macroeconomics Annual 2025, volume 40, National Bureau of Economic Research, Inc.
    3. 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.
    4. Jan Pruser, 2024. "A large non-Gaussian structural VAR with application to Monetary Policy," Papers 2412.17598, arXiv.org.
    5. Dimitris Korobilis, 2025. "Exploring Monetary Policy Shocks with Large-Scale Bayesian VARs," Papers 2505.06649, arXiv.org.

  4. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.

    Cited by:

    1. Anushka Mitra, 2025. "Imperfect Information and Slow Recoveries in the Labor Market," International Finance Discussion Papers 1423, Board of Governors of the Federal Reserve System (U.S.).
    2. Ciccarelli, Matteo & Marotta, Fulvia, 2024. "Demand or Supply? An empirical exploration of the effects of climate change on the macroeconomy," Energy Economics, Elsevier, vol. 129(C).

  5. Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Harrison Katz & Robert E. Weiss, 2025. "Bayesian Shrinkage in High-Dimensional VAR Models: A Comparative Study," Papers 2504.05489, arXiv.org, revised Feb 2026.
    2. Shovon Sengupta & Sunny Kumar Singh & Tanujit Chakraborty, 2025. "Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks," Papers 2510.23347, arXiv.org.
    3. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    4. Florian Huber & Karin Klieber & Massimiliano Marcellino & Luca Onorante & Michael Pfarrhofer, 2024. "Asymmetries in Financial Spillovers," Papers 2410.16214, arXiv.org.
    5. Mattera, Raffaele & Franses, Philip Hans, 2025. "Forecasting house price growth rates with factor models and spatio-temporal clustering," International Journal of Forecasting, Elsevier, vol. 41(1), pages 398-417.
    6. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.

  6. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.

    Cited by:

    1. Shovon Sengupta & Bhanu Pratap & Amit Pawar, 2025. "Non-linear Phillips Curve for India: Evidence from Explainable Machine Learning," Papers 2504.05350, arXiv.org.
    2. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    3. Artemova, Mariia, 2025. "An order-invariant score-driven dynamic factor model," Journal of Econometrics, Elsevier, vol. 251(C).
    4. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    5. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    6. Demetrescu, Matei & Kruse-Becher, Robinson, 2025. "Is U.S. real output growth non-normal? A tale of time-varying location and scale," Journal of Economic Dynamics and Control, Elsevier, vol. 171(C).
    7. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    8. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    9. Florian Huber, 2023. "Bayesian Nonlinear Regression using Sums of Simple Functions," Papers 2312.01881, arXiv.org.
    10. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    11. Daniele Valenti & Andrea Bastianin & Matteo Manera, 2022. "A weekly structural VAR model of the US crude oil market," Working Papers 2022.11, Fondazione Eni Enrico Mattei.
    12. Freddy Garc'ia-Alb'an & Juan Jarr'in, 2025. "Tracking the economy at high frequency," Papers 2507.07450, arXiv.org.
    13. Keijsers, Bart & van Dijk, Dick, 2025. "Does economic uncertainty predict real activity in real time?," International Journal of Forecasting, Elsevier, vol. 41(2), pages 748-762.
    14. Davidson, Sharada Nia & Moccero, Diego Nicolas, 2024. "The nonlinear effects of banks’ vulnerability to capital depletion in euro area countries," Working Paper Series 2912, European Central Bank.
    15. Morão, Hugo, 2024. "An economic policy uncertainty index for Portugal," International Economics, Elsevier, vol. 178(C).
    16. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    17. Evgenidis, Anastasios & Fasianos, Apostolos, 2023. "Modelling monetary policy’s impact on labour markets under Covid-19," Economics Letters, Elsevier, vol. 230(C).
    18. Arabinda Basistha, "undated". "Estimates of Quarterly and Monthly Episodes of Global Recessions: Evidence from Markov-switching Dynamic Factor Models," Working Papers 24-07, Department of Economics, West Virginia University.
    19. Hwee Kwan Chow & Keen Meng Choy, 2023. "Economic forecasting in a pandemic: some evidence from Singapore," Empirical Economics, Springer, vol. 64(5), pages 2105-2124, May.
    20. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    21. Colunga-Ramos, Luis Fernando & Cepeda, Leonardo E. Torre, 2024. "Regional supply, demand and labor shocks on the manufacturing sector during COVID-19 in Mexico," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(2).
    22. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).
    23. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2024. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Post-Print hal-05056934, HAL.
    24. Laura Liu & Yulong Wang, 2025. "Binary Outcome Models with Extreme Covariates: Estimation and Prediction," Papers 2502.16041, arXiv.org.
    25. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    26. 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.
    27. 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.
    28. 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.
    29. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    30. Barauskaitė Griškevičienė, Kristina & Nguyen, Anh D.M. & Rousová, Linda & Cappiello, Lorenzo, 2022. "The impact of credit supply shocks in the euro area: market-based financing versus loans," Working Paper Series 2673, European Central Bank.
    31. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    32. Frank Schorfheide & Dongho Song, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," NBER Working Papers 29535, National Bureau of Economic Research, Inc.
    33. Leonardo N. Ferreira & Haroon Mumtaz & Ana Skoblar, 2025. "Stochastic Volatility-in-mean VARs with Time-Varying Skewness," Papers 2510.08415, arXiv.org.
    34. Budnik, Katarzyna & Groß, Johannes & Vagliano, Gianluca & Dimitrov, Ivan & Lampe, Max & Panos, Jiri & Velasco, Sofia & Boucherie, Louis & Jančoková, Martina, 2023. "BEAST: A model for the assessment of system-wide risks and macroprudential policies," Working Paper Series 2855, European Central Bank.
    35. Chan, Joshua C.C., 2023. "Comparing stochastic volatility specifications for large Bayesian VARs," Journal of Econometrics, Elsevier, vol. 235(2), pages 1419-1446.
    36. Sun, Weihong & Liu, Ding, 2023. "Great moderation with Chinese characteristics: Uncovering the role of monetary policy," Economic Modelling, Elsevier, vol. 121(C).
    37. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
    38. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    39. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.
    40. Colunga L. Fernando & Torre Cepeda Leonardo, 2023. "Effects of Supply, Demand, and Labor Market Shocks in the Mexican Manufacturing Sector," Working Papers 2023-10, Banco de México.
    41. Budnik, Katarzyna & Ponte Marques, Aurea & Giglio, Carla & Grassi, Alberto & Durrani, Agha & Figueres, Juan Manuel & Konietschke, Paul & Le Grand, Catherine & Metzler, Julian & Población García, Franc, 2024. "Advancements in stress-testing methodologies for financial stability applications," Occasional Paper Series 348, European Central Bank.
    42. Chen, Sihan & Ming, Lei & Yang, Haoxi & Yang, Shenggang, 2025. "Iterated Dynamic Model Averaging and application to inflation forecasting," International Review of Financial Analysis, Elsevier, vol. 102(C).
    43. Serena Ng, 2021. "Modeling Macroeconomic Variations after Covid-19," NBER Working Papers 29060, National Bureau of Economic Research, Inc.
    44. Júlio, Paulo & Maria, José R., 2024. "Trends and cycles during the COVID-19 pandemic period," Economic Modelling, Elsevier, vol. 139(C).
    45. Morley, James & Rodríguez-Palenzuela, Diego & Sun, Yiqiao & Wong, Benjamin, 2023. "Estimating the euro area output gap using multivariate information and addressing the COVID-19 pandemic," European Economic Review, Elsevier, vol. 153(C).
    46. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    47. Martin Iseringhausen & Konstantinos Theodoridis, 2025. "A survey-based measure of asymmetric macroeconomic risk in the euro area," Working Papers 68, European Stability Mechanism, revised 11 Feb 2025.
    48. Durand, Luigi & Fornero, Jorge Alberto, 2024. "Estimating the output gap in times of COVID-19," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(4).
    49. Basistha, Arabinda, 2025. "A Markov-switching dynamic factor framework for dating global economic cycles," Journal of International Money and Finance, Elsevier, vol. 157(C).
    50. Domenech Palacios, Mar, 2025. "Firms’ risk and monetary transmission: revisiting the excess bond premium," Working Paper Series 3118, European Central Bank.
    51. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2023. "Modelling Okun’s law: Does non-Gaussianity matter?," Empirical Economics, Springer, vol. 64(5), pages 2183-2213, May.
    52. Cubadda, Gianluca & Grassi, Stefano & Guardabascio, Barbara, 2025. "The time-varying Multivariate Autoregressive Index model," International Journal of Forecasting, Elsevier, vol. 41(1), pages 175-190.
    53. Juvonen, Petteri & Lindblad, Annika, 2025. "Nowcasting in real time: Large Bayesian vector autoregression in a test," Bank of Finland Research Discussion Papers 6/2025, Bank of Finland.
    54. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    55. Anton I. Votinov & Julia A. Polshchikova & Karen A. Nersisyan, 2025. "Macroeconomic Modeling in Post-pandemic Times," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 62-73, February.
    56. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," Working Papers 21-08R, Federal Reserve Bank of Cleveland, revised 12 Jul 2022.
    57. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.
    58. Andrejs Zlobins, 2021. "On the Time-varying Effects of the ECB's Asset Purchases," Working Papers 2021/02, Latvijas Banka.
    59. Danilo Cascaldi-Garcia, 2022. "Pandemic Priors," International Finance Discussion Papers 1352, Board of Governors of the Federal Reserve System (U.S.).
    60. Granados, Camilo & Parra-Amado, Daniel, 2024. "Estimating the output gap after COVID: How to address unprecedented macroeconomic variations," Economic Modelling, Elsevier, vol. 135(C).
    61. Allayioti, Anastasia & Gόrnicka, Lucyna & Holton, Sarah & Martínez Hernández, Catalina, 2024. "Monetary policy pass-through to consumer prices: evidence from granular price data," Working Paper Series 3003, European Central Bank.
    62. Alessandro Morico & Ovidijus Stauskas, 2025. "Robust Tests for Factor-Augmented Regressions with an Application to the novel EA-MD-QD Dataset," Papers 2504.08455, arXiv.org, revised Nov 2025.
    63. Barend Abeln & Jan P.A.M. Jacobs, 2021. "COVID19 and Seasonal Adjustment," CIRANO Working Papers 2021s-05, CIRANO.
    64. Diego Fresoli, 2024. "Spanish GDP short-term point and density forecasting using a mixed-frequency dynamic factor model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 15(2), pages 145-177, June.
    65. Dimitris Korobilis, 2025. "Exploring Monetary Policy Shocks with Large-Scale Bayesian VARs," Papers 2505.06649, arXiv.org.
    66. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    67. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    68. Zacharias Bragoudakis & Ioannis Krompas, 2025. "Greek GDP Forecasting Using Bayesian Multivariate Models," Bulletin of Applied Economics, Risk Market Journals, vol. 12(2), pages 63-76.
    69. Celani, Alessandro & Pedini, Luca, 2025. "Moderate Time-Varying Parameter VARs," Working Papers 2025:16, Örebro University, School of Business.
    70. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.

  7. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.

    Cited by:

    1. Szendrei, Tibor & Varga, Katalin, 2023. "Revisiting vulnerable growth in the Euro Area: Identifying the role of financial conditions in the distribution," Economics Letters, Elsevier, vol. 223(C).
    2. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    3. Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2023. "Fiscal Policy Regimes in Resource-Rich Economies," Working Papers No 13/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    4. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    5. Michal Franta & Jan Vlcek, 2025. "Inflation at Risk: The Czech Case," Working Papers 2025/8, Czech National Bank, Research and Statistics Department.
    6. Falconio, Andrea & Manganelli, Simone, 2020. "Financial conditions, business cycle fluctuations and growth at risk," Working Paper Series 2470, European Central Bank.
    7. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024. "Labour at risk," European Economic Review, Elsevier, vol. 170(C).
    8. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    9. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    10. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    11. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    12. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.
    13. Kevin Moran & Dalibor Stevanovic & Stéphane Surprenant, 2024. "Risk Scenarios and Macroeconomic Impacts: Insights for Canadian Policy," CIRANO Working Papers 2024s-03, CIRANO.
    14. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022. "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, vol. 46(PA).
    15. Andrey Polbin & Andrei Shumilov, 2025. "Nowcasting and forecasting Russian GDP and its components using quantile models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 79, pages 5-26.
    16. Deng, Chuang & Wu, Jian, 2023. "Macroeconomic downside risk and the effect of monetary policy," Finance Research Letters, Elsevier, vol. 54(C).
    17. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    18. Mihail Yanchev, 2022. "Deep Growth-at-Risk Model: Nowcasting the 2020 Pandemic Lockdown Recession in Small Open Economies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 7, pages 20-41.
    19. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    20. Sui, Jianli & Lv, Wenqiang & Gao, Xiang & Koedijk, Kees G., 2024. "China’s GDP-at-Risk: Real-Time Monitoring, Risk Tracing, and Macroeconomic Policy Effects," Journal of International Money and Finance, Elsevier, vol. 147(C).
    21. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    22. Tobias Adrian & Domenico Giannone & Matteo Luciani & Mike West, 2025. "Scenario Synthesis and Macroeconomic Risk," Papers 2505.05193, arXiv.org.
    23. Diana Lima & Ivan De Lorenzo Buratta, 2025. "The vulnerability channel: assessing the impact of financial conditions on the output gap," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    24. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    25. Huang, Yu-Fan & Liao, Wenting & Luo, Sui & Ma, Jun, 2024. "Financial conditions, macroeconomic uncertainty, and macroeconomic tail risks," Journal of Economic Dynamics and Control, Elsevier, vol. 163(C).
    26. Kevin Moran & Dalibor Stevanovic & Stephane Surprenant, 2024. "Risk Scenarios and Macroeconomic Forecasts," Working Papers 24-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised May 2025.
    27. Yannick Hoga & Christian Schulz, 2025. "Self-Normalized Inference in (Quantile, Expected Shortfall) Regressions for Time Series," Papers 2502.10065, arXiv.org, revised Jun 2025.
    28. Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
    29. Liu, Han & Wang, Lijun & Zhuo, Xingxuan, 2025. "Unveiling the shadows: The effects of financial conditions on the tail risks of China's macroeconomic activities," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 1-14.
    30. Adams, Patrick A. & Adrian, Tobias & Boyarchenko, Nina & Giannone, Domenico, 2021. "Forecasting macroeconomic risks," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1173-1191.
    31. Carboni, Giacomo & Fonseca, Luís & Fornari, Fabio & Urrutia, Leonardo, 2026. "Structural drivers of growth at risk: insights from a VAR-quantile regression approach," Working Paper Series 3171, European Central Bank.
    32. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2025. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 57-73, January.

  8. Andrea Carriero & Massimiliano Marcellino & Tommaso Tornese, 2022. "Macro Uncertainty in the Long Run," BAFFI CAREFIN Working Papers 22188, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Mathias Krogh & Giovanni Pellegrino, "undated". "Real Activity and Uncertainty Shocks: The Long and the Short of It," "Marco Fanno" Working Papers 0310, Dipartimento di Scienze Economiche "Marco Fanno".
    2. Andrzej Cieślik & Mehmet Burak Turgut, 2024. "Uncertainty and long-run economy: the role of R &D and business dynamism," Empirical Economics, Springer, vol. 66(4), pages 1403-1441, April.
    3. Bacchiocchi, Emanuele & Dragomirescu-Gaina, Catalin, 2024. "Uncertainty spill-overs: When policy and financial realms overlap," Journal of International Money and Finance, Elsevier, vol. 143(C).

  9. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2020. "Measuring Uncertainty and Its Effects in the COVID-19 Era," Working Papers 20-32R, Federal Reserve Bank of Cleveland, revised 05 Jan 2022.

    Cited by:

    1. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    2. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.
    3. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).

  10. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," CEPR Discussion Papers 13970, C.E.P.R. Discussion Papers.

    Cited by:

    1. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    2. Nektarios Aslanidis & Aurelio Bariviera & George Kapetanios & Vasilis Sarafidis, 2025. "Heterogeneous Exposures to Systematic and Idiosyncratic Risk across Crypto Assets: A Divide-and-Conquer Approach," Papers 2506.21100, arXiv.org.
    3. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    4. Iader Giraldo & Carlos Giraldo & Jos� E. Gomez-Gonzalez & Jorge Mario Uribe, 2023. "US uncertainty shocks, credit, production, and prices: The case of fourteen Latin American countries," Documentos de trabajo 20667, FLAR.
    5. Arce-Alfaro, Gabriel, 2025. "The economic implications of oil supply uncertainty," Energy Economics, Elsevier, vol. 145(C).
    6. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    7. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    8. Bobasu, Alina & Geis, André & Quaglietti, Lucia & Ricci, Martino, 2021. "Tracking global economic uncertainty: implications for the euro area," Working Paper Series 2541, European Central Bank.
    9. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).
    10. Shen, Yifan & He, Jia & Shi, Xunpeng & Zeng, Ting, 2025. "Uncertainty, macroeconomic activity and commodity price: A global analysis," International Review of Financial Analysis, Elsevier, vol. 101(C).
    11. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
    12. 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).
    13. Lodge, David & Pérez, Javier J. & Albrizio, Silvia & Everett, Mary & De Bandt, Olivier & Georgiadis, Georgios & Ca' Zorzi, Michele & Lastauskas, Povilas & Carluccio, Juan & Parraga Rodriguez, Susana &, 2021. "The implications of globalisation for the ECB monetary policy strategy," Occasional Paper Series 263, European Central Bank.
    14. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2021. ""Vulnerable Funding in the Global Economy"," IREA Working Papers 202106, University of Barcelona, Research Institute of Applied Economics, revised Mar 2021.
    15. Ogbuabor, Jonathan E. & Ukwueze, Ezebuilo R. & Mba, Ifeoma C. & Ojonta, Obed I. & Orji, Anthony, 2023. "The asymmetric impact of economic policy uncertainty on global retail energy markets: Are the markets responding to the fear of the unknown?," Applied Energy, Elsevier, vol. 334(C).
    16. Andreas Dibiasi & Samad Sarferaz, 2020. "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers 2006.09007, arXiv.org, revised Dec 2020.
    17. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    18. Arigoni, Filippo & Lenarčič, Črt, 2023. "Foreign economic policy uncertainty shocks and real activity in the Euro area," MPRA Paper 120022, University Library of Munich, Germany.
    19. Gomez-Gonzalez, Jose Eduardo & Hirs-Garzon, Jorge & Uribe, Jorge M., 2020. "Global effects of US uncertainty: real and financial shocks on real and financial markets," Working papers 69, Red Investigadores de Economía.
    20. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Uribe, Jorge M., 2024. "US uncertainty shocks on real and financial markets: A multi-country perspective," Economic Systems, Elsevier, vol. 48(3).
    21. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    22. Cubadda, Gianluca & Grassi, Stefano & Guardabascio, Barbara, 2025. "The time-varying Multivariate Autoregressive Index model," International Journal of Forecasting, Elsevier, vol. 41(1), pages 175-190.
    23. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    24. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    25. Bonciani, Dario & Ricci, Martino, 2020. "The international effects of global financial uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 109(C).
    26. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    27. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    28. Baxa, Jaromír & Šestořád, Tomáš, 2025. "Common and country-specific uncertainty shocks in europe: Why their nature matters for policy," Economic Modelling, Elsevier, vol. 150(C).
    29. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    30. Wu, Ping, 2024. "Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility," International Journal of Forecasting, Elsevier, vol. 40(3), pages 903-917.
    31. Nina Biljanovska & Francesco Grigoli & Martina Hengge, 2021. "Fear thy neighbor: Spillovers from economic policy uncertainty," Review of International Economics, Wiley Blackwell, vol. 29(2), pages 409-438, May.
    32. Jaromir Baxa & Tomas Sestorad, 2024. "Economic Policy Uncertainty in Europe: Spillovers and Common Shocks," Working Papers 2024/9, Czech National Bank, Research and Statistics Department.

  11. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Endogenous Uncertainty," Working Papers (Old Series) 1805, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Qazi Haque & Leandro M. Magnusson & Kazuki Tomioka, 2021. "Empirical Evidence on the Dynamics of Investment Under Uncertainty in the U.S," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1193-1217, October.
    2. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
    3. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
    4. Gian Paulo Soave, 2020. "International Drivers of Policy Uncertainty in Emerging Economies," Economics Bulletin, AccessEcon, vol. 40(1), pages 716-726.

  12. 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.

    Cited by:

    1. Luis J. Álvarez & Maria Dolores Gadea & Ana Gómez‐Loscos, 2021. "Inflation comovements in advanced economies: Facts and drivers," The World Economy, Wiley Blackwell, vol. 44(2), pages 485-509, February.
    2. Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019. "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers) 1225, Bank of Italy, Economic Research and International Relations Area.
    3. Ascari, Guido & Fosso, Luca, 2024. "The international dimension of trend inflation," Journal of International Economics, Elsevier, vol. 148(C).
    4. Kim, Won Joong & Ko, Juyoung & Kwon, Won Soon & Piao, Chunyan, 2025. "Time-varying sources of fluctuations in global inflation," Economic Modelling, Elsevier, vol. 143(C).
    5. Ignacio Garr'on & C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "International vulnerability of inflation," Papers 2410.20628, arXiv.org, revised Oct 2024.
    6. Francesco Corsello & Alex Tagliabracci, 2023. "Assessing the pass-through of energy prices to inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 745, Bank of Italy, Economic Research and International Relations Area.
    7. Lodge, David & Pérez, Javier J. & Albrizio, Silvia & Everett, Mary & De Bandt, Olivier & Georgiadis, Georgios & Ca' Zorzi, Michele & Lastauskas, Povilas & Carluccio, Juan & Parraga Rodriguez, Susana &, 2021. "The implications of globalisation for the ECB monetary policy strategy," Occasional Paper Series 263, European Central Bank.
    8. Efrem Castelnuovo, 2019. "Domestic and Global Uncertainty: A Survey and Some New Results," CESifo Working Paper Series 7900, CESifo.
    9. İbrahim Özmen & Şerife Özşahin, 2023. "Effects of global energy and price fluctuations on Turkey's inflation: new evidence," Economic Change and Restructuring, Springer, vol. 56(4), pages 2695-2728, August.
    10. Cai, Yan & Li, Yanyun & Lin, Faqin & Yan, Wenshou, 2025. "The direct and indirect effects of trade policy uncertainty on the volatility of world agricultural prices," Journal of Asian Economics, Elsevier, vol. 100(C).
    11. Jongrim Ha & M. Ayhan Kose & Franziska Ohnsorge & Hakan Yilmazkuday, 2023. "What Explains Global Inflation," Koç University-TUSIAD Economic Research Forum Working Papers 2310, Koc University-TUSIAD Economic Research Forum.
    12. Casalin, Fabrizio & Cerniglia, Floriana & Dia, Enzo, 2023. "Stock-flow adjustments, public debt management and interest costs," Economic Modelling, Elsevier, vol. 129(C).
    13. Jiang, Yanhui & Qu, Bo & Hong, Yun & Xiao, Xiyue, 2024. "Dynamic connectedness of inflation around the world: A time-varying approach from G7 and E7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 111-125.
    14. Koirala, Niraj P. & Nyiwul, Linus, 2023. "Inflation volatility: A Bayesian approach," Research in Economics, Elsevier, vol. 77(1), pages 185-201.
    15. Gabriel Rodríguez & Luis Surco, 2024. "Modeling the trend, persistence, and volatility of inflation in Pacific Alliance countries: an empirical application using a model with inflation bands," Documentos de Trabajo / Working Papers 2024-533, Departamento de Economía - Pontificia Universidad Católica del Perú.
    16. Martin Feldkircher & Pierre L. Siklos, 2018. "Global Inflation Dynamics and Inflation Expectations," CAMA Working Papers 2018-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Lorenzo Burlon & Alessandro Notarpietro & Massimiliano Pisani, 2018. "Exchange rate pass-through into euro area inflation. An estimated structural model," Temi di discussione (Economic working papers) 1192, Bank of Italy, Economic Research and International Relations Area.
    18. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    19. Lenin Arango-Castillo & María José Orraca & Regina Briseño, 2025. "Inflation volatility across advanced and emerging economies during the COVID-19 pandemic," Working Papers 2025-13, Banco de México.
    20. Cubadda, Gianluca & Grassi, Stefano & Guardabascio, Barbara, 2025. "The time-varying Multivariate Autoregressive Index model," International Journal of Forecasting, Elsevier, vol. 41(1), pages 175-190.
    21. Garrón Vedia, Ignacio & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2024. "International vulnerability of inflation," DES - Working Papers. Statistics and Econometrics. WS 44814, Universidad Carlos III de Madrid. Departamento de Estadística.
    22. Stefano Neri & Fabio Busetti & Cristina Conflitti & Francesco Corsello & Davide Delle Monache & Alex Tagliabracci, 2023. "Energy price shocks and inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 792, Bank of Italy, Economic Research and International Relations Area.
    23. Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org, revised Sep 2025.
    24. Ilaria De Angelis & Guido de Blasio & Lucia Rizzica, 2018. "On the unintended effects of public transfers: evidence from EU funding to Southern Italy," Temi di discussione (Economic working papers) 1180, Bank of Italy, Economic Research and International Relations Area.
    25. Stefano Neri & Stefano Siviero, 2019. "The non-standard monetary policy measures of the ECB: motivations, effectiveness and risks," Questioni di Economia e Finanza (Occasional Papers) 486, Bank of Italy, Economic Research and International Relations Area.
    26. Luis J. Álvarez & Ana Gómez-Loscos & María Dolores Gadea, 2019. "Inflation interdependence in advanced economies," Working Papers 1920, Banco de España.
    27. Aysun, Uluc & Wright, Cardel, 2024. "A two-step dynamic factor modelling approach for forecasting inflation in small open economies," Emerging Markets Review, Elsevier, vol. 62(C).
    28. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High‐Dimensional Vector Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1123-1152, October.

  13. A. Carriero & Sarah Mouabbi & E. Vangelista, 2016. "UK term structure decompositions at the zero lower bound," Working papers 589, Banque de France.

    Cited by:

    1. Kim, Young Min & Kang, Kyu Ho & Ka, Kook, 2020. "Do bond markets find inflation targets credible? Evidence from five inflation-targeting countries," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 66-84.
    2. Jens Christensen & Sarah Mouabbi, 2024. "The Natural Rate of Interest in the Euro Area: Evidence from Inflation-Indexed Bonds," Working papers 948, Banque de France.
    3. Schupp, Fabian, 2020. "The (ir)relevance of the nominal lower bound for real yield curve analysis," Discussion Papers 32/2020, Deutsche Bundesbank.
    4. Beauregard, Remy & Christensen, Jens H.E. & Fischer, Eric & Zhu, Simon, 2024. "Inflation expectations and risk premia in emerging bond markets: Evidence from Mexico," Journal of International Economics, Elsevier, vol. 151(C).
    5. Zhou, Siwen, 2018. "Measuring the Signaling Effect of the ECB’s Asset Purchase Programme at the Effective Lower Bound," MPRA Paper 87084, University Library of Munich, Germany.
    6. Kavanagh, Ella & Zhu, Sheng & O’Sullivan, Niall, 2022. "Monetary policy, trade-offs and the transmission of UK Monetary Policy," Journal of Policy Modeling, Elsevier, vol. 44(6), pages 1128-1147.
    7. Etienne Vaccaro-Grange, 2019. "Quantitative Easing and the Term Premium as a Monetary Policy Instrument," Working Papers halshs-02359503, HAL.
    8. Cristhian Hernando Ruiz Cardozo & Jens H. E. Christensen, 2024. "The Benefit of Inflation-Indexed Debt: Evidence from an Emerging Bond Market," Working Paper Series 2023-04, Federal Reserve Bank of San Francisco.
    9. Lemke, Wolfgang & Vladu, Andreea L., 2016. "Below the zero lower bound: A shadow-rate term structure model for the euro area," Discussion Papers 32/2016, Deutsche Bundesbank.
    10. Roussellet, Guillaume, 2025. "The term structure of macroeconomic risks at the effective lower bound," Journal of Econometrics, Elsevier, vol. 248(C).
    11. Adam Golinski & Sophie Guilloux-Nefussi & Jean-Paul Renne, 2025. "The Shadow Rate Model: Let’s Make it Real!," Working papers 1014, Banque de France.
    12. Coroneo, Laura & Pastorello, Sergio, 2020. "European spreads at the interest rate lower bound," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    13. Albert K. Tsui & Junxiang Wu & Zhaoyong Zhang & Zhongxi Zheng, 2023. "Forecasting term structure of the Japanese bond yields in the presence of a liquidity trap," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1205-1227, August.
    14. Alain Monfort & Fulvio Pegoraro & Jean-Paul Renne & Guillaume Roussellet, 2017. "Staying at zero with affine processes : an application to term structure modelling," Rue de la Banque, Banque de France, issue 52, november.
    15. Boeckx, Jef & Iania, Leonardo & Wauters, Joris, 2023. "Macroeconomic drivers of Inflation Expectations and Inflation Risk Premia," LIDAM Discussion Papers LFIN 2023003, Université catholique de Louvain, Louvain Finance (LFIN).

  14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Gian Paulo Soave, 2023. "A panel threshold VAR with stochastic volatility-in-mean model: an application to the effects of financial and uncertainty shocks in emerging economies," Applied Economics, Taylor & Francis Journals, vol. 55(4), pages 397-431, January.
    2. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2017. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," CEPII Policy Brief 2017-20, CEPII research center.
    3. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2018. "Economic Policy Uncertainty Spillovers in Booms and Busts," "Marco Fanno" Working Papers 0220, Dipartimento di Scienze Economiche "Marco Fanno".
    4. Ma, Xiaohan & Samaniego, Roberto, 2020. "The macroeconomic impact of oil earnings uncertainty: New evidence from analyst forecasts," Energy Economics, Elsevier, vol. 90(C).
    5. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    6. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2022. "The macroeconomic impact of economic uncertainty and financial shocks under low and high financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    7. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    8. Juan M. Londono & Sai Ma & Beth Anne Wilson, 2025. "The Global Transmission of Real Economic Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 57(5), pages 1103-1133, August.
    9. Xianbo Zhou & Zhuoran Chen, 2023. "The Impact of Uncertainty Shocks to Consumption under Different Confidence Regimes Based on a Stochastic Uncertainty-in-Mean TVAR Model," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    10. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    11. Karamysheva, Madina, 2022. "How do fiscal adjustments work? An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    12. Fabio Bertolotti & Massimiliano Marcellino, 2019. "Tax shocks with high and low uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 972-993, September.
    13. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2021. "The Real Effects of Financial Uncertainty Shocks: A Daily Identification Approach," Documentos de Trabajo 559, Instituto de Economia. Pontificia Universidad Católica de Chile..
    14. Magnus, Jan R. & Pijls, Henk G.J. & Sentana, Enrique, 2021. "The Jacobian of the exponential function," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    15. Hernández Vega Marco A., 2021. "The Nonlinear Effect of Uncertainty in Portfolio Flows to Mexico," Working Papers 2021-11, Banco de México.
    16. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Yoosoon Chang & Ana María Herrera & Elena Pesavento, 2023. "Oil prices uncertainty, endogenous regime switching, and inflation anchoring," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 820-839, September.
    18. Popiel Michal Ksawery, 2020. "Fiscal policy uncertainty and US output," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    19. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    20. Joonseok Oh, 2020. "The Propagation Of Uncertainty Shocks: Rotemberg Versus Calvo," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(3), pages 1097-1113, August.
    21. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    22. Luca Rossi, 2020. "Indicators of uncertainty: a brief user’s guide," Questioni di Economia e Finanza (Occasional Papers) 564, Bank of Italy, Economic Research and International Relations Area.
    23. Arce-Alfaro, Gabriel, 2025. "The economic implications of oil supply uncertainty," Energy Economics, Elsevier, vol. 145(C).
    24. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    25. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    26. Liao, Wenting & Ma, Jun & Zhang, Chengsi, 2024. "Commodity returns co-movement, uncertainty shocks, and the US dollar exchange rate," Journal of International Money and Finance, Elsevier, vol. 143(C).
    27. Tosapol Apaitan & Pongsak Luangaram & Pym Manopimoke, 2020. "Uncertainty and Economic Activity: Does it Matter for Thailand?," PIER Discussion Papers 130, Puey Ungphakorn Institute for Economic Research.
    28. González-Sánchez, Mariano & Nave, Juan & Rubio, Gonzalo, 2020. "Effects of uncertainty and risk aversion on the exposure of investment-style factor returns to real activity," Research in International Business and Finance, Elsevier, vol. 53(C).
    29. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    30. Ganwen Zheng & Songping Zhu, 2021. "Research on the Effectiveness of China’s Macro Control Policy on Output and Technological Progress under Economic Policy Uncertainty," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    31. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    32. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).
    33. Hauzenberger, Niko & Böck, Maximilian & Pfarrhofer, Michael & Stelzer, Anna & Zens, Gregor, 2018. "Implications of macroeconomic volatility in the Euro area," ESRB Working Paper Series 80, European Systemic Risk Board.
    34. Aviral Kumar Tiwari & Micheal Kofi Boachie & Rangan Gupta, 2019. "Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory," Working Papers 201982, University of Pretoria, Department of Economics.
    35. Karaki, Mohamad B. & Rangaraju, Sandeep Kumar, 2023. "The confidence channel of U.S. financial uncertainty: Evidence from industry-level data," Economic Modelling, Elsevier, vol. 129(C).
    36. Jafari, Mahboubeh, 2024. "Uncertainty and entrepreneurship in oil-rich developing countries: Does institution matter?," Resources Policy, Elsevier, vol. 99(C).
    37. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2021. "The regional transmission of uncertainty shocks on income inequality in the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 887-900.
    38. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    39. Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers 2020s-47, CIRANO.
    40. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
    41. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    42. 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).
    43. Marco Brianti, 2021. "Financial Shocks, Uncertainty Shocks, and Monetary Policy Trade-Offs," Working Papers 2021-05, University of Alberta, Department of Economics.
    44. Siye Bae & Soojin Jo & Myungkyu Shim, 2025. "Does Economic Policy Uncertainty differ from other uncertainty measures? Replication of Baker, Bloom, and Davis (2016)," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 58(1), pages 40-74, February.
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    Cited by:

    1. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    2. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    3. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    4. Petrova, Katerina, 2019. "A quasi-Bayesian local likelihood approach to time varying parameter VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 286-306.
    5. Harry Turunen & Anastasia Zhutova & Matthieu Lemoine, 2023. "Stochastic Simulation of the FR-BDF Model and an Assessment of Uncertainty around Conditional Forecasts," Working papers 920, Banque de France.
    6. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper Series 43, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    7. Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
    8. Bognanni, Mark, 2022. "Comment on “Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors”," Journal of Econometrics, Elsevier, vol. 227(2), pages 498-505.
    9. Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
    10. David Kohns & Galina Potjagailo, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    11. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2023. "Time-varying impacts of monetary policy uncertainty on China's housing market," Economic Modelling, Elsevier, vol. 118(C).
    12. Dellaportas, Petros & Titsias, Michalis K. & Petrova, Katerina & Plataniotis, Anastasios, 2023. "Scalable inference for a full multivariate stochastic volatility model," Journal of Econometrics, Elsevier, vol. 232(2), pages 501-520.

  16. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2015. "Structural Analysis with Multivariate Autoregressive Index Models," CEPR Discussion Papers 10801, C.E.P.R. Discussion Papers.

    Cited by:

    1. Gianluca Cubadda & Alain Hecq, 2021. "Reduced Rank Regression Models in Economics and Finance," CEIS Research Paper 525, Tor Vergata University, CEIS, revised 08 Nov 2021.
    2. Alain Hecq & Ivan Ricardo & Ines Wilms, 2024. "Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach," Papers 2407.07973, arXiv.org.
    3. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    4. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2016. "Structural analysis with Multivariate Autoregressive Index models," Journal of Econometrics, Elsevier, vol. 192(2), pages 332-348.
    5. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    6. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    7. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
    8. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2020. "The economic drivers of volatility and uncertainty," Temi di discussione (Economic working papers) 1285, Bank of Italy, Economic Research and International Relations Area.
    9. 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.
    10. Monica Billio & Roberto Casarin & Sylvia Kaufmann & Matteo Iacopini, 2018. "Bayesian Dynamic Tensor Regression," Working Papers 2018:13, Department of Economics, University of Venice "Ca' Foscari".
    11. Mike G. Tsionas, 2016. "Alternative Bayesian compression in Vector Autoregressions and related models," Working Papers 216, Bank of Greece.
    12. Mike G. Tsionas, 2016. "Alternatives to large VAR, VARMA and multivariate stochastic volatility models," Working Papers 217, Bank of Greece.
    13. Gianluca Cubadda & Barbara Guardabascio, 2017. "Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model," CEIS Research Paper 397, Tor Vergata University, CEIS, revised 13 Jul 2018.
    14. Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org, revised Sep 2025.
    15. Huang, Feiqing & Lu, Kexin & Zheng, Yao & Li, Guodong, 2025. "Supervised factor modeling for high-dimensional linear time series," Journal of Econometrics, Elsevier, vol. 249(PB).
    16. Gianluca Cubadda & Marco Mazzali, 2023. "The Vector Error Correction Index Model: Representation, Estimation and Identification," CEIS Research Paper 556, Tor Vergata University, CEIS, revised 04 Apr 2023.

  17. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    2. Martin Feldkircher & Florian Huber, 2016. "Unconventional US Monetary Policy: New Tools, Same Channels?," Department of Economics Working Papers wuwp222, Vienna University of Economics and Business, Department of Economics.
    3. Martin Feldkircher & Elizaveta Lukmanova & Gabriele Tondl, 2019. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," Department of Economics Working Papers wuwp289, Vienna University of Economics and Business, Department of Economics.
    4. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    5. Florian Huber & Thomas Zörner, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Papers wuwp250, Vienna University of Economics and Business, Department of Economics.
    6. Joshua Chan & Arnaud Doucet & Roberto Leon-Gonzalez & Rodney W. Strachan, 2018. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," GRIPS Discussion Papers 18-12, National Graduate Institute for Policy Studies.
    7. Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.
    8. Feldkircher Martin & Gruber Thomas & Huber Florian, 2019. "International effects of a compression of euro area yield curves," Working Papers in Economics 2019-1, University of Salzburg.
    9. Emmanuel C. Mamatzakis & Steven Ongena & Mike G. Tsionas, 2023. "The response of household debt to COVID-19 using a neural networks VAR in OECD," Empirical Economics, Springer, vol. 65(1), pages 65-91, July.
    10. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    11. MOLTENI, Francesco, PAPPA, Evi, 2017. "The Combination of Monetary and Fiscal Policy Shocks: A TVP-FAVAR Approach," Economics Working Papers MWP 2017/13, European University Institute.
    12. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.

  18. Kristle Romero Cortes & Philip E. Strahan, 2014. "Tracing Out Capital Flows: How Financially Integrated Banks Respond to Natural Disasters," Working Papers (Old Series) 1412, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Thomas Bassetti & Lorenzo Dal Maso & Valentina Pieroni, 2025. "Firms’ borrowing costs and neighbors’ flood risk," Small Business Economics, Springer, vol. 64(3), pages 917-933, March.
    2. Noth, Felix & Rehbein, Oliver, 2019. "Badly hurt? Natural disasters and direct firm effects," Finance Research Letters, Elsevier, vol. 28(C), pages 254-258.
    3. Wang, Teng, 2021. "Local banks and the effects of oil price shocks," Journal of Banking & Finance, Elsevier, vol. 125(C).
    4. Giovanni Dell'Ariccia & Dalida Kadyrzhanova & Camelia Minoiu & Lev Ratnovski, 2020. "Bank Lending in the Knowledge Economy," Finance and Economics Discussion Series 2020-040, Board of Governors of the Federal Reserve System (U.S.).
    5. João Granja & Christian Leuz & Raghuram Rajan, 2018. "Going the Extra Mile: Distant Lending and Credit Cycles," NBER Working Papers 25196, National Bureau of Economic Research, Inc.
    6. Attila, Joseph & Combes, Jean-Louis & Ouedraogo, Rasmané, 2025. "Natural disasters and bank liquidity creation in Sub-Saharan African countries: Evidence from banks panel data," The Quarterly Review of Economics and Finance, Elsevier, vol. 100(C).
    7. Elizabeth A. Berger & Nathan Seegert, 2024. "Half Banked: The Economic Impact of Cash Management in the Marijuana Industry," Journal of Finance, American Finance Association, vol. 79(4), pages 2759-2796, August.
    8. Stefano Federico & Fadi Hassan & Veronica Rappoport, 2020. "Trade shocks and credit reallocation," Temi di discussione (Economic working papers) 1289, Bank of Italy, Economic Research and International Relations Area.
    9. Duqi, Andi & McGowan, Danny & Onali, Enrico & Torluccio, Giuseppe, 2021. "Natural disasters and economic growth: The role of banking market structure," Journal of Corporate Finance, Elsevier, vol. 71(C).
    10. Aguilar-Gomez, Sandra & Gutierrez, Emilio & Heres, David & Jaume, David & Tobal, Martin, 2024. "Thermal stress and financial distress: Extreme temperatures and firms’ loan defaults in Mexico," Journal of Development Economics, Elsevier, vol. 168(C).
    11. Petkov, Ivan, 2023. "Small business lending and the bank-branch network," Journal of Financial Stability, Elsevier, vol. 64(C).
    12. Kakuho Furukawa & Hibiki Ichiue & Noriyuki Shiraki, 2020. "How Does Climate Change Interact with the Financial System? A Survey," Bank of Japan Working Paper Series 20-E-8, Bank of Japan.
    13. Hua Song & Yudong Yang & Zheng Tao, 2020. "How different types of financial service providers support small- and medium- enterprises under the impact of COVID-19 pandemic: from the perspective of expectancy theory," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-27, December.
    14. Chakraborty, Indraneel & Goldstein, Itay & MacKinlay, Andrew, 2020. "Monetary stimulus and bank lending," Journal of Financial Economics, Elsevier, vol. 136(1), pages 189-218.
    15. Czura, Kristina & Klonner, Stefan, 2023. "Financial market responses to a natural disaster: Evidence from credit networks and the Indian Ocean tsunami," Journal of Development Economics, Elsevier, vol. 160(C).
    16. Roman Horvath, 2020. "Natural Catastrophes and Financial Development: An Empirical Analysis," Working Papers IES 2020/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2020.
    17. Franziska Bremus & Malte Rieth, 2023. "Integrating Out Natural Disaster Shocks," Discussion Papers of DIW Berlin 2063, DIW Berlin, German Institute for Economic Research.
    18. Ivan Petkov, 2022. "Weather Shocks, Population, and Housing Prices: the Role of Expectation Revisions," Economics of Disasters and Climate Change, Springer, vol. 6(3), pages 495-540, November.
    19. Schüwer, Ulrich & Lambert, Claudia & Noth, Felix, 2017. "How do banks react to catastrophic events? Evidence from Hurricane Katrina," SAFE Working Paper Series 94, Leibniz Institute for Financial Research SAFE, revised 2017.
    20. Koetter, Michael & Noth, Felix & Rehbein, Oliver, 2020. "Borrowers under water! Rare disasters, regional banks, and recovery lending," Journal of Financial Intermediation, Elsevier, vol. 43(C).
    21. Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2018. "Shock Contagion, Asset Quality and Lending Behavior," Working Papers 01/2018, National Bank of Ukraine.
    22. Feng, Zhi-Yuan & Wang, Chou-Wen & Lu, Yu-Hong, 2022. "The impact of climatic disaster on corporate investment policy," Journal of Multinational Financial Management, Elsevier, vol. 66(C).
    23. Kilian Huber, 2020. "Are Bigger Banks Better? Firm-Level Evidence from Germany," CESifo Working Paper Series 8746, CESifo.
    24. Allen N. Berger & Filippo Curti & Nika Lazaryan & Atanas Mihov & Raluca A. Roman, 2023. "Climate Risks in the U.S. Banking Sector: Evidence from Operational Losses and Extreme Storms," Working Papers 21-31, Federal Reserve Bank of Philadelphia.
    25. Ivan Faiella & Filippo Natoli, 2018. "Natural catastrophes and bank lending: the case of flood risk in Italy," Questioni di Economia e Finanza (Occasional Papers) 457, Bank of Italy, Economic Research and International Relations Area.
    26. Shi, Yining, 2022. "Financial liberalization and house prices: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 145(C).
    27. Trinh, Hai Hong & Tran, Thao Phuong, 2024. "Global banking systems, financial stability, and uncertainty: How have countries coped with geopolitical risks?," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    28. Avril, Pauline & Levieuge, Grégory & Turcu, Camelia, 2025. "Natural disasters and financial stress: can macroprudential regulation tame green swans?," Journal of International Money and Finance, Elsevier, vol. 154(C).
    29. Dou, Yiwei & Hung, Mingyi & She, Guoman & Wang, Lynn Linghuan, 2024. "Learning from peers: Evidence from disclosure of consumer complaints," Journal of Accounting and Economics, Elsevier, vol. 77(2).
    30. Braun, Alexander & Braun, Julia & Weigert, Florian, 2023. "Extreme weather risk and the cost of equity," CFR Working Papers 23-08, University of Cologne, Centre for Financial Research (CFR).
    31. James R. Brown & Matthew T. Gustafson & Ivan T. Ivanov, 2021. "Weathering Cash Flow Shocks," Journal of Finance, American Finance Association, vol. 76(4), pages 1731-1772, August.
    32. Erel, Isil & Liebersohn, Jack, 2022. "Can FinTech reduce disparities in access to finance? Evidence from the Paycheck Protection Program," Journal of Financial Economics, Elsevier, vol. 146(1), pages 90-118.
    33. Vinzenz Peters, 2025. "How Banks are Impacted by and Mediate the Economic Consequences of Natural Disasters and Climate Shocks: A Review," De Economist, Springer, vol. 173(1), pages 47-85, March.
    34. Mercy Berman DeMenno, 2023. "Environmental sustainability and financial stability: can macroprudential stress testing measure and mitigate climate-related systemic financial risk?," Journal of Banking Regulation, Palgrave Macmillan, vol. 24(4), pages 445-473, December.
    35. Holod, Dmytro & Torna, Gökhan, 2018. "Do community banks contribute to international trade? Evidence from U.S. Data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 185-204.
    36. Sebastian Doerr & Philipp Schaz, 2018. "Bank loan supply during crises: the importance of geographic diversification," ECON - Working Papers 288, Department of Economics - University of Zurich, revised Mar 2019.
    37. Noth, Felix & Schüwer, Ulrich, 2023. "Natural disasters and bank stability: Evidence from the U.S. financial system," Journal of Environmental Economics and Management, Elsevier, vol. 119(C).
    38. Wang, Jiaxin & Zhu, Zhaowei & Huang, Xiang, 2023. "Stock bubbles under sudden public crises: A perspective from the excessive financialization of firms," Finance Research Letters, Elsevier, vol. 57(C).
    39. Flynn, Sean & Wang, Jing, 2025. "Social connections and bank deposits," Journal of Banking & Finance, Elsevier, vol. 178(C).
    40. Wu, Baohui & Wen, Fenghua & Zhang, Yun & Huang, Zhijian (James), 2024. "Climate risk and the systemic risk of banks: A global perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 95(C).
    41. Ruchi Avtar & Kristian S. Blickle & Rajashri Chakrabarti & Janavi Janakiraman & Maxim L. Pinkovskiy, 2023. "Understanding the Linkages between Climate Change and Inequality in the United States," Economic Policy Review, Federal Reserve Bank of New York, vol. 29(1), pages 1-39, June.
    42. Victor Aguirregabiria & Robert Clark & Hui Wang, 2024. "The geographic flow of bank funding and access to credit: Branch networks, local synergies and competition," Papers 2407.03517, arXiv.org.
    43. Ryan, Alexander, 2025. "Financial Risks in Flooding: Bank Response to Climate-Induced Natural Disasters," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO 360730, Agricultural and Applied Economics Association.
    44. Nguyen, Harvey & Pham, Anh Viet & Pham, Man Duy (Marty) & Pham, Mia Hang, 2025. "Climate change and corporate credit worthiness: International evidence," Global Finance Journal, Elsevier, vol. 64(C).
    45. Waheed Ullah Shah & Ibtissem Missaoui & Ijaz Younis & Xiyu Liu, 2025. "Climate risk co-movements effect on South Asia’s emerging stock market for financial inclusion," Future Business Journal, Springer, vol. 11(1), pages 1-20, December.
    46. José-Luis Peydró [AP BACKUP – NOW EXTERNAL] & Salih Fendoğlu & Eda Gülşen & José-Luis Peydró, 2019. "Global Liquidity and Impairment of Local Monetary Policy," Working Papers 1131, Barcelona School of Economics.
    47. Barth, James R. & Hu, Qinyou & Sickles, Robin & Sun, Yanfei & Yu, Xiaoyu, 2024. "Direct and indirect impacts of natural disasters on banks: A spatial framework," Journal of Financial Stability, Elsevier, vol. 70(C).
    48. Cuñat, Vicente & Cvijanovic, Dragana & Yuan, Kathy, 2018. "Within-bank spillovers of real estate shocks," LSE Research Online Documents on Economics 87374, London School of Economics and Political Science, LSE Library.
    49. Antonio Forte & Selay Sahan & Damiano B. Silipo, 2024. "Do Natural Disasters Reduce Loans to the More CO 2 -Emitting Sectors?," Sustainability, MDPI, vol. 16(10), pages 1-24, May.
    50. Thiago Christiano Silva & Paulo Victor Berri Wilhelm & Solange Maria Guerra, 2025. "Weathering the Storm: how supply chains adapt to extreme climate events," Working Papers Series 613, Central Bank of Brazil, Research Department.
    51. Wan-Li Zhang & Chun-Ping Chang & Yang Xuan, 2022. "The impacts of climate change on bank performance: What’s the mediating role of natural disasters?," Economic Change and Restructuring, Springer, vol. 55(3), pages 1913-1952, August.
    52. Rubio-Andrés, Mercedes & Ramos-González, Mª del Mar & Sastre-Castillo, Miguel Ángel & Gutiérrez-Broncano, Santiago, 2023. "Stakeholder pressure and innovation capacity of SMEs in the COVID-19 pandemic: Mediating and multigroup analysis," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    53. Nuno Paixao, 2019. "Propagation of House Price Shocks through the Banking System," 2019 Meeting Papers 1237, Society for Economic Dynamics.
    54. Huang, Xiaowei & Cheng, Ge & Zhang, Man, 2025. "Climate change risk and real estate prices—Micro evidence from coastal cities in China," Pacific-Basin Finance Journal, Elsevier, vol. 90(C).
    55. Markus Herrmann & Martin Hibbeln, 2023. "Trading and liquidity in the catastrophe bond market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(2), pages 283-328, June.
    56. Allen, Kyle D. & Whitledge, Matthew D. & Winters, Drew B., 2022. "Community bank liquidity: Natural disasters as a natural experiment," Journal of Financial Stability, Elsevier, vol. 60(C).
    57. Teng Liu, 2024. "Save the Farms: Nonlinear Impact of Climate Change on Banks' Agricultural Lending," Papers 2409.19463, arXiv.org.
    58. Schüwer, Ulrich & Gropp, Reint E. & Noth, Felix, 2016. "What drives banks' geographic expansion? The role of locally non-diversifiable risk," VfS Annual Conference 2016 (Augsburg): Demographic Change 145885, Verein für Socialpolitik / German Economic Association.
    59. Smolyansky, Michael, 2019. "Policy externalities and banking integration," Journal of Financial Economics, Elsevier, vol. 132(3), pages 118-139.
    60. Seungho Lee & Md Zahangir Alam, 2024. "The impact of climate risk on bank profitability through liquidity creation channel: empirical evidence from G7 countries," Journal of Asset Management, Palgrave Macmillan, vol. 25(7), pages 726-739, December.
    61. Agus Sugiarto & Ni Nyoman Puspani & Mustika Septiyas Trisilia, 2023. "The Shocks of Climate Change on Bank Loans," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 493-514, September.
    62. Garbarino, Nicola & Guin, Benjamin, 2021. "High water, no marks? Biased lending after extreme weather," Journal of Financial Stability, Elsevier, vol. 54(C).
    63. Eid, Nourhan & Yang, Junhong & Duygun, Meryem, 2024. "Bridging the credit gap: The influence of regional bank structure on the expansion of peer-to-peer lending," The British Accounting Review, Elsevier, vol. 56(6).
    64. Li, Jie & An, Yahui & Wang, Lidan & Zhang, Yongjie, 2022. "Combating the COVID-19 pandemic: The role of disaster experience," Research in International Business and Finance, Elsevier, vol. 60(C).
    65. Doerr, Sebastian & Schaz, Philipp, 2021. "Geographic diversification and bank lending during crises," Journal of Financial Economics, Elsevier, vol. 140(3), pages 768-788.
    66. Henry He Huang & Joseph Kerstein & Chong Wang & Feng (Harry) Wu, 2022. "Firm climate risk, risk management, and bank loan financing," Strategic Management Journal, Wiley Blackwell, vol. 43(13), pages 2849-2880, December.
    67. Martin R. Goetz & Juan Carlos Gozzi, 2020. "Financial Integration and the Co-Movement of Economic Activity: Evidence from U.S. States," International Finance Discussion Papers 1305, Board of Governors of the Federal Reserve System (U.S.).
    68. Matteo Alessi & Ilaria Manti & Luca Santabarbara, 2024. "Natural Disasters, Local banking, and Recovery lending: evidence from an Italian earthquake," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(6), pages 1-2.
    69. Douglas Kiarelly Godoy de Araujo & Fernando Linardi & Luis Vissotto, 2025. "Supply chain transmission of climate-related physical risks," BIS Working Papers 1260, Bank for International Settlements.
    70. Benincasa, Emanuela & Betz, Frank & Gattini, Luca, 2024. "How do firms cope with losses from extreme weather events?," Journal of Corporate Finance, Elsevier, vol. 84(C).
    71. Bayangos, Veronica B. & Cachuela, Rafael Augusto D. & Prado, Fatima Lourdes E. Del, 2021. "Impact of extreme weather episodes on the Philippine banking sector – Evidence using branch-level supervisory data," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(1).
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    74. Pauline Avril & Gregory Levieuge & Camelia Turcu, 2023. "Do bankers want their umbrellas back when it rains? Evidence from typhoons in China," Working Papers 2023.08, International Network for Economic Research - INFER.
    75. Dmytro Holod & Joe Peek & Gökhan Torna, 2024. "Relationship Lending: That Ship Has Not Sailed for Community Banks," Working Papers 24-5, Federal Reserve Bank of Boston.
    76. Kristian S. Blickle & Evan Perry & João A. C. Santos, 2024. "Do Mortgage Lenders Respond to Flood Risk?," Staff Reports 1101, Federal Reserve Bank of New York.
    77. Celil, Hursit S. & Oh, Seungjoon & Selvam, Srinivasan, 2022. "Natural disasters and the role of regional lenders in economic recovery," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 116-132.
    78. Ge, Shan & Weisbach, Michael S., 2021. "The role of financial conditions in portfolio choices: The case of insurers," Journal of Financial Economics, Elsevier, vol. 142(2), pages 803-830.
    79. Sebastian Doerr & Thomas Drechsel & Donggyu Lee, 2021. "Income inequality, financial intermediation, and small firms," BIS Working Papers 944, Bank for International Settlements.
    80. Marcinkowska, Monika & Brzeszczyński, Janusz & Charteris, Ailie & Gajdka, Jerzy & Obojska, Lidia & Szczygielski, Jan Jakub, 2025. "Sustainability, energy finance and the role of central banks: A review of current insights and future research directions," Energy Economics, Elsevier, vol. 144(C).
    81. Xu, Minhong & Xu, Yilan, 2023. "Do non-damaging earthquakes shake mortgage lenders' risk perception?," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    82. Zhang, Jiang, 2025. "International information flow and market quality," Journal of Banking & Finance, Elsevier, vol. 173(C).
    83. Bos, Jaap W.B. & Li, Runliang & Sanders, Mark W.J.L., 2022. "Hazardous lending: The impact of natural disasters on bank asset portfolio," Economic Modelling, Elsevier, vol. 108(C).
    84. Cortés, Kristle R. & Demyanyk, Yuliya & Li, Lei & Loutskina, Elena & Strahan, Philip E., 2020. "Stress tests and small business lending," Journal of Financial Economics, Elsevier, vol. 136(1), pages 260-279.
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    87. Brei, Michael & Mohan, Preeya & Strobl, Eric, 2019. "The impact of natural disasters on the banking sector: Evidence from hurricane strikes in the Caribbean," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 232-239.
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    89. Francisco Zabala Aguayo & Beata Ślusarczyk, 2020. "Risks of Banking Services’ Digitalization: The Practice of Diversification and Sustainable Development Goals," Sustainability, MDPI, vol. 12(10), pages 1-10, May.
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    94. Hashimoto, Ryuichiro & Sudo, Nao, 2024. "Transmission of flood damage to the real economy and financial intermediation: Simulation analysis using a DSGE model," Journal of Environmental Economics and Management, Elsevier, vol. 128(C).
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    115. Lee, Chien-Chiang & Wang, Chih-Wei & Thinh, Bui Tien & Xu, Zhi-Ting, 2022. "Climate risk and bank liquidity creation: International evidence," International Review of Financial Analysis, Elsevier, vol. 82(C).
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    123. Giovanni Calice & Yong Kyu Gam, 2023. "US National Banks and Local Economic Fragility," Journal of Financial Services Research, Springer;Western Finance Association, vol. 63(3), pages 313-338, June.
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    128. Radoslav Raykov & Consuelo Silva-Buston, 2018. "Multibank Holding Companies and Bank Stability," Staff Working Papers 18-51, Bank of Canada.
    129. Shala, Iliriana & Schumacher, Benno, 2022. "The impact of natural disasters on banks' impairment flow: Evidence from Germany," Discussion Papers 36/2022, Deutsche Bundesbank.
    130. Bos, Jaap & Li, Runliang & Sanders, Mark, 2018. "Hazardous Lending: The Impact of Natural Disasters on Banks'Asset Portfolio," Research Memorandum 021, Maastricht University, Graduate School of Business and Economics (GSBE).
    131. Pedro Gete & Athena Tsouderou & Susan M. Wachter, 2024. "Climate risk in mortgage markets: Evidence from Hurricanes Harvey and Irma," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 52(3), pages 660-686, May.
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    133. Kristian S. Blickle & Sarah Ngo Hamerling & Donald P. Morgan, 2021. "How Bad Are Weather Disasters for Banks?," Staff Reports 990, Federal Reserve Bank of New York.
    134. Victor Orestes & Thiago Silva & Henry Zhang, 2025. "Volatility and Under-Insurance in Economies with Limited Pledgeability: evidence from a frost shock," Working Papers Series 628, Central Bank of Brazil, Research Department.
    135. Shouwei Li & Qingqing Li & Shuai Lu, 2024. "The impact of climate risk on credit supply to private and public sectors: an empirical analysis of 174 countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(1), pages 2443-2465, January.
    136. Corell, Felix, 2025. "Hand-to-mouth banks: Deposit inflows and the marginal propensity to lend," LawFin Working Paper Series 59, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    137. Robert Clark & Hui Wang & Victor Aguirregabiria, 2017. "The Geographic Flow Of Bank Funding And Access To Credit: Branch Networks And Local-market Competition," Working Paper 1402, Economics Department, Queen's University.
    138. Corell, Felix, 2025. "Hand-to-mouth banks: deposit inflows and the marginal propensity to lend," Working Paper Series 3085, European Central Bank.
    139. Breckenfelder, Johannes & Maćkowiak, Bartosz & Marqués-Ibáñez, David & Olovsson, Conny & Popov, Alexander & Porcellacchia, Davide & Schepens, Glenn, 2023. "The climate and the economy," Working Paper Series 2793, European Central Bank.
    140. Nie,Ou & Regelink,Martijn Gert Jan & Wang,Dieter, 2023. "Banking Sector Risk in the Aftermath of Climate Change and Environmental-RelatedNatural Disasters," Policy Research Working Paper Series 10326, The World Bank.
    141. Le, Anh-Tuan & Tran, Thao Phuong & Mishra, Anil V., 2023. "Climate risk and bank stability: International evidence," Journal of Multinational Financial Management, Elsevier, vol. 70.
    142. Petkov, Ivan, 2015. "Small Business Lending and the Bank-Branch Network," MPRA Paper 85762, University Library of Munich, Germany, revised 13 Oct 2017.
    143. Ricardo Correa & Ai He & Christoph Herpfer & Ugur Lel, 2022. "The rising tide lifts some interest rates: climate change, natural disasters, and loan pricing," International Finance Discussion Papers 1345, Board of Governors of the Federal Reserve System (U.S.).
    144. Yavuz Arslan & Ahmet Degerli & Gazi Kabaş, 2021. "Unintended Consequences of Unemployment Insurance Benefits: The Role of Banks," Finance and Economics Discussion Series 2021-027, Board of Governors of the Federal Reserve System (U.S.).
    145. Hu, Yichuan & Xue, Chang & Zhou, Xiaoyu, 2023. "Risk without strike: Nuclear crisis and corporate investment," European Economic Review, Elsevier, vol. 159(C).
    146. Littke, Helge C. N., 2018. "Channeling the Iron Ore Super-Cycle: The role of regional bank branch networks in emerging markets," IWH Discussion Papers 11/2018, Halle Institute for Economic Research (IWH).
    147. Liu, Xinheng & Lv, Shumei & Yang, Xin & Cao, Jie & Huang, Chuangxia, 2025. "Extreme temperature shocks and firms’ financial distress," International Review of Economics & Finance, Elsevier, vol. 98(C).
    148. Vinzenz Peters & Jingtian Wang & Mark Sanders, 2023. "Resilience to extreme weather events and local financial structure of prefecture-level cities in China," Climatic Change, Springer, vol. 176(9), pages 1-21, September.
    149. Rehbein, Oliver, 2018. "Flooded through the back door: Firm-level effects of banks' lending shifts," IWH Discussion Papers 4/2018, Halle Institute for Economic Research (IWH).
    150. Olga Gorbachev & María José Luengo-Prado, 2019. "The Credit Card Debt Puzzle: The Role of Preferences, Credit Access Risk, and Financial Literacy," The Review of Economics and Statistics, MIT Press, vol. 101(2), pages 294-309, May.
    151. Tetsuji Okazaki & Toshihiro Okubo & Eric Strobl, 2021. "The Bright and Dark Side of Financial Support from Local and Central Banks after a Natural Disaster: Evidence from the Great Kanto Earthquake, 1923 Japan," CIGS Working Paper Series 21-001E, The Canon Institute for Global Studies.
    152. Hua, Renhai & Liu, Qingfu & Tse, Yiuman & Yu, Qin, 2023. "The impact of natural disaster risk on the return of agricultural futures," Journal of Asian Economics, Elsevier, vol. 87(C).
    153. Chalabi-Jabado, Fatima & Ziane, Ydriss, 2024. "Climate risks, financial performance and lending growth: Evidence from the banking industry," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    154. Yoshiaki OGURA & Duc Giang NGUYEN & Thu Ha NGUYEN, 2022. "Floods and Loan Reallocation: New evidence," Discussion papers 22088, Research Institute of Economy, Trade and Industry (RIETI).
    155. Edison Yu, 2025. "Banking Trends: Where Depositors Fear to Tread," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 10(1), pages 18-21, March.
    156. Izadi, Mohammad & Saadi, Vahid, 2023. "Banking Market Structure and Trade Shocks," Journal of Banking & Finance, Elsevier, vol. 153(C).
    157. Sergio Mayordomo & Omar Rachedi, 2019. "The China syndrome affects banks: the credit supply channel of foreign import competition (Updated February 2020)," Working Papers 1908, Banco de España, revised Feb 2020.
    158. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    159. Bos, Jaap & Li, Runliang, 2017. "Understanding the Trembles of Nature: How Do Disaster Experiences Shape Bank Risk Taking?," Research Memorandum 033, Maastricht University, Graduate School of Business and Economics (GSBE).
    160. Noth, Felix & Rehbein, Oliver, 2017. "Badly hurt? Natural disasters and direct firm effects," IWH Discussion Papers 25/2017, Halle Institute for Economic Research (IWH).
    161. Sujuan Han & Mei Zhou, 2025. "Assessing the impact of climate change on entrepreneurship: short-term and long-term effects," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-8, December.
    162. MD Gyasuddin Ansari & Rudra Sensarma, 2023. "Monetary Policy, Liquidity Shock and Bank lending: The Case of Currency Demonetization in India," Working papers 575, Indian Institute of Management Kozhikode.
    163. Ivan T. Ivanov & Marco Macchiavelli & João A. C. Santos, 2022. "Bank lending networks and the propagation of natural disasters," Financial Management, Financial Management Association International, vol. 51(3), pages 903-927, September.
    164. Neville Francis & Laura E. Jackson & Michael T. Owyang, 2014. "How Has Empirical Monetary Policy Analysis Changed After the Financial Crisis?," Working Papers 2014-19, Federal Reserve Bank of St. Louis.
    165. Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2021. "Shock contagion, asset quality and lending behaviour: The case of war in Eastern Ukraine," Kyklos, Wiley Blackwell, vol. 74(2), pages 243-269, May.
    166. Chabot, Miia & Bertrand, Jean-Louis, 2023. "Climate risks and financial stability: Evidence from the European financial system," Journal of Financial Stability, Elsevier, vol. 69(C).
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    168. Alogoskoufis, Spyros & Dunz, Nepomuk & Emambakhsh, Tina & Hennig, Tristan & Kaijser, Michiel & Kouratzoglou, Charalampos & Muñoz, Manuel A. & Parisi, Laura & Salleo, Carmelo, 2021. "ECB’s economy-wide climate stress test," Occasional Paper Series 281, European Central Bank.
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  19. 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.

    Cited by:

    1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    2. 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.
    3. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    4. Niko Hauzenberger & Florian Huber & Massimiliano Marcellino & Nico Petz, 2021. "Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty," Papers 2112.01995, arXiv.org, revised Nov 2022.
    5. Sinem Hacioglu Hoke, 2019. "Macroeconomic effects of political risk shocks," Bank of England working papers 841, Bank of England.
    6. Orkideh Gharehgozli & Sunhyung Lee, 2022. "Money Supply and Inflation after COVID-19," Economies, MDPI, vol. 10(5), pages 1-14, April.
    7. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    8. 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.
    9. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    10. Rachidi Kotchoni & Dalibor Stevanovic, 2020. "GDP Forecast Accuracy During Recessions," Working Papers 20-06, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    11. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    12. Rachidi Kotchoni & Dalibor Stevanovic, 2016. "Forecasting U.S. Recessions and Economic Activity," Working Papers hal-04141569, HAL.
    13. George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
    14. Jarociński, Marek & Bobeica, Elena, 2017. "Missing disinflation and missing inflation: the puzzles that aren't," Working Paper Series 2000, European Central Bank.
    15. Kavanagh, Ella & Zhu, Sheng & O’Sullivan, Niall, 2022. "Monetary policy, trade-offs and the transmission of UK Monetary Policy," Journal of Policy Modeling, Elsevier, vol. 44(6), pages 1128-1147.
    16. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    17. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    18. Antonio Maria Conti & Stefano Neri & Alessandro Notarpietro, 2024. "Credit strikes back: the macroeconomic impact of the 2022-23 ECB monetary tightening and the role of lending rates," Questioni di Economia e Finanza (Occasional Papers) 884, Bank of Italy, Economic Research and International Relations Area.
    19. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    20. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    21. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    22. Shang, Fei, 2022. "The effect of uncertainty on the sensitivity of the yield curve to monetary policy surprises," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    23. Conti, Antonio M. & Nobili, Andrea & Signoretti, Federico M., 2023. "Bank capital requirement shocks: A narrative perspective," European Economic Review, Elsevier, vol. 151(C).
    24. Rodney Edvinsson & Sune Karlsson & Pär Österholm, 2025. "Does money growth predict inflation in Sweden? Evidence from vector autoregressions using four centuries of data," Empirical Economics, Springer, vol. 68(4), pages 1613-1635, April.
    25. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    26. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    27. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers No 01/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    28. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    29. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
    30. Karlsson, Sune & Österholm, Pär, 2019. "Volatilities, drifts and the relation between treasury yields and the corporate bond yield spread in australia," Finance Research Letters, Elsevier, vol. 30(C), pages 378-384.
    31. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    32. 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.
    33. Chan, Joshua C.C. & Pettenuzzo, Davide & Poon, Aubrey & Zhu, Dan, 2025. "Conditional forecasts in large Bayesian VARs with multiple equality and inequality constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 173(C).
    34. Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
    35. Edvinsson, Rodney & Karlsson, Sune & Österholm, Pär, 2023. "Does Money Growth Predict Inflation? Evidence from Vector Autoregressions Using Four Centuries of Data," Working Papers 2023:3, Örebro University, School of Business.
    36. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    37. Antolín-Díaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan F., 2021. "Structural scenario analysis with SVARs," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 798-815.
    38. Benjamin Garcia & Arsenios Skaperdas, 2017. "Inferring the Shadow Rate from Real Activity," Finance and Economics Discussion Series 2017-106, Board of Governors of the Federal Reserve System (U.S.).
    39. Neville Francis & Laura E. Jackson & Michael T. Owyang, 2014. "How Has Empirical Monetary Policy Analysis Changed After the Financial Crisis?," Working Papers 2014-19, Federal Reserve Bank of St. Louis.

  20. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.

    Cited by:

    1. Huber, Florian & Krisztin, Tamás & Piribauer, Philipp, 2014. "Forecasting Global Equity Indices Using Large Bayesian VARs," Department of Economics Working Paper Series 184, WU Vienna University of Economics and Business.
    2. Andrea Renzetti, 2023. "Theory coherent shrinkage of Time-Varying Parameters in VARs," Papers 2311.11858, arXiv.org, revised Nov 2024.
    3. Minchul Shin & Molin Zhong, 2013. "Does realized volatility help bond yield density prediction?," PIER Working Paper Archive 13-064, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Gregor Bäurle & Daniel Kaufmann, 2018. "Measuring Exchange Rate, Price, and Output Dynamics at the Effective Lower Bound," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(6), pages 1243-1266, December.

  21. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.

    Cited by:

    1. Galvão, Ana Beatriz & Giraitis, Liudas & Kapetanios, George & Petrova, Katerina, 2016. "A time varying DSGE model with financial frictions," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 690-716.
    2. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    3. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    4. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    5. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    6. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Density Forecasting," Papers 2404.02671, arXiv.org, revised Nov 2024.
    7. 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.
    8. Edward S. Knotek & Saeed Zaman, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series) 1403, Federal Reserve Bank of Cleveland.
    9. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    10. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    11. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    12. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    13. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    14. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    15. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2024. "Nowcasting Norwegian household consumption with debit card transaction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1220-1244, November.
    16. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    17. Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2025. "Panel Machine Learning with Mixed-Frequency Data: Monitoring State-Level Fiscal Variables," CIRANO Working Papers 2025s-15, CIRANO.
    18. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    19. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    20. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    21. Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
    22. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    23. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
    24. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    25. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    26. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    27. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    28. 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.
    29. Ana Beatriz Galvão & Michael Owyang, 2022. "Forecasting low‐frequency macroeconomic events with high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1314-1333, November.
    30. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    31. 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.
    32. 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.
    33. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    34. Boriss Siliverstovs, 2021. "New York FED Staff Nowcasts and Reality: What Can We Learn about the Future, the Present, and the Past?," Econometrics, MDPI, vol. 9(1), pages 1-25, March.
    35. Liu, Yang & Swanson, Norman R., 2024. "An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1391-1409.
    36. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    37. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    38. 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).
    39. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
    40. 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.
    41. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    42. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    43. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    44. Robert M. Kunst & Martin Wagner, 2020. "Economic forecasting: editors’ introduction," Empirical Economics, Springer, vol. 58(1), pages 1-5, January.
    45. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    46. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    47. Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
    48. Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
    49. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    50. Philipp Wegmueller & Christian Glocker, 2024. "Capturing Swiss economic confidence," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-17, December.
    51. Soojin Jo & Rodrigo Sekkel, 2017. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Working Papers 1702, Federal Reserve Bank of Dallas.
    52. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    53. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    54. Lucas P. Harlaar & Jacques J.F. Commandeur & Jan A. van den Brakel & Siem Jan Koopman & Niels Bos & Frits D. Bijleveld, 2024. "Statistical Early Warning Models with Applications," Tinbergen Institute Discussion Papers 24-037/III, Tinbergen Institute.
    55. George Athanasopoulos & Puwasala Gamakumara & Anastasios Panagiotelis & Rob J Hyndman & Mohamed Affan, 2019. "Hierarchical Forecasting," Monash Econometrics and Business Statistics Working Papers 2/19, Monash University, Department of Econometrics and Business Statistics.
    56. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
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    59. Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
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    61. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
    62. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
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  22. Andrea Carriero & Haroon Mumtaz & Konstantinos Theodoridis & Angeliki Theophilopoulou, 2013. "The Impact of Uncertainty Shocks under Measurement Error. A Proxy SVAR Approach," Working Papers 707, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Angus Moore, 2016. "Measuring Economic Uncertainty and Its Effects," RBA Research Discussion Papers rdp2016-01, Reserve Bank of Australia.
    2. Boer, Lukas & Lütkepohl, Helmut, 2021. "Qualitative versus quantitative external information for proxy vector autoregressive analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    3. Angelini, Giovanni & Fanelli, Luca, 2018. "Exogenous uncertainty and the identification of Structural Vector Autoregressions with external instruments," MPRA Paper 93864, University Library of Munich, Germany, revised May 2019.
    4. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    5. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2022. "The macroeconomic impact of economic uncertainty and financial shocks under low and high financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    6. Mathias Krogh & Giovanni Pellegrino, "undated". "Real Activity and Uncertainty Shocks: The Long and the Short of It," "Marco Fanno" Working Papers 0310, Dipartimento di Scienze Economiche "Marco Fanno".
    7. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    8. Bekiros, Stelios & Gupta, Rangan & Majumdar, Anandamayee, 2016. "Incorporating economic policy uncertainty in US equity premium models: A nonlinear predictability analysis," Finance Research Letters, Elsevier, vol. 18(C), pages 291-296.
    9. Balcilar, Mehmet & Demirer, Riza & Gupta, Rangan & van Eyden, Reneé, 2017. "The impact of US policy uncertainty on the monetary effectiveness in the Euro area," Journal of Policy Modeling, Elsevier, vol. 39(6), pages 1052-1064.
    10. Giovanni Pellegrino, 2020. "Uncertainty and Monetary Policy in the US: A Journey into Non-Linear Territory," Economics Working Papers 2020-05, Department of Economics and Business Economics, Aarhus University.
    11. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    12. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial regimes and uncertainty shocks," BCAM Working Papers 1404, Birkbeck Centre for Applied Macroeconomics.
    13. Karel Mertens & Morten O. Ravn, 2018. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States: Reply to Jentsch and Lunsford," Working Papers 1805, Federal Reserve Bank of Dallas.
    14. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    15. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    16. Yoshito Funashima, 2024. "How does economic policy uncertainty respond to permanent and transitory shocks?," Bulletin of Economic Research, Wiley Blackwell, vol. 76(1), pages 267-282, January.
    17. Alsalman, Zeina & Herrera, Ana María & Rangaraju, Sandeep Kumar, 2023. "Oil news shocks and the U.S. stock market," Energy Economics, Elsevier, vol. 126(C).
    18. Eul Noh, 2024. "Revisiting the effects of conventional and unconventional monetary policies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 943-951, August.
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    20. Rangan Gupta & Charl Jooste, 2018. "Unconventional monetary policy shocks in OECD countries: how important is the extent of policy uncertainty?," International Economics and Economic Policy, Springer, vol. 15(3), pages 683-703, July.
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    22. Kurt Graden Lunsford, 2015. "Identifying Structural VARs with a Proxy Variable and a Test for a Weak Proxy," Working Papers (Old Series) 1528, Federal Reserve Bank of Cleveland.
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    28. Muhammad Mohsin & Mohammad Nurunnabi & Jijian Zhang & Huaping Sun & Nadeem Iqbal & Robina Iram & Qaiser Abbas, 2021. "The evaluation of efficiency and value addition of IFRS endorsement towards earnings timeliness disclosure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1793-1807, April.
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    30. Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
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    32. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2014. "Uncertainty and Monetary Policy in Good and Bad Times," "Marco Fanno" Working Papers 0188, Dipartimento di Scienze Economiche "Marco Fanno".
    33. Michele Piffer & Maximilian Podstawski, 2017. "Identifying Uncertainty Shocks Using the Price of Gold," CESifo Working Paper Series 6327, CESifo.
    34. Giovanni Pellegrino & Efrem Castelnuovo & Giovanni Caggiano, 2023. "Uncertainty And Monetary Policy During The Great Recession," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(2), pages 577-606, May.
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    40. Michael Ryan, 2020. "A Narrative Approach to Creating Instruments with Unstructured and Voluminous Text: An Application to Policy Uncertainty," Working Papers in Economics 20/10, University of Waikato.
    41. Efrem Castelnuovo, 2019. "Domestic and Global Uncertainty: A Survey and Some New Results," CESifo Working Paper Series 7900, CESifo.
    42. Refk Selmi & Jamal Bouoiyour & Shawkat Hammoudeh, 2020. "Common and country-specific uncertainty fluctuations in oil-producing countries : Measures, macroeconomic effects and policy challenges," Post-Print hal-02929898, HAL.
    43. Cascaldi-Garcia, Danilo, 2025. "Forecast revisions as instruments for news shocks," Journal of Monetary Economics, Elsevier, vol. 151(C).
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    45. Alhussaini, Abdullah & Parhi, Mamata, 2022. "How do economies adjust speed at uncertain times?," Research in International Business and Finance, Elsevier, vol. 63(C).
    46. Kim, Wongi, 2019. "Government spending policy uncertainty and economic activity: US time series evidence," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    47. Giovanni Pellegrino & Federico Ravenna & Gabriel Züllig, 2021. "The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 841-869, August.
    48. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2022. "Proxy SVAR identification of monetary policy shocks - Monte Carlo evidence and insights for the US," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    49. Emna Trabelsi, 2025. "Monetary Policy Under Global and Spillover Uncertainty Shocks: What Do the Bayesian Time-Varying Coefficient VAR, Local Projections, and Vector Error Correction Model Tell Us in Tunisia?," JRFM, MDPI, vol. 18(3), pages 1-74, March.
    50. Carlos Canizares Martinez & Arne Gieseck, 2024. "The effects of macro uncertainty shocks in the euro area: A FAVAR approach," Working and Discussion Papers WP 6/2024, Research Department, National Bank of Slovakia.
    51. Jentsch, Carsten & Lunsford, Kurt G., 2016. "Proxy SVARs : asymptotic theory, bootstrap inference, and the effects of income tax changes in the United States," Working Papers 16-10, University of Mannheim, Department of Economics.
    52. Thomai Filippeli & Konstantinos Theodoridis, 2014. "DSGE Priors for BVAR Models," Working Papers 713, Queen Mary University of London, School of Economics and Finance.
    53. Christina Christou & Rangan Gupta & Christis Hassapis, 2016. "Does Economic Policy Uncertainty Forecast Real Housing Returns in a Panel of OECD Countries? A Bayesian Approach," Working Papers 201637, University of Pretoria, Department of Economics.
    54. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
    55. Andrea Giovanni Gazzani & Alejandro Vicondoa, 2019. "Proxy-SVAR as a Bridge for Identification with Higher Frequency Data," 2019 Meeting Papers 855, Society for Economic Dynamics.
    56. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    57. Mehmet Balcilar & Riza Demirer & Rangan Gupta & Reneé van Eyden, 2016. "Effectiveness of Monetary Policy in the Euro Area: The Role of US Economic Policy Uncertainty," Working Papers 201620, University of Pretoria, Department of Economics.
    58. Munechika Katayama & Kwang Hwan Kim, 2017. "Uncertainty Shocks and the Relative Price of Investment Goods," Discussion papers e-16-015, Graduate School of Economics , Kyoto University.
    59. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2014. "Signals from the Government: Policy Uncertainty and the Transmission of Fiscal Shocks," MPRA Paper 56136, University Library of Munich, Germany.
    60. Benjamin Born & Johannes Pfeifer, 2021. "Uncertainty‐driven business cycles: Assessing the markup channel," Quantitative Economics, Econometric Society, vol. 12(2), pages 587-623, May.
    61. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    62. Josué Diwambuena & Jean-Paul K. Tsasa, 2021. "The Real Effects of Uncertainty Shocks: New Evidence from Linear and Nonlinear SVAR Models," BEMPS - Bozen Economics & Management Paper Series BEMPS87, Faculty of Economics and Management at the Free University of Bozen.
    63. Ma, Xiaohan & Samaniego, Roberto, 2019. "Deconstructing uncertainty," European Economic Review, Elsevier, vol. 119(C), pages 22-41.
    64. Christou, Christina & Cunado, Juncal & Gupta, Rangan & Hassapis, Christis, 2017. "Economic policy uncertainty and stock market returns in PacificRim countries: Evidence based on a Bayesian panel VAR model," Journal of Multinational Financial Management, Elsevier, vol. 40(C), pages 92-102.
    65. Helena Chuliá & Rangan Gupta & Jorge M. Uribe & Mark E. Wohar, 2016. "Impact of US Uncertainties on Emerging and Mature Markets: Evidence from a Quantile-Vector Autoregressive Approach," Working Papers 201656, University of Pretoria, Department of Economics.
    66. Bhattarai, Saroj & Chatterjee, Arpita & Park, Woong Yong, 2021. "Effects of US quantitative easing on emerging market economies," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).
    67. Sheung-Chi Chow & Juncal Cunado & Rangan Gupta & Wing-Keung Wong, 2016. "Causal Relationships between Economic Policy Uncertainty and Housing Market Returns in China and India: Evidence from Linear and Nonlinear Panel and Time Series Models," Working Papers 201674, University of Pretoria, Department of Economics.
    68. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    69. Ricardo Caballero & Güneş Kamber, 2019. "On the global Impact of risk-off shocks and policy-put frameworks," BIS Working Papers 772, Bank for International Settlements.
    70. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    71. Syed M. Hussain, Zara Liaqat, 2025. "News Shocks, Consumer Confidence, and Business Cycles," LCERPA Working Papers jc0155, Laurier Centre for Economic Research and Policy Analysis, revised Apr 2025.
    72. Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2016. "The Impact of US Uncertainty on the Euro Area in Good and Bad Times: Evidence from a Quantile Structural Vector Autoregressive Model," Working Papers 201681, University of Pretoria, Department of Economics.
    73. Wei‐Fong Pan & James Reade & Shixuan Wang, 2022. "Measuring US regional economic uncertainty," Journal of Regional Science, Wiley Blackwell, vol. 62(4), pages 1149-1178, September.
    74. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
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    Cited by:

    1. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    2. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    3. 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.
    4. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    5. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
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    Cited by:

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    140. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
    141. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014. "Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors," Working Papers 189, Oesterreichische Nationalbank (Austrian Central Bank).
    142. Garegnani, Lorena & Gómez Aguirre, Maximiliano, 2018. "Forecasting Inflation in Argentina," IDB Publications (Working Papers) 8940, Inter-American Development Bank.
    143. Ho, Paul, 2023. "Global robust Bayesian analysis in large models," Journal of Econometrics, Elsevier, vol. 235(2), pages 608-642.
    144. Shin, Minchul & Zhong, Molin, 2017. "Does realized volatility help bond yield density prediction?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 373-389.
    145. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.

  25. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.

    Cited by:

    1. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    2. Andrea Carriero & Lorenzo Ricci & Elisabetta Vangelista, 2022. "Expectations and term premia in EFSF bond yields," Working Papers 54, European Stability Mechanism.
    3. Giacomini, Raffaella & Ragusa, Giuseppe, 2011. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion Papers 8604, C.E.P.R. Discussion Papers.
    4. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," MPRA Paper 63844, University Library of Munich, Germany.
    5. Tommaso Tornese, 2023. "A Euro Area Term Structure Model with Time Varying Exposures," BAFFI CAREFIN Working Papers 23199, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    6. Fabricio Tourrucôo & João F. Caldeira & Guilherme V. Moura & André A. P. Santos, 2016. "Forecasting The Yield Curve With The Arbitrage-Free Dynamic Nelson-Siegel Model: Brazilian Evidence," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 028, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. Cao, Shuo & Crump, Richard K. & ,, 2020. "Fundamental Disagreement about Monetary Policy and the Term Structure of Interest Rates," CEPR Discussion Papers 15122, C.E.P.R. Discussion Papers.
    8. Rui Liu, 2019. "Forecasting Bond Risk Premia with Unspanned Macroeconomic Information," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-62, March.
    9. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    10. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Working Papers 2014.21, Fondazione Eni Enrico Mattei.
    11. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    12. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    13. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    14. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    15. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    16. Vieira, Fausto José Araújo & Chague, Fernando Daniel & Fernandes, Marcelo, 2017. "A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US," Textos para discussão 445, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    17. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2010. "Forecasting Government Bond Yields with Large Bayesian VARs," CEPR Discussion Papers 7796, C.E.P.R. Discussion Papers.
    18. Chen, Jiazi & Hong, Zhiwu & Niu, Linlin, 2025. "Forecasting interest rates with shifting endpoints: The role of the functional demographic age distribution," International Journal of Forecasting, Elsevier, vol. 41(1), pages 153-174.
    19. Carlo A. Favero & Arie E. Gozluklu & Haoxi Yang, 2016. "Demographics and the Behavior of Interest Rates," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(4), pages 732-776, November.
    20. Martin Beraja & Erik Hurst & Juan Ospina, 2016. "The Aggregate Implications of Regional Business Cycles," NBER Working Papers 21956, National Bureau of Economic Research, Inc.
    21. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    22. Giacomini, Raffaella & Ragusa, Giuseppe, 2014. "Theory-coherent forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 145-155.
    23. Guidolin, Massimo & Pedio, Manuela, 2019. "Forecasting and trading monetary policy effects on the riskless yield curve with regime switching Nelson–Siegel models," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    24. Wali ULLAH & Khadija Malik BARI, 2018. "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-28, September.
    25. Caio Almeida & Axel Simonsen & José Valentim Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
    26. Frank J. Fabozzi & Francesco A. Fabozzi & Diana Tunaru, 2023. "A comparison of multi-factor term structure models for interbank rates," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 323-356, July.
    27. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

  26. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2010. "Forecasting Government Bond Yields with Large Bayesian VARs," CEPR Discussion Papers 7796, C.E.P.R. Discussion Papers.

    Cited by:

    1. Haroon Mumtaz & Alexandra Solovyeva & Elena Vasilieva, 2012. "Asset prices, credit and the Russian economy," Joint Research Papers 1, Centre for Central Banking Studies, Bank of England.
    2. George Kapetanios & Haroon Mumtaz & Ibrahim Stevens & Konstantinos Theodoridis, 2012. "Assessing the economy-wide effects of quantitative easing," Bank of England working papers 443, Bank of England.
    3. Cristina Fuentes-Albero & Leonardo Melosi, 2011. "Methods for Computing Marginal Data Densities from the Gibbs Output," Departmental Working Papers 201131, Rutgers University, Department of Economics.
    4. Vladimir Habrov, 2012. "Optimization of portfolio management based on vector autoregression models and multivariate volatility models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 28(4), pages 35-62.
    5. 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.
    6. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.
    7. Simon Gilchrist & Egon Zakrajsek & Cristina Fuentes Albero & Dario Caldara, 2013. "On the Identification of Financial and Uncertainty Shocks," 2013 Meeting Papers 965, Society for Economic Dynamics.
    8. Caio Almeida & Axel Simonsen & José Valentim Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.

  27. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2009. "Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models," CEPR Discussion Papers 7446, C.E.P.R. Discussion Papers.

    Cited by:

    1. Teresa Buchen & Klaus Wohlrabe, 2013. "Assessing the Macroeconomic Forecasting Performance of Boosting - Evidence for the United States, the Euro Area, and Germany," CESifo Working Paper Series 4148, CESifo.
    2. Gianluca Cubadda & Alain Hecq, 2021. "Reduced Rank Regression Models in Economics and Finance," CEIS Research Paper 525, Tor Vergata University, CEIS, revised 08 Nov 2021.
    3. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    4. Kwon, Hyuck-Shin & Bang, Doo Won & Kim, Myeong Hyeon, 2017. "Korean Housing Cycle: Implications for Risk Management (Factor-augmented VAR Approach)," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 39(3), pages 43-62.
    5. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
    6. 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.
    7. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    8. Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
    9. Rohan Churm & Mike Joyce & George Kapetanios & Konstantinos Theodoridis, 2015. "Unconventional monetary policies and the macroeconomy: the impact of the United Kingdom's QE2 and Funding for Lending Scheme," Bank of England working papers 542, Bank of England.
    10. Götz, T.B. & Hecq, A.W., 2014. "Testing for Granger causality in large mixed-frequency VARs," Research Memorandum 028, Maastricht University, Graduate School of Business and Economics (GSBE).
    11. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2016. "Structural analysis with Multivariate Autoregressive Index models," Journal of Econometrics, Elsevier, vol. 192(2), pages 332-348.
    12. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    13. Marco Centoni & Gianluca Cubadda, 2015. "Common Feature Analysis of Economic Time Series: An Overview and Recent Developments," CEIS Research Paper 355, Tor Vergata University, CEIS, revised 05 Oct 2015.
    14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    15. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    16. Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
    17. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    18. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    19. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    20. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    21. Eran Raviv & Kees E. Bouwman & Dick van Dijk, 2013. "Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices," Tinbergen Institute Discussion Papers 13-068/III, Tinbergen Institute.
    22. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    23. Jonas E. Arias & Juan F. Rubio-Ram'irez & Minchul Shin, 2025. "A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs," Papers 2505.23542, arXiv.org, revised May 2025.
    24. Bernardini, Emmanuela & Cubadda, Gianluca, 2015. "Macroeconomic forecasting and structural analysis through regularized reduced-rank regression," International Journal of Forecasting, Elsevier, vol. 31(3), pages 682-691.
    25. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    26. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
    27. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    28. Matilainen, M. & Croux, C. & Nordhausen, K. & Oja, H., 2017. "Supervised dimension reduction for multivariate time series," Econometrics and Statistics, Elsevier, vol. 4(C), pages 57-69.
    29. 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.
    30. Bartkus Algirdas, 2016. "A New Model with Regime Switching Errors: Forecasting Gdp in Times of Great Recession," Ekonomika (Economics), Sciendo, vol. 95(2), pages 7-29, February.
    31. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    32. Doo Won Bang & HyuckShin Kwon, 2022. "Policy Impact Analysis of Housing Policies Using Housing Cycles," SAGE Open, , vol. 12(3), pages 21582440221, July.
    33. Wilms, Ines & Croux, Christophe, 2016. "Forecasting using sparse cointegration," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1256-1267.
    34. Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
    35. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    36. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
    37. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2025. "A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs," Working Papers 25-19, Federal Reserve Bank of Philadelphia.
    38. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2020. "The economic drivers of volatility and uncertainty," Temi di discussione (Economic working papers) 1285, Bank of Italy, Economic Research and International Relations Area.
    39. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper Series 43, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    40. Pirschel, Inske & Wolters, Maik, 2014. "Forecasting German key macroeconomic variables using large dataset methods," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100587, Verein für Socialpolitik / German Economic Association.
    41. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    42. Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019. "Macroeconomic forecasting for Australia using a large number of predictors," International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
    43. Christophe Croux & Peter Exterkate, 2011. "Sparse and Robust Factor Modelling," Tinbergen Institute Discussion Papers 11-122/4, Tinbergen Institute.
    44. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    45. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.
    46. Marco Lombardi & Chiara Osbat & Bernd Schnatz, 2012. "Global commodity cycles and linkages: a FAVAR approach," Empirical Economics, Springer, vol. 43(2), pages 651-670, October.
    47. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2010. "Forecasting Government Bond Yields with Large Bayesian VARs," CEPR Discussion Papers 7796, C.E.P.R. Discussion Papers.
    48. Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
    49. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.
    50. Gianluca Cubadda & Barbara Guardabascio, 2017. "Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model," CEIS Research Paper 397, Tor Vergata University, CEIS, revised 13 Jul 2018.
    51. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss," Resources Policy, Elsevier, vol. 47(C), pages 95-107.
    52. 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.
    53. Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org, revised Sep 2025.
    54. Adam Nowak & Patrick Smith, 2015. "Textual Analysis in Real Estate," Working Papers 15-34, Department of Economics, West Virginia University.
    55. Zeng, Jing, 2014. "Forecasting Aggregates with Disaggregate Variables: Does boosting help to select the most informative predictors?," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100310, Verein für Socialpolitik / German Economic Association.
    56. Prüser, Jan, 2023. "Data-based priors for vector error correction models," International Journal of Forecasting, Elsevier, vol. 39(1), pages 209-227.
    57. Jing Zeng, 2014. "Forecasting Aggregates with Disaggregate Variables: Does Boosting Help to Select the Most Relevant Predictors?," Working Paper Series of the Department of Economics, University of Konstanz 2014-20, Department of Economics, University of Konstanz.
    58. Dias, Gustavo Fruet & Kapetanios, George, 2018. "Estimation and forecasting in vector autoregressive moving average models for rich datasets," Journal of Econometrics, Elsevier, vol. 202(1), pages 75-91.
    59. Churm, Rohan & Joyce, Michael & Kapetanios, George & Theodoridis, Konstantinos, 2021. "Unconventional monetary policies and the macroeconomy: The impact of the UK's QE2 and funding for lending scheme," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 721-736.
    60. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    61. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Nov 2024.
    62. Gianluca Cubadda & Marco Mazzali, 2023. "The Vector Error Correction Index Model: Representation, Estimation and Identification," CEIS Research Paper 556, Tor Vergata University, CEIS, revised 04 Apr 2023.

  28. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2008. "Forecasting Exchange Rates with a Large Bayesian VAR," CEPR Discussion Papers 7008, C.E.P.R. Discussion Papers.

    Cited by:

    1. Teona Shugliashvili, 2023. "The words have power: the impact of news on exchange rates," FFA Working Papers 5.006, Prague University of Economics and Business, revised 31 Jul 2023.
    2. Koop, Gary & Korobilis, Dimitris, 2016. "Model uncertainty in Panel Vector Autoregressive models," European Economic Review, Elsevier, vol. 81(C), pages 115-131.
    3. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    4. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
    5. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    6. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 176, WU Vienna University of Economics and Business.
    7. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    8. Kwon, Hyuck-Shin & Bang, Doo Won & Kim, Myeong Hyeon, 2017. "Korean Housing Cycle: Implications for Risk Management (Factor-augmented VAR Approach)," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 39(3), pages 43-62.
    9. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
    10. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2010. "Forecasting with Factor-augmented Error Correction Models," CEPR Discussion Papers 7677, C.E.P.R. Discussion Papers.
    11. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    12. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    13. Yoonsik Hong & Diego Klabjan, 2025. "Graph Learning for Foreign Exchange Rate Prediction and Statistical Arbitrage," Papers 2508.14784, arXiv.org.
    14. Santos, André A.P. & Nogales, Francisco J. & Ruiz, Esther & Dijk, Dick Van, 2012. "Optimal portfolios with minimum capital requirements," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1928-1942.
    15. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    16. Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2014. "Large Bayesian VARMAs," SIRE Discussion Papers 2015-06, Scottish Institute for Research in Economics (SIRE).
    17. Koop, Gary & Korobilis, Dimitris, 2012. "Large time-varying parameter VARs," MPRA Paper 38591, University Library of Munich, Germany.
    18. Xin Sheng & Rangan Gupta & Afees A. Salisu & Elie Bouri, 2021. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Working Papers 202101, University of Pretoria, Department of Economics.
    19. Alexander Chudik & M. Hashem Pesaran, 2014. "Theory and practice of GVAR modeling," Globalization Institute Working Papers 180, Federal Reserve Bank of Dallas.
    20. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
    21. Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.
    22. Abdul-Rashid Abdul-Rahaman & Coleman Martha & Emmanuel Caesar Ayamba, 2024. "Exchange Rate Models and the Management of Forex Losses in Ghana: Modelling Exchange Rate Volatilities for Businesses," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 49(4), pages 679-703, November.
    23. Martin McCarthy, Stephen Snudden, 2024. "Forecasts of Period-Average Exchange Rates: New Insights from Real-Time Daily Data," LCERPA Working Papers jc0148, Laurier Centre for Economic Research and Policy Analysis, revised Oct 2024.
    24. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    25. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
    26. Huber Florian, 2016. "Forecasting exchange rates using multivariate threshold models," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 193-210, January.
    27. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    28. Halil Ibrahim Gunduz & Furkan Emirmahmutoglu & M. Eray Yucel, 2025. "A New Look at Cross-Country Aggregation in the Global VAR Approach: Theory and Monte Carlo Simulation," Computational Economics, Springer;Society for Computational Economics, vol. 65(1), pages 21-67, January.
    29. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    30. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2009. "Forecasting with Factor-Augmented Error Correction Models," Discussion Papers 09-06r, Department of Economics, University of Birmingham.
    31. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    32. Huber, Florian & Krisztin, Tamás & Piribauer, Philipp, 2014. "Forecasting Global Equity Indices Using Large Bayesian VARs," Department of Economics Working Paper Series 184, WU Vienna University of Economics and Business.
    33. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2018-08, Department of Economics, University of Konstanz.
    34. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
    35. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    36. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
    37. Ponomareva, Natalia & Sheen, Jeffrey & Wang, Ben Zhe, 2019. "Forecasting exchange rates using principal components," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    38. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2012. "Prior selection for vector autoregressions," Working Paper Series 1494, European Central Bank.
    39. Ashwin Madhou & Tayushma Sewak & Imad Moosa & Vikash Ramiah, 2017. "GDP nowcasting: application and constraints in a small open developing economy," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3880-3890, August.
    40. Lukas Berend & Jan Pruser, 2025. "Large structural VARs with multiple linear shock and impact inequality restrictions," Papers 2505.19244, arXiv.org, revised Jul 2025.
    41. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112999, Verein für Socialpolitik / German Economic Association.
    42. 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.
    43. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
    44. George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
    45. Ms. Adina Popescu & Ms. Alina Carare, 2011. "Monetary Policy and Risk-Premium Shocks in Hungary: Results from a Large Bayesian VAR," IMF Working Papers 2011/259, International Monetary Fund.
    46. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    47. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2016. "Testing for Instability in Covariance Structures," Working papers 2016-33, University of Connecticut, Department of Economics.
    48. Yemba, Boniface P. & Otunuga, Olusegun Michael & Tang, Biyan & Biswas, Nabaneeta, 2023. "Nowcasting of the Short-run Euro-Dollar Exchange Rate with Economic Fundamentals and Time-varying Parameters," Finance Research Letters, Elsevier, vol. 52(C).
    49. Doo Won Bang & HyuckShin Kwon, 2022. "Policy Impact Analysis of Housing Policies Using Housing Cycles," SAGE Open, , vol. 12(3), pages 21582440221, July.
    50. Florian Huber, 2014. "Density Forecasting using Bayesian Global Vector Autoregressions with Common Stochastic Volatility," Department of Economics Working Papers wuwp179, Vienna University of Economics and Business, Department of Economics.
    51. Papahristodoulou, Christos, 2019. "Is there any theory that explains the SEK?," MPRA Paper 95072, University Library of Munich, Germany, revised 08 Jul 2019.
    52. Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
    53. Florian Huber & Jesus Crespo-Cuaresma & Martin Feldkircher, 2014. "Forecasting with Bayesian Global Vector Autoregressions," ERSA conference papers ersa14p25, European Regional Science Association.
    54. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    55. Grant, Angelia L. & Chan, Joshua C.C., 2017. "Reconciling output gaps: Unobserved components model and Hodrick–Prescott filter," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 114-121.
    56. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    57. Marcellino, Massimiliano & Abbate, Angela, 2016. "Point, interval and density forecasts of exchange rates with time-varying parameter models," CEPR Discussion Papers 11559, C.E.P.R. Discussion Papers.
    58. Bacchetta, Philippe & van Wincoop, Eric & Beutler, Toni, 2009. "Can Parameter Instability Explain the Meese-Rogoff Puzzle?," CEPR Discussion Papers 7383, C.E.P.R. Discussion Papers.
    59. Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    60. Sun, Shaolong & Wang, Shouyang & Wei, Yunjie, 2019. "A new multiscale decomposition ensemble approach for forecasting exchange rates," Economic Modelling, Elsevier, vol. 81(C), pages 49-58.
    61. 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.
    62. Kim, Young Min & Lee, Seojin, 2020. "Exchange rate predictability: A variable selection perspective," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 117-134.
    63. Brian D. Deaton, 2018. "Effects of the Swiss Franc/Euro Exchange Rate Floor on the Calibration of Probability Forecasts," Forecasting, MDPI, vol. 1(1), pages 1-23, May.
    64. Brahim Gaies, Khaled Guesmi, Thomas Porcher, Raphael Boroumand, 2020. "Financial instability and oil price fluctuations: evidence from oil exporting developing countries," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 17(1), pages 55-71, June.
    65. Auer, Simone, 2019. "Monetary policy shocks and foreign investment income: Evidence from a large Bayesian VAR," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 142-166.
    66. 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.
    67. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    68. Zhang, Bo & Nguyen, Bao H. & Sun, Chuanwang, 2024. "Forecasting oil prices: Can large BVARs help?," Energy Economics, Elsevier, vol. 137(C).
    69. Antonio Pacifico, 2022. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure," Econometrics, MDPI, vol. 10(3), pages 1-24, July.
    70. Ana Sofia Monteiro & Helder Sebastião & Nuno Silva, 2025. "Prediction and Allocation of Stocks, Bonds, and REITs in the US Market," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1191-1230, March.
    71. Chan, Joshua C.C., 2023. "Comparing stochastic volatility specifications for large Bayesian VARs," Journal of Econometrics, Elsevier, vol. 235(2), pages 1419-1446.
    72. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    73. Paresh Date & Janeeta Maunthrooa, 2025. "Modelling and Forecasting of Exchange Rate Pairs Using the Kalman Filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 606-622, March.
    74. Albis, Manuel Leonard F. & Mapa, Dennis S., 2014. "Bayesian Averaging of Classical Estimates in Asymmetric Vector Autoregressive (AVAR) Models," MPRA Paper 55902, University Library of Munich, Germany.
    75. Joshua C. C. Chan, 2019. "Large Bayesian Vector Autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    76. Korobilis, Dimitris, 2016. "Prior selection for panel vector autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 110-120.
    77. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    78. 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.
    79. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016. "Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
    80. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2010. "Forecasting Government Bond Yields with Large Bayesian VARs," CEPR Discussion Papers 7796, C.E.P.R. Discussion Papers.
    81. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.
    82. Crespo Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava, 2017. "Exchange rate forecasting and the performance of currency portfolios," Economics Series 326, Institute for Advanced Studies.
    83. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    84. Haroon Mumtaz & Nitin Kumar, 2012. "An application of data-rich environment for policy analysis of the Indian economy," Joint Research Papers 2, Centre for Central Banking Studies, Bank of England.
    85. Haskamp, Ulrich, 2017. "Forecasting exchange rates: The time-varying relationship between exchange rates and Taylor rule fundamentals," Ruhr Economic Papers 704, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    86. Kéa Baret & Frédérique Bec & Marion Cochard, 2025. "Quantifying Uncertainty in France’s Debt Trajectory: A VAR Based Analysis," Working papers 1019, Banque de France.
    87. Ahmed Ibrahim & Rasha Kashef & Menglu Li & Esteban Valencia & Eric Huang, 2020. "Bitcoin Network Mechanics: Forecasting the BTC Closing Price Using Vector Auto-Regression Models Based on Endogenous and Exogenous Feature Variables," JRFM, MDPI, vol. 13(9), pages 1-21, August.
    88. Jan Pruser, 2024. "A large non-Gaussian structural VAR with application to Monetary Policy," Papers 2412.17598, arXiv.org.
    89. Pantelis Promponas & David Alan Peel, 2016. "Forecasting the nominal exchange rate movements in a changing world. The case of the U.S. and the U.K," Working Papers 144439514, Lancaster University Management School, Economics Department.
    90. Joshua Chan & Christian Matthes & Xuewen Yu, 2025. "Large Structural VARs with Multiple Sign and Ranking Restrictions," Papers 2503.20668, arXiv.org.
    91. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    92. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
    93. Schüssler, Rainer & Beckmann, Joscha & Koop, Gary & Korobilis, Dimitris, 2018. "Exchange rate predictability and dynamic Bayesian learning," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181523, Verein für Socialpolitik / German Economic Association.
    94. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
    95. Valentina Aprigliano, 2020. "A large Bayesian VAR with a block‐specific shrinkage: A forecasting application for Italian industrial production," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1291-1304, December.
    96. Feldkircher, Martin & Huber, Florian, 2016. "The international transmission of US shocks—Evidence from Bayesian global vector autoregressions," European Economic Review, Elsevier, vol. 81(C), pages 167-188.
    97. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2023. "Directed graphs and variable selection in large vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 223-246, March.
    98. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    99. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    100. Lance Kent, 2014. "Bilateral Linkages and the International Transmission of Business Cycles," Working Papers 149, Economics Department, William & Mary.
    101. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
    102. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014. "Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors," Working Papers 189, Oesterreichische Nationalbank (Austrian Central Bank).

  29. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2008. "Forecasting with Dynamic Models using Shrinkage-based Estimation," Working Papers 635, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Gustavo Fruet Dias & George Kapetanios, 2014. "Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets," CREATES Research Papers 2014-37, Department of Economics and Business Economics, Aarhus University.
    2. Emrah Oral & Gazanfer Unal, 2017. "Co-movement of precious metals and forecasting using scale by scale wavelet transform," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-21, March.

  30. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2007. "Forecasting Large Datasets with Reduced Rank Multivariate Models," Working Papers 617, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Branimir, Jovanovic & Magdalena, Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," MPRA Paper 43162, University Library of Munich, Germany.
    2. Jana Eklund & George Kapetanios, 2008. "A Review of Forecasting Techniques for Large Data Sets," Working Papers 625, Queen Mary University of London, School of Economics and Finance.
    3. Branimir Jovanovic & Magdalena Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," Working Papers 2010-02, National Bank of the Republic of North Macedonia, revised Aug 2010.

  31. Andrea Carriero, 2007. "A Simple Test of the New Keynesian Phillips Curve," Working Papers 592, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Cornea, A. & Hommes, C.H. & Massaro, D., 2012. "Behavioral Heterogeneity in U.S. Inflation Dynamics," CeNDEF Working Papers 12-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    2. Mavroeidis, Sophocles & Plagborg-Moller, Mikkel & Stock, James H., 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Scholarly Articles 22795845, Harvard University Department of Economics.
    3. Adriana Cornea‐Madeira & João Madeira, 2022. "Econometric Analysis of Switching Expectations in UK Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 651-673, June.
    4. Liu, Chunping & Minford, Patrick, 2014. "Comparing behavioural and rational expectations for the US post-war economy," Economic Modelling, Elsevier, vol. 43(C), pages 407-415.
    5. Barbara Annicchiarico & Silvia Surricchio & Robert J. Waldmann, 2018. "A Behavioral Model of the Credit Cycle," CEIS Research Paper 446, Tor Vergata University, CEIS, revised 30 Oct 2018.
    6. Carlos Medel, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," Working Papers Central Bank of Chile 769, Central Bank of Chile.
    7. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2012. "Changes in Inflation Dynamics under Inflation Targeting? Evidence from Central European Countries," Working Papers 2012/04, Czech National Bank, Research and Statistics Department.

  32. Andrea Carriero & Massimiliano Marcellino, 2007. "A Comparison of Methods for the Construction of Composite Coincident and Leading Indexes for the UK," Working Papers 590, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    2. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
    3. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    4. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    5. 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.
    6. Jason Angelopoulos & Costas I. Chlomoudis, 2017. "A Generalized Dynamic Factor Model for the U.S. Port Sector," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 67(1), pages 22-37, January-M.
    7. Jason Angelopoulos, 2017. "Creating and assessing composite indicators: Dynamic applications for the port industry and seaborne trade," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 126-159, March.
    8. Andrea Carriero & Massimiliano Marcellino, 2007. "Monitoring the Economy of the Euro Area: A Comparison of Composite Coincident Indexes," Working Papers 319, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Shirly Siew-Ling WONG & Chin-Hong PUAH & Shazali ABU MANSOR & Venus Khim-Sen LIEW, 2016. "Measuring Business Cycle Fluctuations: An Alternative Precursor To Economic Crises," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 235-248.
    10. Javier Maldonado & Esther Ruiz, 2021. "Accurate Confidence Regions for Principal Components Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1432-1453, December.
    11. Lupu, Radu & Călin, Adrian Cantemir & Dumitrescu, Dan Gabriel & Lupu, Iulia, 2025. "Introducing a novel fragility index for assessing financial stability amid asset bubble episodes," The North American Journal of Economics and Finance, Elsevier, vol. 75(PA).
    12. Fichtner, Ferdinand & Rüffer, Rasmus & Schnatz, Bernd, 2009. "Leading indicators in a globalised world," Working Paper Series 1125, European Central Bank.
    13. Schnatz, Bernd & D'Agostino, Antonello, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
    14. Heij, C., 2007. "Improved forecasting with leading indicators: the principal covariate index," Econometric Institute Research Papers EI 2007-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  33. Andrea Carriero, 2007. "Forecasting the Yield Curve Using Priors from No Arbitrage Affine Term Structure Models," Working Papers 612, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Fabricio Tourrucôo & João F. Caldeira & Guilherme V. Moura & André A. P. Santos, 2016. "Forecasting The Yield Curve With The Arbitrage-Free Dynamic Nelson-Siegel Model: Brazilian Evidence," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 028, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    2. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    3. David Bolder & Yuliya Romanyuk, 2008. "Combining Canadian Interest-Rate Forecasts," Staff Working Papers 08-34, Bank of Canada.
    4. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    5. Vieira, Fausto José Araújo & Chague, Fernando Daniel & Fernandes, Marcelo, 2017. "A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US," Textos para discussão 445, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    6. Bojan Baskot & Silvije Orsag & Dejan Mikerevic, 2018. "Yield Curve In Bosnia And Herzegovina: Financial And Macroeconomic Framework," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 9(1), pages 1-15.
    7. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.
    8. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
    9. Wali ULLAH & Khadija Malik BARI, 2018. "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-28, September.
    10. Caio Almeida & Axel Simonsen & José Valentim Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
    11. Frank J. Fabozzi & Francesco A. Fabozzi & Diana Tunaru, 2023. "A comparison of multi-factor term structure models for interbank rates," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 323-356, July.
    12. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

  34. Andrea Carriero & Massimiliano Marcellino, 2007. "Monitoring the Economy of the Euro Area: A Comparison of Composite Coincident Indexes," Working Papers 319, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

    Cited by:

    1. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2008. "A Monthly Indicator of the Euro Area GDP," Economics Working Papers ECO2008/32, European University Institute.

  35. Andrea Carriero & Massimiliano Marcellino, 2007. "Sectoral Survey-based Confidence Indicators for Europe," Working Papers 320, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

    Cited by:

    1. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    2. Christian Seiler, 2014. "Mode Preferences in Business Surveys: Evidence from Germany," ifo Working Paper Series 193, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. Nicoletta Pashourtidou & Andreas Tsiaklis, 2011. "An Analysis of Firms’ Expectations about Activity and Employment," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 5(1), pages 71-85, June.
    4. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, vol. 29(4), pages 644-658.
    5. Thomas Lux & Duc Thi Luu & Boyan Yanovski, 2020. "An analysis of systemic risk in worldwide economic sentiment indices," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 909-928, November.
    6. Andrea Carriero & Massimiliano Marcellino, 2007. "Monitoring the Economy of the Euro Area: A Comparison of Composite Coincident Indexes," Working Papers 319, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    7. Luu, Duc Thi & Yanovski, Boyan & Lux, Thomas, 2018. "An analysis of systematic risk in worldwide econonomic sentiment indices," Economics Working Papers 2018-03, Christian-Albrechts-University of Kiel, Department of Economics.
    8. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    9. Camila Figueroa S. & Michael Pedersen, 2019. "Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile)," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 098-131, December.
    10. Willem Vanlaer & Samantha Bielen & Wim Marneffe, 2020. "Consumer Confidence and Household Saving Behaviors: A Cross-Country Empirical Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 677-721, January.

  36. Andrea Carriero, 2007. "A Bayesian Framework for the Expectations Hypothesis. How to Extract Additional Information from the Term Structure of Interest Rates," Working Papers 591, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.

  37. Favero, Carlo A. & Carriero, Andrea & Kaminska, Iryna, 2004. "Financial Factors, Macroeconomic Information and the Expectations Theory of the Term Structure of Interest Rates," CEPR Discussion Papers 4301, C.E.P.R. Discussion Papers.

    Cited by:

    1. Charles Goodhart, 2009. "The Interest Rate Conditioning Assumption," International Journal of Central Banking, International Journal of Central Banking, vol. 5(2), pages 85-108, June.
    2. Erdenebat Bataa & Dong H. Kim & Denise R. Osborn, 2007. "Expectations Hypothesis Tests in the Presence of Model Uncertainty," Discussion Paper Series 0703, Institute of Economic Research, Korea University.
    3. Carlo A. Favero & Linlin Niu & Luca Sala, 2007. "Term Structure Forecasting: No-arbitrage Restrictions vs. Large Information Set," Working Papers 318, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Goodhart, Charles, 2004. "The interaction between the Bank of England's forecasts and policy, and the outturn," LSE Research Online Documents on Economics 24710, London School of Economics and Political Science, LSE Library.
    5. Francesco Bianchi & Haroon Mumtaz & Paolo Surico, 2009. "Dynamics of the term structure of UK interest rates," Bank of England working papers 363, Bank of England.
    6. Mao-Wei Hung & Jr-Yan Wang, 2011. "Loss aversion and the term structure of interest rates," Applied Economics, Taylor & Francis Journals, vol. 43(29), pages 4623-4640.
    7. Favero, Carlo A. & Giglio, Stefano, 2006. "Fiscal Policy and the Term Structure: Evidence from the Case of Italy in the EMS and the EMU Periods," CEPR Discussion Papers 5793, C.E.P.R. Discussion Papers.
    8. Galvao, Ana Beatriz & Costa, Sonia, 2013. "Does the euro area forward rate provide accurate forecasts of the short rate?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 131-141.
    9. Dungey, Mardi & Tugrul Vehbi, M, 2011. "A SVECM Model of the UK Economy and The Term Premium," Working Papers 11610, University of Tasmania, Tasmanian School of Business and Economics.
    10. Chen, Lin & Wen, Fenghua & Zhang, Yun & Miao, Xiao, 2023. "Oil supply expectations and corporate social responsibility," International Review of Financial Analysis, Elsevier, vol. 87(C).
    11. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    12. Ayse Tuncer & Mehmet Ivrendi, 2025. "Exploring the Nexus Between Short- and Long-Run Rate of Interests in Turkey’s Bond Market," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 11(1), pages 39-62, June.
    13. Zhu, Xiaoneng, 2011. "Revisiting the expectations hypothesis: The Japanese term structure and regime shifts," Journal of Economics and Business, Elsevier, vol. 63(3), pages 237-249, May.
    14. Favero, Carlo A., 2006. "Taylor rules and the term structure," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1377-1393, October.
    15. Bianchi, Francesco & Mumtaz, Haroon & Surico, Paolo, 2009. "The great moderation of the term structure of UK interest rates," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 856-871, September.
    16. Mariam Camarero & Javier Ordóñez & Cecilio Tamarit, 2009. "External Macroeconomic Factors and the Link between Short‐ and Long‐Run European Interest Rates: A Note," Southern Economic Journal, John Wiley & Sons, vol. 75(4), pages 1212-1219, April.
    17. Haroon Mumtaz & Paolo Surico, 2009. "Time-varying yield curve dynamics and monetary policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 895-913.
    18. Søren Johansen & Anders Rygh Swensen, 2009. "On a Numerical and Graphical Technique for Evaluating some Models Involving Rational Expectations," Discussion Papers 09-10, University of Copenhagen. Department of Economics.
    19. Clive G. Bowsher & Roland Meeks, 2006. "The Impossibility of Stationary Yield Spreads and I(1) Yields under the Expectations Theory of the Term Structure," Economics Papers 2006-W05, Economics Group, Nuffield College, University of Oxford.
    20. Andrea Carriero, 2006. "Explaining US–UK Interest Rate Differentials: A Reassessment of the Uncovered Interest Rate Parity in a Bayesian Framework," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 879-899, December.
    21. Suzan Hol, 2006. "Determinants of long-term interest rates in the Scandinavian countries," Discussion Papers 469, Statistics Norway, Research Department.
    22. Daniel L. Thornton, 2005. "Predictions of short-term rates and the expectations hypothesis of the term structure of interest rates," Working Papers 2004-010, Federal Reserve Bank of St. Louis.
    23. Martina Makarieva, 2021. "Yield curve modelling and forecasting in an undeveloped financial market: The case of Bulgaria," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 61-83,84-10.
    24. Ricardo Gimeno & José Manuel Marqués, 2009. "Extraction of financial market expectations about inflation and interest rates from a liquid market," Working Papers 0906, Banco de España.
    25. Sónia Costa & Ana Beatriz Galvão, 2006. "The Forward Premium of Euro Interest Rates," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    26. Zeno Rotondi, 2006. "The Macroeconomy and the Yield Curve: A Review of the Literature with Some New Evidence," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 65(2), pages 193-224, November.
    27. George Halkos & Stephanos Papadamou, 2007. "Significance of risk modelling in the term structure of interest rates," Applied Financial Economics, Taylor & Francis Journals, vol. 17(3), pages 237-247.
    28. Daniel L. Thornton, 2004. "Testing the expectations hypothesis: some new evidence for Japan," Review, Federal Reserve Bank of St. Louis, vol. 86(Sep), pages 21-40.
    29. Zhu, Xiaoneng & Rahman, Shahidur, 2015. "A regime-switching Nelson–Siegel term structure model of the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 1-17.
    30. Andrea Carriero, 2007. "A Bayesian Framework for the Expectations Hypothesis. How to Extract Additional Information from the Term Structure of Interest Rates," Working Papers 591, Queen Mary University of London, School of Economics and Finance.
    31. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2009. "The expectation hypothesis of interest rates and network theory: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1137-1149.
    32. Sarno, Lucio & Thornton, Daniel L & Valente, Giorgio, 2005. "The Empirical Failure of the Expectations Hypothesis of the Term Structure of Bond Yields," CEPR Discussion Papers 5259, C.E.P.R. Discussion Papers.
    33. Goodhart, Charles, 2015. "The interest rate conditioning assumption," LSE Research Online Documents on Economics 24666, London School of Economics and Political Science, LSE Library.
    34. Goodhart Charles A.E., 2005. "The Monetary Policy Committee's Reaction Function: An Exercise in Estimation," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-42, August.
    35. Afonso, António & Martins, Manuel M.F., 2012. "Level, slope, curvature of the sovereign yield curve, and fiscal behaviour," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1789-1807.
    36. Goodhart, Charles, 2004. "The Monetary Policy Committee's reaction function: an exercise in estimation," LSE Research Online Documents on Economics 24708, London School of Economics and Political Science, LSE Library.
    37. ZHU Xiaoneng & Shahidur RAHMAN, 2009. "A Regime Switching Macro-finance Model of the Term Structure," Economic Growth Centre Working Paper Series 0901, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.

Articles

  1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2025. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 57-73, January.
    See citations under working paper version above.
  2. Andrea Carriero & Alessio Volpicella, 2025. "Max Share Identification of Multiple Shocks: An Application to Uncertainty and Financial Conditions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(1), pages 1-13, January.

    Cited by:

    1. Milov{s} Ciganovi'c & Elena Scola Gagliardi & Massimiliano Tancioni, 2025. "Disentangling the Distributional Effects of Financial Shocks in the Euro Area," Papers 2510.11289, arXiv.org.

  3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
    See citations under working paper version above.
  4. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2024. "Capturing Macro‐Economic Tail Risks with Bayesian Vector Autoregressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(5), pages 1099-1127, August.
    See citations under working paper version above.
  5. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2024. "Blended identification in structural VARs," Journal of Monetary Economics, Elsevier, vol. 146(C).
    See citations under working paper version above.
  6. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2023. "Macro uncertainty in the long run," Economics Letters, Elsevier, vol. 225(C).
    See citations under working paper version above.
  7. 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.
    See citations under working paper version above.
  8. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.

    Cited by:

    1. 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.
    2. Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
    3. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2024. "Nowcasting Norwegian household consumption with debit card transaction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1220-1244, November.
    4. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    5. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    6. Ignacio Garr'on & Andrey Ramos, 2025. "High-frequency Density Nowcasts of U.S. State-Level Carbon Dioxide Emissions," Papers 2501.03380, arXiv.org.
    7. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    8. 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).
    9. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    10. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.
    11. 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.
    12. Gloria González‐Rivera & C. Vladimir Rodríguez‐Caballero & Esther Ruiz, 2024. "Expecting the unexpected: Stressed scenarios for economic growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 926-942, August.
    13. Labonne, Paul, 2025. "Asymmetric uncertainty: Nowcasting using skewness in real-time data," International Journal of Forecasting, Elsevier, vol. 41(1), pages 229-250.
    14. Tobias Adrian & Hongqi Chen & Max-Sebastian Dov`i & Ji Hyung Lee, 2025. "Machine-learning Growth at Risk," Papers 2506.00572, arXiv.org.
    15. Andrey Polbin & Andrei Shumilov, 2025. "Nowcasting and forecasting Russian GDP and its components using quantile models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 79, pages 5-26.
    16. James Mitchell & Aubrey Poon & Dan Zhu, 2024. "Constructing density forecasts from quantile regressions: Multimodality in macrofinancial dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 790-812, August.
    17. Efrem Castelnuovo & Lorenzo Mori, 2025. "Uncertainty, Skewness, and the Business Cycle Through the MIDAS Lens," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 89-107, January.
    18. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2024. "A Quantile Nelson-Siegel model," Papers 2401.09874, arXiv.org, revised Jul 2025.
    19. Polbin, Andrey & Shumilov, Andrei, 2025. "Наукастинг И Прогнозирование Ввп России И Его Компонентов С Помощью Квантильных Моделей [Nowcasting and forecasting Russian GDP and its components using quantile models]," MPRA Paper 125440, University Library of Munich, Germany.
    20. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    21. Mai Dao & Lam Nguyen, 2025. "Variable selection in macroeconomic stress test: a Bayesian quantile regression approach," Empirical Economics, Springer, vol. 68(3), pages 1113-1169, March.
    22. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2025. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 57-73, January.
    23. Narasingha Das & Partha Gangopadhyay, 2023. "Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.

  9. Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
    See citations under working paper version above.
  10. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.

    Cited by:

    1. Chang, Hao-Wen & Chang, Tsangyao & Lee, Chien-Chiang, 2023. "Return and volatility connectedness among the BRICS stock and oil markets," Resources Policy, Elsevier, vol. 86(PA).
    2. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    3. Gnangnon, Sèna Kimm, 2023. "Effect of Economic Uncertainty on Remittances Flows from Developed Countries," EconStor Preprints 279480, ZBW - Leibniz Information Centre for Economics.
    4. Che, Ming & Zhu, Zixiang & Li, Yujia, 2023. "Geopolitical risk and economic policy uncertainty: Different roles in China's financial cycle," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
    6. Andrea Carriero & Massimiliano Marcellino & Tommaso Tornese, 2022. "Macro Uncertainty in the Long Run," BAFFI CAREFIN Working Papers 22188, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    7. Alina Bobasu & Lucia Quaglietti & Martino Ricci, 2024. "Tracking Global Economic Uncertainty: Implications for the Euro Area," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(2), pages 820-857, June.
    8. Mohammed El-Khodary & Amine El Kadri & Sara Dassouli, 2025. "A comprehensive analysis of the inter-relationships of impact between automotive industry, economic growth, natural resources and environmental degradation: Morocco as an example," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(8), pages 18837-18868, August.
    9. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    10. Beckmann, Joscha & Czudaj, Robert L., 2024. "Uncertainty Shocks and Inflation: The Role of Credibility and Expectation Anchoring," MPRA Paper 119971, University Library of Munich, Germany.
    11. Yujia, Li & Zixiang, Zhu & Ming, Che, 2024. "Exploring the relationship between China's economic policy uncertainty and business cycles: Exogenous impulse or endogenous responses?," Emerging Markets Review, Elsevier, vol. 58(C).
    12. Gabriele Fiorentini & Alessio Moneta & Francesca Papagni, 2024. "Identification of one independent shock in structural VARs," LEM Papers Series 2024/28, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    13. Koivisto, Tero, 2024. "Asset price shocks and inflation in the Finnish economy," BoF Economics Review 6/2024, Bank of Finland.
    14. Bacchiocchi, Emanuele & Dragomirescu-Gaina, Catalin, 2024. "Uncertainty spill-overs: When policy and financial realms overlap," Journal of International Money and Finance, Elsevier, vol. 143(C).
    15. Moreno-Pérez, Carlos & Minozzo, Marco, 2024. "‘Making text talk’: The minutes of the Central Bank of Brazil and the real economy," Journal of International Money and Finance, Elsevier, vol. 147(C).
    16. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    17. Carboni, Giacomo & Fonseca, Luís & Fornari, Fabio & Urrutia, Leonardo, 2026. "Structural drivers of growth at risk: insights from a VAR-quantile regression approach," Working Paper Series 3171, European Central Bank.
    18. Ambrocio, Gene, 2022. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2022, Bank of Finland.
    19. Sèna Kimm Gnangnon, 2024. "The effect of economic uncertainty on remittance flows from developed countries," Economic Affairs, Wiley Blackwell, vol. 44(2), pages 267-280, June.

  11. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
    See citations under working paper version above.
  12. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 273-293, April.
    See citations under working paper version above.
  13. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.

    Cited by:

    1. Ha, Jongrim & Kose, M. Ayhan & Ohnsorge, Franziska, 2021. "Inflation During the Pandemic: What Happened? What is Next?," MPRA Paper 108677, University Library of Munich, Germany.
    2. Dimitris Korobilis & Maximilian Schröder, 2023. "Probabilistic Quantile Factor Analysis," Working Papers No 05/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    3. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    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. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    6. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    7. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Density Forecasting," Papers 2404.02671, arXiv.org, revised Nov 2024.
    8. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    9. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    10. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024. "Labour at risk," European Economic Review, Elsevier, vol. 170(C).
    11. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    12. Annalisa Cadonna & Sylvia Fruhwirth-Schnatter & Peter Knaus, 2019. "Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models," Papers 1912.03100, arXiv.org.
    13. Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
    14. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    15. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    16. Maximilian Böck & Martin Feldkircher & Florian Huber, 2020. "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R," Globalization Institute Working Papers 395, Federal Reserve Bank of Dallas.
    17. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
    18. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    19. Niko Hauzenberger & Florian Huber & Luca Onorante, 2021. "Combining shrinkage and sparsity in conjugate vector autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
    20. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    21. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    22. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    23. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
    24. Florian Huber & Gary Koop, 2024. "Fast and order‐invariant inference in Bayesian VARs with nonparametric shocks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1301-1320, November.
    25. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    26. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    27. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    28. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    29. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
    30. Hauzenberger Niko & Huber Florian & Koop Gary, 2024. "Dynamic Shrinkage Priors for Large Time-Varying Parameter Regressions Using Scalable Markov Chain Monte Carlo Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 201-225, April.
    31. Frank C. Z. Wu, 2024. "Bayesian collapsed Gibbs sampling for a stochastic volatility model with a Dirichlet process mixture," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 697-704, June.
    32. Pedro A. Lima & Carlos M. Carvalho & Hedibert F. Lopes & Andrew Herren, 2025. "Minnesota BART," Papers 2503.13759, arXiv.org.
    33. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    34. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
    35. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
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    84. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    85. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    86. Boeck, Maximilian & Feldkircher, Martin, 2021. "The Impact of Monetary Policy on Yield Curve Expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 887-901.
    87. Zhang, Wen, 2022. "China’s government spending and global inflation dynamics: The role of the oil price channel," Energy Economics, Elsevier, vol. 110(C).
    88. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    89. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    90. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.
    91. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    92. Xiaolei Wang & Tomasz Wo'zniak, 2025. "Bayesian Analyses of Structural Vector Autoregressions with Sign, Zero, and Narrative Restrictions Using the R Package bsvarSIGNs," Papers 2501.16711, arXiv.org.
    93. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    94. Tomasz Wo'zniak, 2024. "Fast and Efficient Bayesian Analysis of Structural Vector Autoregressions Using the R Package bsvars," Papers 2410.15090, arXiv.org, revised Apr 2025.
    95. Nadja Klein & Michael Stanley Smith & David J. Nott, 2023. "Deep distributional time series models and the probabilistic forecasting of intraday electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 493-511, June.
    96. Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Papers 2020_21, Business School - Economics, University of Glasgow.
    97. Paponpat Taveeapiradeecharoen & Nattapol Aunsri, 2025. "Forecasting in small open emerging economies Evidence from Thailand," Papers 2509.14805, arXiv.org.
    98. Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    99. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
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    101. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023. "Labour at risk," Working Paper Series 2840, European Central Bank.
    102. Todd E. Clark & Matthew V. Gordon & Saeed Zaman, 2023. "Forecasting Core Inflation and Its Goods, Housing, and Supercore Components," Working Papers 23-34, Federal Reserve Bank of Cleveland.
    103. Jongrim Ha & M. Ayhan Kose & Franziska Ohnsorge, 2022. "Global Stagflation," Koç University-TUSIAD Economic Research Forum Working Papers 2204, Koc University-TUSIAD Economic Research Forum.
    104. 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.
    105. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    106. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org, revised Sep 2025.
    107. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Structural Vector Autoregressions with Non-Centred Stochastic Volatility," Papers 2404.11057, arXiv.org, revised Oct 2025.
    108. Panovska, Irina & Zhang, Licheng, 2024. "Jobless recoveries and time variation in labor markets," Journal of Macroeconomics, Elsevier, vol. 81(C).
    109. Dimitris Korobilis, 2022. "A new algorithm for structural restrictions in Bayesian vector autoregressions," Papers 2206.06892, arXiv.org.
    110. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    111. 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.
    112. Massimiliano Marcellino & Andrea Renzetti & Tommaso Tornese, 2024. "Nowcasting distributions: a functional MIDAS model," Papers 2411.05629, arXiv.org.
    113. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
    114. Gideon du Rand & Hylton Hollander & Dawie van Lill, 2023. "Time-varying fiscal multipliers for South Africa: A large time-varying parameter vector autoregression approach," WIDER Working Paper Series wp-2023-106, World Institute for Development Economic Research (UNU-WIDER).
    115. Kunovac, Davor & Palenzuela, Diego Rodriguez & Sun, Yiqiao, 2022. "A new optimum currency area index for the euro area," Working Paper Series 2730, European Central Bank.
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    117. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    118. James Cloyne & Joseba Martinez & Haroon Mumtaz & Paolo Surico, 2023. "The Dynamic Effects of Income Tax Changes in a World of Ideas," Working Papers 970, Queen Mary University of London, School of Economics and Finance.
    119. Anna Pajor & Justyna Wróblewska & Łukasz Kwiatkowski & Jacek Osiewalski, 2024. "Hybrid SV‐GARCH, t‐GARCH and Markov‐switching covariance structures in VEC models—Which is better from a predictive perspective?," International Statistical Review, International Statistical Institute, vol. 92(1), pages 62-86, April.
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    123. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    124. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.
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  14. 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.

    Cited by:

    1. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    2. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    3. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    4. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    5. Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
    6. 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.
    7. Paranhos, Livia, 2021. "Predicting Inflation with Neural Networks," The Warwick Economics Research Paper Series (TWERPS) 1344, University of Warwick, Department of Economics.
    8. 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).
    9. Jan Čapek & Jesús Crespo Cuaresma & Jakub Chalmovianský & Vlastimil Reichel, 2025. "Real‐Time Data, Revisions and the Predictive Ability of DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 87(6), pages 1059-1080, December.
    10. Ba Chu & Shafiullah Qureshi, 2021. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers 21-12, Carleton University, Department of Economics.
    11. Shovon Sengupta & Sunny Kumar Singh & Tanujit Chakraborty, 2025. "Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks," Papers 2510.23347, arXiv.org.
    12. 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.
    13. Labonne, Paul, 2025. "Asymmetric uncertainty: Nowcasting using skewness in real-time data," International Journal of Forecasting, Elsevier, vol. 41(1), pages 229-250.
    14. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
    15. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    16. 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.).
    17. Michael P. Clements & Ana Beatriz Galvão, 2023. "Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 164-185, March.
    18. Yolanda S. Stander, 2023. "The Governance and Disclosure of IFRS 9 Economic Scenarios," JRFM, MDPI, vol. 16(1), pages 1-27, January.
    19. Ana Beatriz Galvão & Marta Lopresto, 2020. "Real-time Probabilistic Nowcasts of UK Quarterly GDP Growth using a Mixed-Frequency Bottom-up Approach," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-06, Economic Statistics Centre of Excellence (ESCoE).
    20. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    21. Nikoleta Anesti & Eleni Kalamara & George Kapetanios, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, Bank of England.
    22. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    23. Livia Paranhos, 2021. "Predicting Inflation with Recurrent Neural Networks," Papers 2104.03757, arXiv.org, revised Oct 2023.
    24. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2020. "Forecasting natural gas prices using highly flexible time-varying parameter models," Working Papers 2020-01, University of Tasmania, Tasmanian School of Business and Economics.
    25. Daniel Hopp, 2024. "Benchmarking econometric and machine learning methodologies in nowcasting GDP," Empirical Economics, Springer, vol. 66(5), pages 2191-2247, May.
    26. David Kohns & Galina Potjagailo, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    27. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.

  15. Andrea Carriero & Sarah Mouabbi & Elisabetta Vangelista, 2018. "UK term structure decompositions at the zero lower bound," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 643-661, August.
    See citations under working paper version above.
  16. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
    See citations under working paper version above.
  17. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2017. "Have Standard VARS Remained Stable Since the Crisis?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 931-951, August.
    See citations under working paper version above.
  18. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
    See citations under working paper version above.
  19. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2016. "Structural analysis with Multivariate Autoregressive Index models," Journal of Econometrics, Elsevier, vol. 192(2), pages 332-348.
    See citations under working paper version above.
  20. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.
    See citations under working paper version above.
  21. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.

    Cited by:

    1. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  22. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.

    Cited by:

    1. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2017. "Measurement errors and monetary policy: Then and now," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 66-78.
    2. Urmat Dzhunkeev, 2025. "MOSES: Macroeconomic Forecasting with Models and Sentiment Synthesis," Russian Journal of Money and Finance, Bank of Russia, vol. 84(4), pages 63-84, December.
    3. Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
    4. M. Mogliani & Thomas Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    5. Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
    6. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    9. Natalia Makeeva, 2025. "The impact of the official statistics revision on the accuracy of the Russian macroeconomic indicators nowcasting models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 79, pages 27-49.
    10. Asimakopoulos, Stylianos & Lalik, Magdalena & Paredes, Joan & Salvado García, José, 2023. "GDP revisions are not cool: the impact of statistical agencies’ trade-off," Working Paper Series 2857, European Central Bank.

  23. Andrea Carriero & Haroon Mumtaz & Konstantinos Theodoridis & Angeliki Theophilopoulou, 2015. "The Impact of Uncertainty Shocks under Measurement Error: A Proxy SVAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(6), pages 1223-1238, September.
    See citations under working paper version above.
  24. 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.
    See citations under working paper version above.
  25. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.

    Cited by:

    1. Alberto Caruso & Laura Coroneo, 2023. "Does Real‐Time Macroeconomic Information Help to Predict Interest Rates?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(8), pages 2027-2059, December.
    2. Kwon, Hyuck-Shin & Bang, Doo Won & Kim, Myeong Hyeon, 2017. "Korean Housing Cycle: Implications for Risk Management (Factor-augmented VAR Approach)," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 39(3), pages 43-62.
    3. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    4. Lewis N.K. Mambo, 2024. "From Multidimensional Ornstein - Uhlenbeck Process to Bayesian Vector Autoregressive Process," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 15(1), pages 1-32, December.
    5. Andrea Carriero & Lorenzo Ricci & Elisabetta Vangelista, 2022. "Expectations and term premia in EFSF bond yields," Working Papers 54, European Stability Mechanism.
    6. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    7. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
    9. Argyropoulos Efthymios & Tzavalis Elias, 2015. "Term spread regressions of the rational expectations hypothesis of the term structure allowing for risk premium effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 49-70, February.
    10. Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
    11. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    12. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
    13. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    14. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2018-08, Department of Economics, University of Konstanz.
    15. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2023. "General Bayesian time‐varying parameter vector autoregressions for modeling government bond yields," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 69-87, January.
    16. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    17. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
    18. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    19. Doo Won Bang & HyuckShin Kwon, 2022. "Policy Impact Analysis of Housing Policies Using Housing Cycles," SAGE Open, , vol. 12(3), pages 21582440221, July.
    20. Gary Koop & Dimitris Korobilis, 2013. "A new index of financial conditions," Working Papers 1307, University of Strathclyde Business School, Department of Economics.
    21. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    22. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2014. "Forecasting with factor-augmented error correction models," International Journal of Forecasting, Elsevier, vol. 30(3), pages 589-612.
    23. 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.
    24. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    25. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    26. Oskar Gustafsson & Mattias Villani & Pär Stockhammar, 2023. "Bayesian optimization of hyperparameters from noisy marginal likelihood estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 577-595, June.
    27. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.
    28. 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.
    29. Guanhao Feng & Nicholas Polson, 2020. "Regularizing Bayesian predictive regressions," Journal of Asset Management, Palgrave Macmillan, vol. 21(7), pages 591-608, December.
    30. Jan Pruser, 2024. "A large non-Gaussian structural VAR with application to Monetary Policy," Papers 2412.17598, arXiv.org.
    31. Gür Ali, Özden & Gürlek, Ragıp, 2020. "Automatic Interpretable Retail forecasting with promotional scenarios," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1389-1406.
    32. 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.
    33. Almeida, Caio & Ardison, Kym & Kubudi, Daniela, 2014. "Approximating Risk Premium on a Parametric Arbitrage-free Term Structure Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.
    34. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org, revised Sep 2025.
    35. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
    36. William Gatt & Germano Ruisi, 2020. "Housing demand shocks, foreign labour inflows and consumption," CBM Working Papers WP/07/2020, Central Bank of Malta.
    37. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
    38. Prüser Jan & Hanck Christoph, 2021. "A Comparison of Approaches to Select the Informativeness of Priors in BVARs," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(4), pages 501-525, August.
    39. И Управления Мир Экономики, 2017. "Байесовский подход к анализу влияния монетарной политики на макроэкономические показатели России. Bayesian approach to the analysis of monetary policy impact on Russian macroeconomics indicators," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 17(4), pages 53-70.
    40. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2023. "Directed graphs and variable selection in large vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 223-246, March.
    41. Joshua C. C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2020. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 692-711, September.
    42. Gelper, Sarah & Wilms, Ines & Croux, Christophe, 2016. "Identifying Demand Effects in a Large Network of Product Categories," Journal of Retailing, Elsevier, vol. 92(1), pages 25-39.
    43. Danilo Leiva-Leon, 2017. "Monitoring the Spanish Economy through the Lenses of Structural Bayesian VARs," Occasional Papers 1706, Banco de España.
    44. Florian Huber & Gregor Kastner & Martin Feldkircher, 2018. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Working Papers in Economics 2018-5, University of Salzburg.
    45. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2017. "Forecasting the term structure of government bond yields in unstable environments," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 209-225.

  26. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, vol. 164(1), pages 21-34, September.
    See citations under working paper version above.
  27. Andrea Carriero & Massimiliano Marcellino, 2011. "Sectoral Survey‐based Confidence Indicators for Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(2), pages 175-206, April.
    See citations under working paper version above.
  28. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2011. "Forecasting large datasets with Bayesian reduced rank multivariate models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 735-761, August.
    See citations under working paper version above.
  29. Andrea Carriero, 2011. "Forecasting The Yield Curve Using Priors From No‐Arbitrage Affine Term Structure Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(2), pages 425-459, May.
    See citations under working paper version above.
  30. Carriero, A. & Kapetanios, G. & Marcellino, M., 2009. "Forecasting exchange rates with a large Bayesian VAR," International Journal of Forecasting, Elsevier, vol. 25(2), pages 400-417.
    See citations under working paper version above.
  31. Carriero, Andrea, 2008. "A simple test of the New Keynesian Phillips Curve," Economics Letters, Elsevier, vol. 100(2), pages 241-244, August.
    See citations under working paper version above.
  32. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    See citations under working paper version above.
  33. Andrea Carriero, 2006. "Explaining US–UK Interest Rate Differentials: A Reassessment of the Uncovered Interest Rate Parity in a Bayesian Framework," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 879-899, December.

    Cited by:

    1. Joseph P. Byrne & Jun Nagayasu, 2008. "Common and idiosyncratic factors of the exchange risk premium in emerging European markets," Working Papers 2008_28, Business School - Economics, University of Glasgow.
    2. Carlos Eduardo Castillo-Maldonado & Fidel Pérez-Macal, 2013. "Assessment of models to forecast exchange rates: The quetzal–U.S. dollar exchange rate," Journal of Applied Economics, Universidad del CEMA, vol. 16, pages 71-99, May.
    3. Byrne, Joseph P & Nagayasu, Jun, 2011. "Common factors of the exchange risk premium in emerging European markets," MPRA Paper 31393, University Library of Munich, Germany.
    4. Nandini Srivastava & Stephen Satchell, 2012. "Are There Bubbles in the Art Market? The Detection of Bubbles when Fair Value is Unobservable," Birkbeck Working Papers in Economics and Finance 1209, Birkbeck, Department of Economics, Mathematics & Statistics.
    5. Lorenzo Pozzi & Barbara Sadaba, 2017. "Detecting Scapegoat Effects in the Relationship Between Exchange Rates and Macroeconomic Fundamentals," Staff Working Papers 17-22, Bank of Canada.

  34. Carriero, Andrea & Favero, Carlo A. & Kaminska, Iryna, 2006. "Financial factors, macroeconomic information and the Expectations Theory of the term structure of interest rates," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 339-358.
    See citations under working paper version above.
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