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Antonello D'Agostino

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. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Time Varying Parameters and Stochastic Volatility
  2. Antonello D'Agostino & Kieran McQuinn & Derry O’Brien, 2012. "Nowcasting Irish GDP," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 21-31.

    Mentioned in:

    1. > Econometrics > Forecasting > Nowcasting

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Antonello D'Agostino & Paolo Surico, 2012. "A Century of Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1097-1106, November.

    Mentioned in:

    1. A Century of Inflation Forecasts (REStat 2012) in ReplicationWiki ()
  2. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.

    Mentioned in:

    1. Macroeconomic forecasting and structural change (Journal of Applied Econometrics 2013) in ReplicationWiki ()

Working papers

  1. Rudolf Alvise Lennkh & Antonello D'Agostino, 2016. "Euro Area Sovereign Ratings: An Analysis of Fundamental Criteria and Subjective Judgement," Working Papers 14, European Stability Mechanism.

    Cited by:

    1. Jan Bruha & Moritz Karber & Beatrice Pierluigi & Ralph Setzer, 2017. "Understanding Rating Movements in Euro Area Countries," Working Papers 2017/06, Czech National Bank.
    2. Annika Luisa Hofmann & Miguel Ferreira & João Lampreia, 2017. "Case Study: DBRS Sovereign Rating of Portugal. Analysis of Rating Methodology and Rating Decisions," GEE Papers 0073, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Jul 2017.
    3. Hu, Haoshen & Prokop, Jörg & Trautwein, Hans-Michael, 2022. "Transnational spillover effects of European sovereign rating signals on bank stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 171-182.

  2. Osbat, Chiara & D'Agostino, Antonello & Modugno, Michele, 2016. "A global trade model for the euro area," Working Paper Series 1986, European Central Bank.

    Cited by:

    1. Christian Grimme & Robert Lehmann & Marvin Noeller, 2019. "Forecasting Imports with Information from Abroad," ifo Working Paper Series 294, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    3. 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.
    4. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    5. André Binette & Tony Chernis & Daniel de Munnik, 2017. "Global Real Activity for Canadian Exports: GRACE," Discussion Papers 17-2, Bank of Canada.
    6. 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.).
    7. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    8. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
    9. Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.

  3. D'Agostino, Antonello & Mendicino, Caterina, 2015. "Expectation-driven cycles: time-varying effects," Working Paper Series 1776, European Central Bank.

    Cited by:

  4. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
    2. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2017. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 81869, London School of Economics and Political Science, LSE Library.
    3. Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
    4. 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.
    5. 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.
    6. 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.).
    7. Scott A. Brave & R. Andrew Butters & David Kelley, 2019. "A New “Big Data” Index of U.S. Economic Activity," Economic Perspectives, Federal Reserve Bank of Chicago, issue 1, pages 1-30.
    8. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    9. Beetsma, Roel & Cimadomo, Jacopo & van Spronsen, Josha, 2022. "One Scheme Fits All: A Central Fiscal Capacity for the EMU Targeting Eurozone, National and Regional Shocks," CEPR Discussion Papers 16829, C.E.P.R. Discussion Papers.
    10. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    11. Robert Lehmann & Magnus Reif & Timo Wollmershäuser, 2020. "ifoCAST: The New Forecast Standard of the ifo Institute," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 73(11), pages 31-39, November.
    12. Petrella, Ivan & Santoro, Emiliano & Simonsen, Lasse de la Porte, 2018. "Time-varying Price Flexibility and Inflation Dynamics," CEPR Discussion Papers 13027, C.E.P.R. Discussion Papers.
    13. Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
    14. Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.

  5. D'Agostino, Antonello & Cimadomo, Jacopo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Paper Series 1856, European Central Bank.

    Cited by:

    1. 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.
    2. Tesi Aliaj & Milos Ciganovic & Massimiliano Tancioni, 2023. "Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 464-480, April.
    3. Francesco Simone Lucidi, 2021. "The Misalignment of Fiscal Multipliers in Italian Regions," Working Papers in Public Economics 204, University of Rome La Sapienza, Department of Economics and Law.
    4. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    5. 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.
    6. Henrique S. Basso & Omar Rachedi, 2021. "The Young, the Old, and the Government: Demographics and Fiscal Multipliers," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 110-141, October.
    7. 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.
    8. Piacentini, Paolo & Prezioso, Stefano & Testa, Giuseppina, 2015. "Effects of fiscal policy in the North and South of Italy," MPRA Paper 62372, University Library of Munich, Germany.
    9. 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.
    10. Guy P. Nason & Ben Powell & Duncan Elliott & Paul A. Smith, 2017. "Should we sample a time series more frequently?: decision support via multirate spectrum estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 353-407, February.
    11. Thomas B. Götz & Alain W. Hecq, 2019. "Granger Causality Testing in Mixed‐Frequency VARs with Possibly (Co)Integrated Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 914-935, November.
    12. 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.
    13. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
    14. Nikolay Hristov & Oliver Hülsewig & Thomas Siemsen & Timo Wollmershäuser, 2019. "Restoring euro area monetary transmission: Which role for government bond rates?," Empirical Economics, Springer, vol. 57(3), pages 991-1021, September.
    15. Thomas B Götz & Klemens Hauzenberger, 2021. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 442-461.
    16. Li, Mingyang & Niu, Linlin, 2021. "Faster fiscal stimulus and a higher government spending multiplier in China: Mixed-frequency identification with SVAR," Economics Letters, Elsevier, vol. 209(C).
    17. Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.
    18. Matteo Deleidi & Davide Romaniello & Francesca Tosi, 2021. "Quantifying fiscal multipliers in Italy: A Panel SVAR analysis using regional data," Papers in Regional Science, Wiley Blackwell, vol. 100(5), pages 1158-1177, October.
    19. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    20. Koester, Gerrit B. & Priesmeier, Christoph, 2015. "The Timing and Responsiveness of Fiscal Policy over the Business Cycle in Germany," MPRA Paper 68412, University Library of Munich, Germany.

  6. Ciccarelli, Matteo & Jeanfils, Philippe & Haavio, Markus & Ĉervená, Marianna & Guarda, Paolo & Mendicino, Caterina & D'Agostino, Antonello & Valderrama, Maria Teresa & Ortega, Eva & Hubrich, Kirstin &, 2013. "Financial shocks and the macroeconomy: heterogeneity and non-linearities," Occasional Paper Series 143, European Central Bank.

    Cited by:

    1. Frauke Schleer & Willi Semmler, 2014. "Financial Sector and Output Dynamics in the Euro Area: Non-linearities Reconsidered," SCEPA working paper series. 2014-5, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    2. Ian Christensen & Paul Corrigan & Caterina Mendicino & Shin-Ichi Nishiyama, 2016. "Consumption, housing collateral and the Canadian business cycle," Canadian Journal of Economics, Canadian Economics Association, vol. 49(1), pages 207-236, February.
    3. Filardo, Andrew J. & Siklos, Pierre L., 2020. "The cross-border credit channel and lending standards surveys," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    4. Claire Giordano & Marco Marinucci & Andrea Silvestrini, 2018. "Firms’ and households’ investment in Italy: the role of credit constraints and other macro factors," Temi di discussione (Economic working papers) 1167, Bank of Italy, Economic Research and International Relations Area.
    5. Valerie Vandermeulen & Werner Roeger, 2021. "Trend Capital when Goods and Capital Market Frictions Exist," European Economy - Discussion Papers 145, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    6. Monica Billio & Roberto Casarin & Enrica De Cian & Malcolm Mistry & Anthony Osuntuyi, 2021. "The Impact of Climate on Economic and Financial Cycles: A Markov-switching Panel Approach," Working Papers 2021:03, Department of Economics, University of Venice "Ca' Foscari".
    7. Tsagkanos, Athanasios & Evgenidis, Anastasios & Vartholomatou, Konstantina, 2018. "Financial and monetary stability across Euro-zone and BRICS: An exogenous threshold VAR approach," Research in International Business and Finance, Elsevier, vol. 44(C), pages 386-393.
    8. Kirstin Hubrich & Daniel F. Waggoner, 2022. "The transmission of financial shocks and leverage of financial institutions: An endogenous regime switching framework," Finance and Economics Discussion Series 2022-034, Board of Governors of the Federal Reserve System (U.S.).
    9. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2019. "Decomposing global yield curve co-movement," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 500-513.
    10. Martin Mandler & Michael Scharnagl, 2022. "Financial Cycles in Euro Area Economies: A Cross‐Country Perspective Using Wavelet Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 569-593, June.
    11. Elena Deryugina & Alexey Ponomarenko, 2021. "Explaining the lead–lag pattern in the money–inflation relationship: a microsimulation approach," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1113-1128, September.
    12. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2015. "Co-Movement, Spillovers and Excess Returns in Global Bond Markets," SIRE Discussion Papers 2015-75, Scottish Institute for Research in Economics (SIRE).
    13. Mandler, Martin & Scharnagl, Michael, 2022. "Financial cycles across G7 economies: A view from wavelet analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    14. Daragh Clancy & Rossana Merola, 2016. "Countercyclical capital rules for small open economies," Working Papers 10, European Stability Mechanism.
    15. Leroy, Aurélien & Pop, Adrian, 2019. "Macro-financial linkages: The role of the institutional framework," Journal of International Money and Finance, Elsevier, vol. 92(C), pages 75-97.
    16. Mehmet Balcilar & Kirsten Thompson & Rangan Gupta & Renee van Eyden, 2014. "Testing the Asymmetric Effects of Financial Conditions in South Africa: A Nonlinear Vector Autoregression Approach," Working Papers 201414, University of Pretoria, Department of Economics.
    17. Schleer, Frauke & Semmler, Willi, 2013. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068, ZEW - Leibniz Centre for European Economic Research.
    18. Bańbura, Marta & Albani, Maria & Ambrocio, Gene & Bursian, Dirk & Buss, Ginters & de Winter, Jasper & Gavura, Miroslav & Giordano, Claire & Júlio, Paulo & Le Roux, Julien & Lozej, Matija & Malthe-Thag, 2018. "Business investment in EU countries," Occasional Paper Series 215, European Central Bank.
    19. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    20. Markus Haavio & Caterina Mendicino & Maria Teresa Punzi, 2014. "Financial and economic downturns in OECD countries," Applied Economics Letters, Taylor & Francis Journals, vol. 21(6), pages 407-412, April.
    21. Bluwstein, Kristina, 2017. "Asymmetric Macro-Financial Spillovers," Working Paper Series 337, Sveriges Riksbank (Central Bank of Sweden).
    22. Ozge Akinci & Albert Queraltó, 2014. "Banks, Capital Flows and Financial Crises," International Finance Discussion Papers 1121, Board of Governors of the Federal Reserve System (U.S.).
    23. James Morley, 2016. "Macro-Finance Linkages," Journal of Economic Surveys, Wiley Blackwell, vol. 30(4), pages 698-711, September.
    24. Paolo Guarda & Alban Moura, 2019. "Measuring real and financial cycles in Luxembourg: An unobserved components approach," BCL working papers 126, Central Bank of Luxembourg.
    25. Ciccarelli Matteo & Ortega Eva & Valderrama Maria Teresa, 2016. "Commonalities and cross-country spillovers in macroeconomic-financial linkages," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 231-275, January.

  7. Ehrmann, Michael & D'Agostino, Antonello, 2013. "The pricing of G7 sovereign bond spreads: the times, they are a-changin," Working Paper Series 1520, European Central Bank.

    Cited by:

    1. António Afonso & Michael G. Arghyrou & María Dolores Gadea & Alexandros Kontonikas, 2017. ""Whatever it takes" to resolve the European sovereign debt crisis? Bond pricing regime switches and monetary policy effects," Working Papers REM 2017/02, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. Dieppe, Alistair & Mourinho Félix, Ricardo & Marchiori, Luca & Grech, Owen & Albani, Maria & Lalouette, Laure & Kulikov, Dmitry & Papadopoulou, Niki & Sideris, Dimitris & Irac, Delphine & Gordo Mora, , 2015. "Public debt, population ageing and medium-term growth," Occasional Paper Series 165, European Central Bank.
    3. Podstawski, Maximilian & Velinov, Anton, 2018. "The state dependent impact of bank exposure on sovereign risk," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 88, pages 63-75.
    4. Fratzscher, Marcel & Beirne, John, 2012. "The Pricing of Sovereign Risk and Contagion during the European Sovereign Debt Crisis," CEPR Discussion Papers 9249, C.E.P.R. Discussion Papers.
    5. Gómez-Puig, Marta & Pieterse-Bloem, Mary & Sosvilla-Rivero, Simón, 2023. "Dynamic connectedness between credit and liquidity risks in euro area sovereign debt markets," Journal of Multinational Financial Management, Elsevier, vol. 68(C).
    6. De Santis, Roberto A., 2020. "Impact of the Asset Purchase Programme on euro area government bond yields using market news," Economic Modelling, Elsevier, vol. 86(C), pages 192-209.
    7. Carlos Alberto Piscarreta Pinto Ferreira, 2021. "Does Public Debt Ownership Structure Matter for a Borrowing Country?," Working Papers REM 2021/0190, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    8. Crifo, Patricia & Diaye, Marc-Arthur & Oueghlissi, Rim, 2017. "The effect of countries’ ESG ratings on their sovereign borrowing costs," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 13-20.
    9. Lo Duca, Marco & Adam, Tomáš, 2017. "Modeling euro area bond yields using a time-varying factor model," Working Paper Series 2012, European Central Bank.
    10. Georgios Bampinas & Theodore Panagiotidis & Panagiotis Politsidis, 2023. "Sovereign bond and CDS market contagion: A story from the Eurozone crisis," Post-Print hal-04164277, HAL.
    11. 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.
    12. Ippei Fuijwara & Lena Mareen Korber & Daisuke Nagakura, 2013. "Asymmetry in Government Bond Returns," Macroeconomics Working Papers 23399, East Asian Bureau of Economic Research.
    13. Hülsewig, Oliver & Rottmann, Horst, 2021. "Euro area periphery countries' fiscal policy and monetary policy surprises," Weidener Diskussionspapiere 81, University of Applied Sciences Amberg-Weiden (OTH).
    14. Afonso, António & Arghyrou, Michael G. & Bagdatoglou, George & Kontonikas, Alexandros, 2013. "On the time-varying relationship between EMU sovereign spreads and their determinants," SIRE Discussion Papers 2013-47, Scottish Institute for Research in Economics (SIRE).
    15. Patricia Crifo & Marc-Arthur Diaye & Rim Oueghlissi, 2015. "Measuring the effect of government ESG performance on sovereign borrowing cost," Working Papers hal-00951304, HAL.
    16. Emilios C. Galariotis & Panagiota Makrichoriti & Spyros Spyrou, 2016. "Sovereign CDS Spread Determinants and Spill-Over Effects During Financial Crisis: A Panel VAR Approach," Post-Print hal-01358715, HAL.
    17. Guillaume Belly & Lukas Boeckelmann & Carlos Mateo Caicedo Graciano & Alberto Di Iorio & Klodiana Istrefi & Vasileios Siakoulis & Arthur Stalla‐Bourdillon, 2023. "Forecasting sovereign risk in the Euro area via machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 657-684, April.
    18. Ehrmann, Michael & Fratzscher, Marcel, 2017. "Euro area government bonds – Fragmentation and contagion during the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 26-44.
    19. Canofari, Paolo & Marini, Giancarlo & Piersanti, Giovanni, 2014. "Expectations and Systemic Risk in EMU Government Bond Spreads," LEAP Working Papers 2014/1, Luiss Institute for European Analysis and Policy.
    20. Malliaropulos, Dimitris & Migiakis, Petros, 2018. "The re-pricing of sovereign risks following the Global Financial Crisis," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 39-56.
    21. Podstawski, Maximilian & Velinov, Anton, 2018. "The state dependent impact of bank exposure on sovereign risk," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 63-75.
    22. Grosse Steffen, Christoph & Podstawski, Maximilian, 2017. "Ambiguity and Time-Varying Risk Aversion in Sovereign Debt Markets," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168101, Verein für Socialpolitik / German Economic Association.
    23. Michael Ehrmann & Marcel Fratzscher, 2015. "Euro Area Government Bonds: Integration and Fragmentation during the Sovereign Debt Crisis," Discussion Papers of DIW Berlin 1479, DIW Berlin, German Institute for Economic Research.
    24. Ashoka Mody & Milan Nedeljkovic, 2018. "Central Bank Policies and Financial Markets: Lessons from the Euro Crisis," Working Papers 253, Princeton University, Department of Economics, Center for Economic Policy Studies..
    25. Hu, Haoshen & Kaspereit, Thomas & Prokop, Jörg, 2016. "The information content of issuer rating changes: Evidence for the G7 stock markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 99-108.
    26. Marta Gómez-Puig & Mary Pieterse-Bloem & Simón Sosvilla-Rivero, 2022. ""Dynamic connectedness between credit and liquidity risks in EMU sovereign debt markets"," IREA Working Papers 202217, University of Barcelona, Research Institute of Applied Economics, revised Oct 2022.
    27. Beirne, John & Renzhi, Nuobu & Volz, Ulrich, 2020. "Feeling the Heat: Climate Risks and the Cost of Sovereign Borrowing," ADBI Working Papers 1160, Asian Development Bank Institute.
    28. Ludovit Odor & Pavol Povala, 2016. "Risk Premiums in Slovak Government Bonds," Discussion Papers Discussion Paper No. 3/20, Council for Budget Responsibility.
    29. Nikolay Hristov & Oliver Hülsewig & Thomas Siemsen & Timo Wollmershäuser, 2019. "Restoring euro area monetary transmission: Which role for government bond rates?," Empirical Economics, Springer, vol. 57(3), pages 991-1021, September.
    30. Jacopo Cimadomo & Peter Claeys & Mr. Marcos Poplawski Ribeiro, 2016. "How do Experts Forecast Sovereign Spreads?," IMF Working Papers 2016/100, International Monetary Fund.
    31. Afonso, António & Tovar Jalles, João, 2019. "Quantitative easing and sovereign yield spreads: Euro-area time-varying evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 208-224.
    32. de Haan, Leo & Hessel, Jeroen & van den End, Jan Willem, 2014. "Are European sovereign bonds fairly priced? The role of modelling uncertainty," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 239-267.
    33. De Santis, Roberto A. & Stein, Michael, 2016. "Correlation changes between the risk-free rate and sovereign yields of euro area countries," Working Paper Series 1979, European Central Bank.
    34. Blommestein, Hans & Eijffinger, Sylvester & Qian, Zongxin, 2016. "Regime-dependent determinants of Euro area sovereign CDS spreads," Journal of Financial Stability, Elsevier, vol. 22(C), pages 10-21.
    35. Antonio Afonso & Mina Kazemi, 2018. "Euro Area Sovereign Yields and the Power of Unconventional Monetary Policy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(2), pages 100-119, April.
    36. Jacob Boudoukh & Jordan Brooks & Matthew Richardson & Zhikai Xu, 2016. "The Complexity of Liquidity: The Extraordinary Case of Sovereign Bonds," NBER Working Papers 22576, National Bureau of Economic Research, Inc.
    37. Peter Schwendner & Martin Schuele & Thomas Ott & Martin Hillebrand, 2015. "European Government Bond Dynamics and Stability Policies: Taming Contagion Risks," Working Papers 8, European Stability Mechanism.
    38. Aitor Erce, 2015. "Bank and sovereign risk feedback loops," Globalization Institute Working Papers 227, Federal Reserve Bank of Dallas.
    39. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank.
    40. António Afonso & Mina Kazemi, 2017. "Euro area sovereign yields and the power of QE," Working Papers Department of Economics 2017/12, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    41. Jørgen Bølstad & Christoph Elhardt, 2015. "To bail out or not to bail out? Crisis politics, credibility, and default risk in the Eurozone," European Union Politics, , vol. 16(3), pages 325-346, September.
    42. Ashoka Mody & Milan Nedeljkovic, 2018. "Central Bank Policies and Financial Markets: Lessons from the Euro Crisis," CESifo Working Paper Series 7400, CESifo.
    43. de Grauwe, Paul & Ji, Yuemei & Macchiarelli, Corrado, 2017. "Fundamentals versus market sentiments in the euro bond markets: implications for QE," LSE Research Online Documents on Economics 85127, London School of Economics and Political Science, LSE Library.
    44. Kliber, Agata & Płuciennik, Piotr, 2017. "Euro or not? Vulnerability of Czech and Slovak economies to regional and international turmoil," Economic Modelling, Elsevier, vol. 60(C), pages 313-323.
    45. Britta Niehof, 2014. "Spillover Effects in Government Bond Spreads: Evidence from a GVAR Model," MAGKS Papers on Economics 201458, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    46. C. Bortoli & L. Harreau & C. Pouvelle, 2014. "Determinants of OECD countries’ sovereign yields: safe havens, purgatory, and the damned," Working papers 494, Banque de France.
    47. Capelle-Blancard, Gunther & Crifo, Patricia & Diaye, Marc-Arthur & Oueghlissi, Rim & Scholtens, Bert, 2019. "Sovereign bond yield spreads and sustainability: An empirical analysis of OECD countries," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 156-169.
    48. Große Steffen, Christoph, 2015. "Uncertainty shocks and non-fundamental debt crises: An ambiguity approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112936, Verein für Socialpolitik / German Economic Association.
    49. Kocsis, Zalan & Monostori, Zoltan, 2016. "The role of country-specific fundamentals in sovereign CDS spreads: Eastern European experiences," Emerging Markets Review, Elsevier, vol. 27(C), pages 140-168.
    50. Moisă Altăr & Alexandru-Adrian Cramer & Adam-Nelu Altăr-Samuel, 2015. "Sovereign Financial Asset Market Linkages across Europe During the Euro Zone Debt Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 29-49, December.
    51. Martijn (M.I.) Droes & Ryan van Lamoen & Simona Mattheussens, 2017. "Quantitative Easing and Exuberance in Government Bond Markets: Evidence from the ECB's Expanded Assets Purchase Program," Tinbergen Institute Discussion Papers 17-080/IV, Tinbergen Institute.

  8. 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.

    Cited by:

    1. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers CWP41/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Kilinc, Zubeyir & Yucel, Eray, 2016. "PMI Thresholds for GDP Growth," MPRA Paper 70929, University Library of Munich, Germany.
    3. Gabe J. Bondt, 2019. "A PMI-Based Real GDP Tracker for the Euro Area," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(2), pages 147-170, December.
    4. Guy P. Nason & James L. Wei, 2022. "Quantifying the economic response to COVID‐19 mitigations and death rates via forecasting purchasing managers' indices using generalised network autoregressive models with exogenous variables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1778-1792, October.

  9. Dieppe, Alistair & Ortega, Eva & D'Agostino, Antonello & Karlsson, Tohmas & Benkovskis, Konstantins & Caivano, Michele & Hurtado, Samuel & Várnai, Tímea, 2011. "Assessing the sensitivity of inflation to economic activity," Working Paper Series 1357, European Central Bank.

    Cited by:

    1. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    2. Thomas Mayer & Holger Schmieding & Manfred Jäger-Ambrozewicz & Michael Lamla & Jan-Egbert Sturm & Ulrich Kater & Leon Leschus & Wolfgang Brachinger, 2011. "ECB rate hike: How large is the risk of inflation?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(14), pages 03-26, July.
    3. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    4. OECD & Elena Rusticelli, 2014. "Rescuing the Phillips curve: Making use of long-term unemployment in the measurement of the NAIRU," OECD Journal: Economic Studies, OECD Publishing, vol. 2014(1), pages 109-127.

  10. Andersson, Magnus & D'Agostino, Antonello & de Bondt, Gabe & Roma, Moreno, 2011. "The predictive content of sectoral stock prices: a US-euro area comparison," Working Paper Series 1343, European Central Bank.

    Cited by:

    1. Dison, Will & Theodoridis, Konstantinos, 2017. "Do macro shocks matter for equities?," Bank of England working papers 692, Bank of England.
    2. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.

  11. Surico, Paolo & ,, 2011. "A Century of Inflation Forecasts," CEPR Discussion Papers 8292, C.E.P.R. Discussion Papers.

    Cited by:

    1. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
    2. Zolotoy, Leon & Frederickson, James R. & Lyon, John D., 2017. "Aggregate earnings and stock market returns: The good, the bad, and the state-dependent," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 157-175.
    3. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    4. Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
    5. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    6. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    7. Ardakani, Omid & Kishor, N. Kundan, 2014. "Examining the Success of the Central Banks in Inflation Targeting Countries: The Dynamics of Inflation Gap and the Institutional Characteristics," MPRA Paper 58402, University Library of Munich, Germany.
    8. Castelnuovo, Efrem, 2016. "Modest macroeconomic effects of monetary policy shocks during the great moderation: An alternative interpretation," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 300-314.
    9. Bermingham, Colin & D'Agostino, Antonello, 2011. "Understanding and forecasting aggregate and disaggregate price dynamics," Working Paper Series 1365, European Central Bank.
    10. Carlo A. Favero & Arie E. Gozluklu & Haoxi Yang, 2011. "Demographics and The Behaviour of Interest Rates," Working Papers 388, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    11. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    12. Daniel Kaufmann, 2019. "Nominal stability over two centuries," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-23, December.
    13. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    14. Gächter, Martin & Hasler, Elias & Scharler, Johann, 2023. "Kicking the can down the road: A historical growth-at-risk perspective," Economics Letters, Elsevier, vol. 228(C).
    15. Fanelli, Luca & Sorge, Marco M., 2017. "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 57-70.
    16. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2014. "Drifts, Volatilities, and Impulse Responses Over the Last Century," Working Paper 14-10, Federal Reserve Bank of Richmond.
    17. Markku Lanne & Jani Luoto & Henri Nyberg, 2014. "Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?," CREATES Research Papers 2014-26, Department of Economics and Business Economics, Aarhus University.
    18. Dur, Ayşe & Martínez García, Enrique, 2020. "Mind the gap!—A monetarist view of the open-economy Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    19. Georgios Karras, 2015. "Low Inflation vs. Stable Inflation: Evidence from the UK, 1688–2009," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(5), pages 505-517, November.
    20. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
    21. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
    22. Gozluklu, Arie & Morin, Annaïg, 2019. "Stock vs. Bond yields and demographic fluctuations," Journal of Banking & Finance, Elsevier, vol. 109(C).

  12. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.

    Cited by:

    1. Magdalena Grothe & Aidan Meyler, 2018. "Inflation Forecasts: Are Market-Based and Survey-Based Measures Informative?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(1), pages 171-188, January.
    2. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    3. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Journal of Finance, American Finance Association, vol. 75(5), pages 2503-2553, October.
    4. Constantin Burgi, 2015. "Can A Subset Of Forecasters Beat The Simple Average In The Spf?," Working Papers 2015-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    5. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    6. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    7. Fabiana Gomez & David Pacini, 2015. "Counting Biased Forecasters: An Application of Multiple Testing Techniques," Bristol Economics Discussion Papers 15/661, School of Economics, University of Bristol, UK.
    8. Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.
    9. Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
    10. Klein, Tony, 2021. "Agree to Disagree? Predictions of U.S. Nonfarm Payroll Changes between 2008 and 2020 and the Impact of the COVID19 Labor Shock," QBS Working Paper Series 2021/07, Queen's University Belfast, Queen's Business School.
    11. Constantin Rudolf Salomo Bürgi, 2023. "How to deal with missing observations in surveys of professional forecasters," Journal of Applied Economics, Taylor & Francis Journals, vol. 26(1), pages 2185975-218, December.
    12. Michael Clements, 2016. "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2016-08, Henley Business School, University of Reading.
    13. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
    14. Gamber, Edward N. & Liebner, Jeffrey P. & Smith, Julie K., 2015. "The distribution of inflation forecast errors," Journal of Policy Modeling, Elsevier, vol. 37(1), pages 47-64.
    15. Joshua Abel & Robert Rich & Joseph Song & Joseph Tracy, 2016. "The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 533-550, April.
    16. Campbell R. Harvey & Yan Liu, 2022. "Luck versus Skill in the Cross Section of Mutual Fund Returns: Reexamining the Evidence," Journal of Finance, American Finance Association, vol. 77(3), pages 1921-1966, June.
    17. Robert W. Rich & Joseph Tracy, 2021. "All Forecasters Are Not the Same: Time-Varying Predictive Ability across Forecast Environments," Working Papers 21-06, Federal Reserve Bank of Cleveland.
    18. Meade, Nigel & Driver, Ciaran, 2023. "Differing behaviours of forecasters of UK GDP growth," International Journal of Forecasting, Elsevier, vol. 39(2), pages 772-790.
    19. Robert W. Rich & Joseph Tracy, 2017. "The behavior of uncertainty and disagreement and their roles in economic prediction: a panel analysis," Staff Reports 808, Federal Reserve Bank of New York.
    20. Baumann, Ursel & Darracq Pariès, Matthieu & Westermann, Thomas & Riggi, Marianna & Bobeica, Elena & Meyler, Aidan & Böninghausen, Benjamin & Fritzer, Friedrich & Trezzi, Riccardo & Jonckheere, Jana & , 2021. "Inflation expectations and their role in Eurosystem forecasting," Occasional Paper Series 264, European Central Bank.
    21. Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
    22. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    23. Tito Nícias Teixeira da Silva Filho, 2013. "Banks, Asset Management or Consultancies' Inflation Forecasts: is there a better forecaster out there?," Working Papers Series 310, Central Bank of Brazil, Research Department.
    24. 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.
    25. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    26. Tim Köhler & Jörg Döpke, 2023. "Will the last be the first? Ranking German macroeconomic forecasters based on different criteria," Empirical Economics, Springer, vol. 64(2), pages 797-832, February.
    27. Clements, Michael P., 2021. "Rounding behaviour of professional macro-forecasters," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1614-1631.
    28. 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.
    29. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Papers 2006.04269, arXiv.org.
    30. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.
    31. Klein, Tony, 2022. "Agree to disagree? Predictions of U.S. nonfarm payroll changes between 2008 and 2020 and the impact of the COVID19 labor shock," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 264-286.
    32. Meyler, Aidan, 2020. "Forecast performance in the ECB SPF: ability or chance?," Working Paper Series 2371, European Central Bank.

  13. D'Agostino, Antonello & Bermingham, Colin, 2010. "Understanding and Forecasting Aggregate and Disaggregate Price Dynamics," Research Technical Papers 8/RT/10, Central Bank of Ireland.

    Cited by:

    1. Katarzyna Maciejowska & Rafal Weron, 2013. "Forecasting of daily electricity spot prices by incorporating intra-day relationships: Evidence form the UK power market," HSC Research Reports HSC/13/01, Hugo Steinhaus Center, Wroclaw University of Technology, revised 15 Apr 2013.
    2. 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.
    3. Guillermo Carlomagno & Nicolas Eterovic & L. G. Hernández-Román, 2023. "Disentangling Demand and Supply Inflation Shocks from Chilean Electronic Payment Data," Working Papers Central Bank of Chile 986, Central Bank of Chile.
    4. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    5. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    6. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers CWP41/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    8. Dr. Marco Huwiler & Daniel Kaufmann, 2013. "Combining disaggregate forecasts for inflation: The SNB's ARIMA model," Economic Studies 2013-07, Swiss National Bank.
    9. Mario Marcel & Carlos Medel & Jessica Mena, 2017. "Determinantes de la Inflación de Servicios en Chile," Working Papers Central Bank of Chile 803, Central Bank of Chile.
    10. 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.
    11. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    12. Itai Areili & Yakov Babichenko & Rann Smorodinsky, 2017. "Robust Forecast Aggregation," Papers 1710.02838, arXiv.org, revised Feb 2018.
    13. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    14. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    15. Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
    16. Karol Szafranek & Aleksandra Hałka, 2017. "Determinants of low inflation in an emerging, small open economy. A comparison of aggregated and disaggregated approaches," NBP Working Papers 267, Narodowy Bank Polski.
    17. Dmytro Krukovets & Olesia Verchenko, 2019. "Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 248, pages 11-20.
    18. Katarzyna Maciejowska & Rafal Weron, 2013. "Forecasting of daily electricity prices with factor models: Utilizing intra-day and inter-zone relationships," HSC Research Reports HSC/13/11, Hugo Steinhaus Center, Wroclaw University of Technology.
    19. Kausik Chaudhuri & Saumitra N. Bhaduri, 2019. "Inflation Forecast: Just use the Disaggregate or Combine it with the Aggregate," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 331-343, June.
    20. Huddleston, Samuel H. & Porter, John H. & Brown, Donald E., 2015. "Improving forecasts for noisy geographic time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1810-1818.
    21. Mihaela SIMIONESCU, 2014. "Improving The Inflation Rate Forecasts Of Romanian Experts Using A Fixed-Effects Models Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 13, pages 87-102, June.
    22. Monterrey Mayoral, Juan & Sánchez Segura, Amparo, 2017. "Una evaluación empírica de los métodos de predicción de la rentabilidad y su relación con las características corporativas," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 20(1), pages 95-106.
    23. Viacheslav Kramkov, 2023. "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series wps112, Bank of Russia.
    24. Edward N. Gamber & Julie K. Smith, 2016. "Time-series measures of core inflation," Working Papers 2016-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    25. Nicoletta Pashourtidou & Christos Papamichael & Charalampos Karagiannakis, 2018. "Forecasting economic activity in sectors of the Cypriot economy," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(2), pages 24-66, December.
    26. Mossfeldt, Marcus & Stockhammar, Pär, 2016. "Forecasting Goods and Services Inflation in Sweden," Working Papers 146, National Institute of Economic Research.
    27. Andrejs Bessonovs & Olegs Krasnopjorovs, 2020. "Short-Term Inflation Projections Model and Its Assessment in Latvia," Working Papers 2020/01, Latvijas Banka.
    28. Barakchian , Seyed Mahdi & Bayat , Saeed & Karami , Hooman, 2013. "Common Factors of CPI Sub-aggregates and Forecast of Inflation," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 8(4), pages 1-17, October.
    29. Moosa, Imad A. & Vaz, John, 2018. "Direct and Indirect Forecasting of Cross Exchange Rates," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 173-190.

  14. D'Agostino, Antonello & Gambetti, Luca & Giannone, Domenico & Giannone, Domenico, 2009. "Macroeconomic Forecasting and Structural Change," Research Technical Papers 8/RT/09, Central Bank of Ireland.

    Cited by:

    1. Huang, Yingying & Duan, Kun & Urquhart, Andrew, 2023. "Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    2. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. 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.
    4. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    5. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
    6. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    7. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
    8. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    9. Fenghua Wen & Jihong Xiao & Chuangxia Huang & Xiaohua Xia, 2018. "Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 319-334, January.
    10. 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.
    11. Boyarchenko, Nina & Adrian, Tobias & Giannone, Domenico, 2020. "Multimodality in Macro-Financial Dynamics," CEPR Discussion Papers 15088, C.E.P.R. Discussion Papers.
    12. 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.
    13. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    14. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    15. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    16. Miguel A.G. Belmonte & Gary Koop & Dimitris Korobilis, 2014. "Hierarchical Shrinkage in Time‐Varying Parameter Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 80-94, January.
    17. 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.
    18. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022. "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
    19. caterina mendicino & Antonello DÁgostino, 2016. "Expectation-driven cycles: Time-Varying Effects," EcoMod2016 9350, EcoMod.
    20. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," CREATES Research Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
    21. 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.
    22. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
    23. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pinter, Gabor, 2016. "VAR models with non-Gaussian shocks," LSE Research Online Documents on Economics 86238, London School of Economics and Political Science, LSE Library.
    24. Guido Ascari & Efrem Castelnuovo & Lorenza Rossi, 2010. "Calvo vs. Rotemberg in a Trend Inflation World: An Empirical Investigation," "Marco Fanno" Working Papers 0116, Dipartimento di Scienze Economiche "Marco Fanno".
    25. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
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    164. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
    165. Bala Dahiru Abdullahi, 2016. "Time-Varying VAR with Stochastic Volatility and Monetary Policy Dynamics in Nigeria," Economics Bulletin, AccessEcon, vol. 36(4), pages 2237-2249.
    166. Dimitris Korobilis, 2014. "Data-based priors for vector autoregressions with drifting coefficients," Working Papers 2014_04, Business School - Economics, University of Glasgow.
    167. Madalina-Gabriela Anghel & Alexandru Manole & Alina-Georgiana Solomon, 2017. "Using the System of National Accounts in the Forecasting Activity," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(2), pages 91-96, April.
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    169. Doo Won Bang & HyuckShin Kwon, 2022. "Policy Impact Analysis of Housing Policies Using Housing Cycles," SAGE Open, , vol. 12(3), pages 21582440221, July.
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    171. Pervin, Shahida, 2018. "Dynamics and Interactions of Monetary Policy and Macroeconomic Variables: Empirical Investigation in the UK Economy with Bayesian VAR," MPRA Paper 91816, University Library of Munich, Germany.
    172. Gary Koop & Dimitris Korobilis, 2013. "A new index of financial conditions," Working Papers 1307, University of Strathclyde Business School, Department of Economics.
    173. 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.
    174. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    175. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
    176. Todd E. Clark & Edward S. Knotek & Saeed Zaman, 2015. "Measuring Inflation Forecast Uncertainty," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2015(03), pages 1-6, March.
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    183. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    184. Rodríguez, Gabriel & Vassallo, Renato & Castillo B., Paul, 2023. "Effects of external shocks on macroeconomic fluctuations in Pacific Alliance countries," Economic Modelling, Elsevier, vol. 124(C).
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    186. 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.
    187. Boufateh, Talel & Saadaoui, Zied, 2021. "The time-varying responses of financial intermediation and inflation to oil supply and demand shocks in the US: Evidence from Bayesian TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 102(C).
    188. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2018. "Modeling volatility dynamics using non-Gaussian stochastic volatility model based on band matrix routine," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 193-201.
    189. D.M.Nguyen, Anh & Dai Hung, Ly, 2019. "Time-Varying Exchange Rate Risk Premium," MPRA Paper 94600, University Library of Munich, Germany.
    190. Krustev, Georgi & Casalis, André, 2020. "Cyclical drivers of euro area consumption: what can we learn from durable goods?," Working Paper Series 2386, European Central Bank.
    191. Guo, Jiaqi & Long, Shaobo & Luo, Weijie, 2022. "Nonlinear effects of climate policy uncertainty and financial speculation on the global prices of oil and gas," International Review of Financial Analysis, Elsevier, vol. 83(C).
    192. Junli Cheng & Feng Lin, 2022. "The Dynamic Effects of Urban–Rural Income Inequality on Sustainable Economic Growth under Urbanization and Monetary Policy in China," Sustainability, MDPI, vol. 14(11), pages 1-23, June.
    193. 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.
    194. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    195. Gabriel Rodríguez & Renato Vassallo, 2022. "Time Evolution of External Shocks on Macroeconomic Fluctuations in Pacific Alliance Countries: Empirical Application using TVP-VAR-SV Models," Documentos de Trabajo / Working Papers 2022-508, Departamento de Economía - Pontificia Universidad Católica del Perú.
    196. Nicoletti, Giulio & Passaro, Raffaele, 2012. "Sometimes it helps: the evolving predictive power of spreads on GDP dynamics," Working Paper Series 1447, European Central Bank.
    197. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    198. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    199. Robert Lehmann & Magnus Reif & Timo Wollmershäuser, 2020. "ifoCAST: The New Forecast Standard of the ifo Institute," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 73(11), pages 31-39, November.
    200. 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.
    201. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    202. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The nexus between the oil price and its volatility risk in a stochastic volatility in the mean model with time-varying parameters," Resources Policy, Elsevier, vol. 61(C), pages 572-584.
    203. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    204. David Alan Peel & Pantelis Promponas, 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.
    205. Joshua C.C. Chan & Eric Eisenstat, 2018. "Comparing hybrid time-varying parameter VARs," CAMA Working Papers 2018-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    206. Denis Belomestny & Ekaterina Krymova & Andrey Polbin, 2020. "Estimating TVP-VAR models with time invariant long-run multipliers," Papers 2008.00718, arXiv.org.
    207. Rozina Shaheen, 2019. "Impact of Fiscal Policy on Consumption and Labor Supply under a Time-Varying Structural VAR Model," Economies, MDPI, vol. 7(2), pages 1-15, June.
    208. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, September.
    209. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
    210. Joshua C.C. Chan & Todd E. Clark & Gary Koop, 2018. "A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(1), pages 5-53, February.
    211. Solikin M. Juhro & Bernard Njindan Iyke, 2019. "Forecasting Indonesian Inflation Within An Inflation-Targeting Framework: Do Large-Scale Models Pay Off?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 423-436.
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    213. David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).
    214. Marco Del Negro & Giorgio E. Primiceri, 2013. "Time-Varying Structural Vector Autoregressions and Monetary Policy: a Corrigendum," Staff Reports 619, Federal Reserve Bank of New York.
    215. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The volatility effect on precious metals price returns in a stochastic volatility in mean model with time-varying parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    216. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    217. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    218. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    219. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
    220. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
    221. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.
    222. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.

  15. D'Agostino, Antonello & McQuinn, Kieran & O' Reilly, Gerard, 2008. "Identifying and Forecasting House Price Dynamics in Ireland," Research Technical Papers 3/RT/08, Central Bank of Ireland.

    Cited by:

    1. Zietz, Joachim & Traian, Anca, 2014. "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 271-281.
    2. Simon Stevenson & James Young, 2015. "The probability of sale and price premiums in withdrawn auctioned properties," Urban Studies, Urban Studies Journal Limited, vol. 52(2), pages 279-297, February.

  16. D'Agostino, Antonello & McQuinn, Kieran & O'Brien, Derry, 2008. "Now-casting Irish GDP," Research Technical Papers 9/RT/08, Central Bank of Ireland.

    Cited by:

    1. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
    2. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    3. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    4. Siliverstovs Boriss & Kholodilin Konstantin A., 2012. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 429-444, August.
    5. Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
    6. Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
    7. 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.
    8. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    9. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    10. 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.).
    11. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    12. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    13. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    14. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    15. Liebermann, Joelle, 2011. "Real-Time Nowcasting of GDP: Factor Model versus Professional Forecasters," Research Technical Papers 3/RT/11, Central Bank of Ireland.
    16. Barış Soybilgen & Ege Yazgan, 2021. "Nowcasting US GDP Using Tree-Based Ensemble Models and Dynamic Factors," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 387-417, January.
    17. Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.
    18. Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
    19. Reichlin, Lucrezia & Andreini, Paolo & Hasenzagl, Thomas & Senftleben-König, Charlotte & Strohsal, Till, 2020. "Nowcasting German GDP," CEPR Discussion Papers 14323, C.E.P.R. Discussion Papers.
    20. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.
    21. Lucrezia Reichlin, 2010. "Comment on "Globalization, the Business Cycle, and Macroeconomic Monitoring"," NBER Chapters, in: NBER International Seminar on Macroeconomics 2010, pages 287-298, National Bureau of Economic Research, Inc.
    22. Sabel, C.E. & Kihal, W. & Bard, D. & Weber, C., 2013. "Creation of synthetic homogeneous neighbourhoods using zone design algorithms to explore relationships between asthma and deprivation in Strasbourg, France," Social Science & Medicine, Elsevier, vol. 91(C), pages 110-121.
    23. Quinn, Emma & Gusciute, Egle & Barrett, Alan, 2015. "Determining Labour and Skills Shortages and the Need for Labour Migration in Ireland," Research Series, Economic and Social Research Institute (ESRI), number RS49, June.
    24. 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.).
    25. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    26. Liebermann, Joëlle, 2012. "Short-term forecasting of quarterly gross domestic product growth," Quarterly Bulletin Articles, Central Bank of Ireland, pages 74-84, February.
    27. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    28. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    29. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    30. Conefrey, Thomas & Liebermann, Joelle, 2013. "A Monthly Business Cycle Indicator for Ireland," Economic Letters 03/EL/13, Central Bank of Ireland.
    31. Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
    32. Alain Kabundi & Elmarie Nel & Franz Ruch, 2016. "Nowcasting Real GDP growth in South Africa," Working Papers 581, Economic Research Southern Africa.
    33. Xisong Jin & Francisco Nadal De Simone, 2012. "An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal," BCL working papers 75, Central Bank of Luxembourg.
    34. Мекенбаева Камила // Mekenbayeva Kamila & Karel Musil, 2017. "Система прогнозирования в Национальном Банке Казахстана: наукаст на основа опросов // Forecasting system at the National Bank of Kazakhstan: survey-based nowcasting," Working Papers #2017-1, National Bank of Kazakhstan.
    35. Conefrey, Thomas & Walsh, Graeme, 2018. "A Monthly Indicator of Economic Activity for Ireland," Economic Letters 14/EL/18, Central Bank of Ireland.
    36. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.

  17. Andersson, Magnus & D'Agostino, Antonello, 2008. "Are sectoral stock prices useful for predicting euro area GDP?," Research Technical Papers 2/RT/08, Central Bank of Ireland.

    Cited by:

    1. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
    2. Smimou, K. & Khallouli, W., 2015. "Does the Euro affect the dynamic relation between stock market liquidity and the business cycle?," Emerging Markets Review, Elsevier, vol. 25(C), pages 125-153.
    3. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    4. Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie D. Chinn, 2022. "Macroeconomic Forecasting using Filtered Signals from a Stock Market Cross Section," NBER Working Papers 30305, National Bureau of Economic Research, Inc.

  18. D'Agostino, Antonello & Whelan, Karl, 2007. "Federal Reserve Information During the Great Moderation," Research Technical Papers 8/RT/07, Central Bank of Ireland.

    Cited by:

    1. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    2. Ásgeir Daníelsson, 2008. "The great moderation Icelandic style," Economics wp38, Department of Economics, Central bank of Iceland.
    3. Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2023. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 355-387, July.
    4. Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2013. "Does Central Bank Staff Beat Private Forecasters?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79925, Verein für Socialpolitik / German Economic Association.
    5. Ichiro Muto, 2007. "Productivity Growth, Transparency, and Monetary Policy," IMES Discussion Paper Series 07-E-08, Institute for Monetary and Economic Studies, Bank of Japan.
    6. Paul Hubert, 2009. "An Empirical Review of Federal Reserve’s Informational Advantage," Documents de Travail de l'OFCE 2009-03, Observatoire Francais des Conjonctures Economiques (OFCE).
    7. Kishor N. Kundan, 2010. "The Superiority of Greenbook Forecasts and the Role of Recessions," NBP Working Papers 74, Narodowy Bank Polski.
    8. Zidong An & Joao Tovar Jalles, 2020. "On the performance of US fiscal forecasts: government vs. private information," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 48(2), pages 367-391, June.
    9. Karnaukh, Nina & Vokata, Petra, 2022. "Growth forecasts and news about monetary policy," Journal of Financial Economics, Elsevier, vol. 146(1), pages 55-70.
    10. Carlo Altavilla & Domenico Giannone, 2014. "The Effectiveness of Non-Standard Monetary Policy Measures: Evidence from Survey Data," Working Papers ECARES ECARES 2014-30, ULB -- Universite Libre de Bruxelles.
    11. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
    12. El-Shagi, Makram, 2019. "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, vol. 79(C), pages 242-246.
    13. Paul Hubert, 2015. "Revisiting the Greenbook’s relative forecasting performance," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(1), pages 151-179.
    14. Gamber, Edward N. & Liebner, Jeffrey P. & Smith, Julie K., 2015. "The distribution of inflation forecast errors," Journal of Policy Modeling, Elsevier, vol. 37(1), pages 47-64.
    15. Paul Hubert, 2009. "Informational Advantage and Influence of Communicating Central Banks," Documents de Travail de l'OFCE 2009-04, Observatoire Francais des Conjonctures Economiques (OFCE).
    16. Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2017. "What's the Story? A New Perspective on the Value of Economic Forecasts," Finance and Economics Discussion Series 2017-107, Board of Governors of the Federal Reserve System (U.S.).
    17. Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2020. "The Power of Narratives in Economic Forecasts," Finance and Economics Discussion Series 2020-001, Board of Governors of the Federal Reserve System (U.S.).
    18. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2016. "Revisiting the relative forecast performances of Fed staff and private forecasters: A dynamic approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 313-323.
    19. Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2014. "Does the federal reserve staff still beat private forecasters?," Working Paper Series 1635, European Central Bank.
    20. Ásgeir Daníelsson, 2008. "Accuracy in forecasting macroeconomic variables in Iceland," Economics wp39, Department of Economics, Central bank of Iceland.
    21. Henning Fischer & Marta García-Bárzana & Peter Tillmann & Peter Winker, 2014. "Evaluating FOMC forecast ranges: an interval data approach," Empirical Economics, Springer, vol. 47(1), pages 365-388, August.
    22. Ekşi Ozan & Taş Bedri Kamil Onur & Orman Cüneyt, 2017. "Has the forecasting performance of the Federal Reserve’s Greenbooks changed over time?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 17(2), pages 1-25, June.
    23. Yoichi Tsuchiya, 2021. "The value added of the Bank of Japan's range forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 817-833, August.
    24. Paul Hubert, 2010. "Monetary policy, imperfect information and the expectations channel [Politique monétaire,information imparfaite et canal des anticipations]," SciencePo Working papers Main tel-04095385, HAL.
    25. Daniel L. Thornton, 2009. "How did we get to inflation targeting and where do we go now? a perspective from the U.S. experience," Working Papers 2009-038, Federal Reserve Bank of St. Louis.
    26. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    27. João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
    28. Sharpe, Steven A. & Sinha, Nitish R. & Hollrah, Christopher A., 2023. "The power of narrative sentiment in economic forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1097-1121.
    29. Lillian R. Gaeto & Sandeep Mazumder, 2019. "Measuring the Accuracy of Federal Reserve Forecasts," Southern Economic Journal, John Wiley & Sons, vol. 85(3), pages 960-984, January.
    30. de Mendonça, Helder Ferreira & Simão Filho, José & Abreu, Vanessa Castro, 2023. "Central bank’s forecasts and lack of transparency: An assessment of the effect on private expectations in a large emerging economy," Economic Systems, Elsevier, vol. 47(2).
    31. Paul Hubert, 2010. "Monetary Policy, Imperfect Information and the Expectations Channel," Sciences Po publications info:hdl:2441/f4rshpf3v1u, Sciences Po.

  19. D'Agostino, Antonello & Surico, Paolo, 2007. "Does global liquidity help to forecast US inflation?," Research Technical Papers 10/RT/07, Central Bank of Ireland.

    Cited by:

    1. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    2. Castelnuovo, Efrem, 2010. "Tracking U.S. inflation expectations with domestic and global indicators," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1340-1356, November.
    3. International Monetary Fund, 2010. "Commodity Prices and Inflation in the Middle East, North Africa, and Central Asia," IMF Working Papers 2010/135, International Monetary Fund.
    4. Ratti, Ronald A & Vespignani, Joaquin L., 2012. "Crude Oil Prices and Liquidity, the BRIC and G3 countries," MPRA Paper 44049, University Library of Munich, Germany.
    5. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    6. Efrem Castelnuovo, 2009. "Estimating the Evolution of Money's Role in the U.S. Monetary Business Cycle," "Marco Fanno" Working Papers 0103, Dipartimento di Scienze Economiche "Marco Fanno".
    7. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "Commodity prices and BRIC and G3 liquidity: A SFAVEC approach," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 18-33.
    8. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Chinese liquidity increases and the U.S. economy," Economic Modelling, Elsevier, vol. 52(PB), pages 764-771.
    9. Milani, Fabio, 2012. "Has Globalization Transformed U.S. Macroeconomic Dynamics?," Macroeconomic Dynamics, Cambridge University Press, vol. 16(2), pages 204-229, April.
    10. Luca Gattini & Huw Pill & Ludger Schuknecht, 2015. "A global perspective on inflation and propagation channels," Journal of Banking and Financial Economics, University of Warsaw, Faculty of Management, vol. 1(3), pages 50-76, May.
    11. Naraidoo, Ruthira & Paya, Ivan, 2012. "Forecasting monetary policy rules in South Africa," International Journal of Forecasting, Elsevier, vol. 28(2), pages 446-455.
    12. Woon Gyu Choi & Taesu Kang & Geun-Young Kim & Byongju Lee, 2017. "Global Liquidity Transmission to Emerging Market Economies, and Their Policy Responses," IMF Working Papers 2017/222, International Monetary Fund.
    13. Petre Caraiani, 2014. "Do money and financial variables help forecasting output in emerging European Economies?," Empirical Economics, Springer, vol. 46(2), pages 743-763, March.
    14. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    15. Mr. Reginald Darius, 2010. "Can Global Liquidity Forecast Asset Prices?," IMF Working Papers 2010/196, International Monetary Fund.
    16. Belke, Ansgar & Bordon, Ingo G. & Hendricks, Torben W., 2010. "Monetary Policy, Global Liquidity and Commodity Price Dynamics," Ruhr Economic Papers 167, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    17. Fabio Milani, 2009. "Global slack and domestic inflation rates: a structural investigation for G-7 countries," Globalization Institute Working Papers 33, Federal Reserve Bank of Dallas.
    18. Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet Ali Soytas, 2017. "Exploring the Nexus between Inflation and Globalization under Inflation Targeting through the Lens of New Zealand’s Experience," Koç University-TUSIAD Economic Research Forum Working Papers 1709, Koc University-TUSIAD Economic Research Forum.
    19. Juan Guillermo Bedoya Ospina, 2017. "Ciclos de crédito, liquidez global y regímenes monetarios: una aproximación para América Latina," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 78, February.
    20. Helge Berger & Pär Österholm, 2011. "Does Money matter for U.S. Inflation? Evidence from Bayesian VARs," CESifo Economic Studies, CESifo Group, vol. 57(3), pages 531-550, September.
    21. Ellington, Michael & Milas, Costas, 2019. "Global liquidity, money growth and UK inflation," Journal of Financial Stability, Elsevier, vol. 42(C), pages 67-74.
    22. Ding, Qian & Huang, Jianbai & Zhang, Hongwei, 2021. "The time-varying effects of financial and geopolitical uncertainties on commodity market dynamics: A TVP-SVAR-SV analysis," Resources Policy, Elsevier, vol. 72(C).
    23. Oliver Hossfeld, 2010. "US Money Demand, Monetary Overhang, and Inflation," Working Papers 2010.4, International Network for Economic Research - INFER.
    24. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "The implications of monetary expansion in China for the US dollar," Journal of Asian Economics, Elsevier, vol. 46(C), pages 71-84.
    25. Janet Koech & Mark Wynne, 2013. "Core Import Price Inflation in the United States," Open Economies Review, Springer, vol. 24(4), pages 717-730, September.
    26. Thomas Conlon & Brian M. Lucey & Gazi Salah Uddin, 2018. "Is gold a hedge against inflation? A wavelet time-scale perspective," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 317-345, August.
    27. Ms. L. Effie Psalida & Tao Sun, 2011. "Does G-4 Liquidity Spill Over?," IMF Working Papers 2011/237, International Monetary Fund.
    28. Gianni Amisano & Roberta Colavecchio, 2013. "Money Growth and Inflation: evidence from a Markov Switching Bayesian VAR," Macroeconomics and Finance Series 201304, University of Hamburg, Department of Socioeconomics.
    29. Asit B Chakraborty & Sanjib Bordoloi, 2013. "International commodity prices – volatility and global liquidity," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the Sixth IFC Conference on "Statistical issues and activities in a changing environment", Basel, 28-29 August 2012., volume 36, pages 239-258, Bank for International Settlements.
    30. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2014. "Liquidity expansion in China and the U.S. economy," MPRA Paper 59338, University Library of Munich, Germany.
    31. Sandra Eickmeier & Leonardo Gambacorta & Boris Hofmann, 2013. "Understanding Global Liquidity," BIS Working Papers 402, Bank for International Settlements.
    32. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2016. "The implications of liquidity expansion in China for the US dollar," Working Papers 2016-02, University of Tasmania, Tasmanian School of Business and Economics.
    33. Ms. Sally Chen & Mr. Philip Liu & Andrea M. Maechler & Chris Marsh & Mr. Sergejs Saksonovs & Mr. Hyun S Shin, 2012. "Exploring the Dynamics of Global Liquidity," IMF Working Papers 2012/246, International Monetary Fund.
    34. Peter Tillmann, 2017. "Global Liquidity and the Impact on SEACEN Economies," Research Studies, South East Asian Central Banks (SEACEN) Research and Training Centre, number rp100.
    35. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
    36. Milas, Costas & Naraidoo, Ruthira, 2012. "Financial conditions and nonlinearities in the European Central Bank (ECB) reaction function: In-sample and out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 173-189, January.
    37. Brett W. Fawley & Yi Wen, 2013. "Low inflation in a world of securitization," Economic Synopses, Federal Reserve Bank of St. Louis.
    38. Fatma Pinar Erdem Kucukbicakci & Etkin Ozen & Ibrahim Unalmis, 2020. "Are Macroprudential Policies Effective Tools to Reduce Credit Growth in Emerging Markets?," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 6(1), pages 73-89, June.
    39. Ruthira Naraidoo & Leroi Raputsoane, 2013. "Financial markets and the response of monetary policy to uncertainty in South Africa," Working Papers 201310, University of Pretoria, Department of Economics.
    40. Markku Lanne & Jani Luoto & Henri Nyberg, 2014. "Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?," CREATES Research Papers 2014-26, Department of Economics and Business Economics, Aarhus University.
    41. Dur, Ayşe & Martínez García, Enrique, 2020. "Mind the gap!—A monetarist view of the open-economy Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    42. Mesut Turkay, 2018. "Does International Liquidity Matter For G-7 Countries? A PVAR Approach," International Econometric Review (IER), Econometric Research Association, vol. 10(1), pages 1-13, April.
    43. Liew, Freddy, 2012. "Forecasting inflation in Asian economies," MPRA Paper 36781, University Library of Munich, Germany.
    44. Fabio Milani, 2009. "The Effect of Global Output on U.S. Inflation and Inflation Expectations: A Structural Estimation," Working Papers 080920, University of California-Irvine, Department of Economics.
    45. Rossi, José Luiz Júnior, 2014. "The Usefulness of Financial Variables in Predicting Exchange Rate Movements," Insper Working Papers wpe_332, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    46. Julio Pindado & Ignacio Requejo & Juan C. Rivera, 2020. "Does money supply shape corporate capital structure? International evidence from a panel data analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 26(6), pages 554-584, April.

  20. D'Agostino, Antonello & Domenico, Giannone & Surico, Paolo, 2006. "(Un)Predictability and Macroeconomic Stability," Research Technical Papers 5/RT/06, Central Bank of Ireland.

    Cited by:

    1. Luca Benati & Paolo Surico, 2008. "Evolving U.S. Monetary Policy and The Decline of Inflation Predictability," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 634-646, 04-05.
    2. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
    3. Abdalla, Ahmed & Carabias, Jose M. & Patatoukas, Panos N., 2021. "The real-time macro content of corporate financial reports: a dynamic factor model approach," LSE Research Online Documents on Economics 108539, London School of Economics and Political Science, LSE Library.
    4. Ippei Fujiwara & Yasuo Hirose, 2011. "Indeterminacy and forecastability," Globalization Institute Working Papers 91, Federal Reserve Bank of Dallas.
    5. Giannone, Domenico & D’Agostino, Antonello & Gambetti, Luca, 2009. "Macroeconomic Forecasting and Structural Change," CEPR Discussion Papers 7542, C.E.P.R. Discussion Papers.
    6. Audrone Jakaitiene & Stephane Dees, 2012. "Forecasting the World Economy in the Short Term," The World Economy, Wiley Blackwell, vol. 35(3), pages 331-350, March.
    7. Marcellino, Massimiliano & Eickmeier, Sandra & Lemke, Wolfgang, 2011. "Classical time-varying FAVAR models - Estimation, forecasting and structural analysis," CEPR Discussion Papers 8321, C.E.P.R. Discussion Papers.
    8. Alain Kabundi & Rangan Gupta, 2009. "A Large Factor Model for Forecasting Macroeconomic Variables in South Africa," Working Papers 137, Economic Research Southern Africa.
    9. Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The empirical (ir)relevance of the interest rate assumption for central bank forecasts," Discussion Papers 11/2013, Deutsche Bundesbank.
    10. D'Agostino, A & Whelan, K, 2007. "Federal Reserve Information During the Great Moderation," MPRA Paper 6092, University Library of Munich, Germany.
    11. Michael Cai & Marco Del Negro & Marc Giannoni & Abhi Gupta & Pearl Li & Erica Moszkowski, 2018. "DSGE forecasts of the lost recovery," Staff Reports 844, Federal Reserve Bank of New York.
    12. Domenico Giannone & Michèle Lenza & Daphné Momferatu & Luca Onorante, 2010. "Short-term inflation projections: a Bayesian vector autoregressive approach," Working Papers ECARES ECARES 2010-011, ULB -- Universite Libre de Bruxelles.
    13. Ásgeir Daníelsson, 2008. "The great moderation Icelandic style," Economics wp38, Department of Economics, Central bank of Iceland.
    14. Gamber, Edward N. & Smith, Julie K. & McNamara, Dylan C., 2014. "Where is the Fed in the distribution of forecasters?," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 296-312.
    15. 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.
    16. Ciccarelli, Matteo & Mojon, Benoît, 2006. "Global Inflation," Kiel Working Papers 1337, Kiel Institute for the World Economy (IfW Kiel).
    17. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    18. Tatevik Sekhposyan & Barbara Rossi, 2009. "Has Economic Modelsí Forecasting Performance for US Output Growth and Inflation Changed Over Time, and When?," Working Papers 09-06, Duke University, Department of Economics.
    19. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Post-Print halshs-00460461, HAL.
    20. Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
    21. 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.
    22. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    23. Mumtaz, Haroon & Surico, Paolo, 2008. "Time-Varying Yield Curve Dynamics and Monetary Policy," Discussion Papers 23, Monetary Policy Committee Unit, Bank of England.
    24. Vugar Ahmadov & Salman Huseynov & Shaig Adigozalov & Fuad Mammadov & Vugar Rahimov, 2018. "Forecasting inflation in post-oil boom years: A case for regime switches?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 369-385, April.
    25. Paul Hubert, 2009. "An Empirical Review of Federal Reserve’s Informational Advantage," Documents de Travail de l'OFCE 2009-03, Observatoire Francais des Conjonctures Economiques (OFCE).
    26. Banerjee, Anindya & Marcellino, Massimiliano, 2008. "Factor-augmented Error Correction Models," CEPR Discussion Papers 6707, C.E.P.R. Discussion Papers.
    27. Mumtaz, Haroon & Surico, Paolo, 2008. "Evolving International Inflation Dynamics: Evidence from a Time-varying Dynamic Factor Model," CEPR Discussion Papers 6767, C.E.P.R. Discussion Papers.
    28. Primiceri, Giorgio & Giannone, Domenico & Lenza, Michele, 2016. "Priors for the Long Run," CEPR Discussion Papers 11261, C.E.P.R. Discussion Papers.
    29. Luca Fanelli & Marco M. Sorge, 2015. "Indeterminacy, Misspecification and Forecastability: Good Luck in Bad Policy?," CSEF Working Papers 402, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    30. Vugar Ahmadov & Shaig Adigozalov & Salman Huseynov & Fuad Mammadov & Vugar Rahimov, 2016. "Forecasting inflation in post-oil boom years: A case for non-linear models?," Working Papers 1601, Central Bank of Azerbaijan Republic.
    31. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
    32. Reichlin, Lucrezia & Giannone, Domenico & Lenza, Michele, 2012. "Money, credit, monetary policy and the business cycle in the euro area," CEPR Discussion Papers 8944, C.E.P.R. Discussion Papers.
    33. Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers 624, Queen Mary University of London, School of Economics and Finance.
    34. Gürkaynak, Refet & Edge, Rochelle, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," CEPR Discussion Papers 8158, C.E.P.R. Discussion Papers.
    35. Liebermann, Joelle, 2011. "Real-Time Nowcasting of GDP: Factor Model versus Professional Forecasters," Research Technical Papers 3/RT/11, Central Bank of Ireland.
    36. Barhoumi, K. & Rünstler, G. & Cristadoro, R. & Den Reijer, A. & Jakaitiene, A. & Jelonek, P. & Rua, A. & Ruth, K. & Benk, S. & Van Nieuwenhuyze, C., 2008. "Short-term forecasting of GDP using large monthly datasets: a pseudo real-time forecast evaluation exercise," Working papers 215, Banque de France.
    37. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    38. Sweder van Wijnbergen & Tim Willems, 2013. "Imperfect information, lagged labour adjustment, and the Great Moderation," Oxford Economic Papers, Oxford University Press, vol. 65(2), pages 219-239, April.
    39. Scharnagl, Michael & Schumacher, Christian, 2007. "Reconsidering the role of monetary indicators for euro area inflation from a Bayesian perspective using group inclusion probabilities," Discussion Paper Series 1: Economic Studies 2007,09, Deutsche Bundesbank.
    40. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    41. Hilde C. Bj�rnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    42. Laurent Ferrara & Dominique Guégan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 186-199.
    43. Paul Hubert, 2015. "Revisiting the Greenbook’s relative forecasting performance," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(1), pages 151-179.
    44. Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
    45. Reichlin, Lucrezia & Giannone, Domenico & De Mol, Christine, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
    46. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
    47. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    48. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    49. Reichlin, Lucrezia & Camba-Mendez, Gonzalo & Angelini, Elena & Rünstler, Gerhard & Giannone, Domenico, 2008. "Short-term Forecasts of Euro Area GDP Growth," CEPR Discussion Papers 6746, C.E.P.R. Discussion Papers.
    50. Marco J. Lombardi & Philipp Maier, 2010. "‘Lean’ versus ‘Rich’ Data Sets: Forecasting during the Great Moderation and the Great Recession," Staff Working Papers 10-37, Bank of Canada.
    51. Michael P. Clements, 2014. "Real-Time Factor Model Forecasting and the Effects of Instability," ICMA Centre Discussion Papers in Finance icma-dp2014-05, Henley Business School, University of Reading.
    52. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Economics Working Papers ECO2008/16, European University Institute.
    53. Sargent, Thomas & Surico, Paolo, 2008. "Monetary policies and low-frequency manifestations of the quantity theory," Discussion Papers 26, Monetary Policy Committee Unit, Bank of England.
    54. Fanelli, Luca & Sorge, Marco M., 2017. "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 57-70.
    55. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    56. Peter Tulip, 2009. "Has the Economy Become More Predictable? Changes in Greenbook Forecast Accuracy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1217-1231, September.
    57. Mr. Helge Berger & Mr. Thomas Harjes & Mr. Emil Stavrev, 2008. "The ECB’s Monetary Analysis Revisited," IMF Working Papers 2008/171, International Monetary Fund.
    58. 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.
    59. Antonello D’ Agostino & Domenico Giannone, 2012. "Comparing Alternative Predictors Based on Large‐Panel Factor Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 306-326, April.
    60. Daniel L. Thornton, 2012. "How did we get to inflation targeting and where do we need to go to now? a perspective from the U.S. experience," Review, Federal Reserve Bank of St. Louis, vol. 94(Jan), pages 65-81.
    61. Claudia Godbout & Marco J. Lombardi, 2012. "Short-Term Forecasting of the Japanese Economy Using Factor Models," Staff Working Papers 12-7, Bank of Canada.
    62. Tatevik Sekhposyan & Barbara Rossi, 2008. "Has modelsí forecasting performance for US output growth and inflation changed over time, and when?," Working Papers 09-02, Duke University, Department of Economics.
    63. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2009. "A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model," Finance and Economics Discussion Series 2009-10, Board of Governors of the Federal Reserve System (U.S.).
    64. Drechsel, Katja & Scheufele, Rolf, 2012. "The performance of short-term forecasts of the German economy before and during the 2008/2009 recession," International Journal of Forecasting, Elsevier, vol. 28(2), pages 428-445.
    65. Edward N. Gamber & Julie K. Smith, 2007. "Are the Fed’s Inflation Forecasts Still Superior to the Private Sector’s?," Working Papers 2007-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Jul 2008.
    66. Gebka, Bartosz & Wohar, Mark E., 2018. "The predictive power of the yield spread for future economic expansions: Evidence from a new approach," Economic Modelling, Elsevier, vol. 75(C), pages 181-195.
    67. Dur, Ayşe & Martínez García, Enrique, 2020. "Mind the gap!—A monetarist view of the open-economy Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    68. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    69. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    70. Berger, Helge & Harjes, Thomas & Stavrev, Emil, 2008. "The ECB's monetary analysis revisited," Discussion Papers 2008/14, Free University Berlin, School of Business & Economics.
    71. Fornari, Fabio & Lemke, Wolfgang, 2010. "Predicting recession probabilities with financial variables over multiple horizons," Working Paper Series 1255, European Central Bank.
    72. Daniel L. Thornton, 2009. "How did we get to inflation targeting and where do we go now? a perspective from the U.S. experience," Working Papers 2009-038, Federal Reserve Bank of St. Louis.
    73. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    74. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
    75. Kim Chang-Jin & Kim Yunmi, 2008. "Is the Backward-Looking Component Important in a New Keynesian Phillips Curve?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-20, September.
    76. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2009. "GDP nowcasting with ragged-edge data : A semi-parametric modelling," Post-Print halshs-00344839, HAL.
    77. David C. Wheelock & Mark E. Wohar, 2009. "Can the term spread predict output growth and recessions? a survey of the literature," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 419-440.
    78. Daniel L. Thornton & Giorgio Valente, 2010. "Predicting bond excess returns with forward rates: an asset-allocation perspective," Working Papers 2010-034, Federal Reserve Bank of St. Louis.
    79. Ronald Ravinesh Kumar & Peter Josef Stauvermann & Hang Thi Thu Vu, 2021. "The Relationship between Yield Curve and Economic Activity: An Analysis of G7 Countries," JRFM, MDPI, vol. 14(2), pages 1-23, February.
    80. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
    81. Andrea Nobili, 2009. "Composite indicators for monetary analysis," Temi di discussione (Economic working papers) 713, Bank of Italy, Economic Research and International Relations Area.

  21. D'Agostino, Antonello & Giannone, Domenico, 2006. "Comparing Alternative Predictors Based on Large-Panel Factor Models," Research Technical Papers 14/RT/06, Central Bank of Ireland.

    Cited by:

    1. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2009. "A Robust Criterion for Determining the Number of Factors in Approximate Factor Models," Working Papers ECARES 2009_023, ULB -- Universite Libre de Bruxelles.
    2. D'Agostino, Antonello & Domenico, Giannone & Surico, Paolo, 2006. "(Un)Predictability and Macroeconomic Stability," Research Technical Papers 5/RT/06, Central Bank of Ireland.
    3. GUO-FITOUSSI, Liang, 2013. "A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets," MPRA Paper 50005, University Library of Munich, Germany.
    4. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
    5. Pietro Dallari & Antonio Ribba, 2015. "Dynamic Factor Models with In nite-Dimensional Factor Space: Asymptotic Analysis," Center for Economic Research (RECent) 115, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    6. Alessandro Giovannelli, 2012. "Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies," CEIS Research Paper 255, Tor Vergata University, CEIS, revised 08 Nov 2012.
    7. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    8. Alessandro Giovannelli & Tommaso Proietti, 2014. "On the Selection of Common Factors for Macroeconomic Forecasting," CREATES Research Papers 2014-46, Department of Economics and Business Economics, Aarhus University.
    9. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    10. Jan J. J. Groen & George Kapetanios, 2009. "Model selection criteria for factor-augmented regressions," Staff Reports 363, Federal Reserve Bank of New York.
    11. Hubrich, Kirstin & Marcellino, Massimiliano & Beck, Günter W., 2006. "Regional inflation dynamics within and across euro area countries and a comparison with the US," Working Paper Series 681, European Central Bank.
    12. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    13. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    14. Darracq Pariès, Matthieu & Maurin, Laurent, 2008. "The role of country-specific trade and survey data in forecasting euro area manufacturing production: perspective from large panel factor models," Working Paper Series 894, European Central Bank.
    15. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    16. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    17. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation of Non-Stationary Large Approximate Dynamic Factor Models," Papers 1910.09841, arXiv.org.
    18. Buss, Ginters, 2010. "A note on GDP now-/forecasting with dynamic versus static factor models along a business cycle," MPRA Paper 22147, University Library of Munich, Germany.
    19. 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.
    20. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    21. 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.
    22. Matteo Barigozzi & Marco Capasso, 2007. "A Multivariate Perspective for Modeling and Forecasting Inflation's Conditional Mean and Variance," LEM Papers Series 2007/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    23. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    24. Guido Bulligan & Massimiliano Marcellino & Fabrizio Venditti, 2012. "Forecasting economic activity with higher frequency targeted predictors," Temi di discussione (Economic working papers) 847, Bank of Italy, Economic Research and International Relations Area.
    25. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    26. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    27. Jon Faust & Jonathan H. Wright, 2007. "Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset," NBER Working Papers 13397, National Bureau of Economic Research, Inc.
    28. 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.
    29. D. Tutberidze & D. Japaridze, 2017. "Macroeconomic Forecasting Using Bayesian Vector Autoregressive Approach," Вестник Киевского национального университета имени Тараса Шевченко. Экономика., Socionet;Киевский национальный университет имени Тараса Шевченко, vol. 2(191), pages 42-49.
    30. F. Della Marra, 2017. "A forecasting performance comparison of dynamic factor models based on static and dynamic methods," Economics Department Working Papers 2017-ME01, Department of Economics, Parma University (Italy).
    31. Hanisch, Max & Kempa, Bernd, 2017. "The international transmission channels of US supply and demand shocks: Evidence from a non-stationary dynamic factor model for the G7 countries," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 70-88.
    32. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    33. Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers 624, Queen Mary University of London, School of Economics and Finance.
    34. Gürkaynak, Refet & Edge, Rochelle, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," CEPR Discussion Papers 8158, C.E.P.R. Discussion Papers.
    35. Liebermann, Joelle, 2011. "Real-Time Nowcasting of GDP: Factor Model versus Professional Forecasters," Research Technical Papers 3/RT/11, Central Bank of Ireland.
    36. Barhoumi, K. & Rünstler, G. & Cristadoro, R. & Den Reijer, A. & Jakaitiene, A. & Jelonek, P. & Rua, A. & Ruth, K. & Benk, S. & Van Nieuwenhuyze, C., 2008. "Short-term forecasting of GDP using large monthly datasets: a pseudo real-time forecast evaluation exercise," Working papers 215, Banque de France.
    37. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
    38. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    39. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    40. Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017. "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, vol. 66(C), pages 132-138.
    41. , 2020. "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper RWP 20-09, Federal Reserve Bank of Kansas City.
    42. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    43. Jokubaitis, Saulius & Celov, Dmitrij & Leipus, Remigijus, 2021. "Sparse structures with LASSO through principal components: Forecasting GDP components in the short-run," International Journal of Forecasting, Elsevier, vol. 37(2), pages 759-776.
    44. Elena Deryugina & Alexey Ponomarenko, 2021. "Explaining the lead–lag pattern in the money–inflation relationship: a microsimulation approach," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1113-1128, September.
    45. Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
    46. Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
    47. Reichlin, Lucrezia & Giannone, Domenico & De Mol, Christine, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
    48. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    49. Viktors Ajevskis & Gundars Davidsons, 2008. "Dynamic Factor Models in Forecasting Latvia's Gross Domestic Product," Working Papers 2008/02, Latvijas Banka.
    50. Christian Schulz, 2008. "Forecasting economic activity for Estonia : The application of dynamic principal component analyses," Bank of Estonia Working Papers 2008-02, Bank of Estonia, revised 30 Oct 2008.
    51. Marco J. Lombardi & Philipp Maier, 2010. "‘Lean’ versus ‘Rich’ Data Sets: Forecasting during the Great Moderation and the Great Recession," Staff Working Papers 10-37, Bank of Canada.
    52. Marc Hallin & Roman Liska, 2008. "Dynamic Factors in the Presence of Block Structure," Economics Working Papers ECO2008/22, European University Institute.
    53. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    54. Xisong Jin & Francisco Nadal De Simone, 2015. "Investment funds? vulnerabilities: A tail-risk dynamic CIMDO approach," BCL working papers 95, Central Bank of Luxembourg.
    55. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Economics Working Papers ECO2008/16, European University Institute.
    56. Marta Bańbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92, January.
    57. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.
    58. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
    59. Aðalheiður Ó. Guðlaugsdóttir & Lilja S. Kro, 2018. "The common component of the CPI - A trendy measure of Icelandic underlying inflation," Economics wp78, Department of Economics, Central bank of Iceland.
    60. Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Center for Economic Research (RECent) 138, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    61. Derek Bunn & Julien Chevallier & Yannick Le Pen & Benoît Sévi, 2017. "Fundamental and Financial Influences on the Co-movement of Oil and Gas prices," Post-Print hal-01619890, HAL.
    62. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components," Tinbergen Institute Discussion Papers 14-113/III, Tinbergen Institute.
    63. Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
    64. Matteo Luciani & Libero Monteforte, 2012. "Uncertainty and Heterogeneity in factor models forecasting," Working Papers 5, Department of the Treasury, Ministry of the Economy and of Finance.
    65. Amstad, Marlene & Ye, Huan & Ma, Guonan, 2018. "Developing an underlying inflation gauge for China," BOFIT Discussion Papers 11/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
    66. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    67. Asger Lunde & Miha Torkar, 2020. "Including news data in forecasting macro economic performance of China," Computational Management Science, Springer, vol. 17(4), pages 585-611, December.
    68. Schnatz, Bernd, 2006. "Is reversion to PPP in euro exchange rates non-linear?," Working Paper Series 682, European Central Bank.
    69. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised Dec 2023.
    70. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
    71. Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
    72. Timmermann, Allan & Aiolfi, Marco & Catão, Luís, 2010. "Common Factors in Latin America?s Business Cycles," CEPR Discussion Papers 7671, C.E.P.R. Discussion Papers.
    73. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2009. "Short-term forecasting of GDP using large datasets: a pseudo real-time forecast evaluation exercise," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 595-611.
    74. Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
    75. Yannick Le Pen & Benoît Sévi, 2013. "Futures Trading and the Excess Comovement of Commodity Prices," AMSE Working Papers 1301, Aix-Marseille School of Economics, France, revised Jan 2013.
    76. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
    77. Jörg Breitung & Sandra Eickmeier, 2014. "Analyzing business and financial cycles using multi-level factor models," CAMA Working Papers 2014-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    78. Christian Schulz, 2007. "Forecasting economic growth for Estonia : application of common factor methodologies," Bank of Estonia Working Papers 2007-09, Bank of Estonia, revised 04 Sep 2007.
    79. Max Hanisch, 2017. "US Monetary Policy and the Euro Area," Discussion Papers of DIW Berlin 1701, DIW Berlin, German Institute for Economic Research.
    80. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    81. Hanisch, Max, 2019. "US monetary policy and the euro area," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 77-96.
    82. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
    83. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
    84. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    85. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    86. Hallin, Marc & Liska, Roman, 2011. "Dynamic factors in the presence of blocks," Journal of Econometrics, Elsevier, vol. 163(1), pages 29-41, July.
    87. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    88. Rochelle M. Edge & Refet S. Gürkaynak, 2011. "How useful are estimated DSGE model forecasts?," Finance and Economics Discussion Series 2011-11, Board of Governors of the Federal Reserve System (U.S.).
    89. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Feb 2022.
    90. Bulligan, Guido & Marcellino, Massimiliano & Venditti, Fabrizio, 2015. "Forecasting economic activity with targeted predictors," International Journal of Forecasting, Elsevier, vol. 31(1), pages 188-206.
    91. Andrea Nobili, 2009. "Composite indicators for monetary analysis," Temi di discussione (Economic working papers) 713, Bank of Italy, Economic Research and International Relations Area.
    92. Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.

  22. D'Agostino, Antonello & Serafini, Roberta & Ward, Melanie, 2006. "Sectoral explanations of employment in Europe: the role of services," Research Technical Papers 8/RT/06, Central Bank of Ireland.

    Cited by:

    1. Muhammad AJMAIR & Khadim HUSSAIN & Sabahat AKRAM & Ambreen ZEB, 2017. "What determines the growth of services sector in Pakistan? A comparison of ARDL bound testing and time varying parametric estimation with general to specific approach," Turkish Economic Review, KSP Journals, vol. 4(3), pages 308-319, September.
    2. Safarov, Bakhtier, 2011. "Challenges and development guidelines of the service industry in Uzbekistan," Perspectives of Innovations, Economics and Business (PIEB), Prague Development Center (PRADEC), vol. 7(1), pages 1-2, January.
    3. DonHee Lee & Dong Lee, 2013. "A comparative study of quality awards: evolving criteria and research," Service Business, Springer;Pan-Pacific Business Association, vol. 7(3), pages 347-362, September.
    4. Burda, Michael & Bachmann, Ronald, 2007. "Sectoral Transformation, Turbulence, and Labour Market Dynamics in Germany," CEPR Discussion Papers 6226, C.E.P.R. Discussion Papers.
    5. Martina Halaskova & Renata Halaskova & Viktor Prokop, 2018. "Evaluation of Efficiency in Selected Areas of Public Services in European Union Countries," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    6. Metka Stare & Andreja Jaklič, 2011. "Towards Explaining Growth of Private and Public services in the Emerging Market Economies," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 13(30), pages 581-598, June.
    7. Gisela Di Meglio & Metka Stare & Andreja Jaklič, 2011. "Explanation for public and private service growth in the enlarged EU," The Service Industries Journal, Taylor & Francis Journals, vol. 32(4), pages 503-514, June.
    8. Luigi BONATTI & Giulia FELICE, 2009. "Trade and growth in a two-country model with home production and uneven technological spillovers," Departmental Working Papers 2009-13, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    9. Luigi Bonatti, 2007. "Home production, labor taxation and trade account," Department of Economics Working Papers 0715, Department of Economics, University of Trento, Italia.
    10. Catherine Lam & Frank Walter & Kan Ouyang, 2014. "Display rule perceptions and job performance in a Chinese retail firm: The moderating role of employees’ affect at work," Asia Pacific Journal of Management, Springer, vol. 31(2), pages 575-597, June.
    11. Andreas Bergh, 2014. "Sweden and the Revival of the Capitalist Welfare State," Books, Edward Elgar Publishing, number 15717.
    12. Bakhtier Safarov, 2011. "Challenges And Development Guidelines Of The Service Industry In Uzbekistan," Perspectives of Innovation in Economics and Business (PIEB), Prague Development Center, vol. 7(1), pages 43-44, January.
    13. Ambreen ZEB & Khadim HUSSAIN & Usman AHMAD & Muhammad AJMAIR, 2017. "Factors affecting the services sector growth in Pakistan: A time varying parametric approach," Journal of Economics Library, KSP Journals, vol. 4(3), pages 388-395, September.
    14. Mensah, Emmanuel & Owusu, Solomon & Foster-McGregor, Neil & Szirmai, Adam, 2018. "Structural change, productivity growth and labour market turbulence in Africa," MERIT Working Papers 2018-025, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    15. Per Skedinger, 2010. "Employment Protection Legislation," Books, Edward Elgar Publishing, number 13686.
    16. Luigi Bonatti & Giulia Felice, 2010. "Trade And Growth In A Two‐Country Model With Home Production And Uneven Technological Spillovers," Manchester School, University of Manchester, vol. 78(5), pages 484-509, September.

  23. Angelini, Elena & McAdam, Peter & D'Agostino, Antonello, 2006. "The Italian block of the ESCB multi-country model," Working Paper Series 660, European Central Bank.

    Cited by:

    1. Katarzyna Budnik & Michal Greszta & Michal Hulej & Marcin Kolasa & Karol Murawski & Michal Rot & Bartosz Rybaczyk & Magdalena Tarnicka, 2009. "The new macroeconometric model of the Polish economy," NBP Working Papers 62, Narodowy Bank Polski.
    2. Francesco Zezza & Gennaro Zezza, 2020. "A Stock-Flow Consistent Quarterly Model of the Italian Economy," Economics Working Paper Archive wp_958, Levy Economics Institute.
    3. Warmedinger, Thomas & Vetlov, Igor, 2006. "The German block of the ESCB multi-country model," Working Paper Series 654, European Central Bank.
    4. Alberto Bagnai & Christian Alexander Mongeau Ospina, 2014. "The a/simmetrie annual macroeconometric model of the Italian economy: structure and properties," a/ Working Papers Series 1405, Italian Association for the Study of Economic Asymmetries, Rome (Italy).
    5. Schnatz, Bernd, 2006. "Is reversion to PPP in euro exchange rates non-linear?," Working Paper Series 682, European Central Bank.
    6. Andres Frick & Michael Graff & Jochen Kurt Hartwig & Boriss Siliverstovs, 2010. "Discretionary Fiscal Policy," KOF Working papers 10-253, KOF Swiss Economic Institute, ETH Zurich.
    7. Ottavio Ricchi, 2013. "Analyzing MeMo-It supply side properties," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(1), pages 57-64.

  24. Paolo Surico & Antonello D'Agostino & Luca Sala, 2005. "The Fed and the Stock Market," Computing in Economics and Finance 2005 293, Society for Computational Economics.

    Cited by:

    1. Cinzia Alcidi , Alessandro Flamini, Andrea Fracasso, 2005. ""Taylored rules". Does one fit (or hide) all?," IHEID Working Papers 04-2005, Economics Section, The Graduate Institute of International Studies, revised Apr 2006.
    2. Søren HOVE RAVN, 2010. "Has the Fed Reacted Asymmetrically to Stock Prices," EcoMod2010 259600076, EcoMod.
    3. Daria Finocchiaro & Virginia Queijo Von Heideken, 2013. "Do Central Banks React to House Prices?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(8), pages 1659-1683, December.
    4. Harold Glenn A. Valera & Mark J. Holmes & Gazi Hassan, 2017. "Stock market uncertainty and interest rate behaviour: a panel GARCH approach," Applied Economics Letters, Taylor & Francis Journals, vol. 24(11), pages 732-735, June.
    5. Mandler, Martin, 2009. "In search of robust monetary policy rules - Should the Fed look at money growth or stock market performance?," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 345-361, June.
    6. Wang, Shen & Mayes, David G., 2012. "Monetary policy announcements and stock reactions: An international comparison," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 145-164.
    7. Mandler, Martin, 2006. "Are there gains from including monetary aggregates and stock market indices in the monetary policy reaction function? A simulation study of recent U.S. monetary policy," MPRA Paper 2318, University Library of Munich, Germany.
    8. Marie-Louise Djigbenou, 2014. "Determinants of Global Liquidity Dynamics:a FAVAR approach," Working Papers hal-00956314, HAL.
    9. Castelnuovo, Efrem & Nisticò, Salvatore, 2010. "Stock market conditions and monetary policy in a DSGE model for the U.S," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1700-1731, September.
    10. Francesco Furlanetto, 2011. "Does Monetary Policy React to Asset Prices? Some International Evidence," International Journal of Central Banking, International Journal of Central Banking, vol. 7(3), pages 91-111, September.
    11. Nan-Kuang Chen & Han-Liang Cheng, 2011. "Asset Price and Monetary Policy - The Effect of Expectation Formation," Working Papers 032011, Hong Kong Institute for Monetary Research.
    12. Cinzia Alcidi & Alessandro Flamini & Andrea Fracasso, 2011. "Policy Regime Changes, Judgment and Taylor rules in the Greenspan Era," Economica, London School of Economics and Political Science, vol. 78(309), pages 89-107, January.
    13. Jovanovic Mario & Zimmermann Tobias, 2010. "Stock Market Uncertainty and Monetary Policy Reaction Functions of the Federal Reserve Bank," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-19, July.
    14. Castelnuovo, Efrem, 2013. "Monetary policy shocks and financial conditions: A Monte Carlo experiment," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 282-303.
    15. Jovanović, Mario & Zimmermann, Tobias, 2008. "Stock Market Uncertainty and Monetary Policy Reaction Functions of the Federal Reserve Bank," Ruhr Economic Papers 77, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

Articles

  1. Antonello D’Agostino & Michele Modugno & Chiara Osbat, 2017. "A Global Trade Model for the Euro Area," International Journal of Central Banking, International Journal of Central Banking, vol. 13(4), pages 1-34, December.
    See citations under working paper version above.
  2. Jacopo Cimadomo & Antonello D'Agostino, 2016. "Combining Time Variation and Mixed Frequencies: an Analysis of Government Spending Multipliers in Italy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1276-1290, November.
    See citations under working paper version above.
  3. Colin Bermingham & Antonello D’Agostino, 2014. "Understanding and forecasting aggregate and disaggregate price dynamics," Empirical Economics, Springer, vol. 46(2), pages 765-788, March.
    See citations under working paper version above.
  4. D’Agostino, Antonello & Ehrmann, Michael, 2014. "The pricing of G7 sovereign bond spreads – The times, they are a-changin," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 155-176.
    See citations under working paper version above.
  5. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.
    See citations under working paper version above.
  6. Antonello D’ Agostino & Domenico Giannone, 2012. "Comparing Alternative Predictors Based on Large‐Panel Factor Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 306-326, April.
    See citations under working paper version above.
  7. Antonello D’agostino & Kieran Mcquinn & Karl Whelan, 2012. "Are Some Forecasters Really Better Than Others?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(4), pages 715-732, June.
    See citations under working paper version above.
  8. Antonello D'Agostino & Paolo Surico, 2012. "A Century of Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1097-1106, November.
    See citations under working paper version above.
  9. Antonello D'Agostino & Kieran McQuinn & Derry O’Brien, 2012. "Nowcasting Irish GDP," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 21-31.
    See citations under working paper version above.
  10. Antonello D'Agostino & Paolo Surico, 2009. "Does Global Liquidity Help to Forecast U.S. Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 479-489, March.
    See citations under working paper version above.
  11. Antonello D'Agostino & Karl Whelan, 2008. "Federal Reserve Information During the Great Moderation," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 609-620, 04-05.
    See citations under working paper version above.Sorry, no citations of articles recorded.

Chapters

  1. Antonello D’Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2016. "Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 569-594, Emerald Group Publishing Limited.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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