IDEAS home Printed from https://ideas.repec.org/r/jae/japmet/v18y2003i4p427-443.html
   My bibliography  Save this item

A new coincident index of business cycles based on monthly and quarterly series

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Mr. Troy D Matheson, 2013. "The Global Financial Crisis: An Anatomy of Global Growth," IMF Working Papers 2013/076, International Monetary Fund.
  2. Michael Graff, 2005. "Internationale Konjunkturverbunde," KOF Working papers 05-108, KOF Swiss Economic Institute, ETH Zurich.
  3. Arias, Maria A. & Gascon, Charles S. & Rapach, David E., 2016. "Metro business cycles," Journal of Urban Economics, Elsevier, vol. 94(C), pages 90-108.
  4. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
  5. Boriss Siliverstovs, 2012. "Are GDP Revisions Predictable? Evidence for Switzerland," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 58(4), pages 299-326.
  6. Markus Leippold & Hanlin Yang, 2023. "Mixed‐frequency predictive regressions with parameter learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1955-1972, December.
  7. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 181-197, April-Jun.
  8. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
  9. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
  10. Martyna Marczak & Víctor Gómez, 2017. "Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter," Empirical Economics, Springer, vol. 52(4), pages 1379-1408, June.
  11. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
  12. 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.
  13. Antonio Diez de los Rios & Enrique Sentana, 2011. "Testing Uncovered Interest Parity: A Continuous‐Time Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 1215-1251, November.
  14. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
  15. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
  16. Michele Modugno & Lucrezia Reichlin & Domenico Giannone & Marta Banbura, 2012. "Nowcasting with Daily Data," 2012 Meeting Papers 555, Society for Economic Dynamics.
  17. 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.
  18. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
  19. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
  20. Hager Ben Romdhane, 2021. "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers 11-2021, Economics Section, The Graduate Institute of International Studies.
  21. Bańbura, 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.
  22. Necmettin Alpay Koçak, 2020. "The Role of Ecb Speeches in Nowcasting German Gdp," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2020(2), pages 05-20.
  23. Boriss Siliverstovs, 2016. "The franc shock and Swiss GDP: how long does it take to start feeling the pain?," Applied Economics, Taylor & Francis Journals, vol. 48(36), pages 3432-3441, August.
  24. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
  25. Balcilar, Mehmet & Gupta, Rangan & Segnon, Mawuli, 2016. "The role of economic policy uncertainty in predicting U.S. recessions: A mixed-frequency Markov-switching vector autoregressive approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-20.
  26. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2013. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
  27. Michal Franta & David Havrlant & Marek Rusnák, 2016. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 165-185, December.
  28. Dal Bianco, Marcos & Camacho, Maximo & Perez Quiros, Gabriel, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 377-396.
  29. Martínez-Martín, Jaime & Rusticelli, Elena, 2021. "Keeping track of global trade in real time," International Journal of Forecasting, Elsevier, vol. 37(1), pages 224-236.
  30. Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2011. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," Discussion Paper Series 1: Economic Studies 2011,35, Deutsche Bundesbank.
  31. 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.
  32. Klaus Abberger & Michael Graff & Boriss Siliverstovs & Jan-Egbert Sturm, 2014. "The KOF Economic Barometer, Version 2014," KOF Working papers 14-353, KOF Swiss Economic Institute, ETH Zurich.
  33. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the Output Gap," Working Papers LuissLab 13103, Dipartimento di Economia e Finanza, LUISS Guido Carli.
  34. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
  35. Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
  36. Gabriele Fiorentini & Alessandro Galesi & Gabriel Pérez-Quirós & Enrique Sentana, 2018. "The rise and fall of the natural interest rate," Working Papers 1822, Banco de España.
  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. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
  39. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andr� Lucas, 2014. "Observation-Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 898-915, December.
  40. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
  41. 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.
  42. Sieds, 2013. "Complete Volume LXVII n.2 2013," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 1-197, April-Jun.
  43. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
  44. Máximo Camacho & Rafael Doménech, 2012. "MICA-BBVA: a factor model of economic and financial indicators for short-term GDP forecasting," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(4), pages 475-497, December.
  45. Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
  46. Raquel Nadal Cesar Gonçalves, 2022. "Nowcasting Brazilian GDP with Electronic Payments Data," Working Papers Series 564, Central Bank of Brazil, Research Department.
  47. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, vol. 29(4), pages 644-658.
  48. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
  49. Helena Rodríguez, 2014. "Un indicador de la evolución del PIB uruguayo en tiempo real," Documentos de trabajo 2014009, Banco Central del Uruguay.
  50. Bräuning, Falk & Koopman, Siem Jan, 2014. "Forecasting macroeconomic variables using collapsed dynamic factor analysis," International Journal of Forecasting, Elsevier, vol. 30(3), pages 572-584.
  51. 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.
  52. Robert C. M. Beyer & Lazar Milivojevic, 2023. "Dynamics and synchronization of global equilibrium interest rates," Applied Economics, Taylor & Francis Journals, vol. 55(28), pages 3195-3214, June.
  53. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
  54. Lehmann, Robert & Wikman, Ida, 2022. "Quarterly GDP Estimates for the German States," MPRA Paper 112642, University Library of Munich, Germany.
  55. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
  56. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
  57. Marie Adanero-Donderis & Olivier Darné & Laurent Ferrara, 2009. "Un indicateur probabiliste du cycle d'accélération pour l'économie française," Economie & Prévision, La Documentation Française, vol. 0(3), pages 95-114.
  58. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.
  59. Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
  60. Paul Viefers & Ferdinand Fichtner & Simon Junker & Maximilian Podstawski, 2014. "Filtering German Economic Conditions from a Large Dataset: The New DIW Economic Barometer," Discussion Papers of DIW Berlin 1414, DIW Berlin, German Institute for Economic Research.
  61. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
  62. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  63. Franky Juliano Galeano-Ramírez & Nicolás Martínez-Cortés & Carlos D. Rojas-Martínez, 2021. "Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches," Borradores de Economia 1168, Banco de la Republica de Colombia.
  64. Uluceviz, Erhan & Yilmaz, Kamil, 2021. "Measuring real–financial connectedness in the U.S. economy," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
  65. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
  66. Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
  67. Müller-Kademann Christian, 2015. "Internal Validation of Temporal Disaggregation: A Cloud Chamber Approach," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(3), pages 298-319, June.
  68. Daniel Aaronson & Scott A. Brave & Michael Fogarty & Ezra Karger & Spencer D. Krane, 2021. "Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade," Working Paper Series WP-2021-05, Federal Reserve Bank of Chicago, revised 18 Jun 2021.
  69. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the output gap," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
  70. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
  71. Bantis, Evripidis & Clements, Michael P. & Urquhart, Andrew, 2023. "Forecasting GDP growth rates in the United States and Brazil using Google Trends," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1909-1924.
  72. Issler, João Victor & Notini, Hilton Hostalacio, 2016. "Estimating Brazilian Monthly GDP: a State-Space Approach," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 70(1), March.
  73. Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
  74. Gonzalo Echavarría M. & Wildo González P, 2011. "Un Modelo de Factores Dinámicos de Pequeña Escala para el Imacec," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 14(2), pages 109-118, August.
  75. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
  76. Ricco, Giovanni & Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia, 2022. "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," CEPR Discussion Papers 17111, C.E.P.R. Discussion Papers.
  77. Takashi Nakazawa, 2022. "Constructing GDP Nowcasting Models Using Alternative Data," Bank of Japan Working Paper Series 22-E-9, Bank of Japan.
  78. David Havrlant & Peter Tóth & Julia Wörz, 2016. "On the optimal number of indicators – nowcasting GDP growth in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 54-72.
  79. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
  80. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
  81. Vegard H�ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  82. Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  83. Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.
  84. Brunhes-Lesage, V. & Darné, O., 2008. "Why calculate a business sentiment indicator for services?," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 21-30, Autumn.
  85. Ana Arencibia Pareja & Ana Gomez-Loscos & Mercedes de Luis López & Gabriel Perez-Quiros, 2020. "A Short Term Forecasting Model for the Spanish GDP and itsDemand Components," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 43(85), pages 1-30.
  86. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
  87. Peter Fuleky & Carl Bonham, 2010. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 2010-17R1, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2013.
  88. Hopp Daniel, 2022. "Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)," Journal of Official Statistics, Sciendo, vol. 38(3), pages 847-873, September.
  89. Kyosuke Chikamatsu, Naohisa Hirakata, Yosuke Kido, Kazuki Otaka, 2018. "Nowcasting Japanese GDPs," Bank of Japan Working Paper Series 18-E-18, Bank of Japan.
  90. Erhan Uluceviz & Kamil Yilmaz, 2020. "Real-financial connectedness in the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-20, December.
  91. Ryadh M. Alkhareif & William Barnett, 2020. "Nowcasting Real Gdp For Saudi Arabia," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202018, University of Kansas, Department of Economics, revised Nov 2020.
  92. Pedregal, Diego J. & Pérez, Javier J., 2010. "Should quarterly government finance statistics be used for fiscal surveillance in Europe?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 794-807, October.
  93. Marcelle Chauvet & James D. Hamilton, 2006. "Dating Business Cycle Turning Points," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 1-54, Emerald Group Publishing Limited.
  94. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2017. "Euromind‐ D : A Density Estimate of Monthly Gross Domestic Product for the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 683-703, April.
  95. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
  96. Leif Anders Thorsrud, 2020. "Words are the New Numbers: A Newsy Coincident Index of the Business Cycle," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 393-409, April.
  97. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
  98. Maximo Camacho & Gabriel Perez-Quiros, 2009. "Ñ-STING: España Short Term INdicator of Growth," Working Papers 0912, Banco de España.
  99. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
  100. Camacho, Maximo & Martinez-Martin, Jaime, 2015. "Monitoring the world business cycle," Economic Modelling, Elsevier, vol. 51(C), pages 617-625.
  101. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
  102. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2008. "A Monthly Indicator of the Euro Area GDP," Economics Working Papers ECO2008/32, European University Institute.
  103. Knut Aastveit & Tørres Trovik, 2012. "Nowcasting norwegian GDP: the role of asset prices in a small open economy," Empirical Economics, Springer, vol. 42(1), pages 95-119, February.
  104. Albu, Lucian Liviu, 2008. "A Model to Estimate the Composite Index of Economic Activity in Romania – IEF-RO," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(2), pages 44-50, June.
  105. Corinna Ghirelli & María Gil & Javier J. Pérez & Alberto Urtasun, 2021. "Measuring economic and economic policy uncertainty and their macroeconomic effects: the case of Spain," Empirical Economics, Springer, vol. 60(2), pages 869-892, February.
  106. William A. Barnett & Marcelle Chauvet & Danilo Leiva-Leon, 2014. "Real-Time Nowcasting of Nominal GDP Under Structural Breaks," Staff Working Papers 14-39, Bank of Canada.
  107. Joan Paredes & Javier J. Pérez & Gabriel Perez Quiros, 2023. "Fiscal targets. A guide to forecasters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 472-492, June.
  108. K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze & G. Rünstler, 2008. "Short-term forecasting of GDP using large monthly datasets – A pseudo real-time forecast evaluation exercise," Working Paper Research 133, National Bank of Belgium.
  109. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023. "Deep Dynamic Factor Models," Working Papers 2023-08, Center for Research in Economics and Statistics.
  110. Maximo Camacho & Gabriel Perez-Quiros, 2014. "Commodity Prices and the Business Cycle in Latin America: Living and Dying by Commodities?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(2), pages 110-137, March.
  111. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
  112. Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2022. "Measuring real activity using a weekly economic index," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 667-687, June.
  113. Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  114. Luciano Campos & Danilo Leiva-León & Steven Zapata- Álvarez, 2022. "Latin American Falls, Rebounds and Tail Risks," Borradores de Economia 1201, Banco de la Republica de Colombia.
  115. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2017. "Tracking the Slowdown in Long-Run GDP Growth," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 343-356, May.
  116. 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.).
  117. Roberto S. Mariano & Yasutomo Murasawa, 2004. "Constructing a Coincident Index of Business Cycles without Assuming a One-factor Model," Working Papers 22-2004, Singapore Management University, School of Economics, revised Oct 2004.
  118. Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2018. "Nowcasting Indonesia," Empirical Economics, Springer, vol. 55(2), pages 597-619, September.
  119. Claudia FORONI & Massimiliano MARCELLINO, 2012. "A Comparison of Mixed Frequency Approaches for Modelling Euro Area Macroeconomic Variables," Economics Working Papers ECO2012/07, European University Institute.
  120. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
  121. Anthony S. Tay, 2007. "Financial Variables as Predictors of Real Output Growth," Development Economics Working Papers 22482, East Asian Bureau of Economic Research.
  122. James Mitchell & Gary Koop & Stuart McIntyre & Aubrey Poon, 2020. "Reconciled Estimates of Monthly GDP in the US," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-16, Economic Statistics Centre of Excellence (ESCoE).
  123. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
  124. Bhaghoe, Sailesh & Ooft, Gavin, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
  125. Cleiton Guollo Taufemback, 2023. "Asymptotic Behavior of Temporal Aggregation in Mixed‐Frequency Datasets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 894-909, August.
  126. 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.
  127. Boniface Yemba & Yi Duan & Nabaneeta Biswas, 2023. "Government spending news and stock price index," Economics Bulletin, AccessEcon, vol. 43(4), pages 1816-1841.
  128. 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.
  129. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
  130. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
  131. repec:fgv:epgrbe:v:67:n:1:a:4 is not listed on IDEAS
  132. 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.
  133. Issler, Joao Victor & Notini, Hilton & Rodrigues, Claudia & Soares, Ana Flávia, 2013. "Constructing coincident indices of economic activity for the Latin American economy," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
  134. Michael Zhemkov, 2022. "Assessment of Monthly GDP Growth Using Temporal Disaggregation Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 81(2), pages 79-104, June.
  135. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2019. "Mixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland," International Journal of Central Banking, International Journal of Central Banking, vol. 15(2), pages 151-178, June.
  136. 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.
  137. Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020. "A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth," International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
  138. Diego J. Pedregal & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "A toolkit to strengthen government budget surveillance," Working Papers 1416, Banco de España.
  139. Yemba, Boniface P. & Otunuga, Olusegun Michael & Tang, Biyan & Biswas, Nabaneeta, 2023. "Nowcasting of the Short-run Euro-Dollar Exchange Rate with Economic Fundamentals and Time-varying Parameters," Finance Research Letters, Elsevier, vol. 52(C).
  140. Lucian-Liviu Albu & Vasile Dinu, 2009. "How Deep and How Long Could Be the Recession in Romania," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 11(Number Sp), pages 675-683, November.
  141. 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.
  142. Deqing Wang & Yinqiu Song & Hongyan Zhang & Shengjie Pan, 2020. "The Effectiveness of Chinas Monetary Policy: Based on the Mixed-Frequency Data," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(3), pages 325-339, March.
  143. Seong, Byeongchan, 2020. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models," Economic Modelling, Elsevier, vol. 91(C), pages 463-468.
  144. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
  145. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model," OECD Statistics Working Papers 2020/01, OECD Publishing.
  146. Ryadh M. Alkhareif & William A. Barnett, 2022. "Nowcasting Real GDP for Saudi Arabia1," Open Economies Review, Springer, vol. 33(2), pages 333-345, April.
  147. Byeongchan Seong & Sung K. Ahn & Peter Zadrozny, 2007. "Cointegration Analysis with Mixed-Frequency Data," CESifo Working Paper Series 1939, CESifo.
  148. Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo.
  149. Camacho, Maximo & Perez Quiros, Gabriel & Poncela, Pilar, 2014. "Green shoots and double dips in the euro area: A real time measure," International Journal of Forecasting, Elsevier, vol. 30(3), pages 520-535.
  150. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
  151. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
  152. 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.
  153. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," American Economic Review, American Economic Association, vol. 100(2), pages 20-24, May.
  154. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
  155. Agne Reklaite, 2011. "Coincident, leading and recession indexes for the Lithuanian economy," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 11(1), pages 91-108, July.
  156. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
  157. Konstantin A., KHOLODILIN & Wension Vincent, YAO, 2004. "Business Cycle Turning Points : Mixed-Frequency Data with Structural Breaks," LIDAM Discussion Papers IRES 2004024, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  158. J. Isaac Miller, 2010. "Cointegrating regressions with messy regressors and an application to mixed‐frequency series," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 255-277, July.
  159. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
  160. Liu, Bin & Xiao, Wen & Zhu, Xingting, 2023. "How does inter-industry spillover improve the performance of volatility forecasting?," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
  161. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2016. "Real-time nowcasting of nominal GDP with structural breaks," Journal of Econometrics, Elsevier, vol. 191(2), pages 312-324.
  162. Cascaldi-Garcia, Danilo & Ferreira, Thiago R.T. & Giannone, Domenico & Modugno, Michele, 2024. "Back to the present: Learning about the euro area through a now-casting model," International Journal of Forecasting, Elsevier, vol. 40(2), pages 661-686.
  163. Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2010. "Green shoots in the euro area. A real time measure," Working Papers 1026, Banco de España.
  164. Franz Ramsauer & Aleksey Min & Michael Lingauer, 2019. "Estimation of FAVAR Models for Incomplete Data with a Kalman Filter for Factors with Observable Components," Econometrics, MDPI, vol. 7(3), pages 1-43, July.
  165. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
  166. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
  167. Antolín-Díaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan F., 2021. "Structural scenario analysis with SVARs," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 798-815.
  168. Marcos Bujosa & Antonio García‐Ferrer & Aránzazu de Juan & Antonio Martín‐Arroyo, 2020. "Evaluating early warning and coincident indicators of business cycles using smooth trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 1-17, January.
  169. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
  170. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
  171. Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient matrix approach for classical inference in state space models," Economics Letters, Elsevier, vol. 181(C), pages 22-27.
  172. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
  173. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers 22-36, Federal Reserve Bank of Cleveland.
  174. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
  175. 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.
  176. David de Antonio Liedo, 2014. "Nowcasting Belgium," Working Paper Research 256, National Bank of Belgium.
  177. Leiva-Leon Danilo, 2014. "Real vs. nominal cycles: a multistate Markov-switching bi-factor approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 1-24, December.
  178. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
  179. Andres Sagner, 2020. "High Dimensional Quantile Factor Analysis," Working Papers Central Bank of Chile 886, Central Bank of Chile.
  180. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
  181. Huseyin Cagri Akkoyun & Mahmut Gunay, 2013. "Milli Gelir Buyume Tahmini : IYA ve PMI Gostergelerinin Rolu," CBT Research Notes in Economics 1331, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  182. Marcellino, Massimiliano & Schumacher, Christian, 2007. "Factor-MIDAS for now- and forecasting with ragged-edge data: a model comparison for German GDP," Discussion Paper Series 1: Economic Studies 2007,34, Deutsche Bundesbank.
  183. Konstantin A. KHOLODILIN, 2002. "Unobserved Leading and Coincident Common Factors in the Post-War U.S. Business Cycle," LIDAM Discussion Papers IRES 2002008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  184. Fumio Hayashi & Yuta Tachi, 2023. "Nowcasting Japan’s GDP," Empirical Economics, Springer, vol. 64(4), pages 1699-1735, April.
  185. William Barnett & Marcelle Chauvet & Danilo Leiva-Leon & Liting Su, 2016. "The Credit-Card-Services Augmented Divisia Monetary Aggregates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201604, University of Kansas, Department of Economics, revised Aug 2016.
  186. Raul Ibarra & Luis M. Gomez-Zamudio, 2017. "Are Daily Financial Data Useful for Forecasting GDP? Evidence from Mexico," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 173-203, April.
  187. Shang, Yuhuang & Zheng, Tingguo, 2018. "Fitting and forecasting yield curves with a mixed-frequency affine model: Evidence from China," Economic Modelling, Elsevier, vol. 68(C), pages 145-154.
  188. Andreini, Paolo & Hasenzagl, Thomas & Reichlin, Lucrezia & Senftleben-König, Charlotte & Strohsal, Till, 2023. "Nowcasting German GDP: Foreign factors, financial markets, and model averaging," International Journal of Forecasting, Elsevier, vol. 39(1), pages 298-313.
  189. Abel Rodríguez Tirado & Marcelo Delajara & Federico Hernández Álvarez, 2016. "Nowcasting Mexico’s Short-Term GDP Growth in Real-Time: A Factor Model versus Professional Forecasters," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2016), pages 167-182, October.
  190. Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
  191. Modugno, Michele, 2013. "Now-casting inflation using high frequency data," International Journal of Forecasting, Elsevier, vol. 29(4), pages 664-675.
  192. 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.
  193. Qian, Hang, 2012. "A Flexible State Space Model and its Applications," MPRA Paper 38455, University Library of Munich, Germany.
  194. Gabriel Pérez-Quiros & Maximo Camacho & Pilar Poncela, 2010. "Green Shoots? Where, when and how?," Working Papers 2010-04, FEDEA.
  195. Porshakov, A. & Ponomarenko, A. & Sinyakov, A., 2016. "Nowcasting and Short-Term Forecasting of Russian GDP with a Dynamic Factor Model," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 60-76.
  196. Pérez-Quirós, Gabriel & Camacho, Máximo & Alvarez, Rocio, 2012. "Finite sample performance of small versus large scale dynamic factor models," CEPR Discussion Papers 8867, C.E.P.R. Discussion Papers.
  197. Wanhai You & Yuming Huang & Chien‐Chiang Lee, 2024. "Forecasting tourist flows in the COVID‐19 era using nonparametric mixed‐frequency VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 473-489, March.
  198. Roberto S. Mariano & Yasutomo Murasawa, 2010. "A Coincident Index, Common Factors, and Monthly Real GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 27-46, February.
  199. Eraslan, Sercan & Götz, Thomas, 2021. "An unconventional weekly economic activity index for Germany," Economics Letters, Elsevier, vol. 204(C).
  200. Kevin Clinton & Marianne Johnson & Mr. Jaromir Benes & Mr. Douglas Laxton & Mr. Troy D Matheson, 2010. "Structural Models in Real Time," IMF Working Papers 2010/056, International Monetary Fund.
  201. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
  202. Emanuele BACCHIOCCHI & Andrea BASTIANIN & Alessandro MISSALE & Eduardo ROSSI, 2016. "Structural Analysis With Mixed Frequency: Monetary Policy, Uncertainty And Gross Capital Flows," Departmental Working Papers 2016-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  203. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
  204. Peter Fuleky & Carl, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 2013-5, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  205. Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.
  206. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2015. "Markov-switching mixed-frequency VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 692-711.
  207. 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.
  208. Boriss Siliverstovs, 2017. "Short-term forecasting with mixed-frequency data: a MIDASSO approach," Applied Economics, Taylor & Francis Journals, vol. 49(13), pages 1326-1343, March.
  209. Döhrn, Roland & Barabas, György & Blagov, Boris & Fuest, Angela & Jäger, Philipp & Jessen, Robin & Micheli, Martin & Rujin, Svetlana, 2018. "Die wirtschaftliche Entwicklung im Inland: Aufschwung setzt sich fort, Gefährdungen nehmen zu," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 69(3), pages 21-56.
  210. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
  211. 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.
  212. Chikamatsu, Kyosuke & Hirakata, Naohisa & Kido, Yosuke & Otaka, Kazuki, 2021. "Mixed-frequency approaches to nowcasting GDP: An application to Japan," Japan and the World Economy, Elsevier, vol. 57(C).
  213. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org.
  214. Rueben Ellul & Germano Ruisi, 2022. "Nowcasting the Maltese economy with a dynamic factor model," CBM Working Papers WP/02/2022, Central Bank of Malta.
  215. Dimitris Korobilis, 2018. "Machine Learning Macroeconometrics: A Primer," Working Paper series 18-30, Rimini Centre for Economic Analysis.
  216. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
  217. Tang, Wenjin & Ding, Saijie & Chen, Hao, 2021. "Economic uncertainty and its spillover networks: Evidence from the Asia-Pacific countries," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
  218. 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.
  219. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
  220. Maximo Camacho & Jaime Martinez-Martin, 2014. "Real-time forecasting US GDP from small-scale factor models," Empirical Economics, Springer, vol. 47(1), pages 347-364, August.
  221. 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.
  222. Jeffrey Sheen & Stefan Trück & Ben Zhe Wang, 2015. "Daily Business and External Condition Indices for the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 38-53, June.
  223. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  224. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank.
  225. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
  226. Barış Soybilgen & Ege Yazgan, 2018. "Nowcasting the New Turkish GDP," Economics Bulletin, AccessEcon, vol. 38(2), pages 1083-1089.
  227. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
  228. Evren Erdogan Cosar & Sevim Kosem & Cagri Sarikaya, 2013. "Do We Really Need Filters In Estimating Output Gap? : Evidence From Turkey," Working Papers 1333, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  229. Daniel Hopp, 2022. "Benchmarking Econometric and Machine Learning Methodologies in Nowcasting," Papers 2205.03318, arXiv.org.
  230. Miroslav Klucik, 2019. "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers Working Paper No. 1/2019, Council for Budget Responsibility.
  231. Germán López, 2015. "Forecast Accuracy of Small and Large Scale Dynamic Factor Models in Developing Economies," Working Papers. Serie AD 2015-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  232. Barnett, William & Chauvet, Marcelle & Leiva-Leon, Danilo & Su, Liting, 2016. "Nowcasting nominal gdp with the credit-card augmented Divisia monetary aggregates," MPRA Paper 73246, University Library of Munich, Germany.
  233. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
  234. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2011. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the euro area," International Journal of Forecasting, Elsevier, vol. 27(2), pages 529-542.
  235. Marius Cristian Acatrinei, 2020. "Financial stability indicator for non-banking markets," Journal of Financial Studies, Institute of Financial Studies, vol. 9(5), pages 3-9, November.
  236. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
  237. Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024. "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers) 1446, Bank of Italy, Economic Research and International Relations Area.
  238. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
  239. Conefrey, Thomas & Liebermann, Joelle, 2013. "A Monthly Business Cycle Indicator for Ireland," Economic Letters 03/EL/13, Central Bank of Ireland.
  240. Graff Michael, 2006. "Internationale Konjunkturverbunde / International Business Cycles," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(4), pages 385-417, August.
  241. Mariano, Roberto S. & Ozmucur, Suleyman, 2015. "High-Mixed-Frequency Dynamic Latent Factor Forecasting Models for GDP in the Philippines/Modelos de factores dinámicos latentes con datos mixtos de alta frecuencia aplicados a la predicción del PIB en," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 451-462, Mayo.
  242. Elizondo Rocío, 2012. "Monthly GDP estimates based on the IGAE," Working Papers 2012-11, Banco de México.
  243. 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.
  244. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2016. "Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 118-127, January.
  245. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
  246. repec:ebl:ecbull:v:3:y:2002:i:20:p:1-20 is not listed on IDEAS
  247. Klaus S. Friesenbichler & Christian Glocker & Werner Hölzl & Philipp Wegmüller, 2018. "Ein neues Modell für die kurzfristige Prognose der Herstellung von Waren und der Ausrüstungsinvestitionen," WIFO Monatsberichte (monthly reports), WIFO, vol. 91(9), pages 651-661, September.
  248. Daniel Baquero & Manuel Gonzalez-Astudillo, 2018. "A Nowcasting Model for the Growth Rate of Real GDP of Ecuador : Implementing a Time-Varying Intercept," Finance and Economics Discussion Series 2018-044, Board of Governors of the Federal Reserve System (U.S.).
  249. 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.
  250. Daniela Bragoli & Jack Fosten, 2018. "Nowcasting Indian GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 259-282, April.
  251. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
  252. Camacho, Maximo & Perez-Quiros, Gabriel & Poncela, Pilar, 2018. "Markov-switching dynamic factor models in real time," International Journal of Forecasting, Elsevier, vol. 34(4), pages 598-611.
  253. Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
  254. 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.
  255. Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
  256. 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.
  257. Máximo Camacho & Matías Pacce & Gabriel Pérez-Quirós, 2020. "Spillover effects in international business cycles," Working Papers 2034, Banco de España.
  258. Ghirelli, Corinna & Pérez, Javier J. & Urtasun, Alberto, 2021. "The spillover effects of economic policy uncertainty in Latin America on the Spanish economy," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(2).
  259. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non‐linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300, April.
  260. Alessandro Giovannelli & Marco Lippi & Tommaso Proietti, 2023. "Band-Pass Filtering with High-Dimensional Time Series," Papers 2305.06618, arXiv.org.
  261. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
  262. Alvarez, Rocio & Camacho, Maximo & Perez-Quiros, Gabriel, 2016. "Aggregate versus disaggregate information in dynamic factor models," International Journal of Forecasting, Elsevier, vol. 32(3), pages 680-694.
  263. Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
  264. Gabriele Fiorentini & Enrique Sentana, 2019. "Dynamic specification tests for dynamic factor models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 325-346, April.
  265. Hagher Ben Rhomdhane & Brahim Mehdi Benlallouna, 2022. "Nowcasting real GDP in Tunisia using large datasets and mixed-frequency models," IHEID Working Papers 02-2022, Economics Section, The Graduate Institute of International Studies.
  266. Aaron G. Grech & Reuben Ellul, 2021. "Are the European Commission’s Business and Consumer Survey Results Coincident Indicators for Maltese Economic Activity?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 91-108, April.
  267. Ana Arencibia Pareja & Ana Gómez Loscos & Mercedes de Luis López & Gabriel Pérez Quirós, 2018. "A short-term forecasting model for the Spanish economy: GDP and its demand components," Occasional Papers 1801, Banco de España.
  268. Klaus Wohlrabe, 2009. "Macroeconomic forecasting with mixed frequencies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
  269. Daniel Hopp, 2021. "Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)," Papers 2106.08901, arXiv.org.
  270. Jürgen Bierbaumer-Polly & Sandra Bilek-Steindl & Thomas Url, 2019. "Monitoring and Nowcasting Sustainable Development Goals. A Case Study for Austria," WIFO Studies, WIFO, number 66635, April.
  271. Björn Roye, 2014. "Financial stress and economic activity in Germany," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(1), pages 101-126, February.
  272. Zhang, Wei & He, Jie & Ge, Chanyuan & Xue, Rui, 2022. "Real-time macroeconomic monitoring using mixed frequency data: Evidence from China," Economic Modelling, Elsevier, vol. 117(C).
  273. Caruso, Alberto, 2019. "Macroeconomic news and market reaction: Surprise indexes meet nowcasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1725-1734.
  274. Neville Francis & Eric Ghysels & Michael T. Owyang, 2011. "The low-frequency impact of daily monetary policy shocks," Working Papers 2011-009, Federal Reserve Bank of St. Louis.
  275. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
  276. 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.
  277. António Rua & João Valle e Azevedo & Siem Jan Koopman, 2003. "Tracking Growth and the Business Cycle: a Stochastic Common Cycle Model for the Euro Area," Working Papers w200316, Banco de Portugal, Economics and Research Department.
  278. Martin Feldkircher & Florian Huber & Josef Schreiner & Julia Woerz & Marcel Tirpak & Peter Toth, 2015. "Small-scale nowcasting models of GDP for selected CESEE countries," Working and Discussion Papers WP 4/2015, Research Department, National Bank of Slovakia.
  279. Éric Dubois, 2006. "Présentation générale," Économie et Prévision, Programme National Persée, vol. 172(1), pages 1-9.
  280. Beate Schirwitz, 2009. "A comprehensive German business cycle chronology," Empirical Economics, Springer, vol. 37(2), pages 287-301, October.
  281. repec:ebl:ecbull:v:3:y:2002:i:5:p:1-15 is not listed on IDEAS
  282. Charfeddine, Lanouar & Klein, Tony & Walther, Thomas, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," QBS Working Paper Series 2018/03, Queen's University Belfast, Queen's Business School.
  283. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, August.
  284. Neville Francis, 2012. "The Low-Frequency Impact of Daily Monetary Policy Shock," 2012 Meeting Papers 198, Society for Economic Dynamics.
  285. Pérez-Quirós, Gabriel & Leiva-León, Danilo & Rots, Eyno, 2020. "Real-Time Weakness of the Global Economy: A First Assessment of the Coronavirus Crisis," CEPR Discussion Papers 14484, C.E.P.R. Discussion Papers.
  286. Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
  287. Beate Schirwitz, 2013. "Business Fluctuations, Job Flows and Trade Unions - Dynamics in the Economy," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 47.
  288. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
  289. Pablo A. Cuba-Borda & Alexander Mechanick & Andrea Raffo, 2018. "Monitoring the World Economy: A Global Conditions Index," IFDP Notes 2018-06-15, Board of Governors of the Federal Reserve System (U.S.).
  290. Francisco Blasques & Siem Jan Koopman & Max Mallee, 2014. "Low Frequency and Weighted Likelihood Solutions for Mixed Frequency Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-105/III, Tinbergen Institute.
  291. Petrella, Ivan & Antolin-Diaz, Juan & Drechsel, Thomas, 2021. "Advances in Nowcasting Economic Activity: Secular Trends, Large Shocks and New Data," CEPR Discussion Papers 15926, C.E.P.R. Discussion Papers.
  292. 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.
  293. Katerina Arnostova & David Havrlant & Luboš Rùžièka & Peter Tóth, 2011. "Short-Term Forecasting of Czech Quarterly GDP Using Monthly Indicators," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 566-583, December.
  294. Valentina Raponi & Cecilia Frale, 2014. "Revisions in official data and forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 451-472, August.
  295. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
  296. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," MPRA Paper 53699, University Library of Munich, Germany.
  297. Claudia Foroni & Massimiliano Marcellino, 2014. "Mixed frequency structural VARs," Working Paper 2014/01, Norges Bank.
  298. Samuel N. Cohen & Silvia Lui & Will Malpass & Giulia Mantoan & Lars Nesheim & 'Aureo de Paula & Andrew Reeves & Craig Scott & Emma Small & Lingyi Yang, 2023. "Nowcasting with signature methods," Papers 2305.10256, arXiv.org.
  299. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions, Second Version," PIER Working Paper Archive 08-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Apr 2008.
  300. Barnett, William & Chauvet, Marcelle & Leiva-Leon, Danilo & Su, Liting, 2016. "Nowcasting Nominal GDP with the Credit-Card Augmented Divisia Monetary," Studies in Applied Economics 59, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
  301. repec:zbw:bofitp:2015_012 is not listed on IDEAS
  302. 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.
  303. Ángel Cuevas & Enrique Quilis, 2012. "A factor analysis for the Spanish economy," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(3), pages 311-338, September.
  304. Abdullah Tahir & Jameel Ahmed & Waqas Ahmed, 2018. "Robust Quarterization of GDP and Determination of Business Cycle Dates for IGC Partner Countries," SBP Working Paper Series 97, State Bank of Pakistan, Research Department.
  305. Satoshi Urasawa, 2023. "The Usefulness of High-Frequency Alternative Data to Obtain Nowcasts for Japan’s GDP: Evidence from Credit Card Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 191-211, September.
  306. 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.
  307. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
  308. Juan Pablo Cote-Barón & Karen L. Pulido-Mahecha & Nicol Valeria Rodríguez-Rodríguez & Carlos D. Rojas-Martínez, 2023. "El ISAE: Un Indicador para Monitorear la Actividad Económica Colombiana en Alta Frecuencia," Borradores de Economia 1225, Banco de la Republica de Colombia.
  309. Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.
  310. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina, 2018. "Deutsche Konjunktur im Frühjahr 2018 - Deutsche Wirtschaft näher am Limit [German Economy Spring 2018 - German economy closer to its limit]," Kieler Konjunkturberichte 41, Kiel Institute for the World Economy (IfW Kiel).
  311. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
  312. Enrique M. Quilis, 2018. "Temporal disaggregation of economic time series: The view from the trenches," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 447-470, November.
  313. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.
  314. María Gil & Danilo Leiva-Leon & Javier J. Pérez & Alberto Urtasun, 2019. "An application of dynamic factor models to nowcast regional economic activity in Spain," Occasional Papers 1904, Banco de España.
  315. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
  316. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, University Library of Munich, Germany.
  317. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
  318. Issler, João Victor & Notini, Hilton Hostalácio & Rodrigues, Claudia Oliveira da Fontoura, 2009. "Um indicador coincidente e antecedente da atividade econômica brasileira," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 695, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
  319. William Barcelona & Danilo Cascaldi-Garcia & Jasper Hoek & Eva Van Leemput, 2022. "What Happens in China Does Not Stay in China," International Finance Discussion Papers 1360, Board of Governors of the Federal Reserve System (U.S.).
  320. 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.
  321. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
  322. Robert Lehmann & Ida Wikman, 2023. "Eine Analyse der Konjunkturzyklen für die deutschen Bundesländer," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 30(02), pages 15-21, April.
  323. Ángel Cuevas & Ramiro Ledo & Enrique M. Quilis, 2021. "Seasonal adjustment of the Spanish sales daily data," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(4), pages 687-708, December.
  324. Marozzi, Armando, 2021. "The ECB's tracker: nowcasting the press conferences of the ECB," Working Paper Series 2609, European Central Bank.
  325. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2020. "Structural analysis with mixed-frequency data: A model of US capital flows," Economic Modelling, Elsevier, vol. 89(C), pages 427-443.
  326. Corinna Ghirelli & Javier J. Pérez & Alberto Urtasun, 2020. "Economic policy uncertainty in Latin America: measurement using Spanish newspapers and economic spillovers," Working Papers 2024, Banco de España.
  327. Davor Kunovac & Borna Špalat, 2014. "Nowcasting GDP Using Available Monthly Indicators," Working Papers 39, The Croatian National Bank, Croatia.
  328. Eraslan, Sercan & Götz, Thomas, 2020. "An unconventional weekly economic activity index for Germany," Technical Papers 02/2020, Deutsche Bundesbank.
  329. Jack Fosten & Daniel Gutknecht, 2021. "Horizon confidence sets," Empirical Economics, Springer, vol. 61(2), pages 667-692, August.
  330. Dimitris Korobilis & Maximilian Schroder, 2022. "Probabilistic quantile factor analysis," Papers 2212.10301, arXiv.org, revised Dec 2022.
  331. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
  332. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
  333. Yoshihiro Ohtsuka, 2018. "Large Shocks and the Business Cycle: The Effect of Outlier Adjustments," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 143-178, April.
  334. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
  335. Martin Feldkircher & Florian Huber & Josef Schreiner & Marcel Tirpák & Peter Tóth & Julia Wörz, 2015. "Bridging the information gap: small-scale nowcasting models of GDP growth for selected CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 56-75.
  336. Romain Aumond & Julien Royer, 2024. "Improving the robustness of Markov-switching dynamic factor models with time-varying volatility," Working Papers 2024-04, Center for Research in Economics and Statistics.
  337. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
  338. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
  339. 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.
  340. Thomas Walther & Lanouar Charfeddine & Tony Klein, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," Working Papers on Finance 1816, University of St. Gallen, School of Finance.
  341. Keeney, Mary & Kennedy, Bernard & Liebermann, Joelle, 2012. "The value of hard and soft data for short-term forecasting of GDP," Economic Letters 11/EL/12, Central Bank of Ireland.
  342. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
  343. Marcos Dal Bianco & Jaime Martinez-Martín & Maximo Camacho, 2013. "Short-Run Forecasting of Argentine GDP Growth," Working Papers 1314, BBVA Bank, Economic Research Department.
  344. Alain Kabundi & Asithandile Mbelu, 2021. "Estimating a time-varying financial conditions index for South Africa," Empirical Economics, Springer, vol. 60(4), pages 1817-1844, April.
  345. Matthieu Cornec & Thierry Deperraz, 2006. "Un nouvel indicateur synthétique mensuel résumant le climat des affaires dans les services en France," Économie et Statistique, Programme National Persée, vol. 395(1), pages 13-38.
  346. González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.
  347. Camacho, Maximo, 2013. "Mixed-frequency VAR models with Markov-switching dynamics," Economics Letters, Elsevier, vol. 121(3), pages 369-373.
  348. Deicy J. Cristiano & Manuel D. Hernández & José David Pulido, 2012. "Pronósticos de corto plazo en tiempo real para la actividad económica colombiana," Borradores de Economia 724, Banco de la Republica de Colombia.
  349. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.
  350. Ruey Yau & C. James Hueng, 2019. "Nowcasting GDP Growth for Small Open Economies with a Mixed-Frequency Structural Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 177-198, June.
  351. Grassi, Stefano & Proietti, Tommaso & Frale, Cecilia & Marcellino, Massimiliano & Mazzi, Gianluigi, 2015. "EuroMInd-C: A disaggregate monthly indicator of economic activity for the Euro area and member countries," International Journal of Forecasting, Elsevier, vol. 31(3), pages 712-738.
  352. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
  353. Qian, Hang, 2016. "A computationally efficient method for vector autoregression with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 433-437.
  354. Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
  355. 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.
  356. Paul Labonne, 2020. "Capturing GDP nowcast uncertainty in real time," Papers 2012.02601, arXiv.org, revised Oct 2021.
  357. Troy D. Matheson, 2014. "New indicators for tracking growth in real time," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 51-71.
  358. Camacho, Maximo & Dal Bianco, Marcos & Martinez-Martin, Jaime, 2015. "Toward a more reliable picture of the economic activity: An application to Argentina," Economics Letters, Elsevier, vol. 132(C), pages 129-132.
  359. Emilian DOBRESCU, 2020. "Self-fulfillment degree of economic expectations within an integrated space: The European Union case study," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-32, December.
  360. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española / Review of Public Economics, IEF, vol. 211(4), pages 117-146, December.
  361. Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
  362. repec:bof:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  363. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
  364. Salvatore Greco & Alessio Ishizaka & Menelaos Tasiou & Gianpiero Torrisi, 2019. "On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 61-94, January.
  365. Teresa Leal & Diego Pedregal & Javier Pérez, 2011. "Short-term monitoring of the Spanish government balance," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(1), pages 97-119, March.
  366. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
  367. Koki Kyo & Hideo Noda & Genshiro Kitagawa, 2022. "Co-movement of Cyclical Components Approach to Construct a Coincident Index of Business Cycles," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 101-127, March.
  368. Konstantin A. KHOLODILIN, 2001. "Markov-Switching Common Dynamic Factor Model with Mixed-Frequency Data," LIDAM Discussion Papers IRES 2001020, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  369. Urasawa, Satoshi, 2014. "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 116-134.
  370. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
  371. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
  372. repec:zbw:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  373. Jens Hogrefe, 2008. "Forecasting data revisions of GDP: a mixed frequency approach," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 271-296, August.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.