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

by Roberto S. Mariano & Yasutomo Murasawa

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  1. Michael Graff, 2005. "Internationale Konjunkturverbunde," KOF Working papers 05-108, KOF Swiss Economic Institute, ETH Zurich.
  2. Arias, Maria A. & Gascon, Charles S. & Rapach, David E., 2016. "Metro business cycles," Journal of Urban Economics, Elsevier, vol. 94(C), pages 90-108.
  3. Boriss Siliverstovs, 2012. "Are GDP Revisions Predictable? Evidence for Switzerland," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 58(4), pages 299-326.
  4. 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 - Italian Review of Economics, Demography and Statistics, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 181-197, April-Jun.
  5. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and forecasting economic growth in the euro area using principal components," DNB Working Papers 415, Netherlands Central Bank, Research Department.
  6. Michele Modugno & Lucrezia Reichlin & Domenico Giannone & Marta Banbura, 2012. "Nowcasting with Daily Data," 2012 Meeting Papers 555, Society for Economic Dynamics.
  7. D'Agostino, Antonello & Giannone, Domenico & Lenza, Michele & Modugno, Michele, 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.).
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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, Kiel Institute for the World Economy (IfW), vol. 10, pages 1-20.
  13. 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.
  14. 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.
  15. 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, Research Centre.
  16. Klaus Abberger & Boriss Siliverstovs & Jan-Egbert Sturm & Michael Graff, 2014. "The KOF Economic Barometer, Version 2014: A Composite Leading Indicator for the Swiss Business Cycle," KOF Working papers 14-353, KOF Swiss Economic Institute, ETH Zurich.
  17. 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.
  18. 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.
  19. 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, Research Centre.
  20. Brave, Scott & Butters, R. Andrew & Justiniano, Alejandro, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
  21. 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.
  22. 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.
  23. Sieds, 2013. "Complete Volume LXVII n.2 2013," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - Italian Review of Economics, Demography and Statistics, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 1-197, April-Jun.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.
  32. 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.
  33. 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.
  34. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  35. 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.
  36. 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.
  37. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, Elsevier.
  38. Issler, João Victor & Notini, Hilton Hostalacio, 2016. "Estimating Brazilian Monthly GDP: a State-Space Approach," Revista Brasileira de Economia, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 70(1), March.
  39. 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.
  40. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland, Institute for Economies in Transition.
  41. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
  42. 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.
  43. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Economics Working Papers ECO2013/02, European University Institute.
  44. 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.
  45. Marczak, Martyna & Gómez, Victor, 2013. "Monthly US business cycle indicators: A new multivariate approach based on a band-pass filter," FZID Discussion Papers 64-2013, University of Hohenheim, Center for Research on Innovation and Services (FZID).
  46. 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.
  47. Marcelle Chauvet & James D. Hamilton, 2005. "Dating Business Cycle Turning Points," NBER Working Papers 11422, National Bureau of Economic Research, Inc.
  48. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CREATES Research Papers 2015-12, Department of Economics and Business Economics, Aarhus University.
  49. Leif Anders Thorsrud, 2016. "Words are the new numbers: A newsy coincident index of business cycles," Working Paper 2016/21, Norges Bank.
  50. Maximo Camacho & Gabriel Perez-Quiros, 2009. "Ñ-STING: España Short Term INdicator of Growth," Working Papers 0912, Banco de España;Working Papers Homepage.
  51. 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.
  52. Camacho, Maximo & Martinez-Martin, Jaime, 2015. "Monitoring the world business cycle," Economic Modelling, Elsevier, vol. 51(C), pages 617-625.
  53. 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.
  54. 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.
  55. 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.
  56. 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.
  57. 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.
  58. 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.
  59. 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.
  60. Troy D Matheson, 2013. "The Global Financial Crisis; An Anatomy of Global Growth," IMF Working Papers 13/76, .
  61. Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese, Giovanni, 2015. "Nowcasting Indonesia," Finance and Economics Discussion Series 2015-100, Board of Governors of the Federal Reserve System (U.S.).
  62. 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.
  63. 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.
  64. Anthony S. Tay, 2007. "Financial Variables as Predictors of Real Output Growth," Development Economics Working Papers 22482, East Asian Bureau of Economic Research.
  65. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
  66. 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.
  67. 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.
  68. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
  69. repec:fgv:epgrbe:v:67:n:1:a:4 is not listed on IDEAS
  70. 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, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 67(1), March.
  71. Diego J. Pedregal & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "A toolkit to strengthen government budget surveillance," Working Papers 1416, Banco de España;Working Papers Homepage.
  72. 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.
  73. 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.
  74. Byeongchan Seong & Sung K. Ahn & Peter Zadrozny, 2007. "Cointegration Analysis with Mixed-Frequency Data," CESifo Working Paper Series 1939, CESifo Group Munich.
  75. Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo Group Munich.
  76. 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.
  77. 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.
  78. 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.
  79. 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.
  80. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
  81. Konstantin A., KHOLODILIN & Wension Vincent, YAO, 2004. "Business Cycle Turning Points : Mixed-Frequency Data with Structural Breaks," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2004024, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  82. 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.
  83. 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.
  84. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, Elsevier.
  85. 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.
  86. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
  87. 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.
  88. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
  89. 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.
  90. David de Antonio Liedo, 2014. "Nowcasting Belgium," Working Paper Research 256, National Bank of Belgium.
  91. 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.
  92. 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.
  93. 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, Research Centre.
  94. Konstantin A. KHOLODILIN, 2002. "Unobserved Leading and Coincident Common Factors in the Post-War U.S. Business Cycle," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2002008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  95. 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.
  96. Modugno, Michele, 2013. "Now-casting inflation using high frequency data," International Journal of Forecasting, Elsevier, vol. 29(4), pages 664-675.
  97. Qian, Hang, 2012. "A Flexible State Space Model and its Applications," MPRA Paper 38455, University Library of Munich, Germany.
  98. Gabriel Pérez-Quiros & Maximo Camacho & Pilar Poncela, 2010. "Green Shoots? Where, when and how?," Working Papers 2010-04, FEDEA.
  99. Alvarez, Rocio & Camacho, Maximo & Pérez-Quirós, Gabriel, 2012. "Finite sample performance of small versus large scale dynamic factor models," CEPR Discussion Papers 8867, C.E.P.R. Discussion Papers.
  100. 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.
  101. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2015. "Markov-switching mixed-frequency VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 692-711.
  102. 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.
  103. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2014. "Tracking the Slowdown in Long-Run GDP Growth," Discussion Papers 1604, Centre for Macroeconomics (CFM), revised Jan 2016.
  104. Kevin Clinton & Marianne Johnson & Jaromir Benes & Douglas Laxton & Troy D Matheson, 2010. "Structural Models in Real Time," IMF Working Papers 10/56, .
  105. repec:crs:ecosta:es395-396b is not listed on IDEAS
  106. 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.
  107. 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.
  108. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank, Research Centre.
  109. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
  110. 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.
  111. Germán López Espinosa, 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).
  112. 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.
  113. 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.
  114. Conefrey, Thomas & Liebermann, Joelle, 2013. "A Monthly Business Cycle Indicator for Ireland," Economic Letters 03/EL/13, Central Bank of Ireland.
  115. 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.
  116. 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 Economía Aplicada, Estudios de Economía Aplicada, vol. 33, pages 451-462, Mayo.
  117. Rocío Elizondo, 2012. "Monthly GDP estimates based on the IGAE," Working Papers 2012-11, Banco de México.
  118. 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.
  119. repec:ebl:ecbull:v:3:y:2002:i:20:p:1-20 is not listed on IDEAS
  120. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
  121. Camacho, Maximo & Pérez-Quirós, Gabriel & Poncela, Pilar, 2012. "Markov-switching dynamic factor models in real time," CEPR Discussion Papers 8866, C.E.P.R. Discussion Papers.
  122. Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
  123. 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.
  124. 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.
  125. Boriss Siliverstovs, 2015. "Short-term forecasting with mixed-frequency data: A MIDASSO approach," KOF Working papers 15-375, KOF Swiss Economic Institute, ETH Zurich.
  126. 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.
  127. Tony Chernis & Rodrigo Sekkel, 2017. "A Dynamic Factor Model for Nowcasting Canadian GDP Growth," Staff Working Papers 17-2, Bank of Canada.
  128. Klaus Wohlrabe, 2009. "Makroökonomische Prognosen mit gemischten Frequenzen," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
  129. 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.
  130. 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.
  131. João Valle e Azevedo & Siem Jan Koopman & António Rua, 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.
  132. 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.
  133. Éric Dubois, 2006. "Présentation générale," Économie et Prévision, Programme National Persée, vol. 172(1), pages 1-9.
  134. Beate Schirwitz, 2009. "A comprehensive German business cycle chronology," Empirical Economics, Springer, vol. 37(2), pages 287-301, October.
  135. repec:ebl:ecbull:v:3:y:2002:i:5:p:1-15 is not listed on IDEAS
  136. Neville Francis, 2012. "The Low-Frequency Impact of Daily Monetary Policy Shock," 2012 Meeting Papers 198, Society for Economic Dynamics.
  137. 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.
  138. 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.
  139. 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.
  140. 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.
  141. 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.
  142. William Barnett & Marcelle Chauvetz & Danilo Leiva-Leonx, "undated". "Real-Time Nowcasting Nominal GDP Under Structural Break," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201313, University of Kansas, Department of Economics.
  143. Tatjana Dahlhaus & Justin-Damien Guénette & Garima Vasishtha, 2015. "Nowcasting BRIC+M in Real Time," Staff Working Papers 15-38, Bank of Canada.
  144. Claudia Foroni & Massimiliano Marcellino, 2014. "Mixed frequency structural VARs," Working Paper 2014/01, Norges Bank.
  145. 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.
  146. 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.
  147. Marcellino, Massimiliano & Porqueddu, Mario & Venditti, Fabrizio, 2013. "Short-term GDP forecasting with a mixed frequency dynamic factor model with stochastic volatility," CEPR Discussion Papers 9334, C.E.P.R. Discussion Papers.
  148. 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.
  149. Paredes-Lodeiro, Joan & Pérez, Javier J & Pérez-Quirós, Gabriel, 2015. "Fiscal targets. A guide to forecasters?," CEPR Discussion Papers 10553, C.E.P.R. Discussion Papers.
  150. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
  151. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.
  152. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, EconWPA.
  153. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
  154. Issler, João Victor & Notini, Hilton Hostalácio & Rodrigues, Claudia Oliveira da Fontoura, 2009. "Um indicador coincidente e antecedente da atividade econômica brasileira," Economics Working Papers (Ensaios Economicos da EPGE) 695, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  155. Jennifer Castle & David Hendry, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
  156. Davor Kunovac & Borna Špalat, 2014. "Nowcasting GDP Using Available Monthly Indicators," Working Papers 39, The Croatian National Bank, Croatia.
  157. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
  158. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
  159. 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.
  160. Marcos Dal Bianco & Jaime Martinez-Martín & Maximo Camacho, 2013. "Short-Run Forecasting of Argentine GDP Growth," Working Papers 1314, BBVA Bank, Economic Research Department.
  161. 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.
  162. Camacho, Maximo, 2013. "Mixed-frequency VAR models with Markov-switching dynamics," Economics Letters, Elsevier, vol. 121(3), pages 369-373.
  163. Daniela Bragoli & Jack Fosten, 2016. "Nowcasting Indian GDP," University of East Anglia School of Economics Working Paper Series 2016-06, School of Economics, University of East Anglia, Norwich, UK..
  164. 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.
  165. Qian, Hang, 2016. "A computationally efficient method for vector autoregression with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 433-437.
  166. Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
  167. 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.
  168. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española, IEF, vol. 211(4), pages 117-146, December.
  169. repec:bof:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  170. 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, Research Centre.
  171. 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.
  172. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
  173. Konstantin A. KHOLODILIN, 2001. "Markov-Switching Common Dynamic Factor Model with Mixed-Frequency Data," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2001020, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  174. 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.
  175. 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.
  176. 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.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.