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Citations for "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models"

by Catherine Doz & Domenico Giannone & Lucrezia Reichlin

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  1. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers.
  2. Giannone, Domenico & Monti, Francesca & Reichlin, Lucrezia, 2015. "Exploiting the monthly data flow in structural forecasting," Staff Reports 751, Federal Reserve Bank of New York.
  3. Borus Jungbacker & Siem Jan Koopman, 2015. "Likelihood‐based dynamic factor analysis for measurement and forecasting," Econometrics Journal, Royal Economic Society, vol. 18(2), pages C1-C21, 06.
  4. Nikolaos Zirogiannis & Yorghos Tripodis, 2013. "A Generalized Dynamic Factor Model for Panel Data: Estimation with a Two-Cycle Conditional Expectation-Maximization Algorithm," Working Papers 2013-1, University of Massachusetts Amherst, Department of Resource Economics.
  5. Antipa, P. & Barhoumi, K. & Brunhes-Lesage, V. & Darné, O., 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Working papers 401, Banque de France.
  6. Zirogiannis, Nikolaos & Tripodis, Yorghos, 2014. "Dynamic Factor Analysis for Short Panels: Estimating Performance Trajectories for Water Utilities," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170592, Agricultural and Applied Economics Association.
  7. Scott Brave & Hesna Genay, 2011. "Federal Reserve policies and financial market conditions during the crisis," Proceedings 1129, Federal Reserve Bank of Chicago.
  8. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
  9. Domenico Giannone & Lucrezia Reichlin & Saverio Simonelli, 2009. "Nowcasting Euro Area Economic Activity in Real-Time: The Role of Confidence Indicator," Working Papers ECARES 2009_021, ULB -- Universite Libre de Bruxelles.
  10. Fornaro, Paolo & Luomaranta, Henri, 2015. "Small Versus Large Firms Employment Patterns in Finland: a Comparison," MPRA Paper 66979, University Library of Munich, Germany.
  11. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," NBER Working Papers 15657, National Bureau of Economic Research, Inc.
  12. 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).
  13. Matteo Ciccarelli & Benoît Mojon, 2005. "Global Inflation," Working Papers Central Bank of Chile 357, Central Bank of Chile.
  14. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," MPRA Paper 39452, University Library of Munich, Germany.
  15. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Dynamic Factor GARCH: Multivariate Volatility Forecast for a Large Number of Series," LEM Papers Series 2006/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  16. Luciana Juvenal & Ivan Petrella, 2011. "Speculation in the oil market," Working Papers 2011-027, Federal Reserve Bank of St. Louis.
  17. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
  18. Antonello D'Agostino & Paolo Surico, 2009. "Does Global Liquidity Help to Forecast U.S. Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 479-489, 03.
  19. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 2009. "Smooth Dynamic Factor Analysis with an Application to the U.S. Term Structure of Interest Rates," CREATES Research Papers 2009-39, Department of Economics and Business Economics, Aarhus University.
  20. M. Pilar Muñoz & Cristina Corchero & F.-Javier Heredia, 2013. "Improving Electricity Market Price Forecasting with Factor Models for the Optimal Generation Bid," International Statistical Review, International Statistical Institute, vol. 81(2), pages 289-306, 08.
  21. Bai, Jushan & Li, Kunpeng, 2012. "Maximum likelihood estimation and inference for approximate factor models of high dimension," MPRA Paper 42099, University Library of Munich, Germany, revised 19 Oct 2012.
  22. Shinya Tanaka & Eiji Kurozumi, 2010. "Investigating Finite Sample Properties of Estimators for Approximate Factor Models When N Is Small," Global COE Hi-Stat Discussion Paper Series gd10-156, Institute of Economic Research, Hitotsubashi University.
  23. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2013. "Do euro area countries respond asymmetrically to the common monetary policy?," Temi di discussione (Economic working papers) 923, Bank of Italy, Economic Research and International Relations Area.
  24. Cheng, Xu & Hansen, Bruce E., 2015. "Forecasting with factor-augmented regression: A frequentist model averaging approach," Journal of Econometrics, Elsevier, vol. 186(2), pages 280-293.
  25. Banbura, Marta & Rünstler, Gerhard, 2007. "A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 0751, European Central Bank.
  26. Branimir Jovanovic & Magdalena Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," Working Papers 2010-02, National Bank of the Republic of Macedonia, revised Aug 2010.
  27. Marco Jacopo Lombardi & Feng Zhu, 2014. "A shadow policy rate to calibrate US monetary policy at the zero lower bound," BIS Working Papers 452, Bank for International Settlements.
  28. Ricardo Reis & Mark W. Watson, 2007. "Relative Goods' Prices, Pure Inflation, and the Phillips Correlation," NBER Working Papers 13615, National Bureau of Economic Research, Inc.
  29. Brave, Scott & Butters, R. Andrew, 2014. "Nowcasting Using the Chicago Fed National Activity Index," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q I, pages 19-37.
  30. Scott Brave & R. Andrew Butters, 2010. "Gathering insights on the forest from the trees: a new metric for financial conditions," Working Paper Series WP-2010-07, Federal Reserve Bank of Chicago.
  31. Arias, Maria A. & Gascon, Charles S. & Rapach, David E., 2014. "Metro Business Cycles," Working Papers 2014-46, Federal Reserve Bank of St. Louis, revised 09 May 2016.
  32. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.
  33. Françoise Charpin, 2009. "Estimation précoce de la croissance : de la régression LARS au modèle à facteurs," Sciences Po publications info:hdl:2441/5l6uh8ogmqi, Sciences Po.
  34. 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.
  35. Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2015. "A spectral EM algorithm for dynamic factor models," CEPR Discussion Papers 10417, C.E.P.R. Discussion Papers.
  36. Beyer, Robert C. M. & Smets, Frank, 2015. "Labour market adjustments in Europe and the US: How different?," Working Paper Series 1767, European Central Bank.
  37. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
  38. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
  39. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
  40. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?," Ifo Working Paper Series Ifo Working Paper No. 171, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  41. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 0589, European Central Bank.
  42. Mirko Wiederholt & Emanuel Moench & Bartosz Maćkowiak, 2009. "Sectoral Price Data and Models of Price Setting," 2009 Meeting Papers 666, Society for Economic Dynamics.
  43. Françoise Charpin, 2011. "Réévaluation des modèles d’estimation précoce de la croissance," Sciences Po publications info:hdl:2441/eu4vqp9ompq, Sciences Po.
  44. Marc Hallin & Marco Lippi, 2013. "Factor Models in High-Dimensional Time Series: A Time-Domain Approach," Working Papers ECARES ECARES 2013-15, ULB -- Universite Libre de Bruxelles.
  45. 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.
  46. Jakob Guldbæk Mikkelsen & Eric Hillebrand & Giovanni Urga, 2015. "Maximum Likelihood Estimation of Time-Varying Loadings in High-Dimensional Factor Models," CREATES Research Papers 2015-61, Department of Economics and Business Economics, Aarhus University.
  47. Mattéo Luciani & Lorenzo Ricci, 2013. "Nowcasting Norway," Working Papers ECARES ECARES 2013-10, ULB -- Universite Libre de Bruxelles.
  48. Drew Creal & Bernd Schwaab & Siem Jan Koopman & André 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.
  49. 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.
  50. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2010. "Nowcasting," Working Paper Series 1275, European Central Bank.
  51. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
  52. Modugno, Michele & Nikolaou, Kleopatra, 2009. "The forecasting power of internal yield curve linkages," Working Paper Series 1044, European Central Bank.
  53. Marcellino, Massimiliano & Schumacher, Christian, 2008. "Factor-MIDAS for now- and forecasting with ragged-edge data: A model comparison for German GDP," CEPR Discussion Papers 6708, C.E.P.R. Discussion Papers.
  54. Lasse Bork, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," CREATES Research Papers 2009-11, Department of Economics and Business Economics, Aarhus University.
  55. Gobillon, Laurent & Magnac, Thierry, 2014. "Regional Policy Evaluation: Interactive Fixed Effects and Synthetic Controls," CEPR Discussion Papers 10253, C.E.P.R. Discussion Papers.
  56. Hideaki Hirata & M. Ayhan Kose & Chris Otrok, . "Regionalization vs. Globalization," Working Paper 164456, Harvard University OpenScholar.
  57. Chadwick, Meltem Gülenay & Fazilet, Fatih & Tekatli, Necati, 2015. "Understanding the common dynamics of the emerging market currencies," Economic Modelling, Elsevier, vol. 49(C), pages 120-136.
  58. Porshakov, Alexey & Deryugina, Elena & Ponomarenko, Alexey & Sinyakov, Andrey, 2015. "Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model," BOFIT Discussion Papers 19/2015, Bank of Finland, Institute for Economies in Transition.
  59. B. Jungbacker & S.J. Koopman & M. van der Wel, 2009. "Dynamic Factor Analysis in The Presence of Missing Data," Tinbergen Institute Discussion Papers 09-010/4, Tinbergen Institute, revised 11 Mar 2011.
  60. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  61. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version," PIER Working Paper Archive 13-061, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Sep 2013.
  62. Angelini, Elena & Camba-Méndez, Gonzalo & Giannone, Domenico & Rünstler, Gerhard & Reichlin, Lucrezia, 2008. "Short-term forecasts of euro area GDP growth," Working Paper Series 0949, European Central Bank.
  63. Matteo Barigozzi & Alessio Moneta, 2016. "Identifying the Independent Sources of Consumption Variation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 420-449, 03.
  64. Gijsbert Suren & Guilherme Moura, 2012. "Heteroskedastic Dynamic Factor Models: A Monte Carlo Study," Economics Bulletin, AccessEcon, vol. 32(4), pages 2884-2898.
  65. Li, Kunpeng & Lu, Lina, 2014. "Efficient estimation of heterogeneous coefficients in panel data models with common shock," MPRA Paper 59312, University Library of Munich, Germany.
  66. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
  67. Jean Boivin & Marc P. Giannoni & Benoît Mojon, 2008. "How Has the Euro Changed the Monetary Transmission?," NBER Working Papers 14190, National Bureau of Economic Research, Inc.
  68. 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.
  69. 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.
  70. Steffen Henzel & Malte Rengel, 2013. "Dimensions of macroeconomic uncertainty: A common factor analysis," Ifo Working Paper Series Ifo Working Paper No. 167, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  71. 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.
  72. Carlos Pérez Montes, 2013. "Estimation of Regulatory Credit Risk Models," Working Papers 1305, Banco de España;Working Papers Homepage.
  73. Karim Barhoumi & Laurent Ferrara, 2015. "A World Trade Leading Index (WTLI)," IMF Working Papers 15/20, International Monetary Fund.
  74. Del Negro, Marco & Otrok, Christopher, 2007. "99 Luftballons: Monetary policy and the house price boom across U.S. states," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1962-1985, October.
  75. Modugno, Michele, 2013. "Now-casting inflation using high frequency data," International Journal of Forecasting, Elsevier, vol. 29(4), pages 664-675.
  76. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
  77. repec:bof:bofitp:urn:nbn:fi:bof-201506091268 is not listed on IDEAS
  78. Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2015. "Fast ML estimation of dynamic bifactor models: an application to European inflation," CEPR Discussion Papers 10461, C.E.P.R. Discussion Papers.
  79. Laurent Ferrara & Dominique Guégan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 186-199.
  80. Michele Lenza & Thomas Warmedinger, 2011. "A Factor Model for Euro-area Short-term Inflation Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 231(1), pages 50-62, February.
  81. Beyer, Robert C.M. & Stemmer, Michael A., 2016. "Polarization or convergence? An analysis of regional unemployment disparities in Europe over time," Economic Modelling, Elsevier, vol. 55(C), pages 373-381.
  82. Kelly, Bryan & Pruitt, Seth, 2015. "The three-pass regression filter: A new approach to forecasting using many predictors," Journal of Econometrics, Elsevier, vol. 186(2), pages 294-316.
  83. Bai, Jushan & Wang, Peng, 2012. "Identification and estimation of dynamic factor models," MPRA Paper 38434, University Library of Munich, Germany.
  84. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2007. "A Review of Nonfundamentalness and Identification in Structural VAR Models," LEM Papers Series 2007/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  85. Gabriele Fiorentini & Enrique Sentana, 2013. "Dynamic Specification Tests For Dynamic Factor Models," Working Papers wp2013_1306, CEMFI.
  86. Rodríguez, Julio & Poncela, Pilar & Fuentes, Julieta, 2012. "Sparse partial least squares in time series for macroeconomic forecasting," DES - Working Papers. Statistics and Econometrics. WS ws122216, Universidad Carlos III de Madrid. Departamento de Estadística.
  87. Dimitra Lamprou, 2015. "Nowcasting GDP in Greece: A Note on Forecasting Improvements from the Use of Bridge Models," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 13(1), pages 85-100.
  88. Lasse Bork & Hans Dewachter & Romain Houssa, 2009. "Identification of Macroeconomic Factors in Large Panels," CREATES Research Papers 2009-43, Department of Economics and Business Economics, Aarhus University.
  89. Elena Andreou & Andros Kourtellos, 2015. "The State and the Future of Cyprus Macroeconomic Forecasting," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 9(1), pages 73-90, June.
  90. Matteo Luciani, 2011. "Forecasting with Approximate Dynamic Factor Models: the Role of Non-Pervasive Shocks," Working Papers ECARES ECARES 2011‐022, ULB -- Universite Libre de Bruxelles.
  91. Jean Boivin & Marc Giannoni & Dalibor Stevanovic, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York.
  92. In Choi & Jorg Breitung, 2011. "Factor models," Working Papers 1121, Research Institute for Market Economy, Sogang University, revised Dec 2011.
    • Jörg Breitung & In Choi, 2013. "Factor models," Chapters, in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 11, pages 249-265 Edward Elgar Publishing.
  93. Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute, revised 20 Mar 2014.
  94. Liu, Philip & Matheson, Troy & Romeu, Rafael, 2012. "Real-time forecasts of economic activity for Latin American economies," Economic Modelling, Elsevier, vol. 29(4), pages 1090-1098.
  95. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
  96. Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.
  97. Emilio Espino & Julian Kozlowski & Juan M. Sánchez, 2013. "Regionalization vs. globalization," Working Papers 2013-002, Federal Reserve Bank of St. Louis.
  98. Scott Brave & R. Andrew Butters, 2012. "Diagnosing the Financial System: Financial Conditions and Financial Stress," International Journal of Central Banking, International Journal of Central Banking, vol. 8(2), pages 191-239, June.
  99. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 0000. "Dynamic Factor Models with Smooth Loadings for Analyzing the Term Structure of Interest Rates," Tinbergen Institute Discussion Papers 09-041/4, Tinbergen Institute, revised 17 Sep 2010.
  100. Daniel Kaufmann & Rolf Scheufele, 2015. "Business Tendency Surveys and Macroeconomic Fluctuations," KOF Working papers 15-378, KOF Swiss Economic Institute, ETH Zurich.
  101. Pegoraro, F. & Siegel, A. F. & Tiozzo Pezzoli, L., 2014. "Specification Analysis of International Treasury Yield Curve Factors," Working papers 490, Banque de France.
  102. Ruiz, Esther & Poncela, Pilar, 2015. "Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment," DES - Working Papers. Statistics and Econometrics. WS ws1502, Universidad Carlos III de Madrid. Departamento de Estadística.
  103. Bai, Jushan & Li, Kunpeng & Lu, Lina, 2014. "Estimation and inference of FAVAR models," MPRA Paper 60960, University Library of Munich, Germany.
  104. Hwee Kwan Chow & Keen Meng Choy, 2008. "Forecasting Business Cycles in a Small Open Economy: A Dynamic Factor Model for Singapore," Economic Growth Centre Working Paper Series 0802, Nanyang Technological University, School of Humanities and Social Sciences, Economic Growth Centre.
  105. Branimir, Jovanovic & Magdalena, Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," MPRA Paper 43162, University Library of Munich, Germany.
  106. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
  107. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
  108. Marco Del Negro & Christopher Otrok, 2008. "Dynamic factor models with time-varying parameters: measuring changes in international business cycles," Staff Reports 326, Federal Reserve Bank of New York.
  109. Gábor Pellényi, 2012. "The Sectoral Effects of Monetary Policy in Hungary: A Structural Factor Analysis," MNB Working Papers 2012/1, Magyar Nemzeti Bank (Central Bank of Hungary).
  110. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
  111. Scotti, Chiara, 2013. "Surprise and uncertainty indexes: real-time aggregation of real-activity macro surprises," International Finance Discussion Papers 1093, Board of Governors of the Federal Reserve System (U.S.), revised 20 May 2016.
  112. Gregor Bäurle, 2008. "Priors from DSGE Models for Dynamic Factor Analysis," Diskussionsschriften dp0803, Universitaet Bern, Departement Volkswirtschaft.
  113. Muriel Nguiffo-Boyom, 2014. "2007-2013: This is what the indicator told us ? Evaluating the performance of real-time nowcasts from a dynamic factor model," BCL working papers 88, Central Bank of Luxembourg.
  114. 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.
  115. Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel
    [The sectoral effects of monetary policy in Hungary: a structural factor]
    ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
  116. 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.
  117. Jean Boivin & Marc P. Giannoni & Benoît Mojon, 2009. "How Has the Euro Changed the Monetary Transmission Mechanism?," NBER Chapters, in: NBER Macroeconomics Annual 2008, Volume 23, pages 77-125 National Bureau of Economic Research, Inc.
  118. Robert Beyer & Michael Stemmer, 2015. "From progress to nightmare - European regional unemployment over time," DNB Working Papers 458, Netherlands Central Bank, Research Department.
  119. 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.).
  120. Jan J. J. Groen & George Kapetanios, 2009. "Model selection criteria for factor-augmented regressions," Staff Reports 363, Federal Reserve Bank of New York.
  121. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
  122. Huang, Huichou & MacDonald, Ronald & Zhao, Yang, 2012. "Global Currency Misalignments, Crash Sensitivity, and Downside Insurance Costs," MPRA Paper 53745, University Library of Munich, Germany, revised 18 Nov 2013.
  123. Maćkowiak, Bartosz & Moench, Emanuel & Wiederholt, Mirko, 2009. "Sectoral price data and models of price setting," Journal of Monetary Economics, Elsevier, vol. 56(S), pages S78-S99.
  124. repec:hal:wpaper:halshs-00849071 is not listed on IDEAS
  125. 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.
  126. Higgins, Patrick C., 2014. "GDPNow: A Model for GDP "Nowcasting"," FRB Atlanta Working Paper 2014-7, Federal Reserve Bank of Atlanta.
  127. Bai, Jushan & Li, Kunpeng, 2010. "Theory and methods of panel data models with interactive effects," MPRA Paper 43441, University Library of Munich, Germany, revised Dec 2012.
  128. Bai, Jushan & Liao, Yuan, 2016. "Efficient estimation of approximate factor models via penalized maximum likelihood," Journal of Econometrics, Elsevier, vol. 191(1), pages 1-18.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.