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Are more data always better for factor analysis?

Citations

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Cited by:

  1. Katja Drechsel & Laurent Maurin, 2011. "Flow of conjunctural information and forecast of euro area economic activity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 336-354, April.
  2. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
  3. Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
  4. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
  5. Jean-Armand Gnagne & Kevin Moran, 2020. "Forecasting Bank Failures in a Data-Rich Environment," Working Papers 20-13, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  6. 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.
  7. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
  8. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511, April.
  9. Dimitris, Korobilis, 2013. "Forecasting with Factor Models: A Bayesian Model Averaging Perspective," MPRA Paper 52724, University Library of Munich, Germany.
  10. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
  11. António Rua & Paulo Esteves, 2012. "Short-term forecasting for the portuguese economy: a methodological overview," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
  12. Bagliano, Fabio C. & Morana, Claudio, 2009. "International macroeconomic dynamics: A factor vector autoregressive approach," Economic Modelling, Elsevier, vol. 26(2), pages 432-444, March.
  13. C. Thubin & T. Ferrière & E. Monnet & M. Marx & V. Oung, 2016. "The PRISME model: can disaggregation on the production side help to forecast GDP?," Working papers 596, Banque de France.
  14. repec:hal:wpspec:info:hdl:2441/9676 is not listed on IDEAS
  15. Sungurtekin Hallam, Bahar, 2022. "Emerging market responses to external shocks: A cross-country analysis," Economic Modelling, Elsevier, vol. 115(C).
  16. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Asymptotics for Panel Models with Common Shocks," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 390-439.
  17. Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
  18. Herman Kamil & José David Pulido & José Luis Torres, 2010. "El IMACO": un índice mensual líder de la actividad económica en Colombia"," Borradores de Economia 7129, Banco de la Republica.
  19. Derek Bunn, Julien Chevallier, Yannick Le Pen, and Benoit Sevi, 2017. "Fundamental and Financial Influences on the Co-movement of Oil and Gas Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
  20. Hilde C. Bjørnland & Julia Zhulanova, 2018. "The Shale Oil Boom and the U.S. Economy: Spillovers and Time-Varying Effects," Working Papers No 8/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  21. Troy D. Matheson, 2006. "Factor Model Forecasts for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 2(2), May.
  22. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  23. 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.
  24. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
  25. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2015. "Dynamic factor models with infinite-dimensional factor spaces: One-sided representations," Journal of Econometrics, Elsevier, vol. 185(2), pages 359-371.
  26. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
  27. Matthieu Darracq Paries, 2018. "Financial frictions and monetary policy conduct," Erudite Ph.D Dissertations, Erudite, number ph18-01 edited by Ferhat Mihoubi.
  28. António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
  29. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Working Papers 334, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  30. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
  31. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
  32. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
  33. Tomohiro Ando & Ruey S. Tsay, 2014. "A Predictive Approach for Selection of Diffusion Index Models," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 68-99, June.
  34. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
  35. Alberto Caruso & Laura Coroneo, 2023. "Does Real‐Time Macroeconomic Information Help to Predict Interest Rates?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(8), pages 2027-2059, December.
  36. 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.
  37. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
  38. Ahn, Seung C. & Perez, M. Fabricio, 2010. "GMM estimation of the number of latent factors: With application to international stock markets," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 783-802, September.
  39. Poncela, Pilar, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
  40. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
  41. Françoise Charpin & Catherine Mathieu & Gian Luigi Mazzi, 2008. "Construction of coincident indicators for the euro area. 5th EUROSTAT Colloquium on Modern Tools For Business Cycle Analysis, Luxembourg, 29th September - 1st October 2008," Post-Print hal-01053253, HAL.
  42. Frank A. G. den Butter & Pieter W. Jansen, 2013. "Beating the random walk: a performance assessment of long-term interest rate forecasts," Applied Financial Economics, Taylor & Francis Journals, vol. 23(9), pages 749-765, May.
  43. László Békési & Lorant Kaszab & Szabolcs Szentmihályi, 2017. "The EAGLE model for Hungary - a global perspective," MNB Working Papers 2017/7, Magyar Nemzeti Bank (Central Bank of Hungary).
  44. Claudia M. Buch & Sandra Eickmeier & Esteban Prieto, 2014. "Macroeconomic Factors and Microlevel Bank Behavior," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 715-751, June.
  45. 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.
  46. Tomohiro Ando & Ruey S. Tsay, 2009. "Model selection for generalized linear models with factor‐augmented predictors," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 207-235, May.
  47. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak Factor Models and the Analysis of High-Dimensional Time Series," Working Papers ECARES 2024-14, ULB -- Universite Libre de Bruxelles.
  48. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  49. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
  50. Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
  51. 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.
  52. repec:dau:papers:123456789/10079 is not listed on IDEAS
  53. Favero, Carlo A. & Sala, Luca & Niu, Linlin, 2007. "Term Structure Forecasting: No-Arbitrage Restrictions vs Large Information Set," CEPR Discussion Papers 6206, C.E.P.R. Discussion Papers.
  54. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
  55. Françoise Charpin, 2009. "Estimation précoce de la croissance," SciencePo Working papers Main hal-03476082, HAL.
  56. 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.
  57. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
  58. Audrone Jakaitiene & Stephane Dees, 2012. "Forecasting the World Economy in the Short Term," The World Economy, Wiley Blackwell, vol. 35(3), pages 331-350, March.
  59. Zhaoxing Gao & Ruey S. Tsay, 2021. "Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data," Papers 2103.14626, arXiv.org.
  60. Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers 2017-14, Economic Research Institute, Bank of Korea.
  61. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
  62. 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.
  63. Marlene Amstad & Ye Huan & Guonan Ma, 2014. "Developing an underlying inflation gauge for China," BIS Working Papers 465, Bank for International Settlements.
  64. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "Commodity prices and BRIC and G3 liquidity: A SFAVEC approach," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 18-33.
  65. Eickmeier, Sandra & Lemke, Wolfgang & Marcellino, Massimiliano, 2011. "Classical time-varying FAVAR models - estimation, forecasting and structural analysis," Discussion Paper Series 1: Economic Studies 2011,04, Deutsche Bundesbank.
  66. Huh, Hyeon-seung & Kim, David & Kim, Won Joong & Park, Cyn-Young, 2015. "A factor-augmented VAR analysis of business cycle synchronization in east Asia and implications for a regional currency union," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 449-468.
  67. Alhassan Abdullah Mohammed, 2011. "A Coincident Indicator of the Gulf Cooperation Council Business Cycle," Review of Middle East Economics and Finance, De Gruyter, vol. 6(3), pages 1-23, February.
  68. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022. "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
  69. Carlomagno, Guillermo, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
  70. Amstad, Marlene & Ye, Huan & Ma, Guonan, 2018. "Developing an underlying inflation gauge for China," BOFIT Discussion Papers 11/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
  71. Bialowolski, Piotr & Kuszewski, Tomasz & Witkowski, Bartosz, 2015. "Bayesian averaging vs. dynamic factor models for forecasting economic aggregates with tendency survey data," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-37.
  72. Magdalena Borys & Roman Horváth & Michal Franta, 2009. "The effects of monetary policy in the Czech Republic: an empirical study," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 36(4), pages 419-443, November.
  73. Simon Reese & Joakim Westerlund, 2018. "Estimation of factor-augmented panel regressions with weakly influential factors," Econometric Reviews, Taylor & Francis Journals, vol. 37(5), pages 401-465, May.
  74. Paccagnini, Alessia, 2019. "Did financial factors matter during the Great Recession?," Economics Letters, Elsevier, vol. 174(C), pages 26-30.
  75. Chevallier, Julien, 2011. "Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model," Economic Modelling, Elsevier, vol. 28(1), pages 557-567.
  76. Kaustubh & Soumya Bhadury & Saurabh Ghosh, 2024. "Reinvigorating Gva Nowcasting In The Postpandemic Period: A Case Study For India," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 27(Spesial I), pages 95-130, Februari.
  77. Pino, Gabriel, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," DES - Working Papers. Statistics and Econometrics. WS ws130807, Universidad Carlos III de Madrid. Departamento de Estadística.
  78. Sarah Drought & Chris McDonald, 2011. "Forecasting house price inflation: a model combination approach," Reserve Bank of New Zealand Discussion Paper Series DP2011/07, Reserve Bank of New Zealand.
  79. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
  80. Raquel Nadal Cesar Gonçalves, 2022. "Nowcasting Brazilian GDP with Electronic Payments Data," Working Papers Series 564, Central Bank of Brazil, Research Department.
  81. Ard H.J. den Reijer, 2005. "Forecasting Dutch GDP using Large Scale Factor Models," DNB Working Papers 028, Netherlands Central Bank, Research Department.
  82. Pilar Poncela & Esther Ruiz, 2016. "Small- Versus Big-Data Factor Extraction in Dynamic Factor Models: An Empirical Assessment," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 401-434, Emerald Group Publishing Limited.
  83. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
  84. Helena Rodríguez, 2014. "Un indicador de la evolución del PIB uruguayo en tiempo real," Documentos de trabajo 2014009, Banco Central del Uruguay.
  85. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
  86. Robert Inklaar & Jan Jacobs & Ward Romp, 2005. "Business Cycle Indexes: Does a Heap of Data Help?," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(3), pages 309-336.
  87. Gupta, Rangan & Kabundi, Alain, 2011. "A large factor model for forecasting macroeconomic variables in South Africa," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1076-1088, October.
  88. Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0070, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  89. Marc Hallin & Roman Liska, 2008. "Dynamic Factors in the Presence of Block Structure," Economics Working Papers ECO2008/22, European University Institute.
  90. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
  91. Neville Francis & Michael T. Owyang & Ozge Savascin, 2017. "An endogenously clustered factor approach to international business cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1261-1276, November.
  92. Olivier Fortin‐Gagnon & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "A large Canadian database for macroeconomic analysis," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(4), pages 1799-1833, November.
  93. Turgut Kisinbay & Chikako Baba, 2011. "Predicting Recessions: A New Approach for Identifying Leading Indicators and Forecast Combinations," IMF Working Papers 2011/235, International Monetary Fund.
  94. Mr. Nicolas Arregui & Mr. Selim A Elekdag & Mr. Gaston Gelos & Romain Lafarguette & Dulani Seneviratne, 2018. "Can Countries Manage Their Financial Conditions Amid Globalization?," IMF Working Papers 2018/015, International Monetary Fund.
  95. Álvaro Aguirre R. & Luis Felipe Céspedes C., 2004. "Uso de Análisis Factorial Dinámico para Proyecciones Macroeconómicas," Working Papers Central Bank of Chile 274, Central Bank of Chile.
  96. 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.
  97. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
  98. 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.
  99. Eickmeier, Sandra & Hofmann, Boris, 2013. "Monetary Policy, Housing Booms, And Financial (Im)Balances," Macroeconomic Dynamics, Cambridge University Press, vol. 17(4), pages 830-860, June.
  100. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
  101. Pérez-Quirós, Gabriel & Diaz, Elena, 2020. "Daily Tracker of Global Economic Activity. A Close-Up of the Covid-19 Pandemic," CEPR Discussion Papers 15451, C.E.P.R. Discussion Papers.
  102. Eichengreen, Barry & Mody, Ashoka & Nedeljkovic, Milan & Sarno, Lucio, 2012. "How the Subprime Crisis went global: Evidence from bank credit default swap spreads," Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1299-1318.
  103. 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.
  104. Konstantins Benkovskis & Andrejs Bessonovs & Martin Feldkircher & Julia Wörz, 2011. "The Transmission of Euro Area Monetary Shocks to the Czech Republic, Poland and Hungary: Evidence from a FAVAR Model," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 8-36.
  105. Fresoli, Diego & Poncela, Pilar & Ruiz, Esther, 2023. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," Economics Letters, Elsevier, vol. 230(C).
  106. Golinelli, Roberto & Parigi, Giuseppe, 2014. "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, vol. 30(4), pages 847-862.
  107. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
  108. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  109. Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017. "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-35, December.
  110. Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024. "What drives the European carbon market? Macroeconomic factors and forecasts," Papers 2402.04828, arXiv.org, revised Feb 2024.
  111. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High‐Dimensional Vector Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1123-1152, October.
  112. repec:dau:papers:123456789/6800 is not listed on IDEAS
  113. 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.
  114. Jiti Gao & Guangming Pan & Yanrong Yang & Bo Zhang, 2019. "Estimation of Cross-Sectional Dependence in Large Panels," Papers 1904.06843, arXiv.org.
  115. Juraj Hucek & Alexander Karsay & Marian Vavra, 2015. "Short-term Forecasting of Real GDP Using Monthly Data," Working and Discussion Papers OP 1/2015, Research Department, National Bank of Slovakia.
  116. Pavel Vidal Alejandro & Lya Paola Sierra Suárez & Johana Sanabria Dominguez & Jaime Andres Collazos Rodríguez, 2015. "Indicador mensual de actividad económica (IMAE) para el Valle del Cauca," Borradores de Economia 13610, Banco de la Republica.
  117. Jun Gao & Sheng Zhu & Niall O’Sullivan & Meadhbh Sherman, 2019. "The Role of Economic Uncertainty in UK Stock Returns," JRFM, MDPI, vol. 12(1), pages 1-16, January.
  118. 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.
  119. 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.
  120. Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
  121. Aßmann, Christian & Boysen-Hogrefe, Jens & Pape, Markus, 2016. "Bayesian analysis of static and dynamic factor models: An ex-post approach towards the rotation problem," Journal of Econometrics, Elsevier, vol. 192(1), pages 190-206.
  122. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
  123. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
  124. Todd E. Clark, 2006. "Disaggregate evidence on the persistence of consumer price inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 563-587, July.
  125. Alberto Caruso & Laura Coroneo, 2019. "Predicting interest rates in real-time," Discussion Papers 19/18, Department of Economics, University of York.
  126. Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  127. 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.
  128. Michael Zhemkov, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, CEPII research center, issue 168, pages 10-24.
  129. Jean-Stéphane Mésonnier & Dalibor Stevanovic, 2012. "Bank Leverage Shocks and the Macroeconomy: a New Look in a Data-Rich Environment," CIRANO Working Papers 2012s-23, CIRANO.
  130. Gloria González‐Rivera & C. Vladimir Rodríguez‐Caballero & Esther Ruiz, 2024. "Expecting the unexpected: Stressed scenarios for economic growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 926-942, August.
  131. 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.
  132. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Generalized Dynamic Factor Model + GARCH Exploiting Multivariate Information for Univariate Prediction," LEM Papers Series 2006/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  133. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
  134. Sung Hoon Choi & Donggyu Kim, 2024. "Matrix-based Prediction Approach for Intraday Instantaneous Volatility Vector," Papers 2403.02591, arXiv.org, revised Dec 2024.
  135. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
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