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Dynamic Factor Models

Citations

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Cited by:

  1. Juan José Echavarría & Andrés González, 2012. "Choques internacionales reales y financieros y su impacto sobre la economía colombiana," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 30(69), pages 14-66, December.
  2. Bates, Brandon J. & Plagborg-Møller, Mikkel & Stock, James H. & Watson, Mark W., 2013. "Consistent factor estimation in dynamic factor models with structural instability," Journal of Econometrics, Elsevier, vol. 177(2), pages 289-304.
  3. Arias, Maria A. & Gascon, Charles S. & Rapach, David E., 2016. "Metro business cycles," Journal of Urban Economics, Elsevier, vol. 94(C), pages 90-108.
  4. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
  5. Ryadh M. Alkhareif & William A. Barnett, 2015. "Core Inflation Indicators for Saudi Arabia," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 62(3), pages 257-266.
  6. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
  7. Poncela, Pilar, 2021. "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS 32210, Universidad Carlos III de Madrid. Departamento de Estadística.
  8. Ponomareva, Natalia & Sheen, Jeffrey, 2013. "Australian labor market dynamics across the ages," Economic Modelling, Elsevier, vol. 35(C), pages 453-463.
  9. Elena Deryugina & Alexey Ponomarenko & Andrey Sinyakov & Constantine Sorokin, 2018. "Evaluating underlying inflation measures for Russia," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 11(2), pages 124-145, May.
  10. Milan Christian de Wet, 2021. "Modelling the Australasian Financial Cycle: A Markov-Regime Switching Approach," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 14(1), pages 69-79, June.
  11. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe & Rudebusch, Glenn D. & Zhang, Boyuan, 2021. "Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1509-1519.
  12. Antonello D’Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2016. "Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 569-594, Emerald Group Publishing Limited.
  13. María Alejandra Hernández-Montes & Ramón Hernández-Ortega & Jonathan Alexander Muñoz-Martínez, 2022. "Aporte de las expectativas de empresarios al pronóstico de las variables macroeconómicas," Borradores de Economia 1202, Banco de la Republica de Colombia.
  14. Bai, Jushan, 2024. "Likelihood approach to dynamic panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 240(1).
  15. Laurent Callot & Johannes Tang Kristensen, 2016. "Regularized Estimation of Structural Instability in Factor Models: The US Macroeconomy and the Great Moderation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 437-479, Emerald Group Publishing Limited.
  16. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2015. "Robust approaches to forecasting," International Journal of Forecasting, Elsevier, vol. 31(1), pages 99-112.
  17. 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.
  18. 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.
  19. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
  20. Amat Adarov, 2022. "Financial cycles around the world," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3163-3201, July.
  21. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2023. "Synchronization patterns in the European Union," Applied Economics, Taylor & Francis Journals, vol. 55(18), pages 2038-2059, April.
  22. S. J. Koopman & G. Mesters, 2017. "Empirical Bayes Methods for Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 486-498, July.
  23. Seshadri Tirunillai & Gerard J. Tellis, 2017. "Does Offline TV Advertising Affect Online Chatter? Quasi-Experimental Analysis Using Synthetic Control," Marketing Science, INFORMS, vol. 36(6), pages 862-878, November.
  24. 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.
  25. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
  26. Jos Jansen & Jasper de Winter, 2016. "Improving model-based near-term GDP forecasts by subjective forecasts: A real-time exercise for the G7 countries," DNB Working Papers 507, Netherlands Central Bank, Research Department.
  27. Jonas Krampe & Efstathios Paparoditis, 2021. "Sparsity concepts and estimation procedures for high‐dimensional vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 554-579, September.
  28. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
  29. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
  30. Molero-González, L. & Trinidad-Segovia, J.E. & Sánchez-Granero, M.A. & García-Medina, A., 2023. "Market Beta is not dead: An approach from Random Matrix Theory," Finance Research Letters, Elsevier, vol. 55(PA).
  31. Hui ‘Fox’ Ling & Christian Franzen, 2017. "Online learning of time-varying stochastic factor structure by variational sequential Bayesian factor analysis," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1277-1304, August.
  32. 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.
  33. Kristensen Johannes Tang, 2014. "Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 309-338, May.
  34. W. Hölzl & S. Kaniovski & Y. Kaniovski, 2019. "Exploring the dynamics of business survey data using Markov models," Computational Management Science, Springer, vol. 16(4), pages 621-649, October.
  35. Hoga, Yannick, 2017. "Monitoring multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 105-121.
  36. Marco Centoni & Gianluca Cubadda, 2015. "Common Feature Analysis of Economic Time Series: An Overview and Recent Developments," CEIS Research Paper 355, Tor Vergata University, CEIS, revised 05 Oct 2015.
  37. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
  38. 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.
  39. Helena Rodríguez, 2014. "Un indicador de la evolución del PIB uruguayo en tiempo real," Documentos de trabajo 2014009, Banco Central del Uruguay.
  40. Yifan Shen & Tilak Abeysinghe, 2021. "International Transmission Mechanism And World Business Cycle," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 510-531, January.
  41. Değerli, Ahmet & Fendoğlu, Salih, 2015. "Reserve option mechanism as a stabilizing policy tool: Evidence from exchange rate expectations," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 166-179.
  42. 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.
  43. Kuhelika De & Ryan A. Compton & Daniel C. Giedeman & Gary A. Hoover, 2021. "Macroeconomic shocks and racial labor market differences," Southern Economic Journal, John Wiley & Sons, vol. 88(2), pages 680-704, October.
  44. 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.
  45. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
  46. Asger Lunde & Miha Torkar, 2020. "Including news data in forecasting macro economic performance of China," Computational Management Science, Springer, vol. 17(4), pages 585-611, December.
  47. Francesco Trebbi & Kairong Xiao, 2015. "Regulation and Market Liquidity," NBER Working Papers 21739, National Bureau of Economic Research, Inc.
  48. Alkhareif, Ryadh, 2016. "Are there significant premiums in the Saudi stock market?," Finance Research Letters, Elsevier, vol. 18(C), pages 108-115.
  49. Franky Juliano Galeano-Ramírez & Nicolás Martínez-Cortés & Carlos D. Rojas-Martínez, 2021. "Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches," Borradores de Economia 1168, Banco de la Republica de Colombia.
  50. 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.
  51. repec:hal:spmain:info:hdl:2441/5q8fnecj1u87ka099dc571bhi2 is not listed on IDEAS
  52. Daniel Aaronson & Scott A. Brave & Michael Fogarty & Ezra Karger & Spencer D. Krane, 2021. "Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade," Working Paper Series WP-2021-05, Federal Reserve Bank of Chicago, revised 18 Jun 2021.
  53. 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.
  54. Skripnikov, A. & Michailidis, G., 2019. "Joint estimation of multiple network Granger causal models," Econometrics and Statistics, Elsevier, vol. 10(C), pages 120-133.
  55. 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.
  56. Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2022. "Nowcasting the Portuguese GDP with Monthly Data," Papers 2206.06823, arXiv.org.
  57. Boriss Siliverstovs & Daniel Wochner, 2019. "Recessions as Breadwinner for Forecasters State-Dependent Evaluation of Predictive Ability: Evidence from Big Macroeconomic US Data," KOF Working papers 19-463, KOF Swiss Economic Institute, ETH Zurich.
  58. repec:hum:wpaper:sfb649dp2017-026 is not listed on IDEAS
  59. 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.
  60. Gelfer, Sacha, 2021. "Evaluating the forecasting power of an open-economy DSGE model when estimated in a data-Rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
  61. Komunjer, Ivana & Zhu, Yinchu, 2020. "Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models," Journal of Econometrics, Elsevier, vol. 218(2), pages 561-586.
  62. Ryadh M. Alkhareif & William A. Barnett, 2020. "Nowcasting Real Gdp For Saudi Arabia," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202018, University of Kansas, Department of Economics, revised Nov 2020.
  63. Simón Sosvilla-Rivero & Amalia Morales-Zumaquero, 2011. "Volatility in EMU sovereign bond yields: Permanent and transitory components," Working Papers del Instituto Complutense de Estudios Internacionales 1106, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
  64. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
  65. Potjagailo, Galina, 2017. "Spillover effects from Euro area monetary policy across Europe: A factor-augmented VAR approach," Journal of International Money and Finance, Elsevier, vol. 72(C), pages 127-147.
  66. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
  67. Casoli, Chiara & Lucchetti, Riccardo (Jack), 2021. "Permanent-Transitory decomposition of cointegrated time series via Dynamic Factor Models, with an application to commodity prices," FEEM Working Papers 312367, Fondazione Eni Enrico Mattei (FEEM).
  68. Kenneth W Clements & Grace Gao, 2013. "A Multi-Market Approach to Measuring the Cycle," Economics Discussion / Working Papers 13-16, The University of Western Australia, Department of Economics.
  69. Chen, Peng, 2015. "Global oil prices, macroeconomic fundamentals and China's commodity sector comovements," Energy Policy, Elsevier, vol. 87(C), pages 284-294.
  70. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
  71. Juan Carlos Carlo Santos, 2019. "Pronósticos del PIB mediante modelos de factores dinámicos," Revista de Análisis del BCB, Banco Central de Bolivia, vol. 30(1), pages 125-174, January -.
  72. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2023. "General Bayesian time‐varying parameter vector autoregressions for modeling government bond yields," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 69-87, January.
  73. Janis Becker & Christian Leschinski, 2021. "Estimating the volatility of asset pricing factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 269-278, March.
  74. Marijn A Bolhuis & Judd N L Cramer & Lawrence H Summers, 2022. "The Coming Rise in Residential Inflation [The repeat rent index]," Review of Finance, European Finance Association, vol. 26(5), pages 1051-1072.
  75. Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
  76. Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021. "Quantile Factor Models," Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
  77. Javier Sebastian, 2016. "Blockchain in financial services: Regulatory landscape and future challenges," Working Papers 16/21, BBVA Bank, Economic Research Department.
  78. 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.
  79. repec:cte:wsrepe:23974 is not listed on IDEAS
  80. Francesco Bianchi & Giovanni Nicolo & Dongho Song, 2023. "Inflation and Real Activity over the Business Cycle," Finance and Economics Discussion Series 2023-038, Board of Governors of the Federal Reserve System (U.S.).
  81. Florian Eckert & Heiner Mikosch, 2020. "Mobility and sales activity during the Corona crisis: daily indicators for Switzerland," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-10, December.
  82. Lütkepohl, Helmut, 2014. "Structural vector autoregressive analysis in a data rich environment: A survey," SFB 649 Discussion Papers 2014-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  83. Kuhelika De & Ryan A. Compton & Daniel C. Giedeman & Gary A. Hoover, 2019. "Macroeconomic Shocks and Racial Labour Market Differences in the U.S," CESifo Working Paper Series 8004, CESifo.
  84. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
  85. Minxian Yang, 2017. "Effects of idiosyncratic shocks on macroeconomic time series," Empirical Economics, Springer, vol. 53(4), pages 1441-1461, December.
  86. Moramarco, Graziano, 2024. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," International Journal of Forecasting, Elsevier, vol. 40(2), pages 777-795.
  87. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
  88. Ivo Krznar, 2011. "Identifying Recession and Expansion Periods in Croatia," Working Papers 29, The Croatian National Bank, Croatia.
  89. Gianluca De Nard & Olivier Ledoit & Michael Wolf, 2018. "Factor models for portfolio selection in large dimensions: the good, the better and the ugly," ECON - Working Papers 290, Department of Economics - University of Zurich, revised Dec 2018.
  90. Itkonen, Juha & Juvonen, Petteri, 2017. "Nowcasting the Finnish economy with a large Bayesian vector autoregressive model," BoF Economics Review 6/2017, Bank of Finland.
  91. Milan Christian Wet & Ilse Botha, 2022. "Constructing and Characterising the Aggregate South African Financial Cycle: A Markov Regime-Switching Approach," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 37-67, March.
  92. Giampiero M. Gallo, 2017. "Hendry, David F. and Doornik, Jurgen A.: Empirical model discovery and theory evaluation: automatic selection methods in econometrics," Journal of Economics, Springer, vol. 120(3), pages 279-281, April.
  93. Ryadh M. Alkhareif & William A. Barnett, 2022. "Nowcasting Real GDP for Saudi Arabia1," Open Economies Review, Springer, vol. 33(2), pages 333-345, April.
  94. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
  95. Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
  96. 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.
  97. De, Kuhelika & Sun, Wei, 2020. "Is the exchange rate a shock absorber or a source of shocks? Evidence from the U.S," Economic Modelling, Elsevier, vol. 89(C), pages 1-9.
  98. Bhattacharya, Rudrani & Kapoor, Mrigankshi, 2020. "Forecasting Consumer Price Index Inflation in India: Vector Error Correction Mechanism Vs. Dynamic Factor Model Approach for Non-Stationary Time Series," Working Papers 20/323, National Institute of Public Finance and Policy.
  99. Di Iorio, Francesca & Fachin, Stefano, 2021. "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, vol. 17(C), pages 64-75.
  100. James Sampi, 2016. "High Dimensional Factor Models: An Empirical Bayes Approach," Working Papers 75, Peruvian Economic Association.
  101. Barigozzi, Matteo & Trapani, Lorenzo, 2020. "Sequential testing for structural stability in approximate factor models," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 5149-5187.
  102. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
  103. Jason Angelopoulos & Costas I. Chlomoudis, 2017. "A Generalized Dynamic Factor Model for the U.S. Port Sector," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 67(1), pages 22-37, January-M.
  104. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  105. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Bank of Russia Working Paper Series wps104, Bank of Russia.
  106. Luke Hartigan, 2015. "Changes in the Factor Structure of the U.S. Economy: Permanent Breaks or Business Cycle Regimes?," Discussion Papers 2015-17, School of Economics, The University of New South Wales.
  107. Nathan Sussman & Osnat Zohar, 2016. "Has Inflation Targeting Become Less Credible? Oil Prices, Global Aggregate Demand and Inflation Expectations during the Global Financial Crisis," Bank of Israel Working Papers 2016.13, Bank of Israel.
  108. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
  109. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
  110. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.
  111. Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2020. "The simpler the better: measuring financial conditions for monetary policy and financial stability," Working Paper Series 2451, European Central Bank.
  112. Stona, Filipe & Morais, Igor A.C. & Triches, Divanildo, 2018. "Economic dynamics during periods of financial stress: Evidences from Brazil," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 130-144.
  113. Rafael R. S. Guimaraes, 2022. "Deep Learning Macroeconomics," Papers 2201.13380, arXiv.org.
  114. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
  115. Chen, Liang, 2015. "Estimating the common break date in large factor models," Economics Letters, Elsevier, vol. 131(C), pages 70-74.
  116. Philipp Gersing & Christoph Rust & Manfred Deistler, 2023. "Weak Factors are Everywhere," Papers 2307.10067, arXiv.org, revised Jan 2024.
  117. Bhattarai, Keshab & Mallick, Sushanta K. & Yang, Bo, 2021. "Are global spillovers complementary or competitive? Need for international policy coordination," Journal of International Money and Finance, Elsevier, vol. 110(C).
  118. Juan Manuel Candelo-Viafara & Andrés Oviedo-Gómez, 2021. "La tasa de cambio y sus impactos en los agregados económicos colombianos: una aproximación FAVAR," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, vol. 29(2), pages 121-142, October.
  119. In Choi & Hanbat Jeong, 2020. "Differencing versus nondifferencing in factor‐based forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 728-750, September.
  120. Jason Angelopoulos, 2017. "Creating and assessing composite indicators: Dynamic applications for the port industry and seaborne trade," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 126-159, March.
  121. Siegfried Hörmann & Gilles Nisol, 2021. "Prediction of Singular VARs and an Application to Generalized Dynamic Factor Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 295-313, May.
  122. Chen, Liang & Ramos Ramirez, Andrey David, 2013. "Revisiting Granger Causality of CO2 on Global Warming: a Quantile Factor Approach," DES - Working Papers. Statistics and Econometrics. WS 35531, Universidad Carlos III de Madrid. Departamento de Estadística.
  123. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
  124. Oviedo Gómez, Andrés Felipe & Sierra, Lya Paola, 2019. "Importancia de los términos de intercambio en la economía colombiana," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
  125. Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
  126. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
  127. Maximo Camacho & Matías José Pacce, 2018. "Forecasting travellers in Spain with Google’s search volume indices," Tourism Economics, , vol. 24(4), pages 434-448, June.
  128. Sadaba, Barbara & Vujić, Sunčica & Maier, Sofia, 2024. "Characterizing the schooling cycle," Economic Modelling, Elsevier, vol. 132(C).
  129. 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.
  130. Kock, Anders Bredahl & Callot, Laurent, 2015. "Oracle inequalities for high dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 186(2), pages 325-344.
  131. Venetis, Ioannis & Ladas, Avgoustinos, 2022. "Co-movement and global factors in sovereign bond yields," MPRA Paper 115801, University Library of Munich, Germany.
  132. Boonman, Tjeerd M. & Jacobs, Jan P.A.M. & Kuper, Gerard H., 2012. "The Global Financial Crisis and currency crises in Latin America," Research Report 12005-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  133. Nikolaos Zirogiannis & Yorghos Tripodis, 2018. "Dynamic factor analysis for short panels: estimating performance trajectories for water utilities," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 131-150, March.
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  176. Pallara, Kevin, 2016. "The dynamic effects of government spending: a FAVAR approach," MPRA Paper 92283, University Library of Munich, Germany.
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  187. Bin Jiang & Anastasios Panagiotelis & George Athanasopoulos & Rob Hyndman & Farshid Vahid, 2016. "Bayesian Rank Selection in Multivariate Regression," Monash Econometrics and Business Statistics Working Papers 6/16, Monash University, Department of Econometrics and Business Statistics.
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