IDEAS home Printed from https://ideas.repec.org/r/now/fnteco/0800000002.html
   My bibliography  Save this item

Large Dimensional Factor Analysis

Citations

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


Cited by:

  1. 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.
  2. Konomi Tonogi & Jun-ichi Nakamura & Kazumi Asako, 2014. "Heterogeneity of Capital Stocks in Japan: Classification by Factor Analysis," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 4(2), pages 1-10, April.
  3. 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.
  4. 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.
  5. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
  6. 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).
  7. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
  8. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components," Tinbergen Institute Discussion Papers 14-113/III, Tinbergen Institute.
  9. Georges Bresson & Jean-Michel Etienne & Pierre Mohnen, 2011. "How important is innovation? A Bayesian factor-augmented productivity model on panel data," Working Papers halshs-00812155, HAL.
  10. 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.
  11. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
  12. 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.
  13. Sven Otto & Nazarii Salish, 2022. "Approximate Factor Models for Functional Time Series," Papers 2201.02532, arXiv.org, revised May 2024.
  14. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
  15. repec:dau:papers:123456789/11382 is not listed on IDEAS
  16. Jan Mutl, 2002. "Panel VAR Models with Spatial Dependence," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A5-2, International Conferences on Panel Data.
  17. Christian Matthes & Felipe Schwartzman, 2019. "The Demand Origins of Business Cycles," 2019 Meeting Papers 1122, Society for Economic Dynamics.
  18. 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.
  19. Emmanuel Thompson & Ahmad M. Talafha, 2017. "Forecasting a Composite Indicator of Economic Activity in Ghana: A Comparison of Data Science Methods," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(4), pages 1-2.
  20. Francis Teal & Markus Eberhardt, 2010. "Productivity Analysis in Global Manufacturing Production," Economics Series Working Papers 515, University of Oxford, Department of Economics.
  21. 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.
  22. Boysen-Hogrefe, Jens & Pape, Markus, 2011. "More than just one labor market cycle in Germany? : an analysis of regional unemployment data," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 44(3), pages 279-292.
  23. Anna Bykhovskaya & Vadim Gorin, 2023. "High-Dimensional Canonical Correlation Analysis," Papers 2306.16393, arXiv.org, revised Aug 2023.
  24. Eberhardt, Markus & Teal, Francis, 2008. "Modeling technology and technological change in manufacturing: how do countries differ?," MPRA Paper 10690, University Library of Munich, Germany.
  25. Goldberg, Lisa R & Papanicolaou, Alex & Shkolnik, Alex, 2022. "The Dispersion Bias," Department of Economics, Working Paper Series qt4kt5g2x3, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  26. 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.
  27. 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.
  28. 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.
  29. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2016. "Fast ML Estimation of Dynamic Bifactor Models: An Application to European Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 215-282, Emerald Group Publishing Limited.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. Polyakovskiy, S. & Neumann, F., 2017. "The Packing While Traveling Problem," European Journal of Operational Research, Elsevier, vol. 258(2), pages 424-439.
  35. 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.
  36. 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.
  37. repec:dau:papers:123456789/6800 is not listed on IDEAS
  38. Skripnikov, A. & Michailidis, G., 2019. "Joint estimation of multiple network Granger causal models," Econometrics and Statistics, Elsevier, vol. 10(C), pages 120-133.
  39. 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.
  40. 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.
  41. Lettau, Martin & Pelger, Markus, 2020. "Estimating latent asset-pricing factors," Journal of Econometrics, Elsevier, vol. 218(1), pages 1-31.
  42. repec:hum:wpaper:sfb649dp2017-026 is not listed on IDEAS
  43. Mattia Guerini & Mauro Napoletano & Claudio Barbieri, 2024. "The anatomy of government bond yields synchronization in the Eurozone," SciencePo Working papers Main hal-04530954, HAL.
  44. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
  45. Matteo Luciani & David Veredas, "undated". "A simple model for vast panels of volatilities," ULB Institutional Repository 2013/136239, ULB -- Universite Libre de Bruxelles.
  46. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
  47. repec:dau:papers:123456789/11692 is not listed on IDEAS
  48. González-Rivera, Gloria & Maldonado, Javier & Ruiz, Esther, 2019. "Growth in stress," International Journal of Forecasting, Elsevier, vol. 35(3), pages 948-966.
  49. Tao Zeng & Yong Li & Jun Yu, 2014. "Deviance Information Criterion for Comparing VAR Models," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 615-637, Emerald Group Publishing Limited.
  50. Peter Fuleky, 2022. "Nowcasting the trajectory of the COVID-19 recovery," Applied Economics Letters, Taylor & Francis Journals, vol. 29(11), pages 1037-1041, June.
  51. Nathan Bedock & Dalibor Stevanović, 2017. "An empirical study of credit shock transmission in a small open economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(2), pages 541-570, May.
  52. Bai, Jushan & Ng, Serena, 2019. "Rank regularized estimation of approximate factor models," Journal of Econometrics, Elsevier, vol. 212(1), pages 78-96.
  53. Andrés Felipe Londoño & Jorge Andrés Tamayo & Carlos Alberto Velásquez, 2012. "Dinámica de la política monetaria e inflación objetivo en Colombia: una aproximación FAVAR," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 30(68), pages 14-71, June.
  54. 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.
  55. repec:ipg:wpaper:2014-414 is not listed on IDEAS
  56. Mao, Guangyu & Shen, Yan, 2019. "Bubbles or fundamentals? Modeling provincial house prices in China allowing for cross-sectional dependence," China Economic Review, Elsevier, vol. 53(C), pages 53-64.
  57. Steffen R. Henzel & Malte Rengel, 2017. "Dimensions Of Macroeconomic Uncertainty: A Common Factor Analysis," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 843-877, April.
  58. Claudio Barbieri & Mattia Guerini & Mauro Napoletano, 2021. "The anatomy of government bond yields synchronization in the Eurozone," SciencePo Working papers Main hal-03373853, HAL.
  59. Eberhardt, Markus & Bond, Stephen, 2009. "Cross-section dependence in nonstationary panel models: a novel estimator," MPRA Paper 17692, University Library of Munich, Germany.
  60. Esteban Gómez & Andrés Murcia & Nancy Zamudio, 2011. "Financial Conditions Index: Early and Leading Indicator for Colombia," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 29(66), pages 174-220, December.
  61. Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021. "Quantile Factor Models," Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
  62. Joakim Westerlund & Simon Reese & Paresh Narayan, 2017. "A Factor Analytical Approach to Price Discovery," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(3), pages 366-394, June.
  63. repec:cte:wsrepe:23974 is not listed on IDEAS
  64. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
  65. Kasper Johansson & Mehmet Giray Ogut & Markus Pelger & Thomas Schmelzer & Stephen Boyd, 2023. "A Simple Method for Predicting Covariance Matrices of Financial Returns," Papers 2305.19484, arXiv.org, revised Nov 2023.
  66. 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.
  67. Luke Hartigan & James Morley, 2020. "A Factor Model Analysis of the Australian Economy and the Effects of Inflation Targeting," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 271-293, September.
  68. Omar Zulaica, 2020. "What share for gold? On the interaction of gold and foreign exchange reserve returns," BIS Working Papers 906, Bank for International Settlements.
  69. Olga Bondarenko, 2020. "The Missing “Cycle” Part and Other Thoughts on the Global Financial Cycle," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 250, pages 15-32.
  70. 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.
  71. 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.
  72. Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2018. "A spectral EM algorithm for dynamic factor models," Journal of Econometrics, Elsevier, vol. 205(1), pages 249-279.
  73. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
  74. Xue, Sen & Yang, Thomas Tao & Zhou, Qiankun, 2018. "Binary choice model with interactive effects," Economic Modelling, Elsevier, vol. 70(C), pages 338-350.
  75. Gregory Connor & Robert A Korajczyk, 2024. "Semi-Strong Factors in Asset Returns," Journal of Financial Econometrics, Oxford University Press, vol. 22(1), pages 70-93.
  76. Badi H. Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: a Bayesian Semiparametric Model With Random Coefficients for a Panel of OECD Countries," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 217-253, Emerald Group Publishing Limited.
  77. Ravi Jagannathan & Srikant Marakani, 2015. "Price-Dividend Ratio Factor Proxies for Long-Run Risks," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 5(1), pages 1-47.
  78. James Sampi, 2016. "High Dimensional Factor Models: An Empirical Bayes Approach," Working Papers 75, Peruvian Economic Association.
  79. 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.
  80. 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.
  81. Jorge M. Uribe & Montserrat Guillen, 2020. "Generalized Market Uncertainty Measurement in European Stock Markets in Real Time," Mathematics, MDPI, vol. 8(12), pages 1-11, December.
  82. Uğur Akkoç & Anıl Akçağlayan & Gamze Kargın Akkoç, 2021. "The impacts of oil price shocks in Turkey: sectoral evidence from the FAVAR approach," Economic Change and Restructuring, Springer, vol. 54(4), pages 1147-1171, November.
  83. 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.
  84. Franz Ramsauer & Aleksey Min & Michael Lingauer, 2019. "Estimation of FAVAR Models for Incomplete Data with a Kalman Filter for Factors with Observable Components," Econometrics, MDPI, vol. 7(3), pages 1-43, July.
  85. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2021. ""Vulnerable Funding in the Global Economy"," IREA Working Papers 202106, University of Barcelona, Research Institute of Applied Economics, revised Mar 2021.
  86. 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.
  87. William A. Barnett & Marcelle Chauvet & Danilo Leiva‐Leon & Liting Su, 2024. "The Credit‐Card‐Services Augmented Divisia Monetary Aggregates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(5), pages 1163-1202, August.
  88. Zhuo Chen & Gregory Connor & Robert A Korajczyk, 2018. "A Performance Comparison of Large-n Factor Estimators," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 8(1), pages 153-182.
  89. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
  90. Mikkelsen, Jakob Guldbæk & Hillebrand, Eric & Urga, Giovanni, 2019. "Consistent estimation of time-varying loadings in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 208(2), pages 535-562.
  91. Hallin, Marc & Lippi, Marco, 2013. "Factor models in high-dimensional time series—A time-domain approach," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2678-2695.
  92. Chen, Liang, 2015. "Estimating the common break date in large factor models," Economics Letters, Elsevier, vol. 131(C), pages 70-74.
  93. Farnè, Matteo & Montanari, Angela, 2024. "Large factor model estimation by nuclear norm plus ℓ1 norm penalization," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
  94. Robertson, Donald & Sarafidis, Vasilis, 2015. "IV estimation of panels with factor residuals," Journal of Econometrics, Elsevier, vol. 185(2), pages 526-541.
  95. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
  96. Declan French, 2012. "Causation between health and income: a need to panic," Empirical Economics, Springer, vol. 42(2), pages 583-601, April.
  97. 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.
  98. Scheffel, Eric Michael, 2012. "Political uncertainty in a data-rich environment," MPRA Paper 37318, University Library of Munich, Germany.
  99. Christian Matthes & Felipe Schwartzman, 2019. "What Do Sectoral Dynamics Tell Us About the Origins of Business Cycles?," Working Paper 19-9, Federal Reserve Bank of Richmond.
  100. Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.
  101. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
  102. Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
  103. 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.
  104. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Vulnerable funding in the global economy," Journal of Banking & Finance, Elsevier, vol. 169(C).
  105. Ming Lin & Eric A. Suess & Robert H. Shumway & Rong Chen, 2016. "Bayesian Deconvolution of Signals Observed on Arrays," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 837-850, November.
  106. Sadaba, Barbara & Vujić, Sunčica & Maier, Sofia, 2024. "Characterizing the schooling cycle," Economic Modelling, Elsevier, vol. 132(C).
  107. Djogbenou, Antoine & Sufana, Razvan, 2024. "Tests for group-specific heterogeneity in high-dimensional factor models," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
  108. Kock, Anders Bredahl & Callot, Laurent, 2015. "Oracle inequalities for high dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 186(2), pages 325-344.
  109. Yannick Le Pen & Benoît Sévi, 2013. "Futures trading and the excess comovement of commodity prices," Post-Print hal-01613916, HAL.
  110. 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.
  111. repec:cte:wsrepe:27047 is not listed on IDEAS
  112. Dimitris Korobilis, 2018. "Machine Learning Macroeconometrics: A Primer," Working Paper series 18-30, Rimini Centre for Economic Analysis.
  113. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
  114. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
  115. Gagliardini, Patrick & Gouriéroux, Christian, 2017. "Double instrumental variable estimation of interaction models with big data," Journal of Econometrics, Elsevier, vol. 201(2), pages 176-197.
  116. André Nunes Maranhão, 2024. "Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(1), pages 1-58, August.
  117. Reese, Simon, 2015. "Asymptotic Inference in the Lee-Carter Model for Modelling Mortality Rates," Working Papers 2015:16, Lund University, Department of Economics.
  118. Bastos, Guadalupe & García-Martos, Carolina, 2017. "BIAS correction for dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 24029, Universidad Carlos III de Madrid. Departamento de Estadística.
  119. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
  120. André Nunes Maranhão & Nicole Rennó Castro, 2023. "Dissecting Brazilian agriculture business cycles in high-dimensional and time-irregular span contexts," Empirical Economics, Springer, vol. 65(4), pages 1543-1578, October.
  121. repec:ipg:wpaper:2013-019 is not listed on IDEAS
  122. Marijn A. Bolhuis & Brett Rayner, 2020. "Deus ex Machina? A Framework for Macro Forecasting with Machine Learning," IMF Working Papers 2020/045, International Monetary Fund.
  123. Camacho, Maximo & Lopez-Buenache, German, 2023. "Factor models for large and incomplete data sets with unknown group structure," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1205-1220.
  124. Alexander Chudik & M. Hashem Pesaran, 2013. "Large Panel Data Models with Cross-Sectional Dependence: A Survey," CESifo Working Paper Series 4371, CESifo.
  125. Gabriele Fiorentini & Enrique Sentana, 2019. "Dynamic specification tests for dynamic factor models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 325-346, April.
  126. Jacobs, Jan P.A.M. & Otter, Pieter W. & den Reijer, Ard H.J., 2012. "Information, data dimension and factor structure," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 80-91.
  127. Martin Solberger & Erik Spånberg, 2020. "Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 875-900, March.
  128. Monika Bours & Ansgar Steland, 2021. "Large‐sample approximations and change testing for high‐dimensional covariance matrices of multivariate linear time series and factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 610-654, June.
  129. Jiahe Lin & George Michailidis, 2019. "Approximate Factor Models with Strongly Correlated Idiosyncratic Errors," Papers 1912.04123, arXiv.org.
  130. Phillip Monin, 2017. "The OFR Financial Stress Index," Working Papers 17-04, Office of Financial Research, US Department of the Treasury.
  131. Matteo Lanzafame, 2014. "Temperature, rainfall and economic growth in Africa," Empirical Economics, Springer, vol. 46(1), pages 1-18, February.
  132. repec:hum:wpaper:sfb649dp2014-004 is not listed on IDEAS
  133. Jorge M. Uribe & Helena Chuliá & Montserrat Guillen, 2018. "Trends in the Quantiles of the Life Table Survivorship Function," European Journal of Population, Springer;European Association for Population Studies, vol. 34(5), pages 793-817, December.
  134. Yannick Le Pen & Benoît Sévi, 2018. "Futures Trading and the Excess Co-movement of Commodity Prices [On the comovement of commodity prices]," Review of Finance, European Finance Association, vol. 22(1), pages 381-418.
  135. Kenwin Maung, 2021. "Estimating high-dimensional Markov-switching VARs," Papers 2107.12552, arXiv.org.
  136. Martin Feldkircher & Florian Huber & Josef Schreiner & Julia Woerz & Marcel Tirpak & Peter Toth, 2015. "Small-scale nowcasting models of GDP for selected CESEE countries," Working and Discussion Papers WP 4/2015, Research Department, National Bank of Slovakia.
  137. Markus Pelger & Ruoxuan Xiong, 2022. "State-Varying Factor Models of Large Dimensions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1315-1333, June.
  138. Lanzafame, Matteo, 2013. "Crime and regional growth in Italy," MPRA Paper 44343, University Library of Munich, Germany.
  139. Li, Yuanbo & Ng, Chi Tim & Yau, Chun Yip, 2022. "GARCH-type factor model," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
  140. Byungsoo Kim & Junmo Song & Changryong Baek, 2021. "Robust test for structural instability in dynamic factor models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 821-853, August.
  141. Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.
  142. Francisco Corona & Pedro Orraca, 2019. "Remittances in Mexico and their unobserved components," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 28(8), pages 1047-1066, November.
  143. Samuel N. Cohen & Silvia Lui & Will Malpass & Giulia Mantoan & Lars Nesheim & 'Aureo de Paula & Andrew Reeves & Craig Scott & Emma Small & Lingyi Yang, 2023. "Nowcasting with signature methods," Papers 2305.10256, arXiv.org.
  144. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
  145. Ergemen, Yunus Emre & Haldrup, Niels & Rodríguez-Caballero, Carlos Vladimir, 2016. "Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads," Energy Economics, Elsevier, vol. 60(C), pages 79-96.
  146. Perez, M. Fabricio & Shkilko, Andriy & Sokolov, Konstantin, 2015. "Factor models for binary financial data," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 177-188.
  147. 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.
  148. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
  149. Phillip J. Monin, 2019. "The OFR Financial Stress Index," Risks, MDPI, vol. 7(1), pages 1-21, February.
  150. Joaqui-Barandica, Orlando & Manotas-Duque, Diego F. & Uribe, Jorge M., 2022. "Commonality, macroeconomic factors and banking profitability," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  151. 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, August.
  152. Bodnar, Taras & Okhrin, Ostap & Parolya, Nestor, 2019. "Optimal shrinkage estimator for high-dimensional mean vector," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 63-79.
  153. David Kohns & Tibor Szendrei, 2020. "Horseshoe Prior Bayesian Quantile Regression," Papers 2006.07655, arXiv.org, revised Mar 2021.
  154. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
  155. Abhyankar, Abhay & Klinkowska, Olga & Lee, Soyeon, 2015. "Consumption risk and the cross-section of government bond returns," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 180-200.
  156. repec:ipg:wpaper:19 is not listed on IDEAS
  157. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  158. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.
  159. Qin Zhang & He Ni & Hao Xu, 2023. "Forecasting models for the Chinese macroeconomy in a data‐rich environment: Evidence from large dimensional approximate factor models with mixed‐frequency data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 719-767, March.
  160. Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting the French index of industrial production: A comparison from bridge and factor models," Economic Modelling, Elsevier, vol. 29(6), pages 2174-2182.
  161. Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
  162. Stephen Boyd & Kasper Johansson & Ronald Kahn & Philipp Schiele & Thomas Schmelzer, 2024. "Markowitz Portfolio Construction at Seventy," Papers 2401.05080, arXiv.org.
  163. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.
  164. Jack Fosten, 2016. "Forecast evaluation with factor-augmented models," University of East Anglia School of Economics Working Paper Series 2016-05, School of Economics, University of East Anglia, Norwich, UK..
  165. Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
  166. Boysen-Hogrefe, Jens & Pape, Markus, 2011. "More than just one labor market cycle in Germany? : an analysis of regional unemployment data," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 44(3), pages 279-292.
  167. Duván Humberto Cataño & Carlos Vladimir Rodríguez-Caballero & Daniel Peña, 2019. "Wavelet Estimation for Dynamic Factor Models with Time-Varying Loadings," CREATES Research Papers 2019-23, Department of Economics and Business Economics, Aarhus University.
  168. Helena Chuliá & Montserrat Guillén & Jorge M. Uribe, 2015. "Mortality and Longevity Risks in the United Kingdom: Dynamic Factor Models and Copula-Functions," Working Papers 2015-03, Universitat de Barcelona, UB Riskcenter.
  169. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
  170. repec:dau:papers:123456789/11663 is not listed on IDEAS
  171. 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.
  172. Yunus Emre Ergemen & Carlos Vladimir Rodríguez-Caballero, 2016. "A Dynamic Multi-Level Factor Model with Long-Range Dependence," CREATES Research Papers 2016-23, Department of Economics and Business Economics, Aarhus University.
  173. Matej Marinč & Mojmir Mrak & Vasja Rant, 2014. "Dimensions of Bank Capital Regulation: A Cross-Country Analysis," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 61(4), pages 415-439, September.
  174. Liu, Lu & Zhang, Xiang, 2019. "Financialization and commodity excess spillovers," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 195-216.
  175. Jushan Bai & Serena Ng, 2017. "Principal Components and Regularized Estimation of Factor Models," Papers 1708.08137, arXiv.org, revised Nov 2017.
  176. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
  177. Uribe, Jorge M. & Chuliá, Helena & Guillén, Montserrat, 2017. "Uncertainty, systemic shocks and the global banking sector: Has the crisis modified their relationship?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 52-68.
  178. Jiahe Lin & George Michailidis, 2019. "Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models," Papers 1912.04146, arXiv.org, revised May 2020.
  179. Fatma Alahouel & Nadia Loukil, 2020. "Financial uncertainty valuation: doesShariahcompliant screening matter?," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 14(1), pages 57-76, August.
  180. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.
  181. Westerlund, Joakim, 2015. "The power of PANIC," Journal of Econometrics, Elsevier, vol. 185(2), pages 495-509.
  182. Anna Bykhovskaya & Vadim Gorin, 2022. "Asymptotics of Cointegration Tests for High-Dimensional VAR($k$)," Papers 2202.07150, arXiv.org, revised Nov 2023.
  183. Chen, Elynn Y. & Fan, Jianqing & Zhu, Xuening, 2023. "Community network auto-regression for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1239-1256.
  184. Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
  185. Francisco Corona & Graciela Gonz'alez-Far'ias & Jes'us L'opez-P'erez, 2021. "A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19," Papers 2101.10383, arXiv.org.
  186. Marc Anderes, 2021. "Housing Demand Shocks and Households Balance Sheets," KOF Working papers 21-492, KOF Swiss Economic Institute, ETH Zurich.
  187. Kapetanios, G. & Pesaran, M.H. & Reese, S., 2021. "Detection of units with pervasive effects in large panel data models," Journal of Econometrics, Elsevier, vol. 221(2), pages 510-541.
  188. Verhoijsen Alex & Krupskiy Pavel, 2022. "Fast inference methods for high-dimensional factor copulas," Dependence Modeling, De Gruyter, vol. 10(1), pages 270-289, January.
  189. Baek, Changryong & Gates, Katheleen M. & Leinwand, Benjamin & Pipiras, Vladas, 2021. "Two sample tests for high-dimensional autocovariances," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  190. Mouloud El Hafidi & Marouane Daoui, 2019. "Chocs de la politique monétaire et croissance économique au Maroc : une approche en terme de modèles FAVAR," Post-Print hal-03311354, HAL.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.