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Citations

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Cited by:

  1. Wu, Jianhong, 2019. "Detecting irrelevant variables in possible proxies for the latent factors in macroeconomics and finance," Economics Letters, Elsevier, vol. 176(C), pages 60-63.
  2. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
  3. Montero-Manso, Pablo & Hyndman, Rob J., 2021. "Principles and algorithms for forecasting groups of time series: Locality and globality," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1632-1653.
  4. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Papers 1806.08278, arXiv.org.
  5. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
  6. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
  7. Ethan Struby & Michael F. Connolly, 2022. "Shadow Rate Models and Monetary Policy," Working Papers 2022-03, Carleton College, Department of Economics.
  8. 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.
  9. Niko Hauzenberger & Florian Huber & Massimiliano Marcellino & Nico Petz, 2025. "Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(1), pages 27-43, January.
  10. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
  11. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
  12. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer & Petra Staufer‐Steinnocher, 2021. "The Dynamic Impact of Monetary Policy on Regional Housing Prices in the United States," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(4), pages 1039-1068, December.
  13. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
  14. Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
  15. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
  16. Cheung, Ying Lun, 2024. "Avoiding jumps in the rotation matrix of time-varying factor models," Finance Research Letters, Elsevier, vol. 67(PB).
  17. Niko Hauzenberger & Florian Huber & Luca Onorante, 2021. "Combining shrinkage and sparsity in conjugate vector autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
  18. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
  19. Fang, Puyi & Gao, Zhaoxing & Tsay, Ruey S., 2023. "Supervised kernel principal component analysis for forecasting," Finance Research Letters, Elsevier, vol. 58(PA).
  20. Popp, Aaron & Zhang, Fang, 2016. "The macroeconomic effects of uncertainty shocks: The role of the financial channel," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 319-349.
  21. 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.
  22. Shuquan Yang & Nengxiang Ling & Yulin Gong, 2022. "Robust estimation of the number of factors for the pair-elliptical factor models," Computational Statistics, Springer, vol. 37(3), pages 1495-1522, July.
  23. Etienne Briand & Massimiliano Marcellino & Dalibor Stevanovic, 2024. "Inflation, Attention and Expectations," Working Papers 24-05, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Dec 2024.
  24. Zichuan Guo & Mihai Cucuringu & Alexander Y. Shestopaloff, 2025. "Generalized Factor Neural Network Model for High-dimensional Regression," Papers 2502.11310, arXiv.org, revised Mar 2025.
  25. Philippe Goulet Coulombe, 2024. "The macroeconomy as a random forest," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 401-421, April.
  26. Fan, Jianqing & Jiang, Bai & Sun, Qiang, 2022. "Bayesian factor-adjusted sparse regression," Journal of Econometrics, Elsevier, vol. 230(1), pages 3-19.
  27. Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
  28. 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.
  29. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org, revised Jan 2025.
  30. Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
  31. Yunjung Kim & Cheolbeom Park, 2020. "Are exchange rates disconnected from macroeconomic variables? Evidence from the factor approach," Empirical Economics, Springer, vol. 58(4), pages 1713-1747, April.
  32. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org, revised Nov 2024.
  33. Giovanni Angelini & Giovanni Caggiano & Efrem Castelnuovo & Luca Fanelli, 2023. "Are Fiscal Multipliers Estimated with Proxy‐SVARs Robust?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 95-122, February.
  34. İshak Demi̇r & Burak A. Eroğlu & Seçi̇l Yildirim‐Karaman, 2022. "Heterogeneous Effects of Unconventional Monetary Policy on the Bond Yields across the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1425-1457, August.
  35. Davig, Troy & Hall, Aaron Smalter, 2019. "Recession forecasting using Bayesian classification," International Journal of Forecasting, Elsevier, vol. 35(3), pages 848-867.
  36. Robert Adamek & Stephan Smeekes & Ines Wilms, 2024. "Local projection inference in high dimensions," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 323-342.
  37. Bai, Jushan & Ng, Serena, 2019. "Rank regularized estimation of approximate factor models," Journal of Econometrics, Elsevier, vol. 212(1), pages 78-96.
  38. Joshua C. C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2020. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 692-711, September.
  39. Nam, Eun-Young & Lee, Kiryoung & Jeon, Yoontae, 2021. "Macroeconomic uncertainty shocks and households’ consumption choice," Journal of Macroeconomics, Elsevier, vol. 68(C).
  40. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
  41. Choi, Chi-Young & Hansz, J. Andrew, 2021. "From banking integration to housing market integration - Evidence from the comovement of U.S. Metropolitan House Prices," Journal of Financial Stability, Elsevier, vol. 54(C).
  42. Caggiano, Giovanni & Castelnuovo, Efrem & Figueres, Juan Manuel, 2017. "Economic policy uncertainty and unemployment in the United States: A nonlinear approach," Economics Letters, Elsevier, vol. 151(C), pages 31-34.
  43. Ignacio Garr'on & C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "International vulnerability of inflation," Papers 2410.20628, arXiv.org, revised Oct 2024.
  44. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
  45. James Mitchell & Gary Koop & Stuart McIntyre & Aubrey Poon, 2020. "Reconciled Estimates of Monthly GDP in the US," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-16, Economic Statistics Centre of Excellence (ESCoE).
  46. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
  47. 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.
  48. Ballarin, Giovanni & Dellaportas, Petros & Grigoryeva, Lyudmila & Hirt, Marcel & van Huellen, Sophie & Ortega, Juan-Pablo, 2024. "Reservoir computing for macroeconomic forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1206-1237.
  49. Mario Giarda, 2023. "Government Purchases, the Labor Earnings Gap, andConsumption Dynamics," Working Papers Central Bank of Chile 972, Central Bank of Chile.
  50. Giovanni Angelini & Emanuele Bacchiocchi & Giovanni Caggiano & Luca Fanelli, 2019. "Uncertainty across volatility regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 437-455, April.
  51. Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021. "Quantile Factor Models," Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
  52. Xin Sheng & Rangan Gupta & Qiang Ji, 2023. "The Effects of Disaggregate Oil Shocks on the Aggregate Expected Skewness of the United States," Risks, MDPI, vol. 11(11), pages 1-9, October.
  53. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
  54. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
  55. Robert Goodhead & Benedikt Kolb, 2025. "Monetary policy communication shocks and the macroeconomy," Economica, London School of Economics and Political Science, vol. 92(365), pages 173-198, January.
  56. Lee, Kiryoung, 2022. "Which uncertainty measures matter for the cross-section of corporate bond returns? Evidence from the U.S. during 1973–2020," Finance Research Letters, Elsevier, vol. 48(C).
  57. Ferreira, Leonardo N., 2022. "Forward guidance matters: Disentangling monetary policy shocks," Journal of Macroeconomics, Elsevier, vol. 73(C).
  58. 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.
  59. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, May.
  60. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," Working Papers halshs-03626503, HAL.
  61. De Gooijer, Jan G. & Zerom, Dawit, 2019. "Semiparametric quantile averaging in the presence of high-dimensional predictors," International Journal of Forecasting, Elsevier, vol. 35(3), pages 891-909.
  62. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
  63. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
  64. Xiao Huang, 2022. "Boosted p-Values for High-Dimensional Vector Autoregression," Papers 2211.02215, arXiv.org, revised Mar 2023.
  65. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
  66. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
  67. Jozef Barunik & Mattia Bevilacqua & Michael Ellington, 2023. "Common Firm-level Investor Fears: Evidence from Equity Options," Papers 2309.03968, arXiv.org.
  68. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
  69. Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2023. "The commodity risk premium and neural networks," Journal of Empirical Finance, Elsevier, vol. 74(C).
  70. Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
  71. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2018. "Dynamic factor model with infinite‐dimensional factor space: Forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 625-642, August.
  72. Rama K. Malladi, 2024. "Benchmark Analysis of Machine Learning Methods to Forecast the U.S. Annual Inflation Rate During a High-Decile Inflation Period," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 335-375, July.
  73. Zhu, Lin & Jiang, Fuwei & Tang, Guohao & Jin, Fujing, 2024. "From macro to micro: Sparse macroeconomic risks and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PB).
  74. Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2024. "Sectoral uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  75. Krist'of N'emeth & D'aniel Hadh'azi, 2023. "GDP nowcasting with artificial neural networks: How much does long-term memory matter?," Papers 2304.05805, arXiv.org, revised Jan 2025.
  76. Jung, Woosung & Park, Haerang, 2024. "Common factors in the returns on cryptocurrencies," Finance Research Letters, Elsevier, vol. 65(C).
  77. Kuusela, Annika & Hännikäinen, Jari, 2017. "What do the shadow rates tell us about future inflation?," MPRA Paper 80542, University Library of Munich, Germany.
  78. Serena Ng, 2021. "Modeling Macroeconomic Variations After COVID-19," Papers 2103.02732, arXiv.org, revised Jul 2021.
  79. Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
  80. Jianqing Fan & Weining Wang & Yue Zhao, 2024. "Conditional nonparametric variable screening by neural factor regression," Papers 2408.10825, arXiv.org.
  81. Philippe Goulet Coulombe, 2021. "Slow-Growing Trees," Papers 2103.01926, arXiv.org, revised Jul 2021.
    • Philippe Goulet Coulombe, 2021. "Slow-Growing Trees," Working Papers 21-02, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  82. Smeekes, Stephan & Wijler, Etienne, 2021. "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, vol. 221(1), pages 247-276.
  83. Li, Xiang & Li, Yu-Ning & Zhang, Li-Xin & Zhao, Jun, 2024. "Inference for high-dimensional linear expectile regression with de-biasing method," Computational Statistics & Data Analysis, Elsevier, vol. 198(C).
  84. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
  85. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
  86. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
  87. Salamaliki, Paraskevi, 2019. "Assessing labor market conditions in Greece: a note," MPRA Paper 97559, University Library of Munich, Germany.
  88. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
  89. Luca Margaritella & Joakim Westerlund, 2023. "Using information criteria to select averages in CCE," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 405-421.
  90. Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
  91. Bae, Juhee, 2024. "Factor-augmented forecasting in big data," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1660-1688.
  92. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  93. Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
  94. Uwe Hassler & Marc-Oliver Pohle & Tanja Zahn, 2025. "Simultaneous Inference Bands for Autocorrelations," Papers 2503.18560, arXiv.org.
  95. Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.
  96. Wanbo Lu & Guanglin Huang & Kris Boudt, 2024. "Estimation of Non-Gaussian Factors Using Higher-order Multi-cumulants in Weak Factor Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1085, Ghent University, Faculty of Economics and Business Administration.
  97. Matteo Mogliani & Florens Odendahl, 2024. "Density forecast transformations," Papers 2412.06092, arXiv.org.
  98. Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
  99. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
  100. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
  101. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024. "Predictive ability tests with possibly overlapping models," Journal of Econometrics, Elsevier, vol. 241(1).
  102. Renato Faccini & Eran Yashiv, 2022. "The importance of hiring frictions in business cycles," Quantitative Economics, Econometric Society, vol. 13(3), pages 1101-1143, July.
  103. Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
  104. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2024. "Out-of-sample predictability in predictive regressions with many predictor candidates," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1166-1178.
  105. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
  106. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 605-635.
  107. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
  108. Luyang Chen & Markus Pelger & Jason Zhu, 2024. "Deep Learning in Asset Pricing," Management Science, INFORMS, vol. 70(2), pages 714-750, February.
  109. Guerrieri, Luca & Harkrader, James Collin, 2021. "What drives bank performance?," Economics Letters, Elsevier, vol. 204(C).
  110. Francis X. Diebold, 2020. "Real-Time Real Economic Activity:Exiting the Great Recession and Entering the Pandemic Recession," PIER Working Paper Archive 20-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  111. Charles Olivier Mao Takongmo & Laetitia Lebihan, 2021. "Government Spending, GDP and Exchange Rate in Zero Lower Bound: Measuring Causality at Multiple Horizons," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 139-160, March.
  112. Jianhao Lin & Jiacheng Fan & Yifan Zhang & Liangyuan Chen, 2023. "Real‐time macroeconomic projection using narrative central bank communication," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 202-221, March.
  113. Peña, Daniel & Smucler, Ezequiel & Yohai, Victor J., 2021. "Sparse estimation of dynamic principal components for forecasting high-dimensional time series," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1498-1508.
  114. Hacıoğlu-Hoke, Sinem, 2024. "Macroeconomic effects of political risk shocks," Economics Letters, Elsevier, vol. 242(C).
  115. Faria, Gonçalo & Verona, Fabio, 2024. "Enhancing forecast accuracy through frequencydomain combination: Applications to financial and economic indicators," Bank of Finland Research Discussion Papers 14/2024, Bank of Finland.
  116. Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
  117. Mont'Alverne Duarte, Angelo & Gaglianone, Wagner Piazza & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor, 2021. "Commodity prices and global economic activity: A derived-demand approach," Energy Economics, Elsevier, vol. 96(C).
  118. repec:zbw:bofrdp:2017_035 is not listed on IDEAS
  119. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2020. "Measuring Uncertainty and Its Effects in the COVID-19 Era," Working Papers 20-32R, Federal Reserve Bank of Cleveland, revised 05 Jan 2022.
  120. Francisco Peñaranda & Enrique Sentana, 2024. "Portfolio management with big data," Working Papers wp2024_2411, CEMFI.
  121. Audzei, Volha & Slobodyan, Sergey, 2022. "Sparse restricted perceptions equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
  122. Hardik A. Marfatia & Christophe André & Rangan Gupta, 2022. "Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(2), pages 189-209, May.
  123. Korobilis, Dimitris, 2018. "Machine Learning Macroeconometrics A Primer," Essex Finance Centre Working Papers 22666, University of Essex, Essex Business School.
  124. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
  125. Herwartz, Helmut & Maxand, Simone & Rohloff, Hannes, 2018. "Lean against the wind or float with the storm? Revisiting the monetary policy asset price nexus by means of a novel statistical identification approach," University of Göttingen Working Papers in Economics 354, University of Goettingen, Department of Economics.
  126. Maurizio Daniele & Julie Schnaitmann, 2019. "A Regularized Factor-augmented Vector Autoregressive Model," Papers 1912.06049, arXiv.org.
  127. Giovanni Angelini & Emanuele Bacchiocchi & Giovanni Caggiano & Luca Fanelli, 2019. "Uncertainty across volatility regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 437-455, April.
  128. Chen, Zilin & Da, Zhi & Huang, Dashan & Wang, Liyao, 2023. "Presidential economic approval rating and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 147(1), pages 106-131.
  129. Giovanni Angelini & Giovanni Caggiano & Efrem Castelnuovo & Luca Fanelli, 2020. "Are Fiscal Multipliers Estimated with Proxy-SVARs Robust?," "Marco Fanno" Working Papers 0257, Dipartimento di Scienze Economiche "Marco Fanno".
  130. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2025. "State-Varying Model Averaging Prediction," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202507, University of Kansas, Department of Economics.
  131. Guilherme Schultz Lindenmeyer & Hudson Silva Torrent, 2024. "Boosting and Predictability of Macroeconomic Variables: Evidence from Brazil," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 377-409, July.
  132. Gonçalves, Sílvia & McCracken, Michael W. & Perron, Benoit, 2017. "Tests of equal accuracy for nested models with estimated factors," Journal of Econometrics, Elsevier, vol. 198(2), pages 231-252.
  133. Eksi, Ozan & Onur Tas, Bedri Kamil, 2022. "Time-varying effect of uncertainty shocks on unemployment," Economic Modelling, Elsevier, vol. 110(C).
  134. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
  135. Tom Boot & Didier Nibbering, 2017. "Inference in high-dimensional linear regression models," Tinbergen Institute Discussion Papers 17-032/III, Tinbergen Institute, revised 05 Jul 2017.
  136. Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, The University of Osaka.
  137. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
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