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Macroeconomics and the reality of mixed frequency data

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Cited by:

  1. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.
  2. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
  3. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
  4. Alexander Chudik & Georgios Georgiadis, 2022. "Estimation of Impulse Response Functions When Shocks Are Observed at a Higher Frequency Than Outcome Variables," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 965-979, June.
  5. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
  6. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
  7. Martin Enilov & Yuan Wang, 2022. "Tourism and economic growth: Multi-country evidence from mixed-frequency Granger causality tests," Tourism Economics, , vol. 28(5), pages 1216-1239, August.
  8. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
  9. Chang, Tsangyao & Hsu, Chen-Min & Chen, Sheng-Tung & Wang, Mei-Chih & Wu, Cheng-Feng, 2023. "Revisiting economic growth and CO2 emissions nexus in Taiwan using a mixed-frequency VAR model," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 319-342.
  10. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2020. "Testing a large set of zero restrictions in regression models, with an application to mixed frequency Granger causality," Journal of Econometrics, Elsevier, vol. 218(2), pages 633-654.
  11. Bevilacqua, Mattia & Morelli, David & Tunaru, Radu, 2019. "The determinants of the model-free positive and negative volatilities," Journal of International Money and Finance, Elsevier, vol. 92(C), pages 1-24.
  12. Ferrara, Laurent & Mogliani, Matteo & Sahuc, Jean-Guillaume, 2022. "High-frequency monitoring of growth at risk," International Journal of Forecasting, Elsevier, vol. 38(2), pages 582-595.
  13. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
  14. Sarah Goldman & Virginia Zhelyazkova, 2023. "CO2 Emissions and GDP: A Revisited Kuznets Curve Version via a Panel Threshold MIDAS-VAR Model in Europe for a Recent Period," Economic Research Guardian, Weissberg Publishing, vol. 13(2), pages 82-99, December.
  15. Dufrénot, Gilles & Rhouzlane, Meryem & Vaccaro-Grange, Etienne, 2022. "Potential growth and natural yield curve in Japan," Journal of International Money and Finance, Elsevier, vol. 124(C).
  16. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
  17. del Barrio Castro, Tomás & Hecq, Alain, 2016. "Testing for deterministic seasonality in mixed-frequency VARs," Economics Letters, Elsevier, vol. 149(C), pages 20-24.
  18. Anna Samarina & Anh D.M. Nguyen, 2019. "Does monetary policy affect income inequality in the euro area?," Bank of Lithuania Working Paper Series 61, Bank of Lithuania.
  19. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
  20. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
  21. Seong, Byeongchan, 2020. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models," Economic Modelling, Elsevier, vol. 91(C), pages 463-468.
  22. Johnson Worlanyo Ahiadorme, 2022. "Monetary policy transmission and income inequality in Sub-Saharan Africa," Economic Change and Restructuring, Springer, vol. 55(3), pages 1555-1585, August.
  23. Morita, Hiroshi & 森田, 裕史, 2019. "Forecasting Public Investment Using Daily Stock Returns," Discussion paper series HIAS-E-88, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
  24. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
  25. Marcos Bujosa & Antonio García‐Ferrer & Aránzazu de Juan & Antonio Martín‐Arroyo, 2020. "Evaluating early warning and coincident indicators of business cycles using smooth trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 1-17, January.
  26. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
  27. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020. "Computationally efficient inference in large Bayesian mixed frequency VARs," Economics Letters, Elsevier, vol. 191(C).
  28. Wanhai You & Yuming Huang & Chien‐Chiang Lee, 2024. "Forecasting tourist flows in the COVID‐19 era using nonparametric mixed‐frequency VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 473-489, March.
  29. Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).
  30. Emanuele BACCHIOCCHI & Andrea BASTIANIN & Alessandro MISSALE & Eduardo ROSSI, 2016. "Structural Analysis With Mixed Frequency: Monetary Policy, Uncertainty And Gross Capital Flows," Departmental Working Papers 2016-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  31. Chari, Anusha & Dilts-Stedman, Karlye & Forbes, Kristin, 2022. "Spillovers at the extremes: The macroprudential stance and vulnerability to the global financial cycle," Journal of International Economics, Elsevier, vol. 136(C).
  32. Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 2016. "Is Industrial Production Still the Dominant Factor for the US Economy?," Swiss Finance Institute Research Paper Series 16-11, Swiss Finance Institute.
  33. Morita, Hiroshi, 2022. "Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach," Discussion paper series HIAS-E-118, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
  34. 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.
  35. Daniel Hopp, 2022. "Benchmarking Econometric and Machine Learning Methodologies in Nowcasting," Papers 2205.03318, arXiv.org.
  36. Dilara Berksun & Nukhet Dogan & M. Hakan Berument, 2021. "Electricity Consumption and Economic Growth in Turkey: A Mixed Frequency Var Approach," Energy Economics Letters, Asian Economic and Social Society, vol. 8(1), pages 95-108, June.
  37. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
  38. Thomas B. Götz & Alain W. Hecq, 2019. "Granger Causality Testing in Mixed‐Frequency VARs with Possibly (Co)Integrated Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 914-935, November.
  39. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
  40. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
  41. Zhang, Wei & He, Jie & Ge, Chanyuan & Xue, Rui, 2022. "Real-time macroeconomic monitoring using mixed frequency data: Evidence from China," Economic Modelling, Elsevier, vol. 117(C).
  42. Jack Fosten & Shaoni Nandi, 2023. "Nowcasting from cross‐sectionally dependent panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 898-919, September.
  43. Charfeddine, Lanouar & Klein, Tony & Walther, Thomas, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," QBS Working Paper Series 2018/03, Queen's University Belfast, Queen's Business School.
  44. Djalilov, Abdulaziz & Ülkü, Numan, 2021. "Individual investors’ trading behavior in Moscow Exchange and the COVID-19 crisis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
  45. William Barnett & Hyun Park, 2023. "Have Credit Card Services Become Important to Monetary Aggregation? An Application of Sign Restricted Bayesian VAR," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202304, University of Kansas, Department of Economics.
  46. Cotter, John & Hallam, Mark & Yilmaz, Kamil, 2023. "Macro-financial spillovers," Journal of International Money and Finance, Elsevier, vol. 133(C).
  47. Khalaf, Lynda & Kichian, Maral & Saunders, Charles J. & Voia, Marcel, 2021. "Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit," Journal of Econometrics, Elsevier, vol. 220(2), pages 589-605.
  48. Andrea Gazzani & Alejandro Vicondoa, 2020. "Bridge Proxy-SVAR: estimating the macroeconomic effects of shocks identified at high-frequency," Temi di discussione (Economic working papers) 1274, Bank of Italy, Economic Research and International Relations Area.
  49. Kanas, Angelos & Molyneux, Philip, 2020. "Do measures of systemic risk predict U.S. corporate bond default rates?," International Review of Financial Analysis, Elsevier, vol. 71(C).
  50. Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Working Paper Series 2206, European Central Bank.
  51. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
    • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  52. Deistler, Manfred & Koelbl, Lukas & Anderson, Brian D.O., 2017. "Non-identifiability of VMA and VARMA systems in the mixed frequency case," Econometrics and Statistics, Elsevier, vol. 4(C), pages 31-38.
  53. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2016. "Testing for Granger causality in large mixed-frequency VARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 418-432.
  54. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2020. "Structural analysis with mixed-frequency data: A model of US capital flows," Economic Modelling, Elsevier, vol. 89(C), pages 427-443.
  55. Akbar Marvasti & Sami Dakhlia, 2021. "Minimum information management and price‐abundance relationships in a fishery," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(4), pages 491-518, December.
  56. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
  57. Tom Dudda & Tony Klein & Duc Khuong Nguyen & Thomas Walther, 2022. "Common Drivers of Commodity Futures?," Working Papers 2207, Utrecht School of Economics.
  58. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
  59. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
  60. Yi-Hui Liu & Wei-Shiun Chang & Wen-Yi Chen, 2019. "Health progress and economic growth in the United States: the mixed frequency VAR analyses," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1895-1911, July.
  61. Michal Franta & David Havrlant & Marek Rusnák, 2016. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 165-185, December.
  62. Emmanuel C. Mamatzakis & Steven Ongena & Mike G. Tsionas, 2023. "The response of household debt to COVID-19 using a neural networks VAR in OECD," Empirical Economics, Springer, vol. 65(1), pages 65-91, July.
  63. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
  64. Lutz Kilian & Xiaoqing Zhou, 2023. "The Econometrics of Oil Market VAR Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 65-95, Emerald Group Publishing Limited.
  65. Zhang, Yuan-Yuan & Zhang, Yue-Jun, 2022. "The impact of institutional analyst forecast divergence on crude oil market: Evidence from the mixed frequency models," International Review of Financial Analysis, Elsevier, vol. 84(C).
  66. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK regional nowcasting using a mixed frequency vector autoregressive model," Working Papers 1805, University of Strathclyde Business School, Department of Economics.
  67. Maas, Daniel & Mayer, Eric & Rüth, Sebastian K., 2018. "Current account dynamics and the housing cycle in Spain," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 22-43.
  68. Anastasiou, Dimitrios & Drakos, Konstantinos, 2021. "European depositors’ behavior and crisis sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 117-136.
  69. Clements, Michael P. & Galvão, Ana Beatriz, 2021. "Measuring the effects of expectations shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 124(C).
  70. Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
  71. Zhang, Chen & Fang, Ying & Niu, Linlin, 2022. "Changing anchor of the renminbi: A Bayesian learning approach to the decade-long transition," Economic Modelling, Elsevier, vol. 116(C).
  72. Cipollini, Andrea & Mikaliunaite, Ieva, 2020. "Macro-uncertainty and financial stress spillovers in the Eurozone," Economic Modelling, Elsevier, vol. 89(C), pages 546-558.
  73. Alain Hecq & Marie Ternes & Ines Wilms, 2021. "Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions," Papers 2102.11780, arXiv.org, revised Mar 2022.
  74. Feng-Li Lin & Mei-Chih Wang, 2019. "Does economic growth cause military expenditure to go up? Using MF-VAR model," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(6), pages 3097-3117, November.
  75. Christian Grimme, 2023. "Uncertainty and the Cost of Bank versus Bond Finance," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(1), pages 143-169, February.
  76. Cleiton Guollo Taufemback, 2023. "Asymptotic Behavior of Temporal Aggregation in Mixed‐Frequency Datasets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 894-909, August.
  77. Anna Samarina & Anh D.M. Nguyen, 2024. "Does Monetary Policy Affect Income Inequality in the Euro Area?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(1), pages 35-80, February.
  78. Angelos Kanas & Panagiotis D. Zervopoulos, 2021. "Systemic risk, real GDP growth, and sentiment," Review of Quantitative Finance and Accounting, Springer, vol. 57(2), pages 461-485, August.
  79. Fernandes, Marcelo & Nunes, Clemens & Reis, Yuri, 2021. "What Drives the Nominal Yield Curve in Brazil?," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 40(2), April.
  80. Joel Hasbrouck, 2021. "Rejoinder on: Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 465-471.
  81. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
  82. Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.
  83. Dergiades, Theologos & Milas, Costas & Panagiotidis, Theodore, 2020. "A mixed frequency approach for stock returns and valuation ratios," Economics Letters, Elsevier, vol. 187(C).
  84. Gong, Xu & Sun, Yi & Du, Zhili, 2022. "Geopolitical risk and China's oil security," Energy Policy, Elsevier, vol. 163(C).
  85. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org.
  86. John Cotter & Mark Hallam & Kamil Yilmaz, 2017. "Mixed-Frequency Macro-Financial Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1704, Koc University-TUSIAD Economic Research Forum.
  87. Andrea Giovanni Gazzani & Alejandro Vicondoa, 2019. "Proxy-SVAR as a Bridge for Identification with Higher Frequency Data," 2019 Meeting Papers 855, Society for Economic Dynamics.
  88. Han Liu & Ying Liu & Yonglian Wang, 2021. "Exploring the influence of economic policy uncertainty on the relationship between tourism and economic growth with an MF-VAR model," Tourism Economics, , vol. 27(5), pages 1081-1100, August.
  89. Martin Enilov & Giorgio Fazio & Atanu Ghoshray, 2023. "Global connectivity between commodity prices and national stock markets: A time‐varying MIDAS analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2607-2619, July.
  90. Motegi, Kaiji & Sadahiro, Akira, 2018. "Sluggish private investment in Japan’s Lost Decade: Mixed frequency vector autoregression approach," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 118-128.
  91. Alessandri, Piergiorgio & Gazzani, Andrea & Vicondoa, Alejandro, 2023. "Are the effects of uncertainty shocks big or small?," European Economic Review, Elsevier, vol. 158(C).
  92. Hong, Yanran & Xu, Pengfei & Wang, Lu & Pan, Zhigang, 2022. "Relationship between the news-based categorical economic policy uncertainty and US GDP: A mixed-frequency Granger-causality analysis," Finance Research Letters, Elsevier, vol. 48(C).
  93. Xu, Qifa & Zhuo, Xingxuan & Jiang, Cuixia & Liu, Xi & Liu, Yezheng, 2018. "Group penalized unrestricted mixed data sampling model with application to forecasting US GDP growth," Economic Modelling, Elsevier, vol. 75(C), pages 221-236.
  94. Ding, Lili & Zhao, Zhongchao & Wang, Lei, 2022. "Probability density forecasts for natural gas demand in China: Do mixed-frequency dynamic factors matter?," Applied Energy, Elsevier, vol. 312(C).
  95. Giusto Andrea & İşcan Talan B., 2018. "The Rescaled VAR Model with an Application to Mixed-Frequency Macroeconomic Forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-16, September.
  96. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
  97. Liu, Yang & Han, Liyan & Yin, Libo, 2019. "News implied volatility and long-term foreign exchange market volatility," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 126-142.
  98. Bergin, Adele & Conroy, Niall & Garcia Rodriguez, Abian & Holland, Dawn & McInerney, Niall & Morgenroth, Edgar & Smith, Donal, 2017. "COSMO: A new COre Structural MOdel for Ireland," Papers WP553, Economic and Social Research Institute (ESRI).
  99. Angelos Kanas & Panagiotis D. Zervopoulos, 2022. "Federal home loan bank advances and systemic risk," Review of Quantitative Finance and Accounting, Springer, vol. 59(4), pages 1525-1557, November.
  100. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
  101. Paolo Berta & Paolo Paruolo & Stefano Verzillo & Pietro Giorgio Lovaglio, 2020. "A bivariate prediction approach for adapting the health care system response to the spread of COVID-19," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
  102. Thomas Walther & Lanouar Charfeddine & Tony Klein, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," Working Papers on Finance 1816, University of St. Gallen, School of Finance.
  103. Kanas, Angelos & Molyneux, Philip & Zervopoulos, Panagiotis D., 2023. "Systemic risk and CO2 emissions in the U.S," Journal of Financial Stability, Elsevier, vol. 64(C).
  104. Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
  105. Consolo, Agostino & Foroni, Claudia & Martínez Hernández, Catalina, 2021. "A mixed frequency BVAR for the euro area labour market," Working Paper Series 2601, European Central Bank.
  106. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
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