Macroeconomic Nowcasting and Forecasting with Big Data
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- Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
- Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
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Citations
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Cited by:
- Martin Ellison & Sang Seok Lee & Kevin Hjortshøj O'Rourke, 2020.
"The Ends of 30 Big Depressions,"
NBER Working Papers
27586, National Bureau of Economic Research, Inc.
- Ellison, Martin & Lee, Sang Seok & O'Rourke, Kevin Hjortshøj, 2020. "The Ends of 30 Big Depressions," CEPR Discussion Papers 15061, C.E.P.R. Discussion Papers.
- Martin Ellison & Sang Seok Lee & Kevin Hjortshøj O’Rourke, 2020. "The Ends of 30 Big Depressions," Economics Series Working Papers 896, University of Oxford, Department of Economics.
- Kevin Hjortshøj O’Rourke & Sang Seok Lee & Martin Ellison, 2020. "The Ends of 30 Big Depressions," Working Papers 20200035, New York University Abu Dhabi, Department of Social Science, revised May 2020.
- Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018.
"Bayesian Vector Autoregressions,"
The Warwick Economics Research Paper Series (TWERPS)
1159, University of Warwick, Department of Economics.
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- Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian Vector Autoregressions," Discussion Papers 1808, Centre for Macroeconomics (CFM).
- Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Sciences Po publications 18, Sciences Po.
- Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," Bank of England working papers 756, Bank of England.
- Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Documents de Travail de l'OFCE 2018-18, Observatoire Francais des Conjonctures Economiques (OFCE).
- Liyang Tang, 2020. "Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment," Papers 2005.08735, arXiv.org.
- Alkhareif, Ryadh M. & Barnett, William A., 2020. "Nowcasting Real GDP for Saudi Arabia," MPRA Paper 104278, University Library of Munich, Germany.
- David Kohns & Arnab Bhattacharjee, 2020. "Developments on the Bayesian Structural Time Series Model: Trending Growth," Papers 2011.00938, arXiv.org.
- Jonas E. Arias & Minchul Shin, 2020. "Tracking U.S. Real GDP Growth During the Pandemic," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 5(3), pages 9-14, September.
- Peter Fuleky, 2020. "Nowcasting the Trajectory of the COVID-19 Recovery," Working Papers 2020-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
- Ryadh M. Alkhareif & William 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.
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- Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Sokol, Andrej & Monti, Francesca, 2020. "Nowcasting with large Bayesian vector autoregressions," Working Paper Series 2453, European Central Bank.
- Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
- Bhadury, Soumya & Ghosh, Saurabh & Kumar, Pankaj, 2019. "Nowcasting GDP Growth Using a Coincident Economic Indicator for India," MPRA Paper 96007, University Library of Munich, Germany.
- , 2020. "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper RWP 20-09, Federal Reserve Bank of Kansas City.
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- Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
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More about this item
Keywords
business cycle analysis; high-dimensional data; monitoring economic conditions; real-time data flow;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2018-02-05 (Big Data)
- NEP-FOR-2018-02-05 (Forecasting)
- NEP-HPE-2018-02-05 (History & Philosophy of Economics)
- NEP-MAC-2018-02-05 (Macroeconomics)
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