Interesting book on "Macroeconomic Forecasting in the Era of Big Data: theory and practice".
Editor: P. Fuleky
It is available here: https://www.springer.com/gp/book/9783030311490#aboutBook
Presents a comprehensive collection of big data tools used in macroeconomic forecasting.
Surveys the most recent developments in the field.
Offers algorithmic descriptions of big data techniques for forecasting.
Useful as a reference, a textbook, and a resource for professional forecasters.
Includes Dynamic Factor Models, BVARs, FAVARs, GVARs, Bayesian Model Averaging, Unit Roots and Cointegration, and much more!
[Thanks to Carlos Montes-Galdon for the suggestion!]
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1. https://github.com/FRBNY-TimeSeriesAnalysis/Nowcasting
This code implements the nowcasting framework described in "Macroeconomic Nowcasting and Forecasting with Big Data" by Brandyn Bok, Daniele Caratelli, Domenico Giannone, Argia M. Sbordone, and Andrea Tambalotti, Staff Reports 830, Federal Reserve Bank of New York (prepared for Volume 10 of the Annual Review of Economics).
Note: These example files do not exactly reproduce the New York Fed Staff Nowcasting Report released every Friday because data redistribution restrictions prevent us from providing the complete data set used in our model.
2. Large Bayesian Vector Autoregressions Joshua Chan (2020) In: P. Fuleky (Eds), Macroeconomic Forecasting in the Era of Big Data, 95-125, Springer, Cham
https://joshuachan.org/code/code_large_BVAR.html