How does the economic structure break change the forecast effect of money and credit on output? : evidence based on machine learning algorithms
Year of publication: |
2024
|
---|---|
Authors: | Lu, Yao ; Zhao, Zhihui ; Tian, Yuan ; Zhan, Minghua |
Published in: |
Pacific-Basin finance journal. - Amsterdam [u.a.] : Elsevier, ISSN 0927-538X, ZDB-ID 2013015-6. - Vol. 84.2024, Art.-No. 102325, p. 1-19
|
Subject: | Credit | Machine learning algorithm | Money | Structural break | Künstliche Intelligenz | Artificial intelligence | Strukturbruch | Prognoseverfahren | Forecasting model | Algorithmus | Algorithm | Geldmenge | Money supply | Bruttoinlandsprodukt | Gross domestic product |
-
Nowcasting Chinese GDP in a data-rich environment : lessons from machine learning algorithms
Zhang, Qin, (2023)
-
Nowcasting nominal GDP with the credit-card augmented divisia monetary aggregates
Barnett, William A., (2016)
-
Newsvendor problems with demand shocks and unknown demand distributions
O'Neil, Shawn, (2016)
- More ...
-
Does Digital Finance Change the Stability of the Money Demand Function? Evidence from China
Lu, Yao, (2022)
-
Does digital finance change the stability of money demand function? : evidence from China
Zhan, Minghua, (2023)
-
Lu, Yao, (2024)
- More ...