Macroeconomic predictions using payments data and machine learning / by James T. E. Chapman and Ajit Desai.: FB3-5/2022-10E-PDF
"This paper demonstrates: (a) that payments systems data which capture a variety of economic transactions can assist in estimating the state of the economy in real time and (b) that machine learning can provide a set of econometric tools to effectively handle a wide variety in payments data and capture sudden and large effects from a crisis"--Abstract.
Permanent link to this Catalogue record:
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| Department/Agency | Bank of Canada, issuing body. |
|---|---|
| Title | Macroeconomic predictions using payments data and machine learning / by James T. E. Chapman and Ajit Desai. |
| Series title | Staff working paper = Document de travail du personnel, 1701-9397 ; 2022-10 |
| Publication type | Series - View Master Record |
| Language | [English] |
| Format | Electronic |
| Electronic document | |
| Note(s) | "Last updated: March 3, 2022." Includes bibliographical references (pages 27-31). |
| Publishing information | Ottawa, Ontario, Canada : Bank of Canada = Banque du Canada, 2022. ©2022 |
| Author / Contributor | Chapman, James T. E., author. |
| Description | 1 online resource (ii, 44 pages) : charts. |
| Catalogue number |
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| Subject terms | Business cycles -- Econometric models. Cycles économiques -- Modèles économétriques. |
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