---
title: Forecasting Chinese Economy
url: https://www.ml-quant.com/papers/repec/bla-acctfi-v-63-y-2023-i-1-p-719-767/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:bla:acctfi:v:63:y:2023:i:1:p:719-767
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1111%2Facfi.13003%3Bh%3Drepec%3Abla%3Aacctfi%3Av%3A63%3Ay%3A2023%3Ai%3A1%3Ap%3A719-767
featured: 2024-07-10
citations: unknown
topic: Econometrics & Forecasting
---


# Forecasting Chinese Economy

The research indicates that mixed-frequency factor models provide better forecasts of the Chinese economy, although they were not significantly superior during the Global Financial Crisis.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1111%2Facfi.13003%3Bh%3Drepec%3Abla%3Aacctfi%3Av%3A63%3Ay%3A2023%3Ai%3A1%3Ap%3A719-767
- Identifier: RePEc:bla:acctfi:v:63:y:2023:i:1:p:719-767
- Released: 2023-02-22
- First featured: Quant Letter No. 56 (2024-07-10): https://www.ml-quant.com/issues/2024-07-10/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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