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Econometrics of Machine Learning Methods in Economic Forecasting

Andrii Babii, Eric Ghysels, Jonas Striaukas

arXiv 21 Aug 2023 · Econometrics · 21 citations (OpenAlex)

arXiv:2308.10993 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper surveys the recent advances in machine learning method for economic forecasting. The survey covers the following topics: nowcasting, textual data, panel and tensor data, high-dimensional Granger causality tests, time series cross-validation, classification with economic losses.

Citation extraction

106
references
129
in-text mentions
106
distinct cited
2
self-citations
6,200
main-text words

appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Babii, Ghysels, and Striaukas (2022) Machine learning time series regressions with an application to nowcasting self0.69361100%
2Babii, Ghysels, and Striaukas (2022) High-Dimensional Granger Causality Tests with an Application to VIX and News self0.69351100%
3Barbaglia, Manzan, and Tosetti (2023) Forecasting loan default in Europe with machine learning0.64422100%
4Granger and Pesaran (2000) Economic and statistical measures of forecast accuracy0.64422100%
5Gu, Kelly, and Xiu (2020) Empirical asset pricing via machine learning0.64422100%
6Babii, Chen, Ghysels, and Kumar (2020) Binary choice with asymmetric loss in a data-rich environment: Theory and an application to racial justice0.58531100%
7Babii, Ghysels, and Pan (2022) Tensor Principal Component Analysis0.58531100%
8Adamek, Smeekes, and Wilms (2023) Lasso inference for high-dimensional time series0.51121100%
9Babii, Ball, Ghysels, and Striaukas (2022) Machine learning panel data regressions with heavy-tailed dependent data: Theory and application0.51121100%
10Babii, Ball, Ghysels, and Striaukas (2023) Panel Data Nowcasting: The Case of Price-Earnings Ratios0.51121100%

Showing the top 10 of 106 scored citations.