A Time Series Synthetic Control Causal Evaluation of the UK’s Mini-Budget Policy on Stock Market

Yan Zhang, Zudi Lu*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

In this paper, we propose a modified synthetic control causal analysis for time series data with volatility in terms of absolute value of return outcomes taken into account in constructing the prediction of potential outcomes for time series causal analysis. The consistency property of the synthetic weight parameter estimators is developed theoretically under a time series data-generating process framework. The application to evaluate the UK’s mini-budget policy, announced by the then Chancellor on 23 September 2022, which had significant implications for the stock market, is examined and analysed. Comparisons with traditional synthetic control and synthetic difference in difference (DID) methods for evaluation of the effect of the mini-budget policy on the UK’s stock market are also discussed. © 2024 by the authors.
Original languageEnglish
Article number3301
JournalMathematics
Volume12
Issue number20
Online published21 Oct 2024
DOIs
Publication statusPublished - Oct 2024

Research Keywords

  • causal inference
  • policy evaluation
  • synthetic control
  • time series analysis

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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