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

Yan Zhang and Zudi Lu ()
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Yan Zhang: School of Mathematical Sciences, University of Southampton, Southampton SO17 1BJ, UK
Zudi Lu: Department of Biostatistics, City University of Hong Kong, Hong Kong SAR, China

Mathematics, 2024, vol. 12, issue 20, 1-25

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.

Keywords: causal inference; synthetic control; time series analysis; policy evaluation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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