Novel dynamic financial stress index and stress regimes in Pakistan: insights from dynamic PCA and Markov switching model

Mumtaz Ahmed, Muhammad Tahir and Abdulrhman Meero

Journal of Financial Economic Policy, 2025, vol. 18, issue 2, 308-324

Abstract: PurposeThis study aims to develop a financial stress index for Pakistan and figure out the stressful and non-stressful regimes for pre- and post-COVID-19 era by making use of available annual time-series data from January 1996 to December 2020.Design/methodology/approachTwo state-of-the-art approaches are used to carry out empirical analysis. First, the generalized dynamic principal components analysis for constructing financial stress index, and second, Markov regime-switching model.FindingsThe empirical results support the hypothesis that economic and political risks play a key role in Pakistan’s greater degree of financial stress in addition to financial market stress. The banking sectors and stock market are found to be among the major contributors to financial stress in both pre- and post-COVID-19 eras. Furthermore, the estimation of the transition probabilities indicates that the model has a high probability of keeping its current state, resulting in only a few state shifts.Originality/valueIn contrast to the existing studies, which typically transform the indicators into a stationary state before analysis and the resultant index is likely to lose of data originality, this study makes use of state-of-the-art recently developed generalized dynamic principal components analysis to develop financial stress index. In addition, Markov regime-switching model is used in this study to distinguish between stressful and unstressful periods of the economy.

Keywords: Generalized principal components analysis; Markov regime model; COVID-19 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jfeppp:jfep-12-2024-0373

DOI: 10.1108/JFEP-12-2024-0373

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