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Volatility spillover between oil and stock prices: Structural connectedness based on a multi-sector DSGE model approach with Bayesian estimation

Ying Tung Chan and Hui Qiao

International Review of Economics & Finance, 2023, vol. 87, issue C, 265-286

Abstract: This paper examine the connectedness between oil and stock markets using the WTI oil price and 10 S&P 500 price subindices data from 1989 to 2021. We present a novel approach for constructing a connectedness index based on a dynamic stochastic general equilibrium (DSGE) model with Bayesian estimation technique. In contrast to existing approaches, our DSGE-based approach has the advantage of (i) incorporating a large number of shocks and effectively distinguish the demand and supply shocks to both oil and stock markets; (ii) allowing the conduction of policy and welfare analyses. By estimating the DSGE model, we find that demand shocks to oil and stock markets produce significant spillover effects compared to the supply shocks. We also show that the role of demand and supply shocks differ largely across sectors. We propose an oil-tax policy rule that can reduce the interconnectedness between oil and stock markets. The optimal oil tax rate that balances the tradeoff between systematic risk and social welfare is computed.

Keywords: Oil shocks; Connectedness; DSGE model; Bayesian estimation (search for similar items in EconPapers)
JEL-codes: E32 G15 Q43 Q48 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:87:y:2023:i:c:p:265-286

DOI: 10.1016/j.iref.2023.04.014

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