Does Partisan Conflict Predict a Reduction in US Stock Market (Realized) Volatility? Evidence from a Quantile-on-Quantile Regression Model

Rangan Gupta, Christian Pierdzioch, Refk Selmi and Mark Wohar ()

No 201744, Working Papers from University of Pretoria, Department of Economics

Abstract: Theory suggests that partisan conflict negatively affects the possibility of economic policy change, implying that financial markets tend to operate under lower policy risk. Given that stock-return volatility measures risk, if the gridlock argument holds, stock–market volatility should be lower under divided than under a unified government. Using a partisan conflict index (PCI), we empirically confirm this theoretical argument for the U.S. stock market based on quantiles-based regressions. In particular, quantile-on-quantile regressions show that PCI tends to predict reduced volatility, with the effect being stronger at levels of volatility that are moderately high (i.e., beyond the median, but not at its extreme) for an increase in the predictor, especially with lower initial values (i.e., when PCI is at its lower quantiles).

Keywords: Partisan Conflict; Realized Volatility; Quantile Regressions (search for similar items in EconPapers)
JEL-codes: C22 E60 G15 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2017-06
New Economics Papers: this item is included in nep-mac, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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