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Government Partisanship, Elections, and the Stock Market

Examining American and British Stock Returns, 1930–2000

Bibliographic Data

ID6231507
AuthorsDavid Leblang (0000-0003-1315-3092, University of Colorado System), Bumba Mukherjee (0000-0002-3453-601X, Florida State University)
Year2005
Volume49
Issue4
Pages780-802
Publication date2005-10-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Journal of Political Science (JOURNAL)
Journal identifiersISSN: 0092-5853 • E-ISSN: 1540-5907
PublisherWiley (PUBLISHER • GB)
DOI10.1111/j.1540-5907.2005.00155.x
OpenAlexW2014709540
LanguageEN
Citations received42
References cited28

We construct a model of speculative trading to examine how the mean and volatility of stock prices is affected both by government partisanship and by traders' expectations of electoral victory by the right‐wing or left‐wing party. Our model predicts that rational expectations of higher inflation under left‐wing administrations lowers the volume of stocks traded in the stock market. The decline in trading volume leads to a decrease in the mean and volatility of stock prices not only during the incumbency of left‐wing governments, but also when traders expect the left‐wing party to win elections. Conversely, expectation of lower inflation under right‐wing administrations leads to higher trading volume. This leads to an increase in the mean and volatility of stock prices during the tenure of right‐wing governments and when traders anticipate the right‐wing party to win elections. Daily and monthly data from U.S. and British equity markets between 1930 and 2000 statistically corroborate the predictions from our formal model

Economics · Equity (law · Financial economics · Monetary economics · Political science · Politics · Stock (firearms · Stock market · Victory · Volatility (finance · Financial Markets and Investment Strategies · Fiscal Policies and Political Economy · Monetary Policy and Economic Impact

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Unique citing works42
Citations per year2,1
Citation span2006 - 2026 (21)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 42

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