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DOWDLE, ANDREW J (3) answer(s).
 
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ID:   080087


Civil wars, international conflicts and other determinants of paramilitary strength in Sub-Saharan Africa / Dowdle, Andrew J   Journal Article
Dowdle, Andrew J Journal Article
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Publication 2007.
Summary/Abstract Previous research on African military spending suggests the existence of civil strife as the best predictor of high levels of military spending. However, little is known about why some African nations maintain strong 'auxiliary' or paramilitary organizations while others do not. This study finds that the presence of civil or interstate war does not strengthen reserve or irregular forces. Civilian governments promote strong paramilitary organizations to counter any threat the regular military might pose to regime survivability as a form of clientelist politics
Key Words Africa  Military Spending  Defence Spending  Civil War 
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2
ID:   149333


Forecasting presidential nominations in 2016: #WePredictedClintonANDTrump / Dowdle, Andrew J; Adkins, Randall E ; Sebold, Karen ; Cuellar, Jarred   Journal Article
Dowdle, Andrew J Journal Article
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Summary/Abstract A number of scholars successfully modeled and predicted presidential nomination outcomes from 1996–2008. However, dramatic changes occurred in subsequent years that would seem to make replicating these results challenging at best. Building on those earlier studies, we utilize a series of OLS models that included measures of preprimary resources and early campaign successes or failures to forecast that Hillary Clinton and Donald Trump would win the Democratic and Republican presidential nominations in 2016. This outcome suggests that some fundamental factors governing nomination outcomes have not changed despite the conventional wisdom.
Key Words Forecasting  Clinton  Presidential Nominations  2016  Trump 
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3
ID:   177214


Fundamentals Matter: Forecasting the 2020 Democratic Presidential Nomination / Dowdle, Andrew J   Journal Article
Dowdle, Andrew J Journal Article
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Summary/Abstract Previous studies used pre-primary variables (e.g., endorsements, national polls, and fundraising) and momentum variables from the Iowa and New Hampshire contests to predict presidential nomination outcomes. Yet, races with no elite favorite and no clear frontrunner in polls, such as in the 2020 Democratic race, are more difficult to forecast. We replicate and extend two forecasting models from 1980 to 2016 used by Dowdle et al. (2016) to predict the 2020 results. Our models suggest that Joe Biden may have been a stronger frontrunner than expected but that subsequent models may need to incorporate other early contests, such as the South Carolina primary. Overall, our results also argue that the fundamental factors in winning presidential nominations have remained relatively stable.
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