VT meta-analyses Flashcards
what are the main meta-analyses?
- Smets & van Ham (2013) - indv
- Geys (2006) - agg
- Cancela & Geys (2016) - agg
- Frank & Martinez i Coma (2021) - agg
- Stockemer (2017) - agg
what does Smets & van Ham (2013) argue?
Data
- we have chosen to consider only peer-reviewed journal articles
- only national elections - not local or European
- for more pragmatic reasons we focus on studies published in 10 top-journals in political science
- In terms of validity then, validated turnout data is the most robust, but at the same time the most difficult data to obtain, while reported turnout data (and turnout intention data) are more prone to bias, but generally easier to obtain. As Table 3 demonstrates, about 82% of the studies included in this paper measure turnout as reported turnout, 11% of the studies use validated turnout, and 7% use turnout intention
- In 90 articles we found over 170 independent variables used to explain voter turnout, none of which were included in all studies. Only 8 of these independent variables were included in more than 25% of the studies we reviewed - Even the two most common independent variables – age and education – were included in only 72% and 74% of studies respectively
findings:
important:
- age; education; region; residential mobility
- political interest, pol knowledge, party ID
- voted in prev elections, media exposure, mobilisation (partisan & non-partisan)
not important:
- gender, occupation type and status, race, citizenship
- union membership
- election closeness
- trust in institutions
what do Frank & i Coma (2021) argue?
method - extreme bound analysis
data
- out of 127 distinct variables, less than 1/2 (44%) appear more than once
- even the most frequent (C.V.) is only in 75% of examined studies
- among the 55 that appear more than once, over half (57%) measured in more than one way
- identify 44 articles on turnout from 1986 to 2017.
- These articles include over 127 potential predictors of voter turnout, and we collect data on seventy of these variables. Using extreme bounds analysis, we run over 15 million regressions to determine which of these 70 variables are robustly associated with voter turnout in 579 elections in 80 democracies from 1945 to 2014
- 22 variables robustly associated w turnout
important:
- concurrent elections
- election closeness
- prev turnout
- comp voting
- inflation
- econ globalisation
Negative effect of increase in party competition - V weird - contrary to the rest of the literature
- Dan suggested potential explanation - new democracies entering the sample w low turnout & high competitiveness
what does Geys (2006) find?
important:
- population size
- election closeness
use 83 aggregate studies
what does Stockemer (2017) find?
important:
- comp voting
- election is important
- small country
inconclusive at best:
- type of electoral system - find PR only important for a minority of cases
- no of parties
- development
- income inequalities
- electoral closeness
data:
- I engage in a systematic search of English-language articles that use macro-level turnout as the dependent variable. This search strategy yielded 135 articles published between 2004 and 2013
- Given that I use a large sample and include more studies from the developing world, my results are somewhat more conservative than Cancela and Geys’ (2016) findings.
what does Cancela & Geys (2016) argue?
- same as Stockemer for important except also incl others such as voter registration, PR & electoral closeness
- incl national and sub-national
- we add 102 studies published between 2002 and 2015 to the initial sample of 83 studies from Geys (2006)
- We find that campaign expenditures, election closeness and registration requirements have more explanatory power in national elections, whereas population size and composition, concurrent elections, and the electoral system play a more important role for explaining turnout in subnational elections.
