Enhancing a Geographic Regression Discontinuity Design Through Matching to Estimate the Effect of Ballot Initiatives on Voter Turnout

Abstract

Ballot initiatives allow the public to vote directly on public policy. The literature in political science has attempted to document whether the presence of an initiative can increase voter turnout. We study this question for an initiative that appeared on the ballot in 2008 in Milwaukee, Wisconsin, using a natural experiment based on geography. This form of natural experiment exploits variation in geography where units in one geographic area receive a treatment whereas units in another area do not. When assignment to treatment via geographic location creates as-if random variation in treatment assignment, adjustment for baseline covariates is unnecessary. In many applications, however, some adjustment for baseline covariates may be necessary. As such, analysts may wish to combine identification strategies-using both spatial proximity and covariates. We propose a matching framework to incorporate information about both geographic proximity and observed covariates flexibly which allows us to minimize spatial distance while preserving balance on observed covariates. This framework is also applicable to regression discontinuity designs that are not based on geography. We find that the initiative on the ballot in Milwaukee does not appear to have increased turnout.

Does Additional Spending Help Urban Schools? An Evaluation Using Boundary Discontinuities

“…To ensure this, we match schools not only on geographical location as in standard geographical boundary discontinuity design, but also on an observable school-level proxy for a key element in the formula that determines central government grants to LEAs-the proportion of children eligible for FSM. This matched, geographical regression discontinuity design is broadly similar to that proposed by Keele et al (2015), who describe the corresponding identifying condition as "conditional geographic treatment ignorability". In the next sections, we set out the underlying structure of relationships between funding, socioeconomic characteristics and school performance that justifies this identification strategy, and set out the design in more detail.…”

“…However, here we are matching schools both on spatial location and on student free meal entitlement, and exploiting a discontinuity in funding with respect to only one of these-geographical location. The identification condition is thus one of "conditional ignorability": that is, conditional on the location of schools and the proportion of their students entitled to free meals, there are no confounders correlated with these LEA-level grant differences (see Keele et al 2015 for further discussion in the context of geographical boundary discontinuity designs). In the education literature, similar techniques have often been used to look at the impact of school test scores on house prices as well as being used in other areas of economics and social sciences.…”

Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate

“…Similarly, our approach extends naturally to settings where multiple running variables are present (see, e.g., Keele and Titiunik [36] and references therein). For example, in geographic RD designs, which involve two running variables, Keele et al [37] discuss how the methodological framework introduced herein can be used to conduct inference employing geographic RD variation.…”

“…For example, our approach can be used to justify (finite-sample exact) inference in RD contexts using panel or longitudinal data, specifying nonlinear models or relying on flexible "matching" on covariates techniques. For a recent example of such an approach, see Keele et al [37].…”

Essays in empirical political economics

“…The empirical strategy employed in this chapter resembles that proposed by Keele, Titiunik & Zubizarreta (2015) and used by Larreguy, Marshall & Snyder (2014), which can be understood as a combination of geographic regression discontinuity (GRD) design with matching techniques. By claiming that one of the main sources of selection is the municipality's location, the strategy employed compares each municipality that had appointed mayors with its most similar neighbor in terms of the Mahalanobis distance.…”