Rejoinder: Matched Pairs and the Future of Cluster-Randomized Experiments

Rejoinder to "The Essential Role of Pair Matching in Cluster-Randomized Experiments, with Application to the Mexican Universal Health Insurance Evaluation" [arXiv:0910.3752]Comment: Published in at http://dx.doi.org/10.1214/09-STS274REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Canvassers tend to seek out supporters who are like themselves, and that's not good for political participation.

Petition canvassers play an important role as political recruiters by introducing citizens to political issues and seeking their support. But not much is known about how these canvassers decide whom to recruit or about their methods. Research by Clayton Nall, Benjamin Schneer, and Daniel Carpenter sets forth a model of political recruiting that changes depending on canvassers' experiences, is constrained ..

The Essential Role of Pair Matching in Cluster-Randomized Experiments, with Application to the Mexican Universal Health Insurance Evaluation

A basic feature of many field experiments is that investigators are only able to randomize clusters of individuals—such as households, com- munities, firms, medical practices, schools or classrooms—even when the individual is the unit of interest. To recoup the resulting efficiency loss, some studies pair similar clusters and randomize treatment within pairs. However, many other studies avoid pairing, in part because of claims in the litera- ture, echoed by clinical trials standards organizations, that this matched-pair, cluster-randomization design has serious problems. We argue that all such claims are unfounded. We also prove that the estimator recommended for this design in the literature is unbiased only in situations when matching is unnecessary; its standard error is also invalid. To overcome this problem without modeling assumptions, we develop a simple design-based estimator with much improved statistical properties. We also propose a model-based approach that includes some of the benefits of our design-based estimator as well as the estimator in the literature. Our methods also address individual- level noncompliance, which is common in applications but not allowed for in most existing methods. We show that from the perspective of bias, efficiency, power, robustness or research costs, and in large or small samples, pairing should be used in cluster-randomized experiments whenever feasible; failing to do so is equivalent to discarding a considerable fraction of one’s data. We develop these techniques in the context of a randomized evaluation we are conducting of the Mexican Universal Health Insurance Program.Governmen

The Complications of Controlling Agency Time Discretion: FDA Review Deadlines and Postmarket Drug Safety

Public agencies have discretion on the time domain, and politicians deploy numerous policy instruments to constrain it. Yet little is known about how administrative procedures that affect timing also affect the quality of agency decisions. We examine whether administrative deadlines shape decision timing and the observed quality of decisions. Using a unique and rich dataset of FDA drug approvals that allows us to examine decision timing and quality, we find that this administrative tool induces a piling of decisions before deadlines, and that these “just-before-deadline” approvals are linked with higher rates of postmarket safety problems (market withdrawals, severe safety warnings, safety alerts). Examination of data from FDA advisory committees suggests that the deadlines may impede quality by impairing late-stage deliberation and agency risk communication. Our results both support and challenge reigning theories about administrative procedures, suggesting they embody expected control-expertise trade-offs, but may also create unanticipated constituency losses.Governmen

Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme

Background: We assessed aspects of Seguro Popular, a programme aimed to deliver health insurance, regular and preventive medical care, medicines, and health facilities to 50 million uninsured Mexicans. Methods: We randomly assigned treatment within 74 matched pairs of health clusters—ie, health facility catchment areas—representing 118 569 households in seven Mexican states, and measured outcomes in a 2005 baseline survey (August, 2005, to September, 2005) and follow-up survey 10 months later (July, 2006, to August, 2006) in 50 pairs (n=32 515). The treatment consisted of encouragement to enrol in a health-insurance programme and upgraded medical facilities. Participant states also received funds to improve health facilities and to provide medications for services in treated clusters. We estimated intention to treat and complier average causal effects non-parametrically. Findings: Intention-to-treat estimates indicated a 23% reduction from baseline in catastrophic expenditures (1·9% points; 95% CI 0·14–3·66). The effect in poor households was 3·0% points (0·46–5·54) and in experimental compliers was 6·5% points (1·65–11·28), 30% and 59% reductions, respectively. The intention-to-treat effect on health spending in poor households was 426 pesos (39–812), and the complier average causal effect was 915 pesos (147–1684). Contrary to expectations and previous observational research, we found no effects on medication spending, health outcomes, or utilisation. Interpretation: Programme resources reached the poor. However, the programme did not show some other effects, possibly due to the short duration of treatment (10 months). Although Seguro Popular seems to be successful at this early stage, further experiments and follow-up studies, with longer assessment periods, are needed to ascertain the long-term effects of the programme. Funding: Mexican Ministry of Health, the National Institute of Public Health of Mexico, and Harvard University Institute for Quantitative Social ScienceGovernmen

Replication data for: The Road to Conflict: How the American Highway System Divides Communities and Polarizes Politics

Enter your study abstract hereWhat explains the partisan divide between Democratic urban areas and their Republican peripheries? This project develops one explanation: that spatial policies–those that shape geographic space–change politics by manipulating the geographic distribution of citizens. This argument is developed by focusing on the impact of the Interstate Highway System, the largest public works project in American history, on American political geography. Drawing upon qualitativ e and quantitative historical data, I show that transportation networks like the Interstate Highway System catalyze processes by which Democrats and Republicans sort into separate communities. This partisan geographic divergence culminates in a growing partisan gap in place-based policy interests. Highways’ contribution to geographic partisan sorting is tested through two empirical analyses that apply matching, regression, and other methods of causal inference to GIS data. Exploiting a database containing project histories from every segment of the Interstate Highway System, the first analysis shows that suburban counties in which Interstate highways were built became more Republican than they would have been otherwise. The second analysis shows that these suburban changes gave rise to a larger urban-suburban partisan gap in metropolitan areas with dense Interstate highway networks. Survey data from the 1970s and 1980s suggest that highways operated through an individual mechanism in which partisan differences in preference for suburban residence were facilitated by the new transportation infrastructure. The final chapters build upon these key findings to examine highways’ additional social and policy implications. The first of these chapters shows that highways a ffected a range of socioeconomic correlates of partisanship, both in suburban areas and across the urban-suburban divide. A final chapter explores whether this partisan divide extends to attitudes towards highways and their alternatives. Contrary to the bipartisan adage that “there are no Republican roads or Democratic roads,” national and local opinion surveys reveal that Republicans are more likely than Democrats to favor spending on highways over their alternatives, and this partisan gap is larger when respondents are forced to make a tradeoff between different transportation options. Changes in the geographic distribution of partisans thus have coincided with a partisan gap around the very policies that contributed to partisan geographic polarization. Complete date fields below for: time period covered; and date of collectio

Replication data for: The Political Consequences of Spatial Policies: How Interstate Highways Facilitated Geographic Polarization

In the postwar era, Democratic voters have become increasingly more likely than Republican voters to live in urban counties. Public policies that shape geographic space have been a major contributor to this geographic polarization. This article examines the effect of the Interstate Highway System, the largest public works project in American history, on this phenomenon. Drawing on a database of US highway construction since the passage of 1956 highway legislation, it shows that suburban Interstate highways made suburban counties less Democratic, especially in the South and where highways were built earlier. Metropolitan areas with denser Interstate networks also became more polarized. Analysis of the Youth-Parent Socialization Panel Study (1965–97) reveals individual-level mechanisms underlying these changes: Interstates drew more white and affluent residents, who tended to be Republican, to the suburbs

Pre-Analysis Plan for: The Ideological Contradictions of NIMBYism

This dataverse contains a preanalysis plan for a research project tentatively titled, "The Ideological Contradictions of NIMBYism." It includes an EGAP-formatted project description and outlines the analyses that will be conducted on a survey experiment performed on an online sample in California's Santa Clara and Alameda Counties

Replication Data for "Why Partisans Don't Sort: The Constraints on Partisan Segregation"

Contains data and R scripts for the JOP article, "Why Partisans Don't Sort: The Constraints on Political Segregation." When downloading tabular data files, ensure that they appear in your working directory in CSV format

Why partisans do not sort: The constraints on political segregation

© 2016 by the Southern Political Science Association. All rights reserved. Social divisions between American partisans are growing, with Republicans and Democrats exhibiting homophily in a range of seemingly nonpolitical domains. It has been widely claimed that this partisan social divide extends to Americans' decisions about where to live. In two original survey experiments, we confirm that Democrats are, in fact, more likely than Republicans to prefer living in more Democratic, dense, and racially diverse places. However, improving on previous studies, we test respondents' stated preferences against their actual moving behavior. While partisans differ in their residential preferences, on average they are not migrating to more politically distinct communities. Using zip-codelevel census and partisanship data on the places where respondents live, we provide one explanation for this contradiction: by prioritizing common concerns when deciding where to live, Americans forgo the opportunity to move to more politically compatible communities