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A Practical Introduction to Regression Discontinuity Designs
In this Element and its accompanying second Element, A Practical Introduction to Regression Discontinuity Designs: Extensions, Matias Cattaneo, Nicolás Idrobo, and Rocıìo Titiunik provide an accessible and practical guide for the analysis and interpretation of regression discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. In this Element, the authors discuss the foundations of the canonical Sharp RD design, which has the following features: (i) the score is continuously distributed and has only one dimension, (ii) there is only one cutoff, and (iii) compliance with the treatment assignment is perfect. In the second Element, the authors discuss practical and conceptual extensions to this basic RD setup.
Handbook of Matching and Weighting Adjustments for Causal Inference
An observational study infers the effects caused by a treatment, policy, program, intervention, or exposure in a context in which randomized experimentation is unethical or impractical. One task in an observational study is to adjust for visible pretreatment differences between the treated and control groups. Multivariate matching and weighting are two modern forms of adjustment. This handbook provides a comprehensive survey of the most recent methods of adjustment by matching, weighting, machine learning and their combinations. Three additional chapters introduce the steps from association to causation that follow after adjustments are complete. When used alone, matching and weighting do not use outcome information, so they are part of the design of an observational study. When used in conjunction with models for the outcome, matching and weighting may enhance the robustness of model-based adjustments. The book is for researchers in medicine, economics, public health, psychology, epidemiology, public program evaluation, and statistics who examine evidence of the effects on human beings of treatments, policies or exposures.
A Practical Introduction to Regression Discontinuity Designs
In this Element, which continues our discussion in Foundations, the authors provide an accessible and practical guide for the analysis and interpretation of Regression Discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. The focus is on extensions to the canonical sharp RD setup that we discussed in Foundations. The discussion covers (i) the local randomization framework for RD analysis, (ii) the fuzzy RD design where compliance with treatment is imperfect, (iii) RD designs with discrete scores, and (iv) and multi-dimensional RD designs.
Advances in Experimental Political Science
Novel collection of essays addressing contemporary trends in political science, covering a broad array of methodological and substantive topics.
Beyond Turnout
Beyond Turnout crafts a new theory that considers the downstream consequences of compulsory voting for both citizens and political parties. This theory is comprehensively tested through data from dozens of countries, with a particular focus on Argentina and Switzerland.
Does Relative Deprivation Condition the Effects of Social Protection Programs on Political Support? Experimental Evidence from Pakistan∗
Could perceived relative economic standing affect citizens’ support for political leaders and institutions? We explore this question by examining Pakistan’s national unconditional cash transfer program, the Benazir Income Support Program (BISP). Leveraging a regression discontinuity approach using BISP’s administrative data and an original survey experiment, we find that perceptions of relative deprivation color citizen reactions to social protection. When citizens do not feel relatively deprived, receiving cash transfers has little sustained effect on individuals’ reported level of support for their political system and its leaders. However, when citizens feel relatively worse off, those receiving cash transfers become more politically satisfied, while those denied transfers become more politically disgruntled. Moreover, the magnitude of the reduction in political support among non-beneficiaries is larger than the magnitude of the increase in political support among beneficiaries. This has important implications for our understanding of the political ramifications of rising perceived inequality.
Unequal Democracies
Introduces the latest research on political inequality and its relationship to economic inequalities in North America and Western Europe.
Housing, health, and happiness
Despite the importance of housing for people's well-being, there has been little work done to assess the causal impact of housing and housing improvement programs on health and welfare. In this paper the authors help fill this gap by investigating the impact of a large-scale effort by the Mexican government to replace dirt floors with cement floors on child health and adult happiness. They find that replacing dirt floors with cement floors significantly reduces parasitic infestations in young children, reduces diarrhea, reduces anemia, and improves cognitive development. Finally, they also find that this program leave adults substantially better off, as measured by satisfaction with their housing and quality of life and by their significantly lower rates of depression and perceived stress.
Regression Discontinuity Designs
The regression discontinuity (RD) design is one of the most widely used nonexperimental methods for causal inference and program evaluation. Over the last two decades, statistical and econometric methods for RD analysis have expanded and matured, and there is now a large number of methodological results for RD identification, estimation, inference, and validation. We offer a curated review of this methodological literature organized around the two most popular frameworks for the analysis and interpretation of RD designs: the continuity framework and the local randomization framework. For each framework, we discuss three main topics: (a) designs and parameters, focusing on different types of RD settings and treatment effects of interest; (b) estimation and inference, presenting the most popular methods based on local polynomial regression and methods for the analysis of experiments, as well as refinements, extensions, and alternatives; and (c) validation and falsification, summarizing an array of mostly empirical approaches to support the validity of RD designs in practice.
Time Counts
How to study the past using data Quantitative Analysis for Historical Social Science advances historical research in the social sciences by bridging the divide between qualitative and quantitative analysis. Gregory Wawro and Ira Katznelson argue for an expansion of the standard quantitative methodological toolkit with a set of innovative approaches that better capture nuances missed by more commonly used statistical methods. Demonstrating how to employ such promising tools, Wawro and Katznelson address the criticisms made by prominent historians and historically oriented social scientists regarding the shortcomings of mainstream quantitative approaches for studying the past. Traditional stat...
