A Practical Introduction to Regression Discontinuity Designs: Extensions

Cattaneo, Matias D.; Idrobo, Nicolás; Titiunik, Rocío

doi:10.48550/arxiv.2301.08958

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…If the score is below the cutoff, the unit is assigned to another cultural group. Thus, the jump exhibited by the observed outcomes of the two groups exactly at the cutoff can be used to estimate the difference in the groups' potential outcomes (Cattaneo et al, 2023;Imbens & Lemieux, 2008). Graphically, this local average treatment effect is represented by the local jump in the two solid curves of Figure 4.…”

Section: Identification Assumptionsmentioning

confidence: 99%

Identifying culture as cause: Challenges and opportunities

Lonati,

Lalive,

Efferson

2024

Evolut. Hum. Sci.

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Causal inference lies at the core of many scientific endeavours. Yet, answering causal questions is challenging, especially when studying culture as a causal force. Against this backdrop, this paper reviews research designs and statistical tools that can be used—together with strong theory and knowledge about the context of study—to identify the causal impact of culture on outcomes of interest. We especially discuss how overlooked strategies in cultural evolutionary studies can allow one to approximate an ideal experiment wherein culture is randomly assigned to individuals or entire groups (instrumental variables, regression discontinuity design, and epidemiological approach). In doing so, we also review the potential outcome framework as a tool to engage in causal reasoning in the cultural evolutionary field.

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Section: Identification Assumptionsmentioning

confidence: 99%

Identifying culture as cause: Challenges and opportunities

Lonati,

Lalive,

Efferson

2024

Evolut. Hum. Sci.

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“…Annotated key references for further information: Cattaneo et al ( 2020) introduce the fundamentals of regression-discontinuity designs, providing pragmatic guidance for analysis, including R and Stata code. Cattaneo et al (2023) consider extensions such as fuzzy regression-discontinuity designs. Huntington-Klein ( 2022) covers (among other things) regression-discontinuity designs, with a strong emphasis on data-generating processes and causal diagrams.…”

Section: Typical Analysis Modelmentioning

confidence: 99%

Natural Experiments: Missed Opportunities for Causal Inference in Psychology

Grosz,

Ayaita,

Arslan

et al. 2024

Advances in Methods and Practices in Psychological Science

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Knowledge about causal effects is essential for building useful theories and designing effective interventions. The preferred design for learning about causal effects is randomized experiments (i.e., studies in which the researchers randomly assign units to treatment and control conditions). However, randomized experiments are often unethical or unfeasible. On the other hand, observational studies are usually feasible but lack the random assignment that renders randomized experiments causally informative. Natural experiments can sometimes offer unique opportunities for dealing with this dilemma, allowing causal inference on the basis of events that are not controlled by researchers but that nevertheless establish random or as-if random assignment to treatment and control conditions. Yet psychological researchers have rarely exploited natural experiments. To remedy this shortage, we describe three main types of studies exploiting natural experiments (standard natural experiments, instrumental-variable designs, and regression-discontinuity designs) and provide examples from psychology and economics to illustrate how natural experiments can be harnessed. Natural experiments are challenging to find, provide information about only specific causal effects, and involve assumptions that are difficult to validate empirically. Nevertheless, we argue that natural experiments provide valuable causal-inference opportunities that have not yet been sufficiently exploited by psychologists.

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A Practical Introduction to Regression Discontinuity Designs: Extensions

Cited by 2 publications

References 26 publications

Identifying culture as cause: Challenges and opportunities

Identifying culture as cause: Challenges and opportunities

Natural Experiments: Missed Opportunities for Causal Inference in Psychology

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