Salīdzināt metodes

	Daudzperiodu regresijas atšķirības dizains	Reģresijas atslēguma dizains panelī (Panel Data Regression Discontinuity Design)
Nozare	Cēloņsakarību secināšana	Cēloņsakarību secināšana
Saime	Regression model	Regression model
Izcelsmes gads	2010s–2020s	1960 (original RDD); panel extension codified 2000s–2010s
Autors	Cattaneo, Idrobo & Titiunik (foundations); extended by multiple authors for repeated-period settings	Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied work
Tips	Quasi-experimental causal inference	Causal inference / quasi-experimental
Pirmavots	Cattaneo, M. D., Idrobo, N., & Titiunik, R. (2020). A Practical Introduction to Regression Discontinuity Designs: Foundations. Cambridge University Press.	Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355.
Citi nosaukumi	multi-wave RD, repeated RDD, dynamic RD, multi-cutoff RDD	Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDD
Saistītās	3	5
Kopsavilkums	Multi-period Regression Discontinuity Design extends the classic RDD to settings where a cutoff-based treatment is applied in multiple waves, across repeated time periods, or with varying thresholds. By pooling or comparing period-specific discontinuity estimates, researchers gain statistical precision and can examine how causal effects evolve or persist over time.	Panel data regression discontinuity design (Panel RDD) combines the sharp local identification of a regression discontinuity with the within-unit variation available in repeated-observation panel data. Units are observed across multiple periods, and treatment is assigned based on whether a running variable crosses a known threshold. By leveraging both the discontinuity and panel structure, researchers can control for unobserved unit-level heterogeneity while estimating a causal treatment effect near the threshold.