Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Desenho Diferença-em-Discontinuidades× | Regressão por Mínimos Quadrados Ordinários (MQO)× | |
|---|---|---|
| Área≠ | Inferência causal | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 2016 | 2019 |
| Autor original≠ | Grembi, Nannicini & Troiano | Wooldridge (textbook treatment); classical least squares |
| Tipo≠ | Hybrid quasi-experimental causal design (RDD + DID) | Linear regression |
| Fonte seminal≠ | Grembi, V., Nannicini, T. & Troiano, U. (2016). Do Fiscal Rules Matter? A Difference-in-Discontinuities Design. American Economic Journal: Applied Economics, 8(3), 1-30. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Outros nomes≠ | diff-in-disc, DiD-RDD, Süreksizliklerde Fark (Difference-in-Discontinuities) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Relacionados | 5 | 5 |
| Resumo≠ | Difference-in-Discontinuities is a hybrid quasi-experimental design that fuses regression discontinuity (RDD) with difference-in-differences (DID), introduced by Grembi, Nannicini and Troiano (2016). It compares the discontinuity at the same cutoff value across two periods to isolate a causal effect. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
| ScholarGateConjunto de dados ↗ |
|
|