Estimation of Causal Effect of treatment via Fuzzy Regression Discontinuity Designs
DOI:
https://doi.org/10.33095/jeas.v28i134.2424Keywords:
Fuzzy Regression Discontinuity, Causal effect of the treatment, Robust Local Polynomial Regression Estimators, Coverage Error Optimality.Abstract
In some cases, researchers need to know the causal effect of the treatment in order to know the extent of the effect of the treatment on the sample in order to continue to give the treatment or stop the treatment because it is of no use. The local weighted least squares method was used to estimate the parameters of the fuzzy regression discontinuous model, and the local polynomial method was used to estimate the bandwidth. Data were generated with sample sizes (75,100,125,150 ) in repetition 1000. An experiment was conducted at the Innovation Institute for remedial lessons in 2021 for 72 students participating in the institute and data collection. Those who used the treatment had an increase in their score after treatment by 25.95%.
Paper type This Research is extracted from a master's thesis on statistics entitled “Estimation of Fuzzy Regression Discontinuity model with the application"
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