Local linear regression is a non-parametric statistical technique used to estimate the relationship between variables by fitting multiple linear regression models in localized subsets of the data. It is particularly useful for smoothing out noisy data and capturing trends without assuming a global form for the entire dataset. This method allows for flexibility in estimating causal relationships, especially in settings like regression discontinuity designs, where it can address issues related to sharp and fuzzy boundaries while employing appropriate bandwidth selection.
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