One-step smoothing splines instrumental regression

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Date

27 juillet 2023

Type de document
Périmètre
Identifiant
  • 2307.14867
Collection

arXiv

Organisation

Cornell University




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Jad Beyhum et al., « One-step smoothing splines instrumental regression », arXiv - économie


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Résumé 0

We extend nonparametric regression smoothing splines to a context where there is endogeneity and instrumental variables are available. Unlike popular existing estimators, the resulting estimator is one-step and relies on a unique regularization parameter. We derive uniform rates of the convergence for the estimator and its first derivative. We also address the issue of imposing monotonicity in estimation and extend the approach to a partly linear model. Simulations confirm the good performances of our estimator compared to two-step procedures. Our method yields economically sensible results when used to estimate Engel curves.

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