Additive Regression Splines With Irrelevant Categorical and Continuous Regressors

Shujie Ma and Jeffrey Racine

Department of Economics Working Papers from McMaster University

Abstract: We consider the problem of estimating a relationship using semiparametric additive regression splines when there exist both continuous and categorical regressors, some of which are irrelevant but this is not known a priori. We show that choosing the spline degree, number of subintervals, and bandwidths via cross-validation can automatically remove irrelevant regressors, thereby delivering 'automatic dimension reduction without the need for pre-testing. Theoretical underpinnings are provided, finite-sample performance is studied, and an illustrative application demonstrates the efficacy of the proposed approach in finite-sample settings. An R package implementing the methods is available from the Comprehensive R Archive Network (Racine and Nie (2011)).

Keywords: B-spline; discrete; kernel (search for similar items in EconPapers)
Pages: 37 pages
Date: 2012-08
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:mcm:deptwp:2012-07

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