Automatic Selection for Non-linear Models

Jennifer Castle and David Hendry

No 473, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: Our strategy for automatic selection in potentially non-linear processes is: test for non-linearity in the unrestricted linear formulation; if that test rejects, specify a general model using polynomials, to be simplified to a minimal congruent representation; finally select by encompassing tests of specific non-linear forms against the selected model. Non-linearity poses many problems: extreme observations leading to non-normal (fat-tailed) distributions; collinearity between non-linear functions; usually more variables than observations when approximating the non-linearity; and excess retention of irrelevant variables; but solutions are proposed. A returns-to-education empirical application demonstrates the feasiblity of the non-linear automatic model selection algorithm Autometrics.

Keywords: Econometric methodology; Model selection; Autometrics; Non-linearity; Outlier; Returns to education (search for similar items in EconPapers)
JEL-codes: C22 C51 C87 (search for similar items in EconPapers)
Date: 2010-01-01
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (12)

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