Semiparametric Estimations under Shape Constraints with Applications to Production Functions

• Departmental Seminar

Date and Location

Monday, January 14, 2013, 10:30 AM - 12:00 PM
3001 Plant and Environmental Sciences

Abstract

Economic theories often provide guidance on econometric modeling. We propose semiparametric estimators consistent with monotonicity and concavity constraints using the method of penalized splines. The shape constraints are maintained via integral transformations of spline basis expansions. We present an effective algorithm, the large sample properties, methods of inferences and of smoothing parameter selection of our estimators. We also consider multiple regressions under the framework of additive models. We conduct Monte Carlo simulations to illustrate the finite sample performance and usefulness of the proposed method. We applied the proposed methods to estimate: (a) the relationship between individuals' degree of optimism and risk tolerance; (b) a production function with multiple inputs.

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