Smoothness Priors and Nonlinear Regression / Robert J. Shiller.

Format:

Book

Author/Creator:

Shiller, Robert J.

Contributor:

National Bureau of Economic Research.

Series:

Technical Working Paper Series (National Bureau of Economic Research) no. t0025.

NBER technical working paper series no. t0025

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 1982.

Summary:

In applications, the linear multiple regression model is often modified to allow for nonlinearity in an independent variable. It is argued here that in practice it may often be desirable to specify a Bayesian prior that the unknown functional form is "simple" or "uncomplicated" rather than to parametize the nonlinearity. "Discrete smoothness priors" and "continuous smoothness priors" are defined and it is shown how posterior mean estimates can easily be derived using ordinary multiple linear regression modified with dummy variables and dummy observations. Relationships with spline and polynomial interpolation are pointed out. Illustrative examples of cost function estimation are provided.

Notes:

Print version record

August 1982.