Inference when a nuisance parameter is not identified under the null hypothesis

Bruce E. Hansen
"Inference when a nuisance parameter is not identified under the null hypothesis"
Econometrica (1996)

Program and Data Files

This program replicates the empirical work reported in the above paper.

The program estimates a threshold autoregression (TAR) by least squares, and tests the hypothesis of linearity using the asymptotic simulated p-values.

Gauss Programs and Data

Matlab Programs and Data

R Programs and Data

Stata Programs

Link to Abstract and PDF File of Paper

Some of the above material is based upon work supported by the National Science Foundation under Grants No. SES-9022176, SES-9120576, SBR-9412339, and SBR-9807111. Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the author(s), and do not necessarily reflect the views of the NSF.

Bruce E. Hansen "Inference when a nuisance parameter is not identified under the null hypothesis" Econometrica (1996)

Program and Data Files

Bruce E. Hansen
"Inference when a nuisance parameter is not identified under the null hypothesis"
Econometrica (1996)