Estimation and inference in unstable nonlinear least squares models

A-Tier
Journal: Journal of Econometrics
Year: 2013
Volume: 172
Issue: 1
Pages: 158-167

Score contribution per author:

2.011 = (α=2.01 / 2 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

There is compelling evidence that many macroeconomic and financial variables are not generated by linear models. This evidence is based on testing linearity against either smooth nonlinearity or piece-wise linearity, but there is no framework that encompasses both. This paper provides an econometric framework that allows for both breaks and smooth nonlinearity in between breaks. We estimate the unknown break-dates simultaneously with other parameters via nonlinear least-squares. Using new central limit results for nonlinear processes, we provide inference methods on break-dates and parameter estimates and several instability tests. We illustrate our methods via simulated and empirical smooth transition models with breaks.

Technical Details

RePEc Handle
repec:eee:econom:v:172:y:2013:i:1:p:158-167
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-24