Estimation and inference in unstable nonlinear least squares models

Otilia Boldea, Alastair R. Hall

Research output: Contribution to journalArticlepeer-review

42 Downloads (Pure)


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. © 2012 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)158-167
Number of pages9
JournalJournal of Econometrics
Issue number1
Publication statusPublished - Jan 2013


  • Multiple breaks
  • Nonlinear least squares
  • Smooth transition


Dive into the research topics of 'Estimation and inference in unstable nonlinear least squares models'. Together they form a unique fingerprint.

Cite this