Estimation and Inference in Unstable Nonlinear Least Squares Models

Otilia Boldea and Alastair Hall

Centre for Growth and Business Cycle Research Discussion Paper Series from Economics, The University of Manchester

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.

Pages: 35 pages
Date: 2012
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Related works:
Journal Article: Estimation and inference in unstable nonlinear least squares models (2013)
Working Paper: Estimation and inference in unstable nonlinear least squares models (2010)
Working Paper: Estimation and Inference in Unstable Nonlinear Least Squares Models (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:man:cgbcrp:174

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