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Estimation and inference in unstable nonlinear least squares models

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  • Boldea, Otilia
  • Hall, Alastair R.

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.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 172 (2013)
Issue (Month): 1 ()
Pages: 158-167

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Handle: RePEc:eee:econom:v:172:y:2013:i:1:p:158-167

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: Multiple breaks; Nonlinear least squares; Smooth transition;

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Cited by:
  1. Otilia Boldea & Alastair R. Hall, 2009. "Estimation and Inference in Unstable Nonlinear Least Squares Models," Centre for Growth and Business Cycle Research Discussion Paper Series 126, Economics, The Univeristy of Manchester.

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