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| Title: | Estimation and Inference in Unstable Nonlinear Least Squares Models (Final) |
| Authors: | Boldea, Otilia |
| Advisors: | Dr. John J. Seater, Committee Member
Dr. Denis Pelletier, Committee Member
Dr. Alastair R. Hall, Committee Chair
Dr. David A. Dickey, Committee Member |
| Keywords: | test for breaks
break-point distribution
nonlinear asymptotic theory
stability tests
unstable NLS
nonlinear least squares
estimation of multiple breaks
multiple change points |
| Issue Date: | 25-Apr-2009 |
| Degree: | PhD |
| Discipline: | Economics |
| Abstract: | In this thesis, we extend Bai and Perron's (1998, Econometrica, pp. 47-78) method for
detecting multiple breaks to nonlinear models. To that end, we consider an unstable univariate
nonlinear least squares (NLS) model with a limited number of parameter shifts occurring at
unknown dates. In our framework, the break-dates are simultaneously estimated with the
parameters via minimization of the residual sum of squares. Using nonlinear asymptotic theory,
we derive the asymptotic distributions of both break-point and parameter estimates and propose
several instability tests. We also present simulation results that validate our procedure. Our
method is useful for estimating and testing nonlinear macroeconomic models with multiple
unknown breaks. As an empirical illustration, we explore the relationship between our model
and smooth transition models in the context of a US interest rate reaction function. Unlike
previous studies, our model can nest nonlinearities and breaks. We provide evidence for at least
two breaks while allowing for smooth transition within each regime, before and after a break. |
| URI: | http://www.lib.ncsu.edu/resolver/1840.16/5011 |
| Appears in Collections: | Dissertations
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