Estimation and inference in unstable nonlinear least squares models

被引:10
|
作者
Boldea, Otilia [1 ,2 ]
Hall, Alastair R. [3 ]
机构
[1] Tilburg Univ, Dept Econometr, NL-5000 LE Tilburg, Netherlands
[2] CentER, NL-5000 LE Tilburg, Netherlands
[3] Univ Manchester, Manchester M13 9PL, Lancs, England
关键词
Multiple breaks; Nonlinear least squares; Smooth transition; MULTIPLE STRUCTURAL-CHANGES; TRANSITION AUTOREGRESSIVE MODELS; MONETARY-POLICY; PARAMETER INSTABILITY; GENERALIZED-METHOD; PHILLIPS-CURVE; LINEAR-MODELS; CHANGE-POINT; TESTS; INFLATION;
D O I
10.1016/j.jeconom.2012.09.004
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:158 / 167
页数:10
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