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Investigating Nonlinearity: A Note on the Estimation of Hamilton’s Random Field Regression Model

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Author Info
D. Bond
M.J. Harrision
E.J. O, Brien (Department of Economics, Trinity College)

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Abstract

This is a revised and extended version of the authors’ 2003 Trinity Economic Paper. It describes Hamilton’s (2001) approach to nonlinear econometric modelling and some of the methods of nonlinear optimization, as before, but adds significantly to the investigation of Hamilton’s Gauss program for the implementation of his methodology. Specifically, it reports on the performance of this program using data relating to Hamilton’s US Phillips curve example, the use of two versions of the Gauss software and a range of numerical optimization options. It also examines the impact of changes in initial parameter estimates, the use of algorithm switching strategies, and the e?ects of changes in the sample data on the results produced by Hamilton’s procedure. The new results presented suggest some further clear conclusions that will be of value to those using Hamilton’s method.

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Paper provided by Trinity College Dublin, Department of Economics in its series Trinity Economics Papers with number tep4.

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Date of creation: Aug 2005
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Handle: RePEc:tcd:tcduee:tep4

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Hamilton, James D, 2001. "A Parametric Approach to Flexible Nonlinear Inference," Econometrica, Econometric Society, vol. 69(3), pages 537-73, May.
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  2. Christian M. Dahl, . "An Investigation of Tests for Linearity and the Accuracy of Flexible Nonlinear Inference," Economics Working Papers 1999-8, School of Economics and Management, University of Aarhus. [Downloadable!]
  3. D. Bond & M. Harrison & E.J. O'Brien, 2003. "Investigating Nonlinearity: A Note on the Implementation of Hamilton's Methodology," Trinity Economics Papers 200312, Trinity College Dublin, Department of Economics. [Downloadable!]
  4. Christian M. Dahl & Yu Qin, 2008. "The limiting behavior of the estimated parameters in a misspecified random field regression model," CREATES Research Papers 2008-45, School of Economics and Management, University of Aarhus. [Downloadable!]
  5. Dahl, Christian M. & Gonzalez-Rivera, Gloria, 2003. "Testing for neglected nonlinearity in regression models based on the theory of random fields," Journal of Econometrics, Elsevier, vol. 114(1), pages 141-164, May. [Downloadable!] (restricted)
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  1. Peter Winker & Dietmar Maringer, 2009. "The convergence of estimators based on heuristics: theory and application to a GARCH model," Computational Statistics, Springer, vol. 24(3), pages 533-550, August. [Downloadable!] (restricted)
  2. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics. [Downloadable!]
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