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

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Author Info

  • Bond Derek

    ()
    (University of Ulster)

  • Harrison Michael J.

    ()
    (Trinity College Dublin)

  • O'Brien Edward J.

    ()
    (Trinity College Dublin)

Abstract

In this paper we give an account of the approach to nonlinear econometric modelling proposed by Hamilton (2001) and briefly describe some of the methods of nonlinear optimization that may be used in the Gauss computer program provided by Hamilton for the implementation of his methodology. The performance of this program is investigated using data relating to Hamilton's example concerning the US Phillips curve, two versions of the Gauss software, and a range of alternative numerical optimization options and values for the Gauss parameter _oprteps. The impact of changes in initial parameter estimates and the use of pairs of optimization algorithms are also briefly examined. Finally, the effects of changes in the sample data on the results produced by Hamilton's procedure are explored. The results presented suggest some clear conclusions, which will be of value to those contemplating working with Hamilton's new method.

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Bibliographic Info

Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 9 (2005)
Issue (Month): 3 (September)
Pages: 1-43

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Handle: RePEc:bpj:sndecm:v:9:y:2005:i:3:n:2

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  1. 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.
  2. Hamilton, James D., 1999. "A Parametric Approach to Flexible Nonlinear Inference," University of California at San Diego, Economics Working Paper Series qt68s8157x, Department of Economics, UC San Diego.
  3. 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.
  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.
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Cited by:
  1. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2007. "Demand for Money: A Study in Testing Time Series for Long Memory and Nonlinearity," The Economic and Social Review, Economic and Social Studies, vol. 38(1), pages 1-24.
  2. Bond, Derek & Harrison, Michael J & Hession, Niall & O’Brien, Edward J., 2006. "Some Empirical Observations on the Forward Exchange Rate Anomaly," Research Technical Papers 3/RT/06, Central Bank of Ireland.
  3. Derek Bond & Niall Hession & Michael J Harrison & Edward J O’Brien, 2007. "Nonlinearity as an Explanation of the Forward Exchange Rate Anomaly," Working Papers 200801, School Of Economics, University College Dublin.
  4. Bond, Derek & Harrison, Michael J & O’Brien, Edward J., 2006. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Research Technical Papers 2/RT/06, Central Bank of Ireland.
  5. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2006. "Purchasing Power Parity: The Irish Experience Re-visited," Trinity Economics Papers tep200615, Trinity College Dublin, Department of Economics.
  6. 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.

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