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Nonlinearity, ComputationaL Complexity and Macroeconomic Modelling

Author

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  • Peter McAdam
  • A. J. Hughes Hallett
Abstract
In this paper we survey and appraise the main contributions to solving and stabilising non‐linear equation systems typically found in Economics. We are keen wherever possible to draw distinctions and limiting cases between different solution methods, define acceleration strategies and encourage the use of hybrid or switching algorithms. Both large‐scale traditional macroeconomic models as well as smaller non‐linear analytical models are considered.

Suggested Citation

  • Peter McAdam & A. J. Hughes Hallett, 1999. "Nonlinearity, ComputationaL Complexity and Macroeconomic Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 577-618, December.
    • Handle: RePEc:bla:jecsur:v:13:y:1999:i:5:p:577-618
    DOI: 10.1111/1467-6419.00099
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    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:

    1. Perez, Javier J. & Hiebert, Paul, 2004. "Identifying endogenous fiscal policy rules for macroeconomic models," Journal of Policy Modeling, Elsevier, vol. 26(8-9), pages 1073-1089, December.
    2. ALISTAIR DIEPPE & KEITH KÜSTER & PETER McADAM, 2005. "Optimal Monetary Policy Rules for the Euro Area: An Analysis Using the Area Wide Model," Journal of Common Market Studies, Wiley Blackwell, vol. 43(3), pages 507-537, September.
    3. McAdam, Peter & Morgan, Julian, 2001. "The monetary transmission mechanism at the euro-area level: issues and results using structural macroeconomic models," Working Paper Series 0093, European Central Bank.
    4. McAdam, Peter & Willman, Alpo & León-Ledesma, Miguel A., 2010. "In dubio pro CES - Supply estimation with mis-specified technical change," Working Paper Series 1175, European Central Bank.
    5. McAdam, Peter & Willman, Alpo, 2007. "Phillips-Curve Dynamics: Mark-Up Cyclicality, Effective Hours and Regime-Dependency," Kiel Working Papers 1359, Kiel Institute for the World Economy (IfW Kiel).
    6. Klump, Rainer & McAdam, Peter & Willman, Alpo, 2008. "Unwrapping some euro area growth puzzles: Factor substitution, productivity and unemployment," Journal of Macroeconomics, Elsevier, vol. 30(2), pages 645-666, June.
    7. A J Hughes Hallett & Peter McAdam, 2001. "Fiscal Consolidation and the Probability Distribution of Deficits: A Stochastic Analysis of the Stability Pact," Studies in Economics 0101, School of Economics, University of Kent.
    8. Perez, Javier J. & Hiebert, Paul, 2004. "Identifying endogenous fiscal policy rules for macroeconomic models," Journal of Policy Modeling, Elsevier, vol. 26(8-9), pages 1073-1089, December.
    9. McAdam, Peter & McNelis, Paul, 2005. "Forecasting inflation with thick models and neural networks," Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September.
    10. McAdam, Peter & Mestre, Ricardo, 2008. "Evaluating macro-economic models in the frequency domain: A note," Economic Modelling, Elsevier, vol. 25(6), pages 1137-1143, November.
    11. McAdam, Peter & Morgan, Julian, 2001. "The monetary transmission mechanism at the euro-area level: issues and results using structural macroeconomic models," Working Paper Series 93, European Central Bank.
    12. Ali Babikir & Henry Mwambi, 2016. "Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods," Empirical Economics, Springer, vol. 51(4), pages 1541-1556, December.

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