Computer Science in Economics and Management

, Volume 5, Issue 3, pp 247–270 | Cite as

Understanding macroeconomic models: Structural sensitivity analysis of a medium-sized model

  • Ullrich Heilemann
  • Heinz Josef Münch
Article

Abstract

To get a better impression of the quantitative relationships in/of the various channels of macroeconomic models, Kuh, Neese, and Hollinger introduced the technique of systematic parameter perturbation. This technique is applied to the RWI-business cycle model, a medium sized (41 stochastic equations, 86 definitions), quarterly macroeconometric model for the FRG. The evaluation of the results concentrates on (1) the sensitivity of the model to parameter perturbations in general, and to (2) the sensitivity of policy goal variables in particular. The findings show that in the model the number of important within-block and between-block relationships is much smaller than suggested by usual incidence matrices, providing additional evidence for Simon's ‘empty world hypothesis’.

Key words

Structural sensitivity analysis parameter perturbation macroeconometric model influential parameters 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chick, V (1983) Macro Economics after Keynes, Cambridge, MA.Google Scholar
  2. Davidson, P. (1980) Post Keynesian Economics, Public Interest, (special issue: The Crisis in Economic Theory) 20, 151–173.Google Scholar
  3. Eckstein, O. (1983) The DRI-Model of the U.S. Economy, New York.Google Scholar
  4. Friedman, M. (1971) A Monetary Theory of Nominal Income, J. Political Economics, 79, 323–327.Google Scholar
  5. Gilbert, C.L. (1986) Professor Hendry's econometric methodology, Oxford Bull. Econom. Statist. 48, 283–307.Google Scholar
  6. Gilli, M. and Shell, M. (1986) TROLL Program CAUSOR (A Program for the Analysis of Recursive and Interdependent Causal Structures), Technical Report TR-45, CECREMS, MIT, Cambridge, MA.Google Scholar
  7. Gruber, J. and Rosemeyer, B. (1982) Sensitivitätsanalyse in großen, nichtlinearen ökonometrischen Modellen — einige Ergebnisse für das RWI-Konjunkturmodell. (Diskussionsbeiträge Fachbereich Wirtschaftswissenschaft der Fernuniversität Gesamthochschule Hagen, 58.) Hagen.Google Scholar
  8. Heilemann, U. (1985). Zur Prognosepraxis ökonometrischer Modelle. Zeit. Wirtschafts- Sozialwissenschaften, 105, 683–708.Google Scholar
  9. Heilemann, U. (1989) ‘Was leisten Prognosemodelle?’ Eine empirische Untersuchung am Beispiel des RWI-Konjunkturmodells., in B. Gahen, B. Meyer, J. Schumann (eds), Wirtschaftswachstum, Srukturwandel und dynamischer Wettbewerb, Ernst Helmstädter zum 65. Geburtstag, Springer, Berlin, Heidelberg, New York, pp. 253–272.Google Scholar
  10. Heilemann, U. and Münch, H.J. (1984a) Einige Bemerkungen zum RWI-Konjunkturmodell in G. Langer, J. Martiensen and A. Quinke (eds), Simulationsrechnungen mit ökonometrischen Makromodellen., München, pp. 355–385.Google Scholar
  11. Heilemann, U. and Münch, H.J. (1984b) The Great Recession: A Crisis in Parameters? in P. Thoft-Christensen (ed.), Proceedings of the 11th IFIP Conference on System Modeling and Optimization, Copenhagen, Denmark, July 1983.. (Lecture Notes in Control and Information Sciences, 59.) Springer, Berlin, Heidelberg, New York, pp. 71–82.Google Scholar
  12. Hollinger, P. (1985) TROLL program TESTMOD, Technical Report TR-17, CCREMS, MIT, Cambridge, MA.Google Scholar
  13. Kuh, E. and Neese, J.W. (1982) Parameter sensitivity, dynamic behavior and model reliability: An initial exploration with the MQEM monetary sector, in E.G. Charatsis (ed.), Proceedings of the Econometric Society European Meeting 1979, Selected Econometric Papers — in Memory of Stefan Valavanis (Contributions to Economic Analysis, 138), North-Holland, Amsterdam.Google Scholar
  14. Kuh, E., Neese, J.W, and Hollinger, P. (1985) Structural Sensitivity in Econometric Models, New York.Google Scholar
  15. Kuh, E., Neese, J.W., and P. Hollinger (1986) Linear analysis of large nonlinear models and model simplification, in D.A. Belsley and E. Kuh (eds), Model Reliability, Cambridge, MA, London.Google Scholar
  16. Simon, H. 1981) The Sciences of the Artificial, 2nd edn, Cambridge, MA.Google Scholar
  17. Terlau, W. (1991) Strukturelle Sensitivitätsanalyse dynamischer ökonometrischer Prognosemodelledargestellt am Beispiel der Westdeutschen Textilwirtschaft. PhD Thesis University of Münster/Westf., forthcoming.Google Scholar
  18. Uebe, G., Huber, G., and Fischer, P. (1990) Survey of macroeconomic models in chronological order based on -Biblio-, the München Bibliography of Macroeconometric Models. München.Google Scholar

Copyright information

© Kluwer Academic Publishers 1992

Authors and Affiliations

  • Ullrich Heilemann
    • 1
  • Heinz Josef Münch
    • 1
  1. 1.Rheinisch-Westfälisches Institut für WirtschaftsforschungEssenGermany

Personalised recommendations