Skip to main content

Part of the book series: Advanced Studies in Theoretical and Applied Econometrics ((ASTA,volume 7))

  • 71 Accesses

Abstract

Planning may be seen as simulating the future. This will be done by extending experience from the past to future situations. Thus planning has an essentially probabilistic aspect, because the genesis of life is irreversible in time. One can only expect what will occur in the future and the usual strategy is to compare data continuously with expectations in order to adapt ‘likelihoods’ to reality.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bensoussan, A., E. G. Hurst, Jr., and B. Näslund (1974): Management Applications of Modern Control Theory, Studies in Mathematical and Managerial Economics Vol. 18. Amsterdam-Oxford.

    Google Scholar 

  2. Chow, G. C. (1975): Analysis and Control of Dynamic Economic Systems. New York-London.

    Google Scholar 

  3. Kemeny, J. G., J. L. Snell, and A. W. Knapp (1966): Denumerable Markov Chains. Toronto-New York-London.

    Google Scholar 

  4. Kendrick, D. (1981). Stochastic Control for Economic Models. Economics Handbook Series. New York.

    Google Scholar 

  5. Larson, R. E. (1968): State Increment Dynamic Programming, Modern Analytic and Computational Methods in Science and Mathematics, No. 12, New York.

    Google Scholar 

  6. Leserer, M. (1983): A Fine-Tuning Scheme for Economic Decision Rules. In: J. Gruber (ed.), Econometric Decision Models, Lecture Notes in Economics and Mathematical Systems, Vol. 208. Heidelberg.

    Google Scholar 

  7. Meier, L., R. E. Larson, and A. J. Tether (1971): Dynamic Programming for Stochastic Control of Discrete Systems. IEEE Transactions on Automatic Control, Vol. AC-16, No. 6, December, pp. 767–775.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1987 Martinus Nijhoff Publishers, Dordrecht

About this chapter

Cite this chapter

Eppers, J., Leserer, M. (1987). Some Remarks in Forward Programming. In: Carraro, C., Sartore, D. (eds) Developments of Control Theory for Economic Analysis. Advanced Studies in Theoretical and Applied Econometrics, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3495-5_8

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-3495-5_8

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-8063-7

  • Online ISBN: 978-94-009-3495-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics