Skip to main content
SpringerLink
Log in
Book cover

The Practice of Econometric Theory pp 19–53Cite as

Econometric Computation

  • Chapter
  • First Online:

Part of the book series: Advanced Studies in Theoretical and Applied Econometrics ((ASTA,volume 44))

Abstract

“Arithmetic” is the elementary branch of mathematics that involves making specific calculations using operators and rules governed by a relatively simple set of algebraic principles. Until approximately the middle of the twentieth century, a common synonym for “calculation” was “computation,” each of these terms then usually being understood to refer to the process of making arithmetic calculations. Furthermore, until about that time, the word “computer” was the designation for a person who professionally made these. As David Grier has pointed out (Grier, 1996, p. 53) “human computation reached its zenith in the late 1930s and early 1940s and was considered a substantial field. It had completed large, successful projects, such as the Work Projects Administration mathematical tables project and had demonstrated the effectiveness of organized computation. It had a journal, Mathematical Tables and Other Aids to Computation, and prominent leaders…” including well-known statisticians and mathematicians. During the seventy or so years since, a revolution has occurred, both terminologically and computationally.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
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

Learn about institutional subscriptions

References

  • Amman, H. M., & Kendrick, D. (1999). Programming languages in economics. Computational Economics, 14(1–2), 151–181

    Google Scholar 

  • Belsley, D. A. (1974). Estimation of systems of simultaneous equations, and computational specification of GREMLIN. Annals of Economic and Social Measurement, 3, 551–614

    Google Scholar 

  • Belsley, D. A. (1999). Mathematica as an environment for doing economics and econometrics. Computational Economics, 14(1–2), 69–87

    Article  Google Scholar 

  • Berk, K. N. (1987). Effective microcomputer statistical software. American Statistician, 41(3), 222–228

    Google Scholar 

  • Bloch, R. M. (1948). Mark I calculator. In Proceedings of a Symposium on Large-Scale Digital Calculating Machinery. Cambridge, MA: Harvard University Press

    Google Scholar 

  • Brillet, J.-L. (1989). Econometric modeling on microcomputers: A review of major software packages. Journal of Applied Econometrics, 4(1), 73–92

    Article  Google Scholar 

  • Brooks, C., Burke, S., & Persand, G. (2001). Benchmarks and the accuracy of GARCH model estimation. International Journal of Forecasting, 17, 45–56

    Article  Google Scholar 

  • Campbell-Kelly, M/ & Williams, M. R. (Eds.). (1985). The Moore School lectures. Cambridge, MA: MIT

    Google Scholar 

  • de la Vina, L. Y. (1985). Econometric software for microcomputers. Journal of Business & Economic Statistics, 3(1), 89–91

    Article  Google Scholar 

  • Desai, M. (2007). Memories of Monroe: Econometric computing in the early 1960s. Journal of Economic and Social Measurement, 32(1), 35–38

    Google Scholar 

  • Dewald, W. G., Thursby,J. G., & Anderson,R. G. (1986). Replication in empirical economics: The Journal of Money, Credit and Banking Project. American Economic Review, 76(4), 587–603

    Google Scholar 

  • Eisner, M., – Pindyck, R. S. (1973). A generalized approach to estimation as implemented in the TROLL/1 system. Annals of Economic and Social Measurement, 2, 29–51

    Google Scholar 

  • Ewald, W. (1996). From Kant to Hilbert. Oxford: Oxford University Press

    Google Scholar 

  • Francis, I. (1973). A comparison of several analysis of variance programs. Journal of the American Statistical Association, 68, 860–865

    Article  Google Scholar 

  • Francis, I., Heiberger, R., & Velleman, P. F. (1975). Criteria and Considerations in the evaluation of statistical program packages. American Statistician, 29, 52–56

    Google Scholar 

  • Giaquinto, M. (2004). The search for certainty. A philosophical account of foundations of mathematics. Oxford: Clarendon

    Google Scholar 

  • Godel, K. (1992). On formally undecidable propositions of principia mathematica and related systems. New York: Dover Publications

    Google Scholar 

  • Goldberger, A. S. (2004). Econometric computation by hand. Journal of Economic and Social Measurement, 29, 115–118

    Google Scholar 

  • Golub, G. H., & Van Loan, C. F. (1996). Matrix computations. (3rd ed.). Baltimore: Johns Hopkins University Press

    Google Scholar 

  • Grier, D. A. (1996). The ENIAC, the verb “to program” and the emergence of digital computers. IEEE Annals of the History of Computing, 18(1), 51–55

    Article  Google Scholar 

  • Hall, R. E. (2003). Email re history of econometric software development. B. H. Hall and C. G. Renfro, Recipients

    Google Scholar 

  • Hendry, D. F. (1993). Econometrics: Alchemy or science?: Essays in econometric methodology. Oxford: B. Blackwell

    Google Scholar 

  • Hendry, D. F., & Srba, F. (1980). AUTOREG: A computer program library for dynamic econometric models with autoregressive errors. Journal of Econometrics, 12, 85–102

    Article  Google Scholar 

  • Herbert, R. D. (2004). Modelling programming languages--appropriate tools? Journal of Economic and Social Measurement, 29, 321–338

    Google Scholar 

  • Hoover, K. D., & Perez, S. J. (1999). Data mining reconsidered: encompassing and the general-to-specific approach to specification search. Econometrics Journal, 2, 167–191

    Article  Google Scholar 

  • Householder, A. S. (1974). Theory of matirces in numerical analysis. New York: Dover

    Google Scholar 

  • Knuth, D. E. (1970). Von Neumann’s first computer program. ACM Computing Surveys, 2(4), 247–260

    Article  Google Scholar 

  • Knuth, D. E. (1996). Selected papers on computer science. Cambridge: Cambridge University Press

    Google Scholar 

  • Knuth, D. E. (1998). The art of computer programming.(3rd ed.). (Vol. 2). Reading, MA: Addison-Wesley

    Google Scholar 

  • Lilien, D. (2000). Econometric software reliability and nonlinear estimation in EViews: comment. Journal of Applied Econometrics, 15(1), 107–110

    Article  Google Scholar 

  • Longley, J. W. (1967). An appraisal of least squares programs for the electronic computer from the point of view of the user. Journal of the American Statistical Association, 62, 819–841

    Article  Google Scholar 

  • Lovell, M. C. (1983). Data mining. Review of Economics and Statistics, 65(1), 1–12

    Article  Google Scholar 

  • Macon, N. (1963). Numerical analysis. New York: Wiley

    Google Scholar 

  • Maddy, P. (1988). Believing the axioms. I. Journal of Symbolic Logic, 53(2), 481–511

    Article  Google Scholar 

  • McCullough, B. D. (1998). Assessing the reliability of statistical software: Part I. American Statistician, 52(4), 358–366

    Google Scholar 

  • McCullough, B. D., & Renfro, C. G. (1998). Benchmarks and software standards: A case study of GARCH procedures. Journal of Economic and Social Measurement, 25, 59–71

    Google Scholar 

  • McCullough, B. D., & Vinod, H. D. (1999). The numerical reliability of econometric software. Journal of Economic Literature, 37(2), 633–665

    Article  Google Scholar 

  • Morgenstern, O. (1960). On the accuracy of economic observations. Princeton, NJ: Princeton University Press

    Google Scholar 

  • Muller, M. E., & Wilkinson, G. N. (1976). A standardized form for describing programs, packages and systems for statistical applications. International Statistical Review, 44(3), 349–353

    Article  Google Scholar 

  • Nagel, E., Newman,J. R..,& Hofstadter, D. R., (2001) Godel’s proof. (Rev. ed.). New York: New York University Press

    Google Scholar 

  • Nerlove, M. (2004). Programming languages: A short history for economists. Journal of Economic and Social Measurement, 29, 189–203

    Google Scholar 

  • Neumann, J. v. (1993/1945). First draft of a report on the EDVAC. IEEE Annals of the History of Computing, 15(4), 27–75

    Article  Google Scholar 

  • Pesaran, M. H., & Slater, L. J. (1980). Dynamic regression: Theory and algorithms. Chichester: Ellis Horwood

    Google Scholar 

  • Ralston, A., & Rabinowitz, P. (2001). A first course in numerical analysis. Mineola, New York: Dover

    Google Scholar 

  • Ramsey, F. P. (1925). The foundations of mathematics. In Proceedings of the London Mathmatical Society, Series 2, 25(5), 338–384

    Google Scholar 

  • Ramsey, F. P. (1928). A mathematical theory of savings. Economic Journal, 38, 543–559

    Article  Google Scholar 

  • Renfro, C. G. (2004b). Econometric software: The first fifty years in perspective. Journal of Economic and Social Measurement, 29(1–3), 9–108[AU25]

    Google Scholar 

  • Rycroft, R. S. (1989). Microcomputer software of interest to forecasters in comparative review. International Journal of Forecasting, 5, 437–462

    Article  Google Scholar 

  • Samuelson, P. A. (1970). What makes for a beautiful problem in science[AU28]. Journal of Political Economy, 78(6), 1372–1377

    Article  Google Scholar 

  • Stokes, H. H. (2004a). Econometric software as a theoretical research tool. Journal of Economic and Social Measurement, 29, 183–188

    Google Scholar 

  • Stokes, H. H. (2005). The sensitivity of econometric results to alternative implementations of least squares. Journal of Economic and Social Measurement , 30(1), 9–38

    Google Scholar 

  • Theil, H. (1971). Principles of econometrics. New York: Wiley

    Google Scholar 

  • Turing, AM, (1936). On computable numbers, with an application to the Entscheidungsproblem. In Proceedings of the London Mathmatical Society, Series 2, Vol. 42, pp. 230–265

    Google Scholar 

  • Wilkes, M. V. (1956). Automatic digital computers. London: Methuen & Co

    Google Scholar 

  • Wilkes, M. V., Wheeler, D. J., & Gill, S. (1951). The preparation of programs for an electronic digital computer: With special reference to the EDSAC and the use of a library of subroutines. Cambridge, MA: Addison Wesley

    Google Scholar 

  • Wilkinson, J. H. (1963). Rounding errors in algebraic processes. Englewood Cliffs, NJ: Prentice-Hall

    Google Scholar 

  • Zivot, E., & Wang, J. (2002). Modelling financial time series with S-PLUS. May 22, 2002 (ed.), Seatle, WA: Insightful Corporation

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Alphametrics Corporation, 11-13 East Princeton Road, Bala Cynwyd, 19004-2242, Pennsylvania, USA

    Charles Renfro

Authors
  1. Charles Renfro
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Charles Renfro .

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Renfro, C. (2009). Econometric Computation. In: The Practice of Econometric Theory. Advanced Studies in Theoretical and Applied Econometrics, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75571-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-75571-5_2

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75570-8

  • Online ISBN: 978-3-540-75571-5

  • eBook Packages: Business and EconomicsEconomics and Finance (R0)

Publish with us

Policies and ethics

Search

Navigation