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Introduction and Basics

In: Introduction to Modern Time Series Analysis

Author

Listed:
  • Gebhard Kirchgässner

    (University of St. Gallen)

  • Jürgen Wolters

    (FU Berlin)

  • Uwe Hassler

    (Goethe University Frankfurt)

Abstract

A time series is defined as a set of quantitative observations arranged in chronological order. We generally assume that time is a discrete variable. Time series have always been used in the field of econometrics. Already at the outset, JAN TINBERGEN (1939) constructed the first econometric model for the United States and thus started the scientific research programme of empirical econometrics. At that time, however, it was hardly taken into account that chronologically ordered observations might depend on each other. The prevailing assumption was that, according to the classical linear regression model, the residuals of the estimated equations are stochastically independent from each other. For this reason, procedures were applied which are also suited for cross section or experimental data without any time dependence.

Suggested Citation

  • Gebhard Kirchgässner & Jürgen Wolters & Uwe Hassler, 2013. "Introduction and Basics," Springer Texts in Business and Economics, in: Introduction to Modern Time Series Analysis, edition 2, chapter 1, pages 1-25, Springer.
    • Handle: RePEc:spr:sptchp:978-3-642-33436-8_1
    DOI: 10.1007/978-3-642-33436-8_1
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