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Measuring uncertainties: a theoretical approach

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  • Carolina Facioni
  • Isabella Corazziari
  • Filomena Maggino

Abstract

When our aim is to draw the possible developments of future events, we are faced with a practical obstacle. Indeed, we cannot have any empirical experience of the future. Have we, therefore, to be inferred that forecasting, exploring future or, better: exploring futures, or anticipating futures have not to be considered activities of a scientific kind? Answer to such a difficult question requires a multidisciplinary approach, where statistical models, methodology of social science and of course statistics and sociology as a whole - are enhanced in their ability to express the change - and sometimes the risk that the change itself implies. A great help in understanding complexity, and trends, comes from a method for multi-way data, based on the joint application of a factorial analysis and regression over time, called dynamic factor analysis (DFA).

Suggested Citation

  • Carolina Facioni & Isabella Corazziari & Filomena Maggino, 2019. "Measuring uncertainties: a theoretical approach," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 9(1/2), pages 5-28.
    • Handle: RePEc:ids:ijcome:v:9:y:2019:i:1/2:p:5-28
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    Cited by:

    1. Giuseppe Gabrielli & Anna Paterno & Silvana Salvini & Isabella Corazziari, 2021. "Demographic trends in less and least developed countries: Convergence or divergence?," Journal of Population Research, Springer, vol. 38(3), pages 221-258, September.

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