Title: Measuring uncertainties: a theoretical approach

Authors: Carolina Facioni; Isabella Corazziari; Filomena Maggino

Addresses: Via Cesare Balbo n. 39, Rome, 00184, Italy ' Viale Liegi, 13, Rome, 00198, Italy ' Dept. of Statistical Sciences, Sapienza University of Rome, P.le A. Moro, 5, Rome, 00185, Italy

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).

Keywords: uncertainty measure; futures studies; DFA; dynamic factor analysis.

DOI: 10.1504/IJCEE.2019.097797

International Journal of Computational Economics and Econometrics, 2019 Vol.9 No.1/2, pp.5 - 28

Received: 24 Nov 2016
Accepted: 21 Aug 2017
Published online: 11 Feb 2019 *

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