Measuring uncertainties: a theoretical approach

Carolina Facioni, Isabella Corazziari and Filomena Maggino

International Journal of Computational Economics and Econometrics, 2019, vol. 9, issue 1/2, 5-28

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. (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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