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A new approach for the quantification of qualitative measures of economic expectations
Claveria, Oscar; Monte Moreno, Enrique; Torra Porras, Salvador
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
In this study a new approach to quantify qualitative survey data about the direction of change is presented. We propose a data-driven procedure based on evolutionary computation that avoids making any assumption about agents’ expectations. The research focuses on experts’ expectations about the state of the economy from the World Economic Survey in twenty eight countries of the Organisation for Economic Co-operation and Development. The proposed method is used to transform qualitative responses into estimates of economic growth. In a first experiment, we combine agents’ expectations about the future to construct a leading indicator of economic activity. In a second experiment, agents’ judgements about the present are combined to generate a coincident indicator. Then, we use index tracking to derive the optimal combination of weights for both indicators that best replicates the evolution of economic activity in each country. Finally, we compute several accuracy measures to assess the performance of these estimates in tracking economic growth. The different results across countries have led us to use multidimensional scaling analysis in order to group all economies in four clusters according to their performance. We obtain the best results for Belgium, Norway, Austria, Lithuania, Japan and the United Kingdom.
Peer Reviewed
-Àrees temàtiques de la UPC::Economia i organització d'empreses::Macroeconomia
-Economic development
-Economic growth
-Qualitative survey data
-Expectations
-Symbolic regression
-Evolutionary algorithms
-Genetic programming JEL
-Desenvolupament econòmic
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
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