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Quality & Quantity

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24.09.2016

A new approach for the quantification of qualitative measures of economic expectations

verfasst von: Oscar Claveria, Enric Monte, Salvador Torra

Erschienen in: Quality & Quantity | Ausgabe 6/2017

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Abstract

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.

Vorheriger Artikel Spatial regimes in regional European growth: an iterated spatially weighted regression approach

Nächster Artikel The causal relationship between land urbanization quality and economic growth: evidence from capital cities in China

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Titel: A new approach for the quantification of qualitative measures of economic expectations
verfasst von: Oscar Claveria
Enric Monte
Salvador Torra
Publikationsdatum: 24.09.2016
Verlag: Springer Netherlands
Erschienen in: Quality & Quantity / Ausgabe 6/2017
Print ISSN: 0033-5177
Elektronische ISSN: 1573-7845
DOI: https://doi.org/10.1007/s11135-016-0416-0

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