What is it about?

Tendency surveys are the main source of agents’ expectations. This study makes use of survey data from the World Economic Survey (WES) with a dual purpose: - First, it proposes a new method to quantify survey-based expectations by means of symbolic regression (SR) via genetic programming (GP). - Second, it combines the main SR-generated indicators to estimate the evolution of GDP in ten Central and Eastern European economies.

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Why is it important?

This research: - Presents a new approach to quantify agents' expectations on the direction of change. - Links quantitative and qualitative information by means of SR, and derives the optimal mathematical expressions to generate estimates of economic growth via GP - Obtains the most accurate forecasts for the Czech Republic and Hungary. - Assesses the impact of the 2008 financial crisis, finding that the capacity of agents’ expectations to anticipate the evolution of GDP in most Central and Eastern European economies improved after the crisis.


This study provides researchers with an innovative approach for the quantification of survey-based expectations. Symbolic Regression via Genetic Programming represents a very versatile technique for empirical modelling, that had never been used before to quantify agents' expectations.

Oscar Claveria
AQR-IREA, Univeristy of Barcelona

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This page is a summary of: Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies, Eastern European Economics, March 2016, Taylor & Francis, DOI: 10.1080/00128775.2015.1136564.
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