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Tracking economic growth by evolving expectations via genetic programming: a two-step approach

Author
Claveria, O.; Monte, E.; Torra Porras, Salvador
Type of activity
Report
Date
2018-10-09
Repository
http://hdl.handle.net/2117/122090 Open in new window
URL
http://xreap.cat/ca/xreap-2018-4-tracking-economic-growth-by-evolving-expectations-via-genetic-programming-a-two-step-approach/ Open in new window
Abstract
The main objective of this study is to present a two-step approach to generate estimates of economic growth based on agents’ expectations from tendency surveys. First, we design a genetic programming experiment to derive mathematical functional forms that approximate the target variable by combining survey data on expectations about different economic variables. We use evolutionary algorithms to estimate a symbolic regression that links survey-based expectations to a quantitative variable used...
Citation
Claveria, O., Monte, E., Torra Porras, S. "Tracking economic growth by evolving expectations via genetic programming: a two-step approach". 2018.
Keywords
2008 financial crisis, Economic expectations, Evolution of GDP, Genetic programming
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
TALP - Centre for Language and Speech Technologies and Applications
VEU - Speech Processing Group

Participants

  • Claveria González, Oscar  (author)
  • Monte Moreno, Enrique  (author)
  • Torra Porras, Salvador  (author)