Correlations versus causality approaches to economic modeling

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


This chapter explores the issue of treating a predictive system as a missing data problem i.e. correlation exercise and compares it to treating as a cause and effect exercise, that is, feed-forward network. An auto-associative neural network is combined with genetic algorithm and then applied to missing economic data estimation. The algorithm is used on data that contain ten economic variables. The results of the missing data imputation approach are compared to those from a feed-forward neural network.

Original languageEnglish
Title of host publicationAdvanced Information and Knowledge Processing
PublisherSpringer London
Number of pages18
Publication statusPublished - 2013

Publication series

NameAdvanced Information and Knowledge Processing
ISSN (Print)1610-3947
ISSN (Electronic)2197-8441

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management
  • Artificial Intelligence


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