Correlations Versus Causality Approaches to Economic Modeling

  • Tshilidzi Marwala
Part of the Advanced Information and Knowledge Processing book series (AI&KP)


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.


Genetic Algorithm Credit Card Receiver Operating Characteristic Granger Causality Hide Unit 
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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Tshilidzi Marwala
    • 1
  1. 1.Faculty of Engineering and the Built EnvironmentUniversity of JohannesburgJohannesburgSouth Africa

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