Applying Directed Acyclic Graphs to Assist Specification of a Hedonic Model

Seong Hoon Cho, Tun Hsiang (Edward) Yu, Seung Gyu Kim, Roland K. Roberts, Daegoon Lee

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This research empirically tests the hypothesis that utilizing directed acyclic graphs (DAGs) as an ex-ante process to select variables for a hedonic model improves the model's performance. The results for both new and existing house submarkets indicated that DAG analysis mitigated the multicollinearity issue commonly observed in hedonic models. Using DAG analysis also improved the goodness-of-fit of the hedonic model for the new submarket. However, model specification through DAG analysis does not offer clear implications for improving forecasting accuracy, efficiency, and spatial error autocorrelation. The findings imply that DAG analysis for model specification can be a complementary step in the process of estimating hedonic models, especially when reducing standard error bias by alleviating potential multicollinearity is important in determining the attributes that affect housing prices.

Original languageEnglish
Pages (from-to)984-1007
Number of pages24
JournalHousing Studies
Volume27
Issue number7
DOIs
StatePublished - Oct 2012

Keywords

  • Directed acyclic graphs
  • spatial hedonic model

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