Modelling housing preferences using decision tables
Method and empirical illustration
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Abstract
Quantitative theories and approaches have been dominant in a variety of disciplines. In this contribution, we will explore an alternative approach: decision tables, i.c. sets of decision rules extracted from an existing data set using a CHAID-based algorithm, that focus on conditions and states leading to particular actions or decisions. These decision tables make for an attractive approach in the context of rule-based (parts of) microsimulation models of consumer choice behaviour. The approach is illustrated by modelling people's preferences in choosing a new dwelling. In addition, the flexibility of the approach is used to demonstrate how the characteristic of 'housing affordability' is related to both the desired dwelling and the potential buyer or tenant. Rules are extracted from data on stated preferences, collected in the Netherlands in 2009.