This research paper tries to answer the questions that, can heterogeneous zones be grouped to produce spatial markets? And are the submarkets produced meaningful geographically? The study shows that the use of small geographical scale helped to identify similar zones and neighbourhoods that have the same housing values and socio-economic characteristics. This is unlike some of the previous studies that combined wider areas together and so failed to identify spatial submarkets. Four different

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... graphical scales were examined to determine the level of disaggregation of data, and the highest level of disaggregative data occurs where cities are divided into small areas by zones. This study utilized both secondary and primary sources of data. The study is based on data collected from sixteen Local Government Areas consisting of 53 residential zones in metropolitan Lagos. Out of the total number of 135,820 properties, a size of about 1% (1,500) was randomly selected. The hypothesis was tested using a combination of analysis of variance, multiple regression model, expansion method and the non hierarchical technique of grouping. The variations in house values by zones are more distinct than house values for communities and local governments that bear the same name. The grouping of the zones with similar house values also helps to identify housing submarkets that exist in the study area. The submarkets have variations in housing values that conform to the socio-economic characteristics of the households.