Application of regression techniques to capture value influences for mass valuation of residential property: A case study of two residential estates in Nairobi

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dc.contributor.author Ochieng, Bernard
dc.date.accessioned 2025-04-03T09:09:39Z
dc.date.available 2025-04-03T09:09:39Z
dc.date.issued 2025-04-03
dc.identifier.citation OchiengB2025 en_US
dc.identifier.uri http://localhost/xmlui/handle/123456789/6654
dc.description Journal of Agriculture Science & Technology en_US
dc.description.abstract This research project sets out to apply statistical techniques in the valuation of land and properties through various models. It focused on comparing predictive accuracies of mass valuation models with a dataset of 500 single-family property transactions in two neighbourhoods within Nairobi city. There are a number of statistical models that are used for mass valuation of properties. The first step in this study was to gather data on property sales used in the development of a base model and proposed model. Each of the property units in the database were geocoded and vectorized. The data was screened and visualized to investigate the nature of the potential association between the response, Y, and predictor variables, X. The predictor variables were tested for multicollinearity and a regression model developed based on hypothesized relationships. The model was tested for lack of fit by ordering the residuals using a residual scatterplots and histograms. Finally, the fitness statistics were reviewed by looking at the spread of the plot and evaluating observed values around the regression line, and examining how accurate the independent variables are in predicting the dependent variables. The results revealed an overall level of 0.96 for Komarock and 0.98 for Runda estate respectively. One measure of how well the model predicts is to compute the correlation between the actual values in the holdout sample and the predicted values. The correlation should be high when the model is valid. The correlation between the assessed value and the actual selling price is 0.71 and 0.98 for Komarock and Runda respectively. Determining the quality of the valuation output also requires measuring uniformity: uniformity between groups of properties and uniformity within groups (Abidoye, Huang, Amidu, & Javad, 2021). The coefficient of dispersion (COD) is the most used measure of valuation uniformity. The results show a COD of 18% and 10% for Komarock and Runda respectively. en_US
dc.language.iso en en_US
dc.subject Regression techniques en_US
dc.subject Mass valuation of residential property en_US
dc.subject Residential estates en_US
dc.title Application of regression techniques to capture value influences for mass valuation of residential property: A case study of two residential estates in Nairobi en_US
dc.type Article en_US


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