# RECORD 9dd3ef8baea1541e7438928532ebd498c89ffa88 # TITLE: Hedonic Valuation of Real Estate Properties in Nigeria, Hedonic Valuation of Properties in Nigeria # YEAR: 2018.0 VENUE: Journal of African Real Estate Research DOI: 10.15641/jarer.v1i1.452 # AUTHORS: R. Abidoye; A. Chan # PAGES: 19 CANDIDATE TABLE PAGES (1-based): [10] # ABSTRACT: Despite the wide adoption of the Hedonic Pricing Model (HPM) approach in property valuation in the real estate domain, a large number of studies conducted by real estate scholars, have tended to focus on the ‘explanatory’ rather than the ‘predictive’ ability of the technique. Given this industry focus, and thus the lack of information on the predictive nature of HPM, the present study sets out to investigate the predictive accuracy of HPM in property valuation. Data on sales transaction of residential properties were collected from registered property firms practising in the Lagos metropolis property market, in Nigeria. The collected data were divided into two categories - the training set which was fitted to the HPM developed, and the testing dataset which was used for the model validation. Accuracy metrics were used to evaluate the predictive accuracy of the HPM developed. The analysis shows that the HPM approach produced inaccurate predicted property values in terms of a high mean absolute percentage error (MAPE), mean absolute error (MAE) and root means square error (RMSE) which may not be acceptable by rational real estate investors. Also, about 60% of the predicted property values produced an inaccuracy that is ± 20% of the actual values, while only 26% yielded an error of margin which is within the industry acceptable margin of between ± 0 and 10%. The HPM could not be entirely relied on to produce accurate property valuation estimates. Therefore, further studies are needed to be carried out to identify more reliable and robust property valuation approaches that can produce values that would be acceptable to all property valuation stakeholders. ===== PAGE 1 (score 4, numeric-paren 0, table-words 0, var-words 4) ===== 1 rotimi.abidoye@connect.polyu.hk; +85234008113 Journal of African Real Estate Research Volume 3, Issue 1 www.journals.uct.ac.za/index.php/JARER/index Hedonic Valuation of Real Estate Properties in Nigeria Rotimi Boluwatife Abidoye1, and Albert P. C. Chan2 1,2 Department of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Hong Kong To cite this article: Abidoye, R. B., & Chan, A. P. C. (2018). Hedonic Valuation of Real Estate Properties in Nigeria. Journal of African Real Estate Research, 3(1), pp.122-140. DOI: 10.15641/jarer.v1i1.452. Abstract Despite the wide adoption of the Hedonic Pricing Model (HPM) approach in property valuation in the real estate domain, a large number of studies conducted by real estate scholars, have tended to focus on the ‘explanatory’ rather than the ‘predictive’ ability of the technique. Given this industry focus, and thus the lack of information on the predictive nature of HPM, the present study sets out to investigate the predictive accuracy of HPM in property valuation. Data on sales transaction of residential properties were collected from registered property firms practising in the Lagos metropolis property market, in Nigeria. The collected data were divided into two categories - the training set which was fitted to the HPM developed, and the testing dataset which was used for the model validation. Accuracy metrics were used to evaluate the predictive accuracy of the HPM developed. The analysis shows that the HPM approach produced inaccurate predicted property values in terms of a high mean absolute percentage error (MAPE), mean absolute error (MAE) and root means square error (RMSE) which may not be acceptable by rational real estate investors. Also, about 60 % of the predicted property values produced an inaccuracy that is ± 20% of the actual values, while only 26% yielded an error of margin which is within the industry acceptable margin of between ± 0 and 10%. The HPM could not be entirely relied on to produce accurate property valuation estimates. Therefore, further studies are needed to be carried out to identify more reliable and robust property valuation approaches that can produce values that would be acceptable to all property valuation stakeholders. Keywords: Hedonic Pricing Model; Property Attributes; Valuation Inaccuracy; Property Valuation; Lagos ===== PAGE 10 (score 30, numeric-paren 0, table-words 7, var-words 13) ===== Journal of African Real Estate Research Volume 3(1) 2018 122-140 131 could result in a low crime rate), this would significantly increase the price of a property. However, this study found that the presence of a security fence (a security measure) in a property could negatively influence its price. This may be attributed to the fact that most of the residential neighbourhoods sampled usually have a general neighbourhood-organised security personnel in addition to each house’s security guards. Suggesting that the presence of a security fence in these neighbourhoods may not be regarded as a security measure for real estate investors. Table 4. Result of the Regression Analysis Independent variables Coefficient t-ratio p-value Bedrooms 8664822.596 0.738 0.461 Bathrooms -20051336.870 -1.448 0.149 Property type 8076944.769 1.144 0.254 Boys’ quarters 102816020.589 15.151 0.000 Parking 9526774.351 2.615 0.009 Age -1635743.326 -1.068 0.286 Floors 4539570.089 1.455 0.147 Security fence -10789691.840 -0.229 0.819 Sea view 154767562.522 4.832 0.000 Location -26885403.503 -6.176 0.000 Constant 98778305.063 1.396 0.164 r2= 0.766, Adj r2= 0.757, F-ratio= 80.381, n=256 Of all the ten variables, the presence of a sea view and the number of boys’ quarters1 (BQ) in a property are the most highly significant variables that influence the price of a property. Both variables had the highest coefficients that contribute to the price formation of a property in the study area. In a similar study by Mok et al. (1995), it was found that a property that has a sea view will command a higher value. Also, the positive influence of the BQ room on the price of properties was reported in the study of Basu and Thibodeau (1998). Model Performance As earlier stated, in order to achieve the objectives of this study, the performance of model developed was tested using the MAPE, MAE and RMSE accuracy metrics. These approaches are commonly adopted in the literature (McCluskey et al., 2013), and the closer the value of both MAE and RMSE are to 0, the better the model (Lin & Mohan, 2011). MAPE is a measure of the prediction error expressed in percentage. The results shown in Table 5 reveals an MAE value of N61,408,856 and an RMSE value of N103,370.573. In addition, a MAPE value of 38.23% was recorded which depicts that the predictions produced an average error of 38%, which may not be acceptable by a rational real estate stakeholder. These suggest that there is 1 Boys Quarters (BQ) refers to servants’ or maid’s quarters on a property ===== PAGE 11 (score 13, numeric-paren 0, table-words 6, var-words 0) ===== Journal of African Real Estate Research Volume 3(1) 2018 122-140 132 some level of inaccuracies in the HPM approach prediction, this is despite the satisfactory r2 value of 0.77. This confirms that the performance of a model could not be evaluated entirely by adopting the r2 value (Willmott, 1981). The findings of the study corroborate the position of Ogunba and Ajayi (1998) and Babawale and Ajayi (2011), who reported that the level of property valuation inaccuracy prevalent in the Nigerian appraisal practice is unacceptable based on the international standard. Table 5. Predictive Accuracy of the HPM Technique Accuracy metric Hedonic Pricing Model r2 0.77 MAPE (%) 38.23 MAE 61,408,856.10 RMSE 103,370.573.40 The HPM generated from the analysis was used to value the holdout sample in order to establish the predictive accuracy of the HPM technique. The result of the predictions was categorised to establish the percentage of the samples that fell within the acceptable margin and those that did not. The information in Table 6 shows that only 26.67% of the predicted property values have an error margin of between ± 0 and 10%, while 13.33% of the predicted values have an error margin of between ± 11 and 19%. In addition, 60% produced an error of ± 20%. It is worth mentioning that the inaccuracies recorded are high, resulting in wide disparities between the actual property values and predicted values (see Figure 2). Table 6. Valuation Accuracy of the HPM Prediction Accuracy range Frequency (n) Percentage (%) ± 0-10% 8 26.67 ± 11-19% 4 13.33 Above ± 20% 18 60.00 Figure 2: Actual and Predicted Property Values 0 50000000 100000000 150000000 200000000 250000000 300000000 350000000 400000000 450000000 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 Actual Property values HPM predicted values Property prices (N)