Fig 1.
Percentage share of rental value of housing on overall household expenditure for different countries.
Authors data set, and Deaton and Zaidi [4].
Table 1.
Summary statistics of variables used in the house rental value predictions.
Table 2.
Determinants of housing rental values based on Ordinary Least Squares (OLS), LASSO, and ridge regressions models in Uganda.
Table 3.
Determinants of housing rental values based on Ordinary Least Squares (OLS), LASSO, and ridge regressions models in Tanzania.
Table 4.
Determinants of housing rental values based on Ordinary Least Squares (OLS), LASSO, and ridge regression models in Malawi.
Fig 2.
Tree regression in Uganda for 2012.
Table 5.
List of explanatory variables by importance in predicting housing rental values using bagging regression in Uganda.
Table 6.
List of explanatory variables by importance in predicting housing rental values using random forest regression in Uganda.
Table 7.
List of explanatory variables by importance in predicting housing rental values using boosting regression in Uganda.
Table 8.
In-sample prediction performances based on standardized mean squared errors of predicting housing rental values by country and years of analysis.
Table 9.
Out-of-sample prediction performances based on standardized mean squared errors of predicting housing rental values by country and by year, accounting spatial lag autocorrelation (SAR).
Table 10.
Out-of-sample prediction performances based on standardized mean squared errors of predicting housing rental values by country and by year, accounting for spatial error autocorrelation (SEM).
Table 11.
Out-of-sample prediction performances based on standardized mean squared errors of predicting housing rental values by country and by year without accounting for spatial autocorrelation.