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An analysis of household water consumption in the City of Cape Town using a panel data set (2016-2020)
Understanding consumer behaviour with respect to water consumption has become an active field of study. This thesis uses a household billing dataset that tracks the quantity of water consumed by households in the City of Cape Town (CoCT) from 2016 to 2020. The household billing data was filtered to...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2023
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| Summary: | Understanding consumer behaviour with respect to water consumption has become an active field of study. This thesis uses a household billing dataset that tracks the quantity of water consumed by households in the City of Cape Town (CoCT) from 2016 to 2020. The household billing data was filtered to include only household observations and then aggregated to the ward level. As a result, the aggregated data is a balanced spatial panel dataset including 20 quarterly observations for each of the 88 wards. Using the billing data set, multiple linear regression models, panel data models as well as spatial panel models were implemented to predict ward level water consumption. Using several visualisations and statistical measures, this thesis found that consumption dropped significantly during the drought period (2016-2018) and also found spatial clusters of water consumption in the CoCT. The data showed that before and after the drought, water consumption exhibited a seasonal pattern which was absent during the drought period. It is also noted that although consumption levels after the drought increase, they do not rise as high as pre-drought levels. The linear models implemented in this thesis resulted in an Adjusted R-squared values of up to 0.85, implying that the independent variables used in the models explain a large amount of variation observed in the dependent variable, quantity of ward level water consumption. |
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