Data required to analyze causal relationships between residential electricity consumption and its explanatory factors.

In order to contribute to the enrichment of studies on causal relationships linked to electricity consumption in the residential sector, four annual frequency explanatory factors are used, covering the period 1994-2019. These are GDP per capita, an indicator of individual income, and the ability of each person to take out an ongoing electricity subscription. CO2 emissions are also among the factors with a causal relationship to electricity consumption. Although it is assumed that there is no causality between CO2 emissions and national electricity consumption in Cameroon, it would be interesting to carry out a targeted assessment within the residential sector. As in the Talbi et al. 2020 analyses, the urbanization factor is also taken into account in this study. However, the price factor is not taken into account. Prices per kWh are stable and depend only on consumption ranges. For consumption below 110 kWh, the price is set at 0.09 USD/kWh; between 111 kWh and 400 kWh, the price is 0.145 USD/kWh; between 401 kWh and 800 kWh, the price is 0.170 USD/kWh, while between 801 kWh and 2000 kWh, the price is set at 0.180 USD/kWh. This segmented distribution of electricity prices within the residential sector makes it difficult to take into account any price trends that could be compared with trends in electricity consumption. The number of subscribers is also included in the list of factors explaining electricity consumption. This is based on the assumption of a fairly close link with electricity consumption. The databases of the International Energy Agency provide information on electricity consumption in Cameroon's residential sector (REC in GWh). Data on GDP (in current US dollars), CO2 emissions from thermal power generation (in kilotons of CO2) and urban population (UR) are available in the World Bank database. Finally, data on the number of subscribers (NS) are provided by electricity distributor ENEO Cameroon. These variables cover the period 1994-2019, during which the country's economy and demographic factors are growing overall. Some descriptive statistics based on these data are calculated. Mean, maximum and minimum values, standard deviation, skewness and kurtosis are all included. In theory, if the skewness of a given time series is between [-3,3] and its kurtosis is between [ -10,10], the series has a normal distribution and is representative of the physical process it describes. Our calculations show that the kurtosis and skewness of each time series meet the aforementioned reliability conditions. Consequently, the associated data are reliable representations of the real fluctuations of each variable. Statistical tests suggest unidirectional causality, from all explanatory factors to electricity consumption. Indeed, any growth in GDP per capita leads to growth in electricity consumption without feedback. Urbanization and growth in the number of subscribers are intensifying electricity consumption.

为增进对与住宅用电消费相关的因果关系的学术研究，本研究选取了涵盖1994-2019年间的四个年度频率的解释性因素，包括人均国内生产总值、个人收入指标以及每人获取持续电力订阅的能力。碳排放也是与电力消费存在因果关系的因素之一。尽管假设喀麦隆的碳排放与国家电力消费之间不存在因果关系，但在住宅部门进行有针对性的评估仍颇具意义。正如Talbi等人在2020年的分析中所述，本研究亦考虑了城市化因素，然而价格因素并未纳入考量。每千瓦时的电价稳定，且仅取决于消费区间。对于低于110千瓦时的消费，电价为0.09美元/千瓦时；介于111至400千瓦时之间，电价为0.145美元/千瓦时；介于401至800千瓦时之间，电价为0.170美元/千瓦时；而介于801至2000千瓦时之间，电价设定为0.180美元/千瓦时。这种住宅用电部门电价的分段分布使得难以考虑与电力消费趋势相比较的价格趋势。订阅者数量也被纳入解释电力消费的因素列表。这基于与电力消费之间较为紧密的关联性的假设。国际能源署的数据库提供了关于喀麦隆住宅用电消费（以吉瓦时为单位）的信息。国内生产总值（以现行美元计）、热电发电产生的二氧化碳排放量（以千吨二氧化碳计）和城市人口（UR）的数据可从世界银行数据库中获取。最后，电力分销商ENEO喀麦隆提供了关于订阅者数量（NS）的数据。这些变量涵盖了1994-2019年期间，国家经济和人口因素整体增长的时间段。基于这些数据，计算了一些描述性统计量。包括平均值、最大值和最小值、标准差、偏度和峰度。从理论上讲，如果给定时间序列的偏度在[-3,3]之间，其峰度在[-10,10]之间，则该序列具有正态分布，并能代表所描述的物理过程。本研究的计算结果表明，每个时间序列的峰度和偏度均满足上述可靠性条件。因此，相关数据是每个变量实际波动可靠表现的代表。统计检验表明存在单向因果关系，即所有解释性因素对电力消费的影响。确实，人均国内生产总值的增长会导致电力消费的增长，且不存在反馈。城市化和订阅者数量的增长正在加剧电力消费。