At present, there is an urgent need for solutions to enable an improvement in water resource use efficiency and water environment quality in China. Therefore, this study conducted detailed measurement of the per capita grey water footprint in 31 provinces of China (excluding Hong Kong, Macao, and Taiwan) from 2000 to 2014. This study explores the regional inequality and driving factors of the per capita grey water footprint to determine the influence of production and traditional factors on the inequality in per capita water resources and environment. The inequality analysis was performed using a factorial decomposition of the second Theil index of inequality. In particular, based on Kaya factors, we decomposed the per capita grey water footprint into the following five factors:environmental efficiency, technical efficiency, capital output, capital deepening, and economic activity. We found that the overall inequality of the per capita grey water footprint showed a slow fluctuation in recent years. The within-group inequality component was the main contributor to the overall inequality during the entire period, since its proportion of the total in 2014 was 59%. A slight decrease was noted in the within-group inequality in each region. In the three regions considered in this study, the within-group inequality was the largest in the western region, with the index reaching 0.0727 in 2014. The between-group inequality index of the total inequality increased annually, from 0.0067 in 2000 to 0.0449 in 2014, corresponding to an increase of 570%. In the aspect of single factors, capital deepening and technical efficiency are the dominant factors in the total and within-group inequality of the per capita grey water footprint of the central and eastern regions, respectively. Economic activity was the weakest driver of all inequality components. In addition to the economic activity, the other factors were vital for driving the within-group inequality of the per capita grey water footprint in the western region, among which technical efficiency was the strongest driver; the relative weight of this factor was 63.61%. The interaction component results showed that the contribution value of the interaction component between the capital output effect and the grey water footprint per unit GDP was the largest for the western region within-group inequality, and that between the capital deepening effect and the grey water footprint per unit of capital stock was greater in the other regions. In terms of the interaction component between the technical and environmental efficiency effects, the improvement in technical efficiency can lead to a decrease in the proportion of grey water footprint in the eastern and western regions and an increase in the proportion of grey water footprint in the central region. The contribution of the interaction component between economic activity and the per capita grey water footprint of the employment population was minimal.