Many earlier studies have assessed Chinese poverty using monetary dimensions, but few have considered the time dimension. This research investigates multidimensional poverty in urban China, using data from the 2013 China Household Income Project, from the standpoints of income and time. A logistic regression model was used to estimate the socioeconomic causes of income poverty, time poverty, and income–constrained time poverty. Empirical results obtained from this study reveal that being a paid female worker or a private enterprise employee and bearing the financial burdens of housing and medical care have significant effects on the probability of being time poor. In addition, workers who have low academic achievement, children, and educational loans are particularly prone to suffering income–constrained time poverty. This study contributes to the assessment of severe poverty situations and suggests an increasing need for working time regulations and more support for less-educated workers in urban China.