In this paper, the convergence clustering in 31 Chinese provinces regarding several important economic indicators over the period 1952 to 2016 was empirically investigated. Several provincial clusters were identified in the per capita (real) gross domestic product (GDP), consumption–income ratio, retail price, and consumer price inflation rates, using a club convergence and clustering procedure. The empirical findings are as follows. First, it was found that all series of the original data contain a significant nonlinear component. Second, it was observed that there are five significant clusters for the per capita income in China. Third, it was found that there are four significant clusters for the consumption–income ratio. Fourth, it was observed that there are four significant clusters for the retail inflation rates and two significant clusters for the consumer inflation rates in China. These results will enable local and central planners to implement economic growth, savings and price adjustment policies for different groups of provinces.