The paper contributes to the measurement of poverty and vulnerability in three ways. First, we propose a new approach to separating poverty into chronic and transient components. Second, we provide corrections for the statistical biases introduced when using a small number of periods to estimate the importance of vulnerability and transient poverty. Third, we apply these tools to the measurement of chronic and transient poverty in China using a rich panel data set that extends over approximately 17 years. We find that alternative measurement techniques yield significantly different estimates of the relative importance of chronic and transient poverty, and that precision of estimates is enhanced with simple statistical corrections.