Can others learn from China's remarkable growth rate? We explore some indirect determinants of Chinas growth success including the degree of openness, institutional change and sectoral change, based on a cross-province dataset. Our methodology is the informal growth regression, which permits the introduction of some explanatory variables that represent the underlying as well as the proximate causes of growth. We first address the problem of model uncertainty by adopting two approaches to model selection, Bayesian Model Averaging and the automated General-to-Specific approach, to consider a wide range of candidate predictors of growth. Then variables flagged as being important by these procedures are used in formulating our models, in which the contribution of factors behind the proximate determinants are examined using panel data system GMM. All three forms of structural change - relative expansion of the trade sector, of the private sector, and of the non-agricultural sector - are found to raise the growth rate. Moreover, structural change in all three dimensions was rapid over the study period. Each change primarily represents an improvement in the efficiency of the economy, moving it towards its production frontier. We conclude that such improvements in productive efficiency have been an important part of the explanation for China's fast growth.