Motivated by the institutional features of China's monetary policy, this paper aims at identifying the most data favored monetary policy rule for China within a dynamic stochastic general equilibrium (DSGE) model framework. In a canonical New-Keynesian DSGE model, we carry out a positive analysis by employing Bayesian methods to estimate three main categories of monetary policy rules, namely a Taylor-type interest rate rule, a money growth rule and an expanded Taylor rule with money. Based on China's quarterly data from 1996Q2 to 2015Q4, our estimation shows that the expanded Taylor rule obtains the best empirical fit to the data. Moreover, impulse responses and forecast error variance decompositions demonstrate that monetary policy rules with or without money provide very different implications for the policy behavior. Our results ultimately suggest that money has so far been more closely targeted than nominal interest rate and still plays an important role as a monetary policy target in China. Furthermore, a conventional Taylor-type interest rate rule is not good enough yet to describe China's monetary policy behavior. •Taylor rule expanded with money fits Chinese data much better than a conventional Taylor rule.•Policy rules with or without money provide very different implications for China's monetary policy.•Money should be an indispensable policy target when a monetary policy rule is chosen for China.•Our results help to establish consensus on the simple monetary policy rule for China.•Our results provide some rationale of DSGE models used to evaluate China's monetary policy.