The paper extends the methodology of parametric decomposition of the Malmquist productivity index using an output distance function. This approach addresses common methodological issues in total factor productivity estimation to produce credible and relevant results. The Malmquist index can be decomposed into several components: technical change (further broken down into technical change magnitude, input bias, and output bias), technical efficiency change, scale efficiency change, and output-mix effect. A translog output distance function is chosen to represent the production technology, and each component of the Malmquist index is computed using the estimated parameters. This parametric approach allows us to statistically test hypotheses regarding different components of the Malmquist index and the nature of production technology. The empirical application to Chinese agriculture shows that productivity grows at 2 percent per year on average from 1978 through 2010. The growth is mostly driven by technical change, which is found to be technology neutral.