This article measures economic returns to research investment in Chinese agriculture using the production function approach. A stock-of-knowledge variable constructed from the past research investment is directly included in the production function as an explanatory variable in the production function. Improved rural infrastructure, irrigation, and education are also included as explanatory variables to avoid the upward bias in the estimates of returns to agricultural research. A two-way variable coefficients technique is used in the estimation to reduce estimation biases due to the remaining measurement and omitted variables problems. Sensitivity analyses are conducted to test the effects of various lag structures on the return estimates, The results show that rates of return to research investment in Chinese agriculture are high, ranging from 36% to 90% in 1997, and the rates are increasing over time.