A refined experimentalist governance approach to incremental policy change: the case of process-tracing China’s central government infrastructure PPP policies between 1988 and 2017

How public policies change incrementally over time remains understudied. This paper contributes to the studies of incremental policy by integrating theories layering and learning into a theoretical framework experimental governance (EG). Using mixed research method, we apply this process-tracing changing trajectory China’s central government infrastructure public-private partnership (PPP) from 1988 2017 looking at evolving goals, measures, co-issuing networks. Results suggest that PPP follows refined EG approach in which pattern, primarily driven learning. Findings provide new account change.