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

Authors

Huanming Wang, Dalian University of Technology
Bin Chen, CUNY Bernard M Baruch CollegeFollow
Joop Koppenjan, Erasmus University Rotterdam

Document Type

Article

Publication Date

2021

Abstract

This article was originally published in Journal of Chinese Governance, available at https://doi.org/10.1080/23812346.2021.1898151

This work is distributed under a Creative Commons Attribution-NonCommercial-NoDerivs International License (CC BY-NC-ND 4.0).

Comments

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