Policy Experimentation in China: the Political Economy of Policy Learning. Shaoda Wang & David Y. Yang. NBER Working Paper 29402. October 2021. DOI 10.3386/w29402
Abstract: Many governments have engaged in policy experimentation in various forms to resolve uncertainty and facilitate learning. However, little is understood about the characteristics of policy experimentation, and how the structure of experimentation may affect policy learning and policy outcomes. We aim to describe and understand China’s policy experimentation since 1980, among the largest and most systematic in recent history. We collect comprehensive data on policy experimentation conducted in China over the past four decades. We find three main results. First, more than 80% of the experiments exhibit positive sample selection in terms of a locality’s economic development, and much of this can be attributed to misaligned incentives across political hierarchies. Second, local politicians allocate more resources to ensure the experiments’ success, and such effort is not replicable when policies roll out to the entire country. Third, the presence of sample selection and strategic effort is not fully accounted for by the central government, thus affecting policy learning and distorting national policies originating from the experimentation. Taken together, these results suggest that while China’s bureaucratic and institutional conditions make policy experimentation at such scale possible, the complex political environments can also limit the scope and bias the direction of policy learning.
Bipartisan Alliance, a Society for the Study of the US Constitution, and of Human Nature, where Republicans and Democrats meet.
The big experiment in China on policy experimentation doesn't offer hard data with which to work. Is it due to human temptations under which we operate? These normal biases make the experiments hardly replicable, they do not scale well. This is very general of human activities, but it is magnified in structured, guided policies.
ReplyDelete