Description:

Please join this joint Comparative/IR Graduate Workshop as they host Qin Huang, Northwestern Political Science Ph.D. candidate.

Abstract: This paper explores the dynamic interplay between state intervention and market forces in China's economic growth since 1978, focusing on the development models of Chinese provinces and their corresponding state types in economic governance. It introduces a novel panel dataset of over 30 macroeconomic variables to categorize provinces into four distinct socialist market economy types through machine learning techniques like time-series hierarchical clustering and UMAP. These types are quasi-liberal market, dual-market, state-dominating, and state-retreating, each characterized by varying degrees of state ownership/investment and market infrastructure development. Through in-depth interviews with government officials, state enterprise managers, and entrepreneurs across eight representative provinces, this chapter elucidates the interactions between different economic agents within these models. It identifies four types of local economic state—entrepreneurial, regulatory, predatory, and passive—corresponding to the developmental models and influenced by fiscal incentives and power dynamics among government agencies. This paper also explores the conditions under which state interventions either replace or enhance market rules. In state-dominated economies with resource-heavy industries, the state monopolizes key resources, overriding market rules, whereas in dual-market systems, the state-owned sector is often embodied in administrative headquarters rather than engaging in direct manufacturing, preserving market principles and private sector opportunities. By comparing the quasi-liberal market and state-retreating economies, my evidence suggests that merely reducing state interventions does not automatically foster the development of market infrastructure; substantial fiscal resources are essential for this development.

Qin Huang is a PhD candidate in the Department of Political Science with a substantive focus on political economy, institutional change, and bureaucratic politics, particularly in the context of China. On the methodological research front, he is keen on exploring the potential of machine-learning algorithms in complementing qualitative induction.