Decoding Political Trust in China: A Machine Learning Analysis

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Abstract

Survey results inflate political trust in China if the observed trust in the central government is mistaken for the latent trust in the Centre. The target of trust in the country is the Centre, which is ultimately the top leader. The critical issue domain for assessing the Centre's trustworthiness is policy implementation rather than policymaking. The Centre's trustworthiness has two dimensions: commitment to good governance and the capacity to discipline local officials. Observed trust in the central government indicates trust in the Centre's commitment, while observed trust in the local government reflects confidence in the Centre's capacity. A machine learning analysis of a national survey reveals how much conventional reading overestimates political trust. At first glance, 85 per cent of the respondents trust the central government. Upon further inspection, 18 per cent have total trust in the Centre, 34 per cent have partial trust and 33 per cent are sceptical.

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APA

Li, L. (2022). Decoding Political Trust in China: A Machine Learning Analysis. China Quarterly, 249, 1–20. https://doi.org/10.1017/S0305741021001077

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