Testing the Chinese Development Model under the Capabilities Approach: The Effects of Preferential Policies and Special Economic Zones on Inequality and Social Justice

Project Information

CHINEQUALJUSTICE

Grant agreement ID: 838534

DOI

10.3030/838534

Project closed

EC signature date 22 October 2019

Start date 1 July 2020

End date 30 June 2022

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 172 932,48

EU contribution

€ 172 932,48

Coordinated by

INSTITUT QUIMIC DE SARRIA
Spain

Periodic Reporting for period 1 - CHINEQUALJUSTICE (Testing the Chinese Development Model under the Capabilities Approach: The Effects of Preferential Policies and Special Economic Zones on Inequality and Social Justice)

Reporting period: 2020-07-01 to 2022-06-30

Summary of the context and overall objectives of the project

Over the last forty years, the PRC has employed a unique model of development, relying on the experimentation of preferential policies in special economic zones and a combination of state-managed and market-oriented economic policies. As a result, the PRC has consistently outperformed negative economic forecasts and outlooks based on traditional western economic theories and modelling, earning it the characterization of a “development and growth miracle”. However, the PRC’s plans are to transition into an economy that won’t be led by production and exports, but instead by services and consumption. This ongoing, and gradual, transition will affect the relationship between China and international economies. Firms that rely on Chinese goods and services will experience higher costs and prices, while new opportunities will emerge for firms selling goods and services to the increasingly-open Chinese consumer market. The main objective of this research proposal is the identification of which sectors of the Chinese population and economy are better prepared and suited for the upcoming transitions.
General Objective 1: Identify which population groups are heading towards prosperity and which are at greatest risk.
General Objective 2: To establish if the identified groups will have sufficient rights and social justice to prosper.
General Objective 3: The creation of a development-capabilities index for different sectors of the Chinese population and economy that will indicate policymakers, domestic and foreign firms, the public and academics what the current state, and potential, for the next market reforms will be.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Data collection. We codified annual statistics reports for over 2600 universities in China to create three novel higher education indices for 31 Chinese provinces: i) the Chinese Higher Education Density Index (CHEDI) to analyze the evolution of the quantitative distribution of higher education institutions (HEIs) in each province from 2001 to 2017, which is further decomposed into subgroups based on the type of college, i.e. four-year undergraduate colleges, two-year vocational colleges, and private institutions; ii) the Chinese Higher Education Quality Index (CHEQI) to examine the supply of higher education in terms of quality using a university ranking system; and iii) the Chinese Higher Education Index (CHEI), a composite indicator that incorporates both the quantity and quality dimensions of higher education institutions for each province, providing a weighted measure of the supply of higher education in China.
We also created a composite analysis of children’s academic development based on comprehensive outcomes, including valuable processes, and introduced a series of innovative indicators rooted in the capability approach.

Jorgenson-Fraumeni Human Capital estimates for 31 Chinese provinces were analyzed using a club convergence clustering algorithm. The results show the regions with highest prosperity, namely, Beijing, Shanghai, and Tianjin, together with Anhui and Chongqing. The latter two, despite still being below a number of other provinces, are accumulating per capita human capital at a faster pace, enabling them to catch up with the top three. Zhejiang leads the largest subgroup, and even diverges away from it when adjusting for the differences in the cost of living, following its own human capital growth path. Most worrying are the provinces at the lower bound, including the western-border members of (Yunnan, Tibet, Gansu, Xinjiang), as well as the divergent Qinghai.
Rights and social justice were analyzed via the capabilities approach, whereby we examined the human development of children in China. We created a composite analysis of children’s academic development based on comprehensive outcomes, including valuable processes, and introduced a series of innovative indicators rooted in the capability approach. The results present an index of parents’ advantages and a new indicator of spending priorities to identify the value of children’s education that families have prioritized through their resource allocation choices.
Finally, the empirical findings indicate a significant and persistent heterogeneity in the supply of higher education between provinces. The higher education indices identify which regions have been substantially rewarded by the higher education expansion of recent decades, going from an undersupply to a proportionate supply of higher education institutions.

Results have been published in the Journal of Asian Economics and China Economic Review. They have also been presented at conferences organized by the Chinese Economists Society, the Chinese Economic Association UK/Europe, and the Spanish Applied Economics Association. The project also organized and sponsored the 1st International Workshop on the Chinese Development Model in Barcelona.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Human capital was for the first time analyzed under the novel club convergence approach, the Kaya-Zenga and the EGR clustering algorithm.
A unique dataset was created by codifying the Annual Reports of Higher Education Institutions published by the Chinese Ministry of Education. It is the first paper to propose and construct indices for the supply of higher education institutions.
A handful of businesses and organizations in Spain have already begun exploiting the project results. A couple of PhD students are already using the project datasets in their research.
By improving resource allocation in human capital accumulation, the project outcomes have the potential to reduce human capital inequalities which are likely to translate and spill over to reductions in other types of economic and social disparities. The results of the project will lead to an improved high-skilled labor market that will promote sustainable development in cities and communities. The project outcomes will improve human development and capabilities. This outcome will make European communities less vulnerable to future crises. Vulnerable people with lower human capital are often less represented in the democratic process. By reducing the human capital inequalities, citizens will be empowered to participate more, thus promoting social inclusion. The project delves into the human capital interventions, human development and capabilities, and research infrastructures in China to bring new knowledge and insights for European society by upgrading independent knowledge on Contemporary China in Europe.

China Development