Industrial Parks: Productivity Gain and Misallocation Cost

Evaluating Place-based Industrial Policies in China

Do massive investments spent on industrial parks facilitate local economic development in China? 

Since 1982, the Chinese Central Government has built thousands of industrial parks. Although these parks only occupy 0.1% of China’s total land area, they contain 40% of the nation’s manufacturing jobs, contribute 10% of China’s GDP, and 33% of foreign direct investment.


China’s government has spent hundreds of billions of dollars to invest in new industrial parks with the intent of boosting economic growth and generating spillovers for the local economy. Are these investments effectively spent? 

The Birth of Edge Cities in China: 

Measuring the Effects of Industrial Parks Policy

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The Revealed Preference of the Chinese Communist Party Leadership:

Investing in Local Economic Development versus Rewarding Social Connections

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The Birth of Edge Cities in China


This paper tests for the effects of new industrial parks on local production activity and consumer behavior in close proximity to the new parks.


Beijing                                    Chengdu                                     Dalian                                   Shenzhen


Shanghai                                    Tianjin                                     Wuhan                                 Xi'an

Using the opening of 110 industrial parks across 8 major Chinese cities (shown above), we quantify the spillover effects on productivity, wages, employment, homes sales, and retail activities for economic activity close to these new suburban centers of productivity (results shown below). 


Note: Parks' impact area = within two kilometers of the parks' boundary

We find that 70% of new industrial parks built during 1998–2007 in the eight major Chinese cities generate positive total factor productivity (TFP) spillovers in their vicinity, while 30% of those parks turn out to have negative or insignificant TFP spillovers.


This kind of place-based policy can produce significant gains. The results speak to questions about the value of place-based industrial policy, while also providing valuable new data about economic spillover effects — the extent to which the presence of industries creates additional economic activity.


The Revealed Preference of the 

Chinese Communist Party Leadership

In the previous paper, we documented that 30% of parks failed to generate local agglomeration benefits. The fact that we observe very different returns raises a question about the initial site selection problem. 

Why do some Chinese leaders choose the “wrong” city to site expensive place-based investments (industrial parks)?


This paper presents a revealed preference analysis of Chinese leaders’ priorities. We assume that each provincial leader has the same objective function defined over three attributes: economic growth (value added GDP), expected inequality reduction (within-province city-level Gini coefficient based on GDP/capita),  and rewarding social connection (whether there are social connections between provincial leaders and city leaders).

In this project, we constructed three unique and comprehensive datasets.

1. Dataset of industrial parks


Our dataset of industrial parks covers 276 prefecture-level cities during the period of 1988-2008. During our study period, 1,417 national and provincial level industrial parks were built in these 276 cities. 

2. Dataset of city attributes


3. Dataset of social networks

A data innovation in this project is our creation of a detailed social networks database that allows us to track the long term connections between provincial leaders and city leaders at different points in time. 


To build these social connections, we construct a data set on the city and provincial leaders between 1980 and 2010 in China by undertaking a large-scale data collection from Duxiu, a local Scholar Search Engine with millions of digitized literatures, newspapers, journalists and books in Chinese provided by China’s CNKI. This data set enables us to construct four measures of connection based on information on workplace, birthplace, alumni networks, and political factions.

We reconstruct the choice set of possible locations to build a new park and we observe where the park is actually built. The graph below demonstrates the results of our choice model:

Estimated GDP increase and Gini coefficient change 

attributed to a real or a hypothetical park in a city


We find that a provincial leader is willing to sacrifice 1.6% of the province’s annual GDP for helping a connected subordinate. Although Chinese Communist Party may be willing to bear some cost to achieve social stability by reducing income inequality, the misallocation cost triggered by rewarding social connections is a pure loss of social welfare.


Siqi Zheng
MIT China Future City Lab, Department of Urban Studies and Planning, 
Center for Real Estate

Weizeng Sun
Institute for Economic and Social Research, Jinan University

Jianfeng Wu
School of Economics and China Center for Economic Studies (CCES), Fudan University

Matthew Kahn
Department of Economics, USC and NBER

Web & Visual

Haijing Liu
MIT China Future City Lab

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