Administrative Division Adjustment and Housing Price Comovement: Evidence from City‐County Mergers in China

• Published date: 01 July 2022
• Author: Sihan Zhang,Ming‐ang Zhang,Weizeng Sun
• Date: 01 July 2022
• DOI: http://doi.org/10.1111/cwe.12431

©2022 Institute of World Economics and Politics, Chinese Academy of Social Sciences

China & World Economy / 149–173, Vol. 30, No. 4, 2022 149

*Sihan Zhang, Assistant Professor, School of Economics and Management, Intelligence Accounting Research

Center, Beijing Information Science and Technology University, China. Email: zhangsihan_zsh@163.com;

Ming-ang Zhang (corresponding author), Assistant Professor, School of Public Finance and Taxation, Central

University of Finance and Economics, China. Email: zhangmingang@cufe.edu.cn; Weizeng Sun, Associate

Professor, School of Economics, Central University of Finance and Economics, China. Email: sunweizeng@

gmail.com. This research was supported financially by the Program for Innovation Research at Central

University of Finance and Economics (No. 020150321004) and the National Natural Science Foundation of

China (No. 71903210). We thank Professor Weida Kuang for his instructions in the early stage of this research.

Administrative Division Adjustment and

Housing Price Comovement:

Evidence from City-County Mergers in China

Sihan Zhang, Ming-ang Zhang, Weizeng Sun*

Abstract

Interregional housing price comovement is a stylized fact worldwide. This study explores

how it is affected by administrative division adjustment. We exploit city-county mergers in

China as a quasi-natural experiment to construct a difference-in-differences strategy for

causal identifi cation. Based on monthly housing price data for districts (counties) in China

from 2010 to 2019, we find that city-county mergers significantly improve correlations

in housing prices between the merged county and the urban district. This effect is more

obvious in cities with a large economic gap between merged counties and urban districts,

located in the central and western regions, and with lower administrative hierarchies (non-

provincial-capital cities). The mechanism test shows that the impact of city-county mergers

on housing price comovement results mainly from integrating housing demand rather

than integrating housing supply, like the unifi ed land supply policy that local government

implements in the new administrative scope after mergers. The results are helpful in

understanding housing price comovement from the view of regional integration and provide

clear policy implications for housing market regulation in China.

Keywords: administrative division adjustment, border effect, city-county merger, housing

price comovement

JEL codes: R12, R31, R58

I. Introduction

Reducing the risks in the housing market and improving its long-term stability and

healthy development are critical for Chinese economy and the vital interests of the people.

Sihan Zhang et al. / 149–173, Vol. 30, No. 4, 2022

©2022 Institute of World Economics and Politics, Chinese Academy of Social Sciences

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Unlike conventional fi nancial assets, a house is typically a nontradeable good, the price

of which has obvious regionalized characteristics. Previous studies have documented that

housing prices and their fl uctuations are not only time series correlated (Jud and Winkler,

2002) but also intercorrelated across regions (Zhang and Morley, 2014; Duan et al.,

2019). Moreover, there is a border effect on housing prices due to the existence

of administrative boundaries (Chien, 2010; Fereidouni et al., 2016). Such spatial

correlation intensifies the transmission of systemic financial risks among housing

markets in different regions (Montagnoli and Nagayasu, 2015) and threatens the stability

of the whole economy. However, little attention has been given to the causal relationship

between spatial boundaries and housing price comovement, especially its underlying

mechanism. This study fills this gap by focusing on one representative regional

integration policy, namely, administrative division adjustment in China, and explores its

effect on house-price spatial comovement.

After nearly 20 years of rapid growth, the real-estate industry has become a pillar

of China’s economy. The risk behind housing prices is closely related to the nation’s

economic stability. Since 2006, the Chinese government has implemented a series of

market control policies and has restrained the excessive growth rate of housing prices

successfully. The previous control policies, either the one-size-fits-all policy in the

early stage or the regional specific policies in the latter stage, did not consider the

linkage of housing prices and the impact of administrative boundaries on housing price

comovement. In this paper, we take advantage of the unique city-county mergers (chexian

shequ) practice in China, which eliminate administrative boundaries among regions, as a

quasi-experiment for empirical analysis.

Based on micro data for county-level housing prices from 2010 to 2019, the

difference-in-differences (DID) estimation finds that city-county merge significantly

enhance housing price comovement between the merged county and the previously

existing municipal districts. This conclusion remains robust when subjected to

various robustness tests, including the parallel-trend test, excluding other concurrent

policies, the permutation test, using the propensity score matching method, excluding

the spillover effect, and excluding municipality samples. A further mechanism test

shows that the impact of city-county mergers on housing price comovement results

primarily from the integration of housing demand rather than the unifi ed land supply.

Heterogeneous analyses fi nd that the impact of city-county mergers on housing price

comovement usually is larger in counties with larger economic gaps with the municipal

district, which are located in central and western China. This evidences the city-county

mergers’ positive roles in stimulating factor fl ow, eliminating the administrative barriers,

and promoting economic synergy, further supporting our mechanism analyses.