Real Estate Boom and Firm Productivity: Evidence from China
| Published date | 01 October 2021 |
| Author | Junxue Jia,Jia Gu,Guangrong Ma |
| Date | 01 October 2021 |
| DOI | http://doi.org/10.1111/obes.12434 |
Real Estate Boom and Firm Productivity: Evidence
from China
JUNXUE JIA,JIA GUand GUANGRONG MA
China Financial Policy Research Center, School of Finance, Renmin University of China,
Beijing, China (e-mail: jiajunx@ruc.edu.cn; 2012200273@ruc.edu.cn; grma@ruc.edu.cn)
Abstract
Studies on the relationship between housing prices and firm behaviours have focused
on the relationship between housing prices and firm financing and investment
decisions. However, housing prices may affect other firm decisions. This study
investigates the impact of housing prices on manufacturing firm productivity in China.
To identify the causal effect, we use a national land regulation policy and city-level
developable land area as exogenous sources of variation in housing prices. Using an
instrumental variable approach to regression analysis and firm-level data, we find that a
10% increase in housing prices leads to a 2.1% reduction in manufacturing firms’total
factor productivity (TFP). An important transmission channel is the inflow of bank
credit to the real estate market caused by rising housing prices, thus crowding out
loans to manufacturing firms. Due to China’s distinctive dual-track land market, rising
housing prices do not translate into an increase in the price of industrial land;
therefore, collateral values for manufacturing firms do not increase. We further find
that the negative effect of housing prices on TFP is more pronounced for firms with
greater external financial dependence or greater financial constraints.
I. Introduction
Considerable research has focused on the co-movement of housing prices and
macroeconomic fundamentals, especially since the rapid collapse of the real estate
bubble in Japan and the United States (e.g. Iacoviello, 2005; Arce and L´
opez-Salido,
2011; Martin and Ventura, 2012). However, to understand the microeconomic
foundations of these phenomena, it is necessary to analyse how firms behave in
response to real estate price fluctuations empirically. The literature has primarily
investigated firm financing and investing behaviours in the face of real estate price
shocks and has emphasized the collateral channel as the underlying mechanism for
this relationship. The collateral channel suggests that because real estate can be used as
Jia acknowledges financial support from National Social Science Foundation of China (No. 17ZDA048),
Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of
China (No. 10XNJ001). Ma acknowledges financial support from the National Natural Science Foundation of
China (Nos 71773125 and 71973142).
1218
©2021 The Department of Economics, University of Oxford and John Wiley & Sons Ltd
OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 83, 5 (2021) 0305-9049
doi: 10.1111/obes.12434
collateral for additional borrowing to finance new projects, real estate boom will
‘crowd in’corporate investment. (Iacoviello, 2005; Gan, 2007; Chaney et al., 2012).
However, it is still unclear whether real estate prices affect firm productivity, a crucial
factor for long-run economic growth.
This study provides direct empirical evidence of how real estate prices affect firm
productivity by exploiting the recent real estate boom in China. China’s real estate
market has experienced a prolonged boom since 2003 (Glaeser et al., 2017).
According to China’s National Bureau of Statistics (NBS), the average per square
metre housing price increased from 2,359 yuan in 2003 to 7,892 yuan in 2017, and
total investment in the real estate market increased from 1.02 trillion yuan in 2003 to
10.98 trillion yuan in 2017.
Drawing on firm-level data that cover approximately 90% of the gross output of
China’s manufacturing sector and city-level housing prices, we examine how housing
prices affect firms’total factor productivity (TFP).
1
To address the potential
endogeneity of housing prices, we use an instrumental variable approach. Specifically,
we exploit two sources of exogenous variation in housing prices. First, since 31
August 2004, the Chinese central government has banned negotiated sales of
commercial-cum-residential land and encouraged more competitive forms of tenders,
auctions and open listings in the commercial-cum-residential land market (hereinafter,
the 2004 Regulatory Policy). This policy resulted in more monopoly power in the real
estate market, thus substantially increasing land prices and then housing prices (see
section III for a more detailed discussion). Second, since steep slopes and water bodies
are topological constraints for housing construction, the 2004 Regulatory Policy has a
larger positive impact on housing prices for cities with less developable land.
Exploiting these two variations, we instrument city-level housing prices using the
interaction between a post-2003 period dummy and the area of city-level developable
land. We find a strong first-stage result: after the 2004 Regulatory Policy was issued,
housing prices increased more rapidly in cities with less developable land. The second-
stage results show that housing price appreciation negatively affects manufacturing
firm productivity. A 10% increase in housing prices leads to a 2.1% decrease in firm-
level TFP. Our findings are robust to alternative TFP measures and housing price
indices.
We further detect that one important underlying channel is the crowding out
channel. In response to the real estate boom, banks grant more credit to the real estate
sector (in both loans to real estate companies and household mortgage loans),
tightening the financing constraints of manufacturing firms and hampering their
productivity. Using city-level information about the composition of bank credit across
sectors, we find that higher housing prices increase the amount of credit flowing into
the real estate sector and simultaneously reduce the amount of credit available to the
1
The housing prices we use are average selling prices for all new commercialized buildings (see section II for
more details). In China, commercialized buildings include three main types: residential buildings, office
buildings and houses for business use. The land used for commercialized buildings is called commercial-cum-
residential land. There are also non-commercialized buildings, such as government-owned houses (often
provided as welfare for government employees), affordable housing (often for low-income families) and
industrial buildings (owned by industrial firms). The land used for industrial buildings is called industrial land.
©2021 The Department of Economics, University of Oxford and John Wiley & Sons Ltd
Real estate boom and firm productivity1219
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