TY - JOUR
T1 - The two faces of urbanisation and productivity
T2 - Enhance or inhibit? New evidence from Chinese firm-level data
AU - Wu, Lichao
AU - Jiang, Yanpeng
AU - Wang, Lili
AU - Qiao, Xinhao
N1 - Publisher Copyright:
© 2022 Crawford School of Public Policy, The Australian National University and John Wiley & Sons Australia, Ltd.
PY - 2022/5
Y1 - 2022/5
N2 - This study employs industrial survey data from China's National Bureau of Statistics covering Chinese manufacturing enterprises during the period 1998–2007 to examine the impact of urbanisation on total factor productivity (TFP) in various industries. In recent years, urbanisation development has varied greatly across China. So Chinese cities can be divided into three urbanisation categories based on the proportion of the urban population to the total population: highly urbanised areas (60 per cent and over), moderately urbanised areas (30–60 per cent), and low urbanised areas (0–30 per cent). We estimate industrial TFP levels across these three categories using the Levinsohn–Petrin semi-parametric estimation method. We also divide regional productivity into a productivity index and an industry composition index. We use aspects of these indexes to analyse the impact of urbanisation on TFP. The results confirm that urbanisation can lead to the gathering of economic activities, which in turn generates a positive impact on TFP by reducing transportation cost, promoting new technology spillovers, and encouraging a higher degree of specialisation. Further, the empirical results indicate that the highest TFP does not always occur in highly urbanised areas—most of the industries with the highest TFP are in moderately urbanised areas. These findings have important policy implications regarding how to improve the TFP of enterprises in order to generate scale effects.
AB - This study employs industrial survey data from China's National Bureau of Statistics covering Chinese manufacturing enterprises during the period 1998–2007 to examine the impact of urbanisation on total factor productivity (TFP) in various industries. In recent years, urbanisation development has varied greatly across China. So Chinese cities can be divided into three urbanisation categories based on the proportion of the urban population to the total population: highly urbanised areas (60 per cent and over), moderately urbanised areas (30–60 per cent), and low urbanised areas (0–30 per cent). We estimate industrial TFP levels across these three categories using the Levinsohn–Petrin semi-parametric estimation method. We also divide regional productivity into a productivity index and an industry composition index. We use aspects of these indexes to analyse the impact of urbanisation on TFP. The results confirm that urbanisation can lead to the gathering of economic activities, which in turn generates a positive impact on TFP by reducing transportation cost, promoting new technology spillovers, and encouraging a higher degree of specialisation. Further, the empirical results indicate that the highest TFP does not always occur in highly urbanised areas—most of the industries with the highest TFP are in moderately urbanised areas. These findings have important policy implications regarding how to improve the TFP of enterprises in order to generate scale effects.
UR - https://www.scopus.com/pages/publications/85126863657
U2 - 10.1111/apel.12352
DO - 10.1111/apel.12352
M3 - 文章
AN - SCOPUS:85126863657
SN - 0818-9935
VL - 36
SP - 126
EP - 142
JO - Asian-Pacific Economic Literature
JF - Asian-Pacific Economic Literature
IS - 1
ER -