Process of Agglomeration and TFP Change


Student thesis: Master's Thesis

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Award date7 Sept 2021


Enterprises' agglomeration generally occurs in urbanized areas and has a snowball effect during the process of agglomeration. This paper employs industrial survey data from the National Bureau of Statistics (NBS), covering Chinese manufacturing enterprises with annual sales of at least RMB 5 million during the period of 1998–2007. We examine the impact of agglomeration on the total factor productivity (TFP) of enterprises in China. In recent years, urbanization within China has developed rapidly, but the urbanization development is disparity all around the country. In this study, Chinese cities are divided into three urbanization categories: high urbanized, moderate urbanized, and low urbanized. We estimate the TFP of enterprises in different categorical urbanized areas using the Levinsohn–Petrin semi-parametric estimation method as well as focus on the relationship between agglomeration and TFP of enterprises. Meanwhile, we also do effect decomposition of regional productivity, and then analyze the impact of agglomeration on the TFP in three categorical urbanized areas from aspects of productivity index and industry composition index. The results confirm that agglomeration can lead to the gathering of economic activities, which thus generate a positive impact on TFP by reducing transportation cost, promoting new technologies spillover, and achieving a higher degree of specialization. Furthermore, our empirical results show that the highest TFP does not always occur in highly urbanized areas—most of the industries have the highest TFP in moderately urbanized areas—which provide new evidence for the ever-increasing research on the issue of agglomeration and enterprises' performance. These findings have an important economic and policy implication regarding how to improve the TFP of enterprises by agglomeration in order to generate scale effect.

    Research areas

  • Agglomeration, Total Factor Productivity, Industry Composition, Levinsohn–Petrin Semi-parametric Estimation Method