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Abstract
Firm relocation has become a critical mechanism for optimizing
resource allocation and promoting regional economic transformation amid urban
functional restructuring and coordinated regional development. Using Beijing
firm relocation data from 2010 to 2024, this study examines firm relocation
dynamics and determinants at both macro and micro levels. At the macro level, a
panel vector autoregression (PVAR) model incorporating firm out-migration,
in-migration, and regional GDP is used to analyze their dynamic interactions.
At the micro level, relocation data of Beijing-listed firms are analyzed using
a zero-inflated negative binomial (ZINB) model to assess the effects of firm
size, firm age, and industry characteristics on relocation frequency. Results
show that firm relocation exhibits significant path dependence and
self-reinforcing dynamics. Short-term out-migration releases spatial resources
and facilitates new firm entry, while persistent out-migration may reduce
long-term regional attractiveness. The economic effects on destination regions
are stage-dependent, shifting from short-term adjustment costs to medium- and
long-term growth benefits. Micro-level findings indicate that larger firms
relocate more frequently, firm age shows an inverted U-shaped relationship with
relocation, manufacturing firms move less often, and high-tech firms tend to
remain location-stable. These findings provide empirical insights for
understanding firm relocation behavior and inform policies for regional
coordination and urban development.
JEL classification numbers: R12, D22, L25.
Keywords: Firm heterogeneity, Panel vector autoregression
(PVAR), Zero-inflated negative binomial model (ZINB).