Email
r.ma9@lse.ac.uk

Office Address
Department of Economics
London School of Economics and Political Science
Houghton Street, London WC2A 2AE

Placement Officer
Matthias Doepke

Supervisors
Silvana Tenreyro
Wouter Den Haan

References
Silvana Tenreyro
Department of Economics
London School of Economics and Political Sciences
Houghton St, London WC2A 2AE
s.tenreyro@lse.ac.uk

Wouter Den Haan
Department of Economics
London School of Economics and Political Sciences
Houghton St, London WC2A 2AE
w.denhaan@lse.ac.uk 

Keyu Jin 
Department of Economics 
London School of Economics and Political Sciences 
Houghton St, London WC2A 2AE
keyujin@gmail.com

Download Runhong's c.v.

How Do Robot Subsidies Affect Aggregate Productivity and Firm Dispersion? Theory and Evidence from China

This study examines the effects of robot subsidies in China’s manufacturing sector. Exploiting differences in the timing of the subsidy implementation across municipalities, I find the introduction of a robot subsidy has heterogeneous impacts across firms of different scale. Although the subsidy results in a 13 percent increase in applications for robot patents, the facilitated access to robotics leads to a 14 percent reduction in new firm's entry in the manufacturing sector, along with a significant increase in turnovers of bigger industrial enterprises. Using a stylised model, I show that the interaction between financial frictions and endogenous automation helps reconcile the empirical findings: ex-ante capital misallocation causes a uniform subsidy to disproportionately benefit firms with better access to capital. The distortion creates an efficiency trade-off: while a subsidy can enhance overall automation, it also exacerbates automation dispersion, which reduces efficiency. To quantify the net efficiency impact of these competing forces, I embed this mechanism into a dynamic heterogeneous firm model, calibrated to match key features of the Chinese industrial sector. The model indicates that a robot subsidy of 20% narrows the gap between mean and optimal automation levels by 22 percentage points, while raising automation dispersion by 49 percentage points. This leads to a 1.2 percent increase in aggregate output, along with a 2.4 percent decline in total factor productivity. I Link to paper.

Works in Progress

Development and Innovation of a New Sector- EV Subsidy in China, with Keyu Jin, and Nan Li.

Credit Reallocation and Skill-Biased Technology Adoption in Recessions.

Automation, Financial Frictions and the Business Cycle.

Trapped in Flood? Migration Decisions in Response to Floods in China, with Yuxiao Hu.

Natural Disasters and Spatial Patterns of Innovation, with Haoyu Gao, Yuxiao Hu, and Peixuan Zhao.