ZHENG FAN

Professor CHANG Pao Li
Email: plchang@smu.edu.sg
Tel: +65 68280830

Professor MEI Yuan
Email: yuanmei@smu.edu.sg
Tel: +65 68085212

Professor MA Lin
Email: linma@smu.edu.sg
Tel: +65 68280876

WORKING PAPERS

"Using Satellite-observed Geospatial Inundation Data to Identify the Impacts of Flood on Firm-level Performances: The Case of China during 2000--2009", With Pao-Li Chang (Job Market Paper)

Among the first in the literature, this paper combines high-resolution satellite-observed inundation maps with geocoded firm-level data to identify the flood exposure at the firm level. We apply the methodology to study the impact of floods on micro-level firm performances in China for the period 2000-2009. Being hit by a flood is associated with an annual loss of output and productivity of around 6% and 5%, respectively, which persists in the long run. The effects are heterogeneous across types of firms and locations of the floods. Firms that are tangible-asset intensive are more negatively affected by the flood events. Meanwhile, the effects on firms located in flood-prone counties are less severe and shorter-lived, suggesting better adaptation of firms experienced with floods. The impacts of floods extend to non-inundated firms in surrounding areas (of 4 kilometres in radius), but the negative effects are much smaller (2% on average) and diminish after three years. Firms beyond the immediate neighborhood expand their output from the second year onward, in contrast with the permanent shrinkage of the inundated firms. By aggregating the firm-level data to the county level, we further identify negative effects of floods at the extensive margin: the firm exit (entry) rate is higher (lower) in counties that are hit by floods, and the effects are stronger in counties subject to more severe floods.

"The Response of the Chinese Economy to the U.S.-China Trade War: 2018-2019", With Pao-Li Chang and Kefang Yao

In this paper, we follow the micro-to-macro approach of Fajgelbaum et al. (2020) and analyze the impacts of the 2018-2019 U.S.-China trade war on the Chinese economy. We use highly disaggregated trade and tariff data with monthly frequency to identify the demand/supply elasticities of Chinese imports/exports, combined with a general equilibrium model for the Chinese economy (that takes into account input-output linkages, and regional heterogeneity in employment and sector specialization) to quantify the partial and general equilibrium effects of the tariff war. This complements the studies focused on the ex post response of the U.S. economy by Amiti et al. (2019), Flaaen et al. (2020), Fajgelbaum et al. (2020), and Cavallo et al. (2021).