Table 5 Estimation results for using quality as the dependent variable.

From: The COVID-19 pandemics and import demand elasticities: evidence from China’s customs data

Full sample

Y = Δ ln Quality

Monthly: 2019m1 to 2021m3

(1)

(2)

(3)

 

All

Ordinary

Processing

Δ ln RER_CNY

0.552*** (0.153)

0.263 (0.190)

1.284*** (0.154)

Δ ln RER_CNY × Policy

−1.586*** (0.236)

−0.857*** (0.266)

−2.831*** (0.284)

Δ ln RER_CNY × HHI

0.131 (0.142)

0.0437 (0.220)

−0.260 (0.319)

Δ ln RER_Comp

0.0381*** (0.003)

0.0444*** (0.003)

0.0244*** (0.003)

Δ ln RER_Comp × Policy

−0.00841*** (0.002)

−0.00786* (0.004)

−0.00524 (0.003)

Δ ln RER_Comp× HHI

−0.0333*** (0.002)

−0.0380*** (0.003)

−0.0231*** (0.005)

Δ ln Cases in exporting country

−0.00558*** (0.002)

−0.00529** (0.002)

−0.00620** (0.002)

Constant

−0.208*** (0.013)

−0.0183*** (0.005)

−0.165*** (0.014)

Controls

Yes

Yes

Yes

Province-time FE

Yes

Yes

Yes

Province-product-country FE

Yes

Yes

Yes

Time FE

Yes

Yes

Yes

N

1272973

696152

374452

R2

0.073

0.101

0.083

Prob > F-statistic

0.000

0.000

0.000

  1. Note: We employ the Chinese customs data on China’s imports, which contain information regarding different Asian countries’ exports to different Chinese provinces. An increase in ΔlnRER_Comp implies a real appreciation of competitors’ currencies, and an increase in ΔlnRER_CNY implies a real depreciation of RMB against that one Asian trading partner’s currency (bilateral). A larger HHI implies a higher degree of market concentration for Asian economies in exporting to China. *, **, *** indicate variables significant at 10%, 5%, and 1% level respectively. Clustered standard errors at provincial level are reported in parenthesis.