Impact of COVID-19 and Nationwide Lockdowns on Vegetable Prices: Evidence from Wholesale Markets in China

Abstract

In this paper, we employ a combination of time regression discontinuity design method (T-RD) and the difference-in-difference method (DID) to identify and quantify the causal effects of the strict lockdown policy on vegetable prices using multiple-year daily price data from 151 wholesale markets of Chinese cabbage. We find that the lockdown policy caused a large and immediate surge in price and price dispersion of Chinese cabbage, though they fluctuated smoothly for the same period in normal years. The DID results further show that the price surge peaked in the fourth week of lockdown but gradually came down to the level of a normal year by week 11. However, the price rose again (though to a much smaller extent) in response to the resurgence of COVID-19 in a few provinces in early-mid April but quickly returned to the normal level in week 15 when the lockdown measures were largely removed. We also find that the supply chain disruption is the driving factor for the price hike. Policy implications are drawn.

Keywords: COVID‐19; China; Chinese cabbage; H12; I18; Q11; Q18; nationwide lockdowns; price dispersion; time regression discontinuity design; vegetable price; wholesale markets.

Figure 1

Possible channels for the lockdown policy to affect vegetable prices

Figure 2

Distribution of the 151 wholesale markets

Figure 3

Discontinuity in Chinese cabbage price. Notes: The solid line shows the fit of fourth‐order polynomial T‐RD estimation and the shaded areas are the 95 percent confidence intervals. The results are robust to the lower orders of polynomial specifications.

Figure 4

Falsification test: Chinese cabbage price of 2018 and 2019. Notes: The solid line shows the fit of fourth‐order polynomial T‐RD estimation and the shaded areas are the 95 percent confidence intervals.

Figure 5

Weekly impacts of nationwide lockdown on Chinese cabbage price. Notes: The circles are point estimates of DID and the intervals are the 95 percent confidence intervals. The week before lockdown is excluded as baseline group.

Figure 6

Discontinuity in difference of Chinese cabbage price between markets. Notes: The solid line shows the fit of fourth‐order polynomial RD estimation based on equation (3) and the shaded areas are the 95 percent confidence intervals.

Figure 7

Discontinuity in labor mobility intensity between cities. Notes: The solid line shows the fit of fourth‐order polynomial T‐RD estimation and the shaded areas are the 95 percent confidence intervals.

Figure 8

Monthly freight volume in 2020 and 2019 by province. Notes: The value of the vertical axis starts from 70 instead of zero.