ABSTRACT
Chinese migrant workers are very exposed to the shocks caused by the COVID-19 pandemic. Falling remittances adversely affect their families who rely on remittance incomes. The impacts of COVID-19 on migrants and remittance-receiving households are assessed using a nationally representative household dataset and a microsimulation model. We found about 70 percent of migrant workers lost part of their wage income during the pandemic lockdown period and rural migrants working in small and medium enterprises were affected the most. This led to about 50 percent of remittance-receiving households being affected adversely by falling remittances, and the average decline in such income was more than 45 percent. Nearly 13 percent of pre-pandemic nonpoor remittance-receiving households could fall into poverty, raising the poverty rate among remittance-receiving households by 4 percentage points. Many households that were poor prior to the pandemic became more impoverished. The results indicate that social protection programs targeting vulnerable migrants and their families at home are important.
ABSTRACT
Purpose: The purpose of this study is to assess the potential economic cost of the COVID-19 pandemic on China's macroeconomy and agri-food system and provide policy recommendations to stimulate economic growth and agri-food system development. Design/methodology/approach: An economy-wide multisector multiplier model built on China's most recent social accounting matrix (SAM) for 2017 with 149 economic sectors is used to assess the impact of COVID-19 on China's macroeconomy and agri-food system. SAM multiplier analysis focuses on supply chain linkages and captures the complexity of an interconnected economy. Findings: The paper finds that both the macroeconomy and agri-food systems are hit significantly by COVID-19. There are three main findings. First, affected by COVID-19, GDP decreased by 6.8% in the first quarter of 2020 compared with that in 2019, while the economic loss of the agri-food system is equivalent to 7% of its value added (about RMB 0.26 trillion). More than 46m agri-food system workers (about 27% of total employment) lost their jobs to COVID-19 in the lockdown phase. The COVID-19 affects the employment of unskilled labor more than that of skilled labor. Second, when the economy starts to recover during the second and third quarters, the growth rate in the value added of the agri-food system turns positive but still modest. Many jobs resume during the period, but the level of agri-food system employment continues to be lower than the base. The agri-food system employment recovery is slower than that of other sectors largely due to the sluggish recovery of restaurants. Agri-food system employment drops by 8.6m, which accounts for about 33% of the total jobs lost. Third, although the domestic economy is expected to be normal in the fourth quarter, external demand still faces uncertainties due to the global pandemic. The agri-food system is projected to grow by 1.1% annually in 2020 with resuming export demand, while only by 0.4% without resuming export demand. These rates are much lower than an annual growth rate of 4.3% for the agri-food system in 2019. The results also show that, without resuming export demand, China's total economy will grow less than 1% in 2020, while, with export demand resumed, the growth rate rises to 1.7%. These rates are much lower than an annual GDP growth rate of 6.1% in 2019. Practical implications: The results show that continuously reducing economic dependency on exports and stimulating domestic demand are key areas that require policy support. The agri-food system can play an important role in supporting broad economic growth and job creation as SMEs are major part of the AFS. Job creation requires policies to promote innovation by entrepreneurs who run numerous SMEs in China. Originality/value: This paper represents the first systematic study assessing the impact of COVID-19 on China's agri-food system in terms of value added and employment. The assessment considers three phases of lockdown, recovery and normal phases in order to capture the full potential cost of COVID-19.