ABSTRACT
Worker scarcity in US agricultural field jobs has occurred often, particularly before COVID-19. Because US domestic workers typically forgo field jobs, their participation could potentially alleviate the scarcity. We implement an attribute-based discrete choice experiment administered before and during COVID-19 to evaluate US domestic workers' willingness to accept field jobs and valuation for non-pecuniary benefits. Domestic workers' average pre-pandemic reservation wage rate of $23.57 per hour was 68% larger than the 2019 national average field-worker wage of $13.99. Non-pecuniary benefits (insurance, housing, food allowance, and transportation) lower their reservation wage. Respondents' willingness to accept agricultural field work increased during the COVID-19 pandemic.
ABSTRACT
We implement a discrete choice experiment to examine the impact of COVID‐19 exposure risk, unemployment risk, enhanced and extended unemployment benefits, and job attributes on low‐skilled workers' willingness to accept (WTA) meatpacking jobs. With a sample average WTA wage of $22.77/h, the current national average meatpacking wage of approximately $15/h is too low for these workers to consider this employment opportunity. Enhanced layoff risk and exposure to COVID‐19 further deterred respondents, while health insurance, retirement benefits, and a signing bonus enhanced respondents' WTA. The additional unemployment benefits of the CARES Act neither deterred nor encouraged respondents WTA.
ABSTRACT
The impacts of COVID-19 on labor in the food supply chain and on workers' decisions to accept essential jobs are discussed. We then analyze surveys administered to low-skilled domestic workers before and during the pandemic to assess respondents' attitudes toward food production, guest workers, immigration policy, and the government's response to COVID-19. Results suggest the outbreak resulted in respondents, on average, shifting their view toward food being a national security issue and a higher degree of empathy for H-2A workers. Regression analysis shows that gender, current agricultural workers, and information on COVID-19 and agricultural field workers influenced respondents' answers.