By Ignacio Aravena González
With Covid-19, uncertainty reigns due to the lack of accurate measures and facts, which represents a challenge to evidence-based decision-making. Under these circumstances, aside from the use of quantitative methods, a holistic vision can help to find weak links to tackle the pandemic. On such approach is offering financial support to undocumented immigrants to nudge them into staying home. Due to this lack of perspective, the city is not ready to open again. More importantly, the city needs to act fast since this is not only a health crisis; we are also facing increasing risks of an economic recession too.
Policymakers are using lagged data between test results — which also have a delay — and the infection time, which can take up to 14 days to emerge; during this time, people can still spread the virus. More importantly, since data relies on testing, the number of cases is underestimated due to lack of test availability, exacerbating uncertainty and the detection of possible patterns,1 transforming this issue into a fat tails problem — meaning that traditional statistics techniques have less power to predict and explain trends. Moreover, models and scenarios rely on several assumptions that are sensitive to variations, like betting that people are immune after recovery, able to get back to their daily routine after getting infected. What would happen if reinfection occurs massively, something that is being contested currently?2 Meanwhile, extending social distancing doesn’t sound plausible in the light of an economic depression that could lead to a worse outcome of extending the health crisis while the fiscal capacity and the economic system becomes weaker.3,4
Accurate counts are important since several decision-making methods, such as cost-benefit analysis, use them; it’s virtually impossible to be accurate when facing fat-tailed distributions and unknown facts that can become potential weak links in an estimation. Furthermore, it is necessary to consider people’s behavior and how they value time and isolation differently than policymakers, especially regarding leisure and social contact. This phenomenon is known as hyperbolic discounting, which is aggravated in low-income families without social security. In many cases, they are forced to keep working to avoid famine and continue paying rent, making it more valuable in the present to work, even if the chances of infection are high. These facts are worsened when considering that the infection rate is higher than 30%, making every day relevant to any decision.
More holistic schools of thought like net assessment and disaster planning help when working under high uncertainty and against time. Examples include thinking about possible missing causal links and tipping points — defined as events with low probabilities of happening that can have a high impact if they do — to prevent situations that can intensify current trends. Focusing on externalities can help to assess this goal, allowing them to think of long-term goals and actions to achieve them. Examples are containment and economic policy rescue, helping to balance between flattening the health curve and appeasing threats of an economic recession curve.5 However, in the US, this policy doesn’t consider informal labor and its subsequent impact on appeasing infection rates, becoming a potential weak link.
Communities with the highest rate of infection are usually in low-income ZIP codes. Here, health issues are more prevalent, and these communities also often work in informal and essential jobs, making social distancing nearly impossible and forcing these people to continue to commute and interact with people frequently. In cities like New York, where there are about 550,000 undocumented people,6 not considering them in the aid package — they don’t have social security numbers — creates high negative externalities. This fact becomes relevant when observing that they cluster in the most infected ZIP codes of the city7 and that the death rates have been found to concentrate in disadvantaged populations.8 In this case, hyperbolic discounting plays an essential role since these families are forced to work and are exposed to infection, all of which decrease the effectiveness of social distancing.
Not providing relief funds to undocumented immigrants is a weak link that can worsen the outcomes of the pandemic, cumulatively undermining other actions — even if they are targeted in the right direction. This crisis can exacerbate rent burden and debt accumulation in disadvantaged communities9 — especially when considering that about 89% of the rent-burdened population are in extremely low- and very-low-income households.10 Then, opportunities such as becoming a shopper or working in delivery become attractive to these families, making them potential infection spreaders across the city. Consequently, not funding them can be counterproductive to overall city goals, leading to more chances of overcrowding hospitals and making health provision less effective — imposing a higher cost to society since death rates can increase.11 Ultimately, another subjacent risk is present: preserving infection clusters can lengthen the shutdown time, exacerbating the negative economic outcome, and multiplying the effects of the pandemic.
Finally, the current situation brings the opportunity of doing a horizon scanning regarding citywide goals. As a city that is proud to host immigrants and make them part of the economic fabric, is New York ready to offer them support in hard times? Or, are they just merely a cheap — and replaceable — part of the supply and production chains?
Due to the observed high rates of infections in the city, uncertainty, and the existence of spatial clusters of infections, the city is not ready to reopen yet. More importantly, every day counts even more due to the exponential growth of the disease, requiring preventive actions to diminish the lockdown times — if not, the economic and health impacts will be higher than expected. The administration has an opportunity to speed this process up by providing financial relief to the city’s undocumented immigrants, something that would also send a consistent message of support to a part of the population that historically has helped the city to become a world’s capital.
Ignacio Aravena González is a Master of Urban Planning candidate at the NYU Wagner School of Public Service, specializing in Housing and Economic Development. He is interested in housing policy, economic analysis and the use of quantitative methods to better inform and design policies aimed at solving inequality and segregation.
1 This is similar to survivorship bias, when concentrating in the known facts instead of asking about the unknown.
11 Based on the premise that the value of life is much higher than funding thousands of families. For example, if considering the SVL as $9 Million, this funds 7,500 grants of $1,200.