Financial Strain and Housing Instability during the Pandemic: An Analysis of Covid-19 Impact Data and New State-Level Housing Policies

Background and Purpose:

Even when the country is not facing the life-threatening challenges created by a novel coronavirus, financial strain and housing insecurity affect millions throughout the US. Given the varying nature of state-level housing ordinances and policies, the force of those effects can be experienced quite differently from state to state. While the economic impacts of Covid-19 are being felt across all regions of the country, different states are choosing to implement widely ranging sorts of housing policies—including eviction bans and new considerations for missed rent or mortgage payments-- in response to the current crisis.

In light of these state-by-state differences, our study aims to reveal the potential implications of the pandemic on housing outcomes by using the latest wave of data from the nationwide COVID Impact Survey and the Eviction Lab’s State Housing Policy Scorecard ratings. We conducted a state-level analysis of associations between states’ population-level financial distress and quality of new housing policies implemented in response to the Covid-19 crisis. Our study is guided by the following research question: Do states with higher proportions of financial distress have fewer housing protections for renters and homeowners?

Methods:

The COVID Impact Survey (CIS), a nationally representative real-time survey of COVID-19 effects from NORC, was first fielded in April 2020. It includes variables related to employment, health, and finances. Our sample consisted of 9,310 cases from the CIS. The IV of interest, financial distress, was constructed as a percentage of those --by state-- who responded they “would not be able to pay for it” when asked how they would pay for “an unexpected expense that costs $400.” These state level proportions of financial distress were then merged into a dataset containing the Eviction Lab’s Housing Policy Scorecard and the High Impact Policy designation. The Housing Policy Scores ranged from 0.00 to 5.00 based on Eviction-Lab’s weights and formula of scoring eviction-prevention measures. The High Impact Policy Score was constricted as only five of ten states were included in the analysis. A bivariate Pearson Correlation analysis was used to test the research question.

Results:

We found a statistically significant negative correlation between the proportion of people in ten identified states that would not be able to afford a $400 emergency expense and their state of residence’s housing policy score (R = -.770, p = .009). We also found a statistically significant negative correlation between the same proportions of those who cannot afford the emergency expense and whether their state has what Eviction Lab determined to be a “high-impact” housing policy (R = -.750, p = .012).

Conclusions and Implications:

The apparent link between high proportions of reported financial distress and low-scoring housing policies holds considerable implications for both research and policy advocacy for increased state-level housing protections, especially during times of increased and widespread financial distress. States with highest levels of folks experiencing financial distress have little to no structural response. This could portend further housing loss and insecurity for already vulnerable populations.