UCLA Center for Neighborhood Knowledge Director Paul Ong was featured in a USA Today article about the disproportionate impact of the COVID-19 pandemic on Black families. Black people are more than twice as likely to rent as white people, eliminating the safety net that comes with owning a home. Furthermore, Black renters are more likely to be low-income and cost burdened, the article noted. The pandemic exacerbated existing inequalities due to racial discrimination and historic inequities in education, employment and housing. “The pre-pandemic disadvantages that were there already – paying a higher share of one’s income to afford housing, having a much more precarious economic standing, not having the same financial fallback with huge differences in wealth and assets – those disadvantages during the pandemic got magnified,” Ong explained. “During the pandemic, our research and other people’s research clearly shows that African Americans were displaced at a much higher rate.”
Paul Ong, director of the Center for Neighborhood Knowledge at UCLA Luskin, spoke to NBC News about the findings of a recent survey on the impact of the COVID-19 pandemic on Asian-owned businesses. The survey of 400 Asian-owned businesses in Southern California found that a disproportionate number were forced to close their doors and fire staff during the pandemic. Ong explained that Asian-owned businesses tend to be in sectors that were the most impacted — such as food service, hospitality and retail — and that many of them didn’t have the money to keep their businesses open when profits took a nosedive. “The racism throughout the pandemic also led people to avoid businesses in Asian neighborhoods altogether,” Ong added. Many small businesses were unable to benefit from federal assistance programs due to language barriers and lack of outreach in Asian communities about the existence of such programs and their application processes.
UCLA Luskin’s Martin Gilens and Paul Ong shared insights on economic and political inequality and opportunity as part of a panel organized by the UCLA Anderson Forecast, a quarterly report that frames the economic outlook for California and the nation. Released Sept. 29, the latest report identified a shift from earlier forecasts, which had raised hopes for a blockbuster recovery as COVID-19 vaccines became widely available. Heading into the final quarter of 2021, these hopes have been tempered by the spread of the Delta variant and stagnating vaccination rates, which in turn have led to consumer caution. A panel of experts hosted by the Anderson Forecast brought context to these findings, with a focus on how income is distributed unevenly across the United States. Gilens, chair of UCLA Luskin Public Policy, said political and economic inequality are intertwined, resulting in policies that cater to moneyed interests. “Taming the role of money in American politics won’t be easy, especially with an unsympathetic Supreme Court, and … won’t by itself fix everything that ails our democracy,” Gilens said. “But it’s hard to see how we can fix American democracy without reducing the dominance of money in our politics.” Ong, director of UCLA’s Center for Neighborhood Knowledge, focused on race and ethnicity as factors in the job, food, housing and educational insecurity that persists across generations. “I would encourage my colleagues to think much more explicitly about the fundamentals of why race and racism exist within an economy,” he said. “Simply saying that everybody should have equal opportunity doesn’t make it so.”
View the Anderson Forecast presentation, including a keynote address by Mary C. Daly, president of the Federal Reserve Bank of San Francisco.
UCLA Center for Neighborhood Knowledge Director Paul Ong spoke to KPCC and LAist about findings from a survey of members of the Asian Business Association of Los Angeles. More than 400 association members described how their businesses were faring, confirming Ong’s fears that Asian-owned businesses have disproportionately suffered during the pandemic, a trend that has been exacerbated by a surge in anti-Asian incidents. More than half of the survey respondents said they had to close at some point during the pandemic, and nearly a third said their operating capacity had dropped by more than 50%. “I actually believe this is a conservative estimate,” said Ong, pointing out that the negative impact might be even worse than the English-only survey was able to capture. “So many of the hardest-hit businesses are run by immigrants who don’t speak English as their first language,” he said. Ong recommended that policymakers prioritize targeted outreach offered in many languages to support Asian-owned businesses.
Director of the Center for Neighborhood Knowledge Paul Ong was featured in the Los Angeles Times, Associated Press and Long Beach Post discussing the results of the 2020 Census and its impact on communities of color. Accurate census counts are crucial for the distribution of federal aid and congressional representation, but Ong’s analysis of the census data suggests that Hispanic and Black populations may have been undercounted more than other groups. “There is strong evidence that undercounts in the 2020 census are worse than in past decades,” he said. Ong noted that renters, undocumented immigrants and low-income households were also undercounted, partially due to the disruption caused by the pandemic and the Trump administration’s attempt to include a citizenship question. “The big-picture implication is it will skew the redistricting process, our undercounted neighborhoods will be underrepresented, and populations that are undercounted will be shortchanged when it comes to the allocation of federal spending,” Ong concluded.
Prior to the 2020 U.S. census, many observers feared that large segments of the population would be undercounted. Those fears appear to have been realized, according to a UCLA analysis of the census data.
The study, conducted by the UCLA Center for Neighborhood Knowledge, found that in Los Angeles County, residents in some neighborhoods were much more likely than others to be excluded from the 2020 census. Specifically, the research (PDF) concluded that — at the census-tract level — undercounts were most likely in areas where the majority of residents are Hispanic or Asian, have lower incomes, rent their homes or were born outside of the U.S.
Paul Ong, a research professor at the UCLA Luskin School of Public Affairs, and Jonathan Ong of Ong and Associates, a public-interest consulting firm, combed through data published Aug. 12 by the U.S. Census Bureau.
“The results are, unfortunately, consistent with our worst fear that the 2020 enumeration faced numerous potentially insurmountable barriers to a complete and accurate count,” Paul Ong said.
The research team compared the information to earlier population estimates drawn from the census bureau’s American Community Survey to determine whether and where the 2020 enumeration appeared to undercount or overcount the population within each neighborhood in Los Angeles County.
A key difference between the American Community Survey and the 2020 census, Paul Ong said, is that the COVID-19 pandemic severely affected data collection for the census. Previous research showed that disruption was particularly pronounced in disadvantaged neighborhoods. That appears to have created a “differential undercount,” meaning that some populations were more likely than other groups not to be counted. That, in turn, means that the scope of ethnic diversity and demographic change in cities like Los Angeles could be significantly underestimated, he said.
Based on comparisons between the latest census data and the most recent American Community Survey estimates, the UCLA study found that in Los Angeles County:
- Predominantly Hispanic neighborhoods are most likely to have the largest undercounts in the census.
- Neighborhoods with the greatest percentage of people living below the poverty line were most likely to have undercounts.
- Neighborhoods with larger percentages of renters, as opposed to homeowners, were more likely to have undercounts.
- Census tracts in which most people are U.S.-born were more likely to be accurately counted than predominantly immigrant neighborhoods.
The pandemic wasn’t the only factor that hampered data collection for the 2020 census. The effort was also adversely affected by the Trump administration’s highly publicized push to include a citizenship question on the questionnaire. Although that effort was ultimately unsuccessful, Paul Ong said the controversy may have depressed participation among immigrants, whether they were undocumented or not.
“The findings indicate that the needless politicization of the 2020 enumeration seriously dampened participation by those targeted by the Trump administration,” he said.
Problems with the self-reporting aspect of the census placed greater pressure on the subsequent on-the-ground outreach in which census-takers canvassed nonresponding households. The success of that follow-up drive will not be known until a post-census analysis is conducted, which is scheduled for 2022.
The UCLA analysis is consistent with results from previous studies that have shown undercounts likelier to occur in disadvantaged communities. How residents are counted is important because census results influence legislative redistricting and government spending, which means the results can have serious political and economic implications.
“Given the analysis, it is imperative that we address the inequality in the census to ensure fair political representation in redistricting,” Paul Ong said.
Unlike previous corrective efforts, which address census undercounts based on national statistics and results from a comparatively small number of districts, the UCLA research relied on data specific to each neighborhood. As a result, Paul Ong said, the new approach should be more accurate and precise, and it could ultimately help officials understand how to adjust population statistics to account for the differential bias in completing the 2020 census and future counts.
Undercounts are of most concern, but the technique could also help identify overcounts, which are rarer but can occur. Military redeployments may lead to overcounts, for example; other situations include some students who get counted twice while splitting time between home and college, and miscounts of people with second homes or people who experience a stay in a nursing home while also holding a permanent residence.
Ong & Associates, of which Paul Ong is the founder, provided services pro bono for the study.
Research by Paul Ong, director of the Center for Neighborhood Knowledge, is highlighted in a Los Angeles Times article focusing on COVID-19’s impact on Korean families involved in the dry cleaning businesses, which has struggled amid the pandemic. In 2015, Ong co-authored a paper that investigated ethnic mobilization among Korean dry cleaners in the United States. Starting in the 1970s, Korean immigrants welcomed one another into the dry cleaning business with loans, moral support and training. “The children are quite often at the business … it’s a way of supervising them in terms of their education,” the researchers wrote. During the pandemic, dry cleaners lost revenue because many customers moved to virtual work, and at least a quarter of these family-oriented businesses have closed because of the pandemic, according to a representative of the Korean Dry Cleaners & Laundry Assn. of Southern California.
A Los Angeles Times story on landlords who skirt anti-eviction rules enacted in response to the COVID-19 outbreak cited research from the Center for Neighborhood Knowledge (CNK) at UCLA Luskin. A Times analysis of data from the Los Angeles Police Department revealed more than 290 instances of potential illegal lockouts and utility shutoffs across the city over 10 weeks beginning in March. The largest share of those police calls was in predominantly Black and Latino neighborhoods in South L.A. CNK research shows that members of these communities, who faced disproportionately high rent burdens even before the pandemic, often work in food service and other sectors with significant wage reductions and job losses due to COVID-19. “This is a web of urban inequality,” CNK Director Paul Ong said. “We could talk about housing, we could talk about jobs, we could talk about health. But the truth of the matter is all these things are interlocked.”
Scholars from the UCLA Center for Neighborhood Knowledge (CNK) and UCLA Luskin Center for Innovation (LCI) collaborated on the new report “Keeping the Lights and Heat On: COVID-19 Utility Debt,” which analyzed the burden of household utility debt for many families, especially in low-income neighborhoods. The report, co-authored by CNK Director Paul Ong and LCI Associate Director Greg Pierce, used data from Pacific Gas and Electric Company (PG&E), an investor-owned utility that provides electricity and gas service to about 40% of California residents, in order to quantify the prevalence and degree of residential past-due accounts and debt. The authors explained that utility debt levels serve as a useful proxy to track households that are facing difficulties paying their rent or mortgage, particularly during economic crises. While roughly 6% of the Northern and Central California households served by PG&E are facing financial difficulties paying for most essential services, utility debt burden is highest among Black, Latino and economically vulnerable neighborhoods, the study found. PG&E recently announced that it will extend a moratorium on utility service disconnections through September 30, although many other emergency customer protections put in place during the COVID-19 pandemic have expired. The authors of the report recommend allocating funding to debt-forgiveness programs for low-income households and severely impacted neighborhoods. They plan to replicate the study in non-PG&E service areas to better understand the impact of energy and water bill debt across regions. — Zoe Day
A Healthcare Innovation article on the use of artificial intelligence and predictive analytics to inform public health efforts put a spotlight on the work of the Center for Neighborhood Knowledge at UCLA Luskin. The center created a tool that maps Los Angeles County neighborhoods to assess residents’ vulnerability to COVID-19 infection. The predictive model used four indicators: preexisting medical conditions, barriers to accessing health care, built-environment characteristics and socioeconomic challenges that create vulnerabilities. “The UCLA case study is emblematic of precisely the kinds of use cases that will be emerging in the coming years, as healthcare leaders start to plumb the vast potential of AI and other forms of predictive analytics to serve the purposes of public health here in the U.S.,” the article said.