Tracking the COVID-19 Recession’s Effects on Food, Housing, and Employment Hardships

The unemployment rate is very high and millions report that their households did not get enough to eat or are not caught up on rent payments. We are able to track the extent of this hardship thanks to nearly real-time data from several sources on the unfolding economic crisis.

The impacts of the pandemic and the economic fallout have been widespread, but are particularly prevalent among Black, Latino,^[1] Indigenous, and immigrant households. These disproportionate impacts reflect harsh, longstanding inequities — often stemming from structural racism — in education, employment, housing, and health care that the current crisis is exacerbating.

Relief measures have mitigated hardship, but there are significant gaps — including, for example, leaving out the poorest households from any increase in SNAP benefits — and implementation challenges that have delayed aid to some households. The measures, which are also temporary, have begun to expire.

The data below, which we will update periodically, drive home the need for substantial, continued relief measures. The extent and severity of continued hardships like hunger, eviction, and homelessness will depend on whether such relief is robust and reaches those in need, as well as the trajectory of the pandemic and the pace of economic recovery. The implications for children in particular are significant: households with children face especially high hardship rates, which research has shown can have serious effects on children’s long-term health and financial security.

Emerging Data Show High Rates of Hardship

The Census Bureau’s Household Pulse Survey, launched in April, has provided nearly real-time weekly data on how the unprecedented health and economic crisis is affecting the nation. Data from this and other sources, such as unemployment data from Census’ Current Population Survey and the Department of Labor, show that tens of millions of people are out of work and struggling to afford adequate food and pay the rent. The impacts on children are large (see figures 1, 4, and 5).

For more on our methodology and data by state, see tables 1-5 at the end of this document.

Difficulty Getting Enough Food

Data from several sources show a dramatic increase in the number of households struggling to put enough food on the table. Nearly 26 million adults — 12 percent of all adults in the country — reported that their household sometimes or often didn’t have enough to eat in the last seven days, according to Household Pulse Survey data collected October 28–November 9. This was far above the pre-pandemic rate: a recent survey released by the Agriculture Department found that 3.7 percent of adults reported that their household had “not enough to eat” at some point over the full 12 months of 2019.^[2] When asked why, 85 percent said they “couldn’t afford to buy more food,” rather than (or in addition to) non-financial factors such as lack of transportation or safety concerns due to the pandemic.

Figure 1

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Adults in households with children were likelier to report that the household didn’t get enough to eat: 16 percent, compared to 9 percent for households without children. (See Figure 1.) And 10 to 14 percent of adults with children reported that their children sometimes or often didn’t eat enough in the last seven days because they couldn’t afford it, well above the pre-pandemic figure. Households typically first scale back on food for adults before cutting back on what children have to eat. (The 10-14 percent range reflects the different ways to measure food hardship in the Household Pulse Survey.)

Also, analysis of more detailed data from the Pulse survey collected October 14–26 shows that between 7 and 11 million children live in a household where children didn’t eat enough because the household couldn’t afford it. These figures are approximations; the Pulse Survey was designed to provide data on adult well-being, not precise counts of children.

Black and Latino adults were more than twice as likely as white adults to report that their household did not get enough to eat: 22 percent and 19 percent, respectively, compared to 9 percent of white adults. (See Figure 2.)

Figure 2

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Inability to Pay Rent or Mortgage

The Household Pulse data also show that millions are not caught up on their rent or mortgage payments. Unfortunately, there are two concerns with the housing questions. First, the Census Bureau reworded the housing questions starting with the late-August survey, making the results non-comparable to earlier weeks of the survey. Second, a large share of the survey respondents chose not to answer the housing questions in the latest survey. This “non-response” is higher among groups that are younger, have lower levels of education, and identify as Black or Latino — groups that are more likely to struggle to afford rent, due to longstanding inequities often stemming from structural racism in education, employment, and housing. For these reasons, the Pulse data likely understate the number of people struggling to pay rent.

Even with these issues, however, the data indicate that millions are having difficulty paying rent. An estimated 13.4 million adults living in rental housing — nearly 1 in 5 adult renters — were not caught up on rent, according to data collected October 28–November 9.^[3] Here, too, renters of color were more likely to report that their household was not caught up on rent: 33 percent of Black renters, 17 percent of Latino renters, and 16 percent of Asian renters said they were not caught up on rent, compared to 14 percent of white renters. (See Figure 3.)

Figure 3

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In addition, 28 percent of renters who are parents or otherwise live with children reported that they were not caught up on rent, twice the 12 percent rate among adults not living with anyone under age 18. (See Figure 4.)

Figure 4

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Children in renter households also face high rates of food hardship. Over 1 in 4 children living in rental housing live in a household that didn’t have enough to eat, according to data for October 14-26 (the latest detailed data that allow us to make these estimates). Four in 10 children living in rental housing live in a household that either isn’t getting enough to eat or is not caught up on rent. (See Figure 5.)

Figure 5

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While households that don’t rent their homes but have mortgage payments typically have higher incomes than renters, they, too, can face difficulties, especially if they have lost their jobs or seen their incomes fall significantly. An estimated 10 million adults are in a household that is not caught up in its mortgage payment.^[4]

Difficulty Covering Household Expenses

Since late August, the Household Pulse Survey has provided data on the overall number of adults struggling to cover usual household expenses such as food, rent or mortgage, car payments, medical expenses, or student loans. Nearly 81 million adults — 1 in 3 — reported it was somewhat or very difficult for their household to cover usual expenses in the past seven days, according to data collected October 28–November 9. While we don’t have comparable data from before the pandemic, the data noted above on rising levels of food hardship over pre-pandemic rates indicate that economic insecurity has increased.

Adults in households with children were more likely to report difficulty paying for usual expenses: 42 percent, compared to 29 percent for households without children. Financial hardship can have serious effects on children’s long-term health and education, research shows.^[5]

In addition, Black and Latino adults reported difficulty covering expenses at higher rates: 52 percent and 47 percent, respectively, compared to 28 percent for Asian adults and 27 percent for white adults. (See Figure 6.) Although the survey does not provide data for other individual racial groups, 41 percent of American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and multiracial adults taken together reported difficulty paying for usual expenses.

Figure 6

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An estimated 43 percent of children live in households that have trouble covering usual expenses, according to our analysis of detailed data from the Pulse survey collected October 14–16. They include 62 percent of children in Black households, 55 percent of children in Latino households, 33 percent of children in white households, and 27 percent of children in Asian households. (The Pulse survey asks the race of the adult respondent, not the children.)

Unemployment Is High, With Job Losses Concentrated in Low-Paid Industries

The unemployment rate jumped in April to a level not seen since the 1930s — and still stood at 6.9 percent in October. Some 10.8 percent of Black workers and 8.8 percent of Latino workers were unemployed in October, compared to 6.0 percent of white workers. Unemployment has also risen faster among workers who were born outside the United States (this includes individuals who are now U.S. citizens) than U.S.-born workers. Changes in unemployment going forward will likely heavily depend on both how well the nation does in controlling the spread of the virus and the steps policymakers take to provide effective stimulus that boosts overall demand for goods and services.

The majority of jobs lost in the crisis have been in industries that pay low average wages, with the lowest-paying industries accounting for 30 percent of all jobs but 52 percent of the jobs lost from February to October, the latest month of Labor Department employment data. Jobs in low-paying industries were down almost twice as much between February and October 2020 (10.7 percent) as jobs in medium-wage industries (5.9 percent) and almost three times as much as in high-wage industries (3.6 percent). (See Figure 7.)

Figure 7

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Data from the Census Bureau’s monthly Current Population Survey released October 7 provide more detail on jobless workers and their family members:

• Some 31 million people either met the official definition of “unemployed” (meaning they actively looked for work in the last four weeks or were on temporary layoff) or lived with an unemployed family member in September. This figure includes 7 million children.
• The official definition of “unemployed” leaves out some workers sidelined by the crisis, such as those who are absent from their jobs without pay and jobless workers who want a job but aren’t currently looking for one. These include owners of businesses shut by the pandemic and people who have health concerns, are sick or caring for a sick relative, or need to care for their children because school or child care is closed. If we also include the family members of these workers, as many as 54 million people, or 1 in 6 people in the country, live in families with a sidelined worker.

State-by-State Food, Housing, and Employment Hardship Data

Data by state show that hardship is widespread. The following tables provide state-level data on:

• the share of adults reporting that their household didn’t have enough to eat (Table 1);
• the share of adults saying children in their household were not eating enough because they couldn’t afford enough (Table 1);
• the increase in SNAP caseloads (Table 2);
• the share of adults not caught up on rent (Table 3);
• the share of adults saying their household had difficulty paying for their usual expenses (Table 4); and
• the three-month moving average unemployment rate and recent jobless claim data (Table 5).

For data from the Pulse survey we average data collected October 14–26 and October 28–November 9 to improve the accuracy of the state estimates.

Differences in Pulse hardship rates between states may reflect sampling error, so we suggest not drawing strong conclusions from modest differences between states. The data do show, however, that high levels of hardship are widespread across the country.

Difficulty Getting Enough Food

The Pulse survey asks adult respondents if their household did not have enough to eat and if children in the household were not eating enough because the household couldn’t afford it.

TABLE 1
High Shares of Households Report Difficulty Getting Enough Food
Among adults; data collected October 14–November 9. How to read this table: In the United States, over 24 million adults reported that their household sometimes or often didn’t have enough to eat in the last seven days. This represents 11 percent of all adults in the country. Nearly 12 million adults living with children reported that “the children were not eating enough because we just couldn’t afford enough food.” This represents 14 percent of adults living with children.
	Adults Reporting That Household Didn’t Have Enough to Eat		Adults Reporting That Children in Household Weren’t Eating Enough Because Couldn’t Afford Enough
State	Number	As a Percent of Adults	Number	As a Percent of Adults Living with Children
United States	24,823,000	11%	11,694,000	14%
Alabama	470,000	15%	156,000	12%
Alaska	52,000	11%	27,000	14%
Arizona	589,000	12%	262,000	15%
Arkansas	263,000	13%	120,000	17%
California	3,056,000	12%	1,680,000	16%
Colorado	384,000	10%	173,000	11%
Connecticut	258,000	11%	112,000	13%
Delaware	81,000	12%	31,000	13%
District of Columbia	47,000	10%	22,000	13%
Florida	1,601,000	11%	667,000	13%
Georgia	856,000	12%	431,000	15%
Hawai’i	77,000	8%	48,000	12%
Idaho	113,000	9%	58,000	12%
Illinois	613,000	7%	425,000	13%
Indiana	542,000	12%	203,000	12%
Iowa	192,000	9%	66,000	9%
Kansas	183,000	10%	90,000	12%
Kentucky	380,000	13%	129,000	12%
Louisiana	561,000	19%	249,000	20%
Maine	70,000	8%	17,000	6%
Maryland	507,000	13%	263,000	16%
Massachusetts	386,000	8%	165,000	10%
Michigan	781,000	12%	263,000	11%
Minnesota	232,000	6%	139,000	10%
Mississippi	351,000	19%	191,000	23%
Missouri	452,000	11%	168,000	12%
Montana	62,000	9%	26,000	11%
Nebraska	138,000	11%	50,000	10%
Nevada	295,000	14%	193,000	22%
New Hampshire	75,000	8%	29,000	9%
New Jersey	486,000	8%	291,000	12%
New Mexico	191,000	13%	116,000	21%
New York	1,598,000	13%	576,000	12%
North Carolina	738,000	10%	361,000	13%
North Dakota	41,000	8%	21,000	13%
Ohio	981,000	13%	452,000	17%
Oklahoma	327,000	13%	132,000	12%
Oregon	262,000	9%	112,000	11%
Pennsylvania	987,000	11%	338,000	11%
Rhode Island	63,000	9%	25,000	11%
South Carolina	551,000	16%	236,000	17%
South Dakota	35,000	6%	12,000	5%
Tennessee	493,000	11%	200,000	11%
Texas	2,619,000	14%	1,513,000	19%
Utah	158,000	8%	69,000	7%
Vermont	39,000	9%	14,000	10%
Virginia	536,000	9%	302,000	14%
Washington	440,000	8%	219,000	12%
West Virginia	149,000	12%	48,000	11%
Wisconsin	416,000	11%	187,000	13%
Wyoming	44,000	11%	17,000	11%

Note: Figures are averages of data collected October 14–26 and October 28–November 9. In the latest data, collected October 28–November 9, 12 percent of all adults reported that their household “sometimes” or “often” in the last seven days had “not enough to eat,” while 14.3 percent of adults living with children reported that the children sometimes or often in the last seven days were “not eating enough because we just couldn't afford enough food.” As recommended by the Census Bureau, percentages exclude persons not replying to the question.

Source: Calculated by Center on Budget and Policy Priorities from Census Bureau’s Household Pulse Survey published tables “food2b,” “food3b,” and “food5,” for survey weeks 17 and 18, https://www.census.gov/programs-surveys/household-pulse-survey/data.html

Table 2 shows the number of SNAP participants based on recent data available for each state through August compared to February 2020, the last month before the economic effects of the pandemic hit. Available data suggest that 6-7 million more people have applied and been approved for benefits since February, a 17 percent increase nationally. This rise is unprecedented: at the onset of the Great Recession it took 17 months to add this number of people to SNAP. While SNAP participation in most states is still substantially lower than during the peak months after the Great Recession, the increase so far due to COVID-19 has been rapid.

Based on this state data the number of people nationally participating in SNAP appears to have leveled at about 43 million over May through August, though in some states over the summer it continued to grow and in others it fell. The differences in the trends in caseloads across states reflect multiple factors including:

• Differences in job losses across the months of the pandemic and the degree to which businesses were operating;
• How quickly states adapted their SNAP application processes to almost entirely remote communications (i.e., online and telephone) and the degree to which they made use of flexibilities offered to help them manage their workloads;^[6]
• How many people received unemployment insurance since the pandemic began in the state and how quickly states processed applications for unemployment insurance (UI) in the spring and early summer (which would have provided income to people who otherwise might have qualified for SNAP);

The slower growth over the summer months may reflect states taking higher income from UI benefits into account (for households that were approved for UI in late April or May), in addition to increased earnings from the economy partially reopening in some places. But UI income fell substantially as a result of the expiration of the temporary $600-per-week federal UI supplement at the end of July, which may have resulted in more SNAP applications in August and September. SNAP caseloads also shrink when the economy is strong, as they did in the years leading up to the COVID-19-related downturn.

TABLE 2
The Number of SNAP Participants Increased Substantially in Almost All States
Preliminary, subject to change. From state- or USDA-reported data, as of October 21, 2020, in thousands
State	February 2020	April 2020	May 2020	June 2020	July 2020	August 2020	Percent change:
							February to May (or April if May data not available)	February to August (or July if August data not available)
Alabama	705	740	755	756	747	751	7%	7%
Alaska	81	86	88	88	88	89	9%	11%
Arizona	801	867	915	902	924	937	14%	17%
Arkansas	318	375	393				24%
California	4,031	4,451	4,689	4,801	4,600	4,600	16%	14%
Colorado	431	507	524	539	552	534	21%	24%
Connecticut	362	382	388	387	388	381	7%	5%
Delaware *	116	126					9%
District of Columbia *	109	118					9%
Florida	2,684	3,212	3,661	3,816	3,845	3,871	36%	44%
Georgia	1,278	1,603	1,707				34%
Guam *	41	52					28%
Hawai’i	152	171	178	180	177		17%	16%
Idaho	149	153	151	153	147	145	2%	-3%
Illinois	1,748	1,929	2,032				16%
Indiana	617	680	715	775	844	726	16%	18%
Iowa	296	330	338	308	301	312	14%	5%
Kansas	190	202	209	213	208	207	10%	9%
Kentucky	482	593	624	653	602	599	29%	24%
Louisiana	770	812	843	853	857	866	10%	12%
Maine	165	176	180	179	176	174	9%	6%
Maryland	591	690	782	845	854	834	32%	41%
Massachusetts	757	882	911	912	852	872	20%	15%
Michigan	1,176	1,499	1,528	1,344	1,235	1,196	30%	2%
Minnesota	370	404	424	426	416	425	14%	15%
Mississippi	424	457	479	445	396	400	13%	-6%
Missouri	657	752	766	773	778	772	17%	17%
Montana	106	108	110	109	110	108	4%	3%
Nebraska*	153	166					8%
Nevada	412	497	512	465	466	469	24%	14%
New Hampshire*	72	77					7%
New Jersey	661	683	718	725	735		9%	11%
New Mexico	445	481	492	493	492	493	11%	11%
New York	2,560	2,683	2,736	2,774	2,750		7%	7%
North Carolina	1,224	1,329	1,383	1,407	1,432	1,466	13%	20%
North Dakota*	48	51					8%
Ohio	1,326	1,632	1,610	1,559	1,518		21%	14%
Oklahoma	576	598	608				6%
Oregon	586	670	691	706	713	703	18%	20%
Pennsylvania	1,737	1,861	1,907	1,904	1,839	1,843	10%	6%
Rhode Island*	146						N/A
South Carolina	568	593	625	639	616	617	10%	9%
South Dakota	78	79	79	78	78	78	2%	0%
Tennessee	844	905	891	876	844	855	6%	1%
Texas	3,284	3,708	3,899	3,932	3,911	3,941	19%	20%
Utah	170	177	166	160	158	163	-2%	-4%
Vermont*	68	72					7%
Virginia	680	747	767	774	785	782	13%	15%
Virgin Islands*	20	22					9%
Washington	801	898	923				15%
West Virginiaa	282	307	299	295	282	280	6%	0%
Wisconsin	598	687	697	689	684	724	17%	21%
Wyoming*	26	27					4%
Total these states (or territories)	36,868 (53 states)	41,300 (52)	42,400 (43)	36,900b (38)	36,400b (37)	31,200b (31)	17%	17%
% U.S. participants in these states	100%	99.9%	98%	85%	85%	73%
Extrapolated to U.S.	36,868	41,400	43,200	43,800b	42,700b	43,000b

* Preliminary Department of Agriculture (USDA) data. All others are state-reported figures. Because for February we have combined data from different sources, the state February figures do not add to USDA’s February national total. Historically, the data states reported have differed only slightly from the USDA data, but for April 2020, the most recent month for which USDA has posted preliminary data, there appear to be data reporting issues in about one-fifth of the states. Because of the data reporting issues USDA has not yet published date for May or subsequent months.

^a Estimated individuals receiving SNAP based on reported households.

^b These estimates for June through August 2020 should be viewed with caution as they rely on data for fewer than 40 states with 85 percent or less of total SNAP participants. The actual national figures may be higher or lower than represented here.

Sources: Compilation of state-reported number of SNAP participants. CBPP, “SNAP Online: A Review of State Government SNAP Websites,” April 23, 2020, https://www.cbpp.org/research/food-assistance/snap-online-a-review-of-state-government-snap-websites, includes links to the data on each state’s website for the states that post them. We also have obtained data for May from a handful of states that do not post their monthly data. The U.S. total for February 2020 and the February and April 2020 figures for states that do not share more recent data are from the Food and Nutrition Service, U.S. Department of Agriculture, “SNAP Data Tables,” FY16 through FY20 National View Summary, https://www.fns.usda.gov/pd/supplemental-nutrition-assistance-program-snap.

Not Caught Up on Rent

Table 3 shows the estimated number of adults whose household was not caught up on rent by state. The Census Bureau changed the Pulse survey’s rent payment question in August, so these rent hardship figures results are not comparable to data from earlier weeks of the Pulse survey. In addition, a large share of Pulse survey respondents chose not to answer the housing questions in the latest survey. Non-response is higher among groups that are younger, have lower levels of education, and identify as Black or Latino — groups that are more likely to struggle to afford rent, due to longstanding inequities that often stem from structural racism in education, employment, and housing. Therefore, the Pulse data likely understate the number of people struggling to pay rent.

TABLE 3
1 in 6 Renters Nationwide Not Caught Up on Rent
Among adults in rental housing; data collected October 14–November 9
	Not Caught Up On Rent
	Estimated Number	Percent
Alabama	164,000	18%
Alaska	25,000	17%
Arizona	273,000	16%
Arkansas	103,000	17%
California	1,476,000	12%
Colorado	127,000	9%
Connecticut	122,000	15%
Delaware	43,000	23%
District of Columbia	41,000	14%
Florida	1,011,000	20%
Georgia	501,000	21%
Hawai’i	49,000	13%
Idaho	31,000	10%
Illinois	571,000	21%
Indiana	205,000	16%
Iowa	62,000	11%
Kansas	75,000	13%
Kentucky	131,000	15%
Louisiana	224,000	24%
Maine	22,000	10%
Maryland	340,000	27%
Massachusetts	265,000	15%
Michigan	312,000	17%
Minnesota	143,000	14%
Mississippi	164,000	29%
Missouri	140,000	11%
Montana	29,000	14%
Nebraska	48,000	12%
Nevada	201,000	23%
New Hampshire	31,000	13%
New Jersey	352,000	17%
New Mexico	104,000	25%
New York	1,433,000	24%
North Carolina	316,000	14%
North Dakota	14,000	8%
Ohio	459,000	19%
Oklahoma	136,000	16%
Oregon	126,000	12%
Pennsylvania	484,000	19%
Rhode Island	44,000	17%
South Carolina	260,000	27%
South Dakota	22,000	13%
Tennessee	318,000	22%
Texas	1,086,000	17%
Utah	67,000	12%
Vermont	13,000	11%
Virginia	306,000	16%
Washington	231,000	12%
West Virginia	51,000	19%
Wisconsin	147,000	12%
Wyoming	14,000	13%

Note: Figures are averages of data collected October 14–26 and October 28–November 9. To adjust for non-response in the Pulse survey, the estimated number is calculated as the Pulse survey’s estimated share not caught up on rent multiplied by the total number of adult renters ages 18 and older from the American Community Survey.

Source: Calculated by Center on Budget and Policy Priorities from Census Bureau’s Household Pulse Survey published table “housing1b” for survey weeks 17 and 18, https://www.census.gov/programs-surveys/household-pulse-survey/data.html; and 2018 American Community Survey public use file.

Difficulty Covering Usual Household Expenses

The Pulse survey asks adult respondents if their household had difficulty paying for usual expenses such as food, rent or mortgage, car payments, medical expenses, or student loans in the last seven days. Table 4 shows the estimated number and percent of adults reporting that it was somewhat or very difficult for their household to pay for their usual expenses in the last seven days.

TABLE 4
1 in 3 Adults Nationwide Has Difficulty Covering Usual Household Expenses
Among adults; data collected October 14–November 9
	Difficulty Covering Usual Household Expenses
	Number	Percent
United States	80,262,000	33%
Alabama	1,348,000	38%
Alaska	161,000	31%
Arizona	1,809,000	34%
Arkansas	775,000	36%
California	9,977,000	35%
Colorado	1,258,000	29%
Connecticut	812,000	31%
Delaware	234,000	32%
District of Columbia	150,000	28%
Florida	5,749,000	35%
Georgia	2,791,000	36%
Hawai’i	368,000	36%
Idaho	371,000	29%
Illinois	2,976,000	32%
Indiana	1,529,000	31%
Iowa	597,000	26%
Kansas	632,000	31%
Kentucky	1,049,000	32%
Louisiana	1,325,000	40%
Maine	301,000	29%
Maryland	1,364,000	31%
Massachusetts	1,466,000	29%
Michigan	2,330,000	32%
Minnesota	1,064,000	26%
Mississippi	853,000	41%
Missouri	1,313,000	30%
Montana	214,000	27%
Nebraska	366,000	27%
Nevada	923,000	40%
New Hampshire	269,000	26%
New Jersey	2,227,000	34%
New Mexico	629,000	40%
New York	5,387,000	38%
North Carolina	2,612,000	34%
North Dakota	126,000	23%
Ohio	2,632,000	31%
Oklahoma	1,049,000	37%
Oregon	965,000	30%
Pennsylvania	2,739,000	29%
Rhode Island	256,000	33%
South Carolina	1,364,000	36%
South Dakota	155,000	25%
Tennessee	1,762,000	35%
Texas	8,186,000	40%
Utah	562,000	25%
Vermont	134,000	28%
Virginia	1,875,000	30%
Washington	1,500,000	26%
West Virginia	420,000	32%
Wisconsin	1,174,000	27%
Wyoming	135,000	32%

Note: Figures are averages of data collected October 14–26 and October 28–November 9. In the latest data, collected October 28–November 9, 81 million adults nationwide (34 percent) reported difficulty paying for usual household expenses.

Source: Calculated by Center on Budget and Policy Priorities from Census Bureau’s Household Pulse Survey published table “spending1” for survey weeks 17 and 18, https://www.census.gov/programs-surveys/household-pulse-survey/data.html

High Unemployment

Table 5 provides state-by-state data on the unemployment rate over the August-October period and data on ongoing unemployment benefit claims.

Unemployment in most states has been highly elevated since April, as has the number of people claiming unemployment insurance benefits.

TABLE 5
Unemployment, Jobless Claims High Across the Country
States	Unemployment rate (August-October average) a	Current jobless benefits claims for week ending October 31b
Alabama	6.0	107,000
Alaska	6.8	38,000
Arizona	6.8	398,000
Arkansas	6.9	99,000
California	10.5	4,299,000
Colorado	6.5	230,000
Connecticut	7.3	186,000
Delaware	7.6	35,000
District of Columbia	8.6	73,000
Florida	7.0	206,000
Georgia	5.5	537,000
Hawai’i	14.1	172,000
Idaho	5.3	24,000
Illinois	9.4	676,000
Indiana	5.9	317,000
Iowa	4.9	73,000
Kansas	6.0	109,000
Kentucky	6.8	97,000
Louisiana	8.4	253,000
Maine	6.2	42,000
Maryland	7.5	330,000
Massachusetts	9.5	826,000
Michigan	7.6	888,000
Minnesota	6.0	227,000
Mississippi	7.5	82,000
Missouri	5.5	141,000
Montana	5.4	47,000
Nebraska	3.5	25,000
Nevada	12.6	289,000
New Hampshire	5.5	43,000
New Jersey	8.7	696,000
New Mexico	9.8	114,000
New York	10.6	2,369,000
North Carolina	6.7	333,000
North Dakota	4.7	18,000
Ohio	7.6	666,000
Oklahoma	5.7	95,000
Oregon	7.8	242,000
Pennsylvania	8.7	1,364,000
Puerto Rico	8.3	284,000
Rhode Island	10.1	77,000
South Carolina	5.3	179,000
South Dakota	4.2	6,000
Tennessee	7.5	190,000
Texas	7.3	1,084,000
Utah	4.4	28,000
Vermont	4.1	28,000
Virgin Islands	12.0*	2,000
Virginia	5.9	383,000
Washington	7.6	261,000
West Virginia	8.0	79,000
Wisconsin	5.8	185,000
Wyoming	6.1	11,000
U.S.	8.2	19,560,000

^a All rates are seasonally adjusted except for the Virgin Islands.

^b Compiled from data for regular state UI benefits, Pandemic Unemployment Assistance, and Pandemic Emergency Unemployment Compensation. Including other smaller programs, 20,319,615 people were claiming benefits in that week.

* Rate is the average from July-September and is not seasonally adjusted.

Source: Local Area Unemployment Statistics from the Bureau of Labor Statistics; Labor Force, Employment and Unemployment for Virgin Islands from Virgin Islands Electronic Workforce System; Unemployment Weekly Claims Report, Department of Labor, November 19, 2020.