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State Dept.: Actions to Implement President Trump's Vision for Venezuelan Oil
WASHINGTON, Feb. 14 -- The U.S. State Department issued the following media note from the Office of the Spokesperson on Feb. 13, 2026:* * *
Actions to Implement President Trump's Vision for Venezuelan Oil
The Trump Administration is rapidly implementing President Trump's vision to reopen and develop Venezuela's oil industry for the shared benefit of the American and Venezuelan people. Thanks to President Trump's leadership, the United States has already issued several general licenses at record speed for oil and gas companies to make unprecedented investments in Venezuela's energy infrastructure. ... Show Full Article WASHINGTON, Feb. 14 -- The U.S. State Department issued the following media note from the Office of the Spokesperson on Feb. 13, 2026: * * * Actions to Implement President Trump's Vision for Venezuelan Oil The Trump Administration is rapidly implementing President Trump's vision to reopen and develop Venezuela's oil industry for the shared benefit of the American and Venezuelan people. Thanks to President Trump's leadership, the United States has already issued several general licenses at record speed for oil and gas companies to make unprecedented investments in Venezuela's energy infrastructure.
On January 29, Treasury's Office of Foreign Asset Control (OFAC) issued Venezuela General License (GL) 46, which authorizes firms incorporated in the United States to market Venezuelan oil to buyers around the world, and largely in the United States. Payment must be made on commercially reasonable terms - in contrast to the heavily discounted prices for which the corrupt Maduro regime sold oil - and must be paid into an account in the United States established and with oversight by the Departments of State and Treasury. We will assure these funds are spent transparently and for the benefit of the Venezuelan people.
* On February 3, OFAC issued Venezuela GL 47, which authorizes firms to sell U.S.-origin diluent - a product essential for oil production - to Venezuela. This action provides significant benefit both to the Venezuelan people and to the U.S. economy.
* On February 10, OFAC issued Venezuela GL 48, which authorizes U.S. firms to provide goods, equipment, and services for the Venezuelan oil and gas industry. By utilizing this GL, U.S. firms will play a critical role in repairing and upgrading Venezuela's oil and gas infrastructure for the benefit of the Venezuelan people.
* On February 13, OFAC issued Venezuela GL 50, which authorizes certain firms in Venezuela to expand their operations, including pursing additional upstream oil and gas projects. On February 13, OFAC issued Venezuela GL 49, which authorizes oil and gas firms to negotiate and enter into contingent contracts with Venezuela to invest in upstream oil and gas projects. The Trump Administration will subsequently review for approval the proposed contracts to ensure they advance the interests of the American and Venezuelan people. These investments will lay the foundation for the modernization of the Venezuelan oil and gas industry, increase production, and shore up U.S. supply lines in our own hemisphere.
Venezuela holds tremendous economic potential, but years of instability, corruption, and economic mismanagement have limited the nation's growth and prosperity. These general licenses invite American and other aligned companies to play a constructive role in supporting economic recovery and responsible investment. Additional authorizations may also be issued as necessary in furtherance of President Trump's vision. The United States is committed to restoring Venezuela's prosperity, safety, and security for the benefit of both the American and Venezuelan people. With renewed cooperation and sound economic stewardship, Venezuela can reemerge as a stable, prosperous partner whose citizens benefit from its vast natural wealth and strengthened ties with the United States.
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Original text here: https://www.state.gov/releases/office-of-the-spokesperson/2026/02/actions-to-implement-president-trumps-vision-for-venezuelan-oil/
Plainfield, Vermont Man Sentenced to 2 Years of Probation for Social Security Disability Fraud
BURLINGTON, Vermont, Feb. 14 -- The office of the U.S. Attorney for the District of Vermont posted the following news release on Feb. 13, 2026:* * *
Plainfield, Vermont Man Sentenced to 2 years of Probation for Social Security Disability Fraud
The United States Attorney's Office for the District of Vermont stated that on February 10, 2026, John Cozza, 64, of Plainfield, Vermont, was sentenced by Chief United States District Judge Christina Reiss to a two-year term of probation and ordered to pay $68,323.20 in restitution to the United States Social Security Administration. Cozza previously ... Show Full Article BURLINGTON, Vermont, Feb. 14 -- The office of the U.S. Attorney for the District of Vermont posted the following news release on Feb. 13, 2026: * * * Plainfield, Vermont Man Sentenced to 2 years of Probation for Social Security Disability Fraud The United States Attorney's Office for the District of Vermont stated that on February 10, 2026, John Cozza, 64, of Plainfield, Vermont, was sentenced by Chief United States District Judge Christina Reiss to a two-year term of probation and ordered to pay $68,323.20 in restitution to the United States Social Security Administration. Cozza previouslypleaded guilty to submitting false information in his application for Social Security Disability Insurance ("SSDI") benefits.
According to court records, Cozza stated in a March 2021 application for SSDI benefits that he had not been self-employed in 2020 or in 2021, through the date of his application. When Cozza submitted the application, he knew that information was false. In fact, Cozza had been working as a handyman through his businesses, J.C. Handy Man Services and Black Bear Building Services from 2019 through the date of his application (and continuing until at least 2023). There was ample evidence of defendant's self-employment through his advertising of his businesses and his social media posts for those businesses. As a result of his false statements to the Social Security Administration, Cozza obtained $68,323.20 in SSDI benefits to which he was not entitled.
First Assistant United States Attorney Jonathan A. Ophardt commended the collaborative investigatory efforts of the Social Security Administration Office of the Inspector General, Office of Investigations (SSA OIG-OI) and the Vermont State Police.
The case was prosecuted by Assistant U.S. Attorneys Thomas Aliberti and Jason Turner. John Cozza was represented by Michael Shklar, Esq.
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Original text here: https://www.justice.gov/usao-vt/pr/plainfield-vermont-man-sentenced-2-years-probation-social-security-disability-fraud
BLS Southeast Region Issues Report on Consumer Price Index, Tampa-St. Petersburg-Clearwater January 2026
ATLANTA, Georgia, Feb. 14 (TNSLrpt) -- Consumer Price Index, Tampa-St. Petersburg-Clearwater January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Southeast Region - Feb. 13, 2026* * *
Area prices rose 0.5 percent over the two months, up 2.3 percent over the year
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The Consumer Price Index for All Urban Consumers (CPI-U) for Tampa-St. Petersburg-Clearwater increased 0.5 percent from November to January, the U.S. Bureau of Labor Statistics (BLS) reported today. Regional Commissioner Victoria G. Lee noted that the index for all items less food and energy increased ... Show Full Article ATLANTA, Georgia, Feb. 14 (TNSLrpt) -- Consumer Price Index, Tampa-St. Petersburg-Clearwater January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Southeast Region - Feb. 13, 2026 * * * Area prices rose 0.5 percent over the two months, up 2.3 percent over the year * The Consumer Price Index for All Urban Consumers (CPI-U) for Tampa-St. Petersburg-Clearwater increased 0.5 percent from November to January, the U.S. Bureau of Labor Statistics (BLS) reported today. Regional Commissioner Victoria G. Lee noted that the index for all items less food and energy increased0.3 percent over the two-month span. The index for food rose 1.3 percent from November to January. The index for energy increased 2.1 percent over the same period. (Data in this report are not seasonally adjusted. Accordingly, bi-monthly changes may reflect the impact of seasonal influences.)
The Tampa area all items CPI-U advanced 2.3 percent for the 12 months ending January. The index for all items less food and energy rose 1.8 percent over the last 12 months. The food index increased 4.7 percent for the 12 months ending January. The energy index rose 5.9 percent over the last year.
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Chart 1. Over-the-year percent change in CPI-U, Tampa-St. Petersburg-Clearwater, FL, January 2023-January 2026
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Food
The food index rose 1.3 percent from November to January. The index for food at home (grocery store purchases) rose 1.7 percent, with higher prices in 5 of the 6 major grocery store food groups. The food away from home index (restaurant, cafeteria, and vending purchases) increased 0.8 percent over the two-month span.
The food index rose 4.7 percent over the last 12 months. The index for food at home rose 4.3 percent over this 12-month span, as prices increased for all six major grocery store food groups. The food away from home index increased 5.1 percent over the past year.
Energy
The energy index increased 2.1 percent from November to January. The gasoline index declined 5.4 percent over the two-month pricing period.
The energy index increased 5.9 percent over the past 12 months. The gasoline index fell 10.8 percent over this 12-month span.
All items less food and energy
The index for all items less food and energy rose 0.3 percent from November to January. The shelter index rose 0.6 percent over the bi-monthly period, due in part to an increase in the lodging away from home index. In comparison, the index for recreation declined 4.5 percent from November to January.
The index for all items less food and energy advanced 1.8 percent over the past 12 months. The shelter index increased 2.6 percent over this 12-month span. The index for owners' equivalent rent increased 2.4 percent over the past year and the index for rent increased 3.1 percent.
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The Consumer Price Index for February 2026 is scheduled to be released on Wednesday, March 11, 2026, at 8:30 a.m. (ET). The Tampa-St. Petersburg-Clearwater Consumer Price Index for March 2026 is scheduled to be released on Friday, April 10, 2026, at 8:30 a.m. (ET).
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Technical Note
The Consumer Price Index (CPI) is a measure of the average change in prices over time in a fixed market basket of goods and services. The Consumer Price Index for Tampa is published bi-monthly. The set of components and sub-aggregates published for regional and metropolitan indexes is more limited than at the U.S. city average level; these indexes are byproducts of the national CPI program. Each local index has a much smaller sample size than the national or regional indexes and is, therefore, subject to substantially more sampling and other measurement error. As a result, local-area indexes are more volatile than the national or regional indexes. In addition, local indexes are not adjusted for seasonal influences. NOTE: Area indexes do not measure differences in the level of prices between cities; they only measure the average change in prices for each area since the base period.
The Tampa-St. Petersburg-Clearwater, FL Core Based Statistical Area includes Hernando, Hillsborough, Pasco, and Pinellas Counties in Florida.
Refer to the national CPI news release technical note or the Handbook of Methods for more information.
If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to access telecommunications relay services.
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Table 1. Tampa-St. Petersburg-Clearwater, FL, CPI-U by expenditure category for January 2026, not seasonally adjusted (1987=100 unless otherwise noted)
Table 2. Tampa-St. Petersburg-Clearwater, FL, CPI-U by special aggregate index for January 2026, not seasonally adjusted (1987=100)
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View original text plus charts and tables here: https://www.bls.gov/regions/southeast/news-release/2026/consumerpriceindex_tampa_20260213.htm
BLS Northeast Region Issues Report on Consumer Price Index, Boston-Cambridge-Newton January 2026
NEW YORK, Feb. 14 (TNSLrpt) -- Consumer Price Index, Boston-Cambridge-Newton January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Northeast Region - Feb. 13, 2026* * *
Area prices up 0.1 percent over the two months, 1.4 percent over the year
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The Consumer Price Index for All Urban Consumers (CPI-U) for Boston-Cambridge-Newton was up 0.1 percent from November to January, the U.S. Bureau of Labor Statistics (BLS) reported today. Acting Regional Commissioner Michael G. Phinney noted that the index for all items less food and energy was the largest contributor to the ... Show Full Article NEW YORK, Feb. 14 (TNSLrpt) -- Consumer Price Index, Boston-Cambridge-Newton January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Northeast Region - Feb. 13, 2026 * * * Area prices up 0.1 percent over the two months, 1.4 percent over the year * The Consumer Price Index for All Urban Consumers (CPI-U) for Boston-Cambridge-Newton was up 0.1 percent from November to January, the U.S. Bureau of Labor Statistics (BLS) reported today. Acting Regional Commissioner Michael G. Phinney noted that the index for all items less food and energy was the largest contributor to theincrease. (Data in this report are not seasonally adjusted. Accordingly, bi-monthly changes may reflect the impact of seasonal influences.)
The Boston area all items CPI-U advanced 1.4 percent for the 12 months ending in January. The index for all items less food and energy rose 1.5 percent, and the food index also increased 1.5 percent. In contrast, the energy index declined 0.5 percent over the same period.
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Chart 1. Over-the-year percent change in CPI-U, Boston-Cambridge-Newton, MA-NH, January 2023-January 2026
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Food
The food index was little changed from November to January, up 0.1 percent. The food away from home index (restaurant, cafeteria, and vending purchases) increased 1.3 percent. The index for food at home (grocery store purchases) decreased 0.7 percent, with lower prices in 4 of the 6 major grocery store food groups.
The food index rose 1.5 percent over the year. The food away from home index increased 5.1 percent. In comparison, the food at home index declined 1.2 percent. Five of the six major grocery store food group indexes declined over the year, including meats, poultry, fish, and eggs (-3.1 percent).
Energy
The energy index increased 0.2 percent over the two-month pricing period. Gasoline prices declined 2.5 percent.
The energy index decreased 0.5 percent from January 2025 to January 2026. Over the year, the gasoline index declined 2.5 percent.
All items less food and energy
The index for all items less food and energy ticked up 0.1 percent from November to January, reflecting higher prices for recreation (+2.6 percent), apparel (+3.4 percent), education and communication (+0.8 percent) and airline fares. In contrast, the index for medical care declined 1.4 percent. Within new and used motor vehicles (-1.1 percent), prices for used cars and trucks decreased 4.9 percent. Within shelter (-0.1 percent), prices for lodging away from home fell, while prices rose for owners' equivalent rent (+0.5 percent) and for rent of primary residence (+0.7 percent).
The index for all items less food and energy increased 1.5 percent over the year. The shelter index (+2.0 percent) was the largest contributor to the increase, due in part to increases in owners' equivalent rent of residences (+4.1 percent) and rent of primary residence (+3.6 percent). Other categories with increases included tuition, other school fees, and childcare, which advanced 6.7 percent, the largest over-the-year increase recorded since the series start in 2018.
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The Consumer Price Index for February 2026 is scheduled to be released on Wednesday, March 11, 2026, at 8:30 a.m. (ET).
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Technical Note
The Consumer Price Index (CPI) is a measure of the average change in prices over time in a fixed market basket of goods and services. The Consumer Price Index for Boston is published bi-monthly. The set of components and sub-aggregates published for regional and metropolitan indexes is more limited than at the U.S. city average level; these indexes are byproducts of the national CPI program. Each local index has a much smaller sample size than the national or regional indexes and is, therefore, subject to substantially more sampling and other measurement error. As a result, local-area indexes are more volatile than the national or regional indexes. In addition, local indexes are not adjusted for seasonal influences. NOTE: Area indexes do not measure differences in the level of prices between cities; they only measure the average change in prices for each area since the base period.
The Boston-Cambridge-Newton, MA-NH Core Based Statistical Area includes Essex, Middlesex, Norfolk, Plymouth, and Suffolk Counties in Massachusetts and Rockingham and Strafford Counties in New Hampshire.
Refer to the national CPI news release technical note or the Handbook of Methods for more information.
If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to access telecommunications relay services.
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Table 1. Boston-Cambridge-Newton, MA-NH, CPI-U by expenditure category for January 2026, not seasonally adjusted (1982-84=100 unless otherwise noted)
Table 2. Boston-Cambridge-Newton, MA-NH, CPI-U by special aggregate index for January 2026, not seasonally adjusted (1982-84=100 unless otherwise noted)
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View original text plus charts and tables here: https://www.bls.gov/regions/northeast/news-release/2026/consumerpriceindex_boston_20260213.htm
BLS Mountain-Plains Region Issues Report on Consumer Price Index, Midwest Region January 2026
KANSAS CITY, Missouri, Feb. 14 (TNSLrpt) -- Consumer Price Index, Midwest region January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Mountain-Plains Region - Feb. 13, 2026* * *
Regional prices rose 0.4 percent in January, up 2.4 percent over the year.
*
The Consumer Price Index for All Urban Consumers (CPI-U) in the Midwest Region advanced 0.4 percent in January, the U.S. Bureau of Labor Statistics (BLS) reported today. The all items less food and energy index increased 0.5 percent, led by rising prices for shelter. The index for food increased 0.3 percent, while ... Show Full Article KANSAS CITY, Missouri, Feb. 14 (TNSLrpt) -- Consumer Price Index, Midwest region January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Mountain-Plains Region - Feb. 13, 2026 * * * Regional prices rose 0.4 percent in January, up 2.4 percent over the year. * The Consumer Price Index for All Urban Consumers (CPI-U) in the Midwest Region advanced 0.4 percent in January, the U.S. Bureau of Labor Statistics (BLS) reported today. The all items less food and energy index increased 0.5 percent, led by rising prices for shelter. The index for food increased 0.3 percent, whilethe energy index declined 0.4 percent over the same period. (Data in this report are not seasonally adjusted. Accordingly, month-to-month changes may reflect seasonal influences.)
The Midwest Region all items CPI-U advanced 2.4 percent for the 12 months ending in January. The index for all items less food and energy increased 2.7 percent, and food prices were up 2.1 percent over the year. Energy prices fell 0.3 percent, led by declining prices for gasoline.
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Chart 1. Over-the-year percent change in CPI-U, Midwest region, January 2023-January 2026
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Food
Food prices rose 0.3 percent for the month of January. Prices for food at home (grocery store purchases) advanced 0.3 percent, and prices for food away from home (restaurant, cafeteria, and vending purchases) increased 0.2 percent for the same period. Within the food at home category, prices for dairy and related products (+2.7 percent) and other food at home (+0.6 percent) led increases. The index for fruits and vegetables led declines, falling 1.6 percent over the month.
The index for food advanced 2.1 percent over the year. The index for food away from home increased 3.8 percent, and the food at home index rose 1.0 percent, with higher prices in 5 of the 6 major grocery store food groups. Prices for meats, poultry, fish, and eggs led the rise, advancing 3.8 percent over the year.
Energy
The energy index declined 0.4 percent over the month, largely due to lower prices for gasoline (-2.6 percent). The indexes for natural gas service and electricity increased 1.9 percent and 1.3 percent, respectively, partially offsetting the decline.
From January 2025 to January 2026, energy prices fell 0.3 percent, due a decline in gasoline prices (-11.2 percent). Prices for electricity advanced 8.1 percent, and prices for natural gas service rose 13.5 percent over the same period.
All items less food and energy
The index for all items less food and energy increased 0.5 percent in January. Among the index's components, prices were higher for owners' equivalent rent of residences (+0.4 percent), public transportation, apparel (+2.7 percent), and education and communication (+0.9 percent). In contrast, prices were lower for used cars and trucks (-2.9 percent).
The index for all items less food and energy increased 2.7 percent over the year. Components contributing to the increase included owners' equivalent rent of residences (+4.1 percent), medical care services (+3.5 percent), and recreation (+4.2 percent). In contrast, prices were lower for used cars and trucks (-1.9 percent).
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The February 2026 Consumer Price Index for the Midwest Region is scheduled to be released on March 11, 2026.
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Technical Note
The Consumer Price Index (CPI) is a measure of the average change in prices over time in a fixed market basket of goods and services. The Consumer Price Index for the Midwest region is published monthly. The set of components and sub-aggregates published for regional and metropolitan indexes is more limited than at the U.S. city average level; these indexes are byproducts of the national CPI program.
The Midwest region is comprised of Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin.
Refer to the national CPI news release technical note or the Handbook of Methods for more information.
If you are deaf, hard of hearing, or have a speech disability, please dial 7-1-1 to access telecommunications relay services.
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Table 1. Midwest region CPI-U by expenditure category for January 2026, not seasonally adjusted (1982-84=100 unless otherwise noted)
Table 2. Midwest region CPI-U by special aggregate index for January 2026, not seasonally adjusted (1982-84=100 unless otherwise noted)
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View original text plus charts and tables here: https://www.bls.gov/regions/mountain-plains/news-release/2026/consumerpriceindex_midwest_20260213.htm
BLS Midwest Region Issues Report on Consumer Price Index, Chicago-Naperville-Elgin Area January 2026
CHICAGO, Illinois, Feb. 14 (TNSLrpt) -- Consumer Price Index, Chicago-Naperville-Elgin area January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Midwest Region - Feb. 13, 2026* * *
Area prices were up 0.4 percent over the past month, up 1.3 percent from a year ago
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The Consumer Price Index for All Urban Consumers (CPI-U) in the Chicago-Naperville-Elgin area advanced 0.4 percent in January, the U.S. Bureau of Labor Statistics (BLS) reported today. Assistant Commissioner for Regional Operations Michael Hirniak noted that food prices were up 1.1 percent while prices ... Show Full Article CHICAGO, Illinois, Feb. 14 (TNSLrpt) -- Consumer Price Index, Chicago-Naperville-Elgin area January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics Midwest Region - Feb. 13, 2026 * * * Area prices were up 0.4 percent over the past month, up 1.3 percent from a year ago * The Consumer Price Index for All Urban Consumers (CPI-U) in the Chicago-Naperville-Elgin area advanced 0.4 percent in January, the U.S. Bureau of Labor Statistics (BLS) reported today. Assistant Commissioner for Regional Operations Michael Hirniak noted that food prices were up 1.1 percent while pricesfor energy were down 4.7 percent in January. The index for all items less food and energy rose 0.6 percent. (Data in this report are not seasonally adjusted. Accordingly, month-to-month changes may reflect seasonal influences.)
The Chicago-Naperville-Elgin area all items CPI-U advanced 1.3 percent for the 12 months ending in January. The index for all items less food and energy increased 1.4 percent over the year. Food prices increased 1.9 percent. Energy prices fell 0.9 percent.
Food
Food prices advanced 1.1 percent for the month of January. Prices for food at home (grocery store purchases) advanced 1.1 percent, with higher prices in 5 of the 6 major grocery store food groups. The food away from home index (restaurant, cafeteria, and vending purchases) increased 1.1 percent for the same period.
Food prices increased 1.9 percent over the year. Prices for food at home declined 0.6 percent, and prices for food away from home increased 6.1 percent. Grocery food categories declining over the year included dairy and related products (-3.4 percent) and fruits and vegetables (-3.7 percent). The indexes for meats, poultry, fish, and eggs (+2.8 percent) and cereals and bakery products (+3.4 percent) were higher over the year.
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Chart 1. Over-the-year percent change in CPI-U, Chicago-Naperville-Elgin, IL-IN-WI, January 2022-January 2025
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Energy
The energy index declined 4.7 percent over the month. Gasoline prices were down 3.9 percent.
Energy prices fell 0.9 percent over the year. From January 2025 to January 2026 the gasoline index declined 9.9 percent.
All items less food and energy
The index for all items less food and energy increased 0.6 percent in January. Among the index's components, prices were higher for education and communication (+3.3 percent) and apparel (+5.4 percent). In contrast, prices were lower for lodging away from home, used cars and trucks (-3.0 percent), and other goods and services (-1.4 percent).
The index for all items less food and energy increased 1.4 percent over the year. Components contributing to the increase included owners' equivalent rent of residences (+4.2 percent), rent of primary residence (+5.1 percent), and recreation (+3.3 percent). In contrast, prices were lower for lodging away from home and education and communication (-3.4 percent).
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The Chicago-Naperville-Elgin Consumer Price Index for February 2026 is scheduled to be released on Wednesday, March 11, 2026, at 7:30 a.m. (CT).
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Technical Note
The Consumer Price Index (CPI) is a measure of the average change in prices over time in a fixed market basket of goods and services. The Consumer Price Index for Chicago is published monthly. The set of components and sub-aggregates published for regional and metropolitan indexes is more limited than at the U.S. city average level; these indexes are byproducts of the national CPI program. Each local index has a much smaller sample size than the national or regional indexes and is, therefore, subject to substantially more sampling and other measurement error. As a result, local-area indexes are more volatile than the national or regional indexes. In addition, local indexes are not adjusted for seasonal influences. NOTE: Area indexes do not measure differences in the level of prices between cities; they only measure the average change in prices for each area since the base period.
The Chicago-Naperville-Elgin, IL-IN-WI Core Based Statistical Area includes Cook, DeKalb, DuPage, Grundy, Kane, Kendall, Lake, McHenry, and Will Counties in Illinois; Jasper, Lake, Newton, and Porter Counties in Indiana; and Kenosha County in Wisconsin.
Refer to the national CPI news release technical note or the Handbook of Methods for more information.
Information in this release will be made available to individuals with sensory impairments upon request. Voice phone: (202) 691-5200; Telecommunications Relay Service: 7-1-1.
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Table 1. Chicago-Naperville-Elgin, IL-IN-WI, CPI-U by expenditure category for January 2026, not seasonally adjusted (1982-84=100 unless otherwise noted)
Table 2. Chicago-Naperville-Elgin, IL-IN-WI, CPI-U by special aggregate index for January 2026, not seasonally adjusted (1982-84=100 unless otherwise noted)
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View original text plus charts and tables here: https://www.bls.gov/regions/midwest/news-release/2026/consumerpriceindex_chicago_20260213.htm
BLS Issues Report on Employment Situation January 2026
WASHINGTON, Feb. 14 (TNSLrpt) -- The Employment Situation January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics - Feb. 13, 2026, (41 pages)* * *
Total nonfarm payroll employment rose by 130,000 in January, and the unemployment rate changed little at 4.3 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, social assistance, and construction, while federal government and financial activities lost jobs.
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Chart 1. Unemployment rate, seasonally adjusted, January 2024 - January 2026
Chart 2. Nonfarm payroll employment over-the-month ... Show Full Article WASHINGTON, Feb. 14 (TNSLrpt) -- The Employment Situation January 2026 - A report from U.S. Department of Labor Bureau of Labor Statistics - Feb. 13, 2026, (41 pages) * * * Total nonfarm payroll employment rose by 130,000 in January, and the unemployment rate changed little at 4.3 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, social assistance, and construction, while federal government and financial activities lost jobs. * * * Chart 1. Unemployment rate, seasonally adjusted, January 2024 - January 2026 Chart 2. Nonfarm payroll employment over-the-monthchange, seasonally adjusted, January 2024 - January 2026
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Changes to Establishment Survey Data and Other Information
Establishment survey data have been revised as a result of the annual benchmarking process and the updating of seasonal adjustment factors. The birth-death model now incorporates current sample information each month. See the notes beginning on page 4 for more information about establishment survey data, household survey population controls, and severe weather.
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This news release presents statistics from two monthly surveys. The household survey measures labor force status, including unemployment, by demographic characteristics. The establishment survey measures nonfarm employment, hours, and earnings by industry. For more information about the concepts and statistical methodology used in these two surveys, see the Technical Note.
Household Survey Data
Both the unemployment rate, at 4.3 percent, and the number of unemployed people, at 7.4 million, changed little in January. These measures are higher than a year earlier, when the jobless rate was 4.0 percent, and the number of unemployed people was 6.9 million. (See table A-1.)
Among the major worker groups, the unemployment rate for teenagers declined to 13.6 percent in January. The jobless rates for adult men (3.8 percent), adult women (4.0 percent), and people who are White (3.7 percent), Black (7.2 percent), Asian (4.1 percent), or Hispanic (4.7 percent) showed little change over the month. (See tables A-1, A-2, and A-3.)
The number of long-term unemployed (those jobless for 27 weeks or more) changed little in January at 1.8 million but is up by 386,000 from a year earlier. The long-term unemployed accounted for 25.0 percent of all unemployed people in January. (See table A-12.)
Both the labor force participation rate, at 62.5 percent, and the employment-population ratio, at 59.8 percent, changed little in January. These measures have shown little change over the year. (See table A-1.)
The number of people employed part time for economic reasons decreased by 453,000 to 4.9 million in January but is up by 410,000 over the year. These individuals would have preferred full-time employment but were working part time because their hours had been reduced or they were unable to find full-time jobs. (See table A-8.)
In January, the number of people not in the labor force who currently want a job decreased by 399,000 to 5.8 million. These individuals were not counted as unemployed because they were not actively looking for work during the 4 weeks preceding the survey or were unavailable to take a job. (See table A-1.)
Among those not in the labor force who wanted a job, the number of people marginally attached to the labor force changed little at 1.7 million in January. These individuals wanted and were available for work and had looked for a job sometime in the prior 12 months but had not looked for work in the 4 weeks preceding the survey. The number of discouraged workers, a subset of the marginally attached who believed that no jobs were available for them, also changed little at 475,000 in January. (See Summary table A.)
Establishment Survey Data
Total nonfarm payroll employment rose by 130,000 in January. Job gains occurred in health care, social assistance, and construction, while federal government and financial activities lost jobs. Payroll employment changed little in 2025 (+15,000 per month on average). (See table B-1. See the note on page 4 and table A for more information about the annual benchmark process.)
Health care added 82,000 jobs in January, with gains in ambulatory health care services (+50,000), hospitals (+18,000), and nursing and residential care facilities (+13,000). Job growth in health care averaged 33,000 per month in 2025.
Employment in social assistance increased by 42,000 in January, primarily in individual and family services (+38,000).
Construction added 33,000 jobs in January, reflecting an employment gain in nonresidential specialty trade contractors (+25,000). Employment in construction was essentially flat in 2025.
In January, federal government employment continued to decline (-34,000) as some federal employees who accepted a deferred resignation offer in 2025 came off federal payrolls. Since reaching a peak in October 2024, federal government employment is down by 327,000, or 10.9 percent.
Financial activities employment declined by 22,000 in January and is down by 49,000 since reaching a recent peak in May 2025. Within the industry, insurance carriers and related activities lost 11,000 jobs over the month.
Employment showed little change over the month in other major industries, including mining, quarrying, and oil and gas extraction; manufacturing; wholesale trade; retail trade; transportation and warehousing; information; professional and business services; leisure and hospitality; and other services.
In January, average hourly earnings for all employees on private nonfarm payrolls rose by 15 cents, or 0.4 percent, to $37.17. Over the past 12 months, average hourly earnings have increased by 3.7 percent. In January, average hourly earnings of private-sector production and nonsupervisory employees rose by 12 cents, or 0.4 percent, to $31.95. (See tables B-3 and B-8.)
The average workweek for all employees on private nonfarm payrolls edged up by 0.1 hour to 34.3 hours in January. In manufacturing, the average workweek edged up by 0.1 hour to 40.1 hours, and overtime was unchanged at 2.9 hours. The average workweek for production and nonsupervisory employees on private nonfarm payrolls increased by 0.1 hour to 33.8 hours. (See tables B-2 and B-7.)
The change in total nonfarm payroll employment for November was revised down by 15,000, from +56,000 to +41,000, and the change for December was revised down by 2,000, from +50,000 to +48,000. With these revisions, employment in November and December combined is 17,000 lower than previously reported. (Monthly revisions result from additional reports received from businesses and government agencies since the last published estimates and from the recalculation of seasonal factors. The annual benchmark process also contributed to the November and December revisions.)
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The Employment Situation for February is scheduled to be released on Friday, March 6, 2026, at 8:30 a.m. (ET).
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Revisions to Establishment Survey Data
In accordance with annual practice, the establishment survey data released today have been benchmarked to reflect comprehensive counts of payroll jobs for March 2025. These counts are derived principally from the Quarterly Census of Employment and Wages (QCEW), which counts jobs covered by the Unemployment Insurance (UI) tax system. The benchmark process results in revisions to not seasonally adjusted data from April 2024 forward. Seasonally adjusted data from January 2021 forward are subject to revision. In addition, data for some series prior to 2021, both seasonally adjusted and unadjusted, incorporate other revisions.
The seasonally adjusted total nonfarm employment level for March 2025 was revised downward by 898,000. On a not seasonally adjusted basis, the total nonfarm employment level for March 2025 was revised downward by 862,000, or -0.5 percent. Not seasonally adjusted, the absolute average benchmark revision over the prior 10 years is 0.2 percent.
The change in total nonfarm employment for 2025 was revised from +584,000 to +181,000 (seasonally adjusted). Table A presents revised total nonfarm employment data on a seasonally adjusted basis from January to December 2025.
All revised historical establishment survey data are available on the BLS website at www.bls.gov/ces/data/home.htm. In addition, an article that discusses the benchmark and postbenchmark revisions and other technical issues is available at www.bls.gov/web/empsit/cesbmart.htm.
Also effective with this news release, the establishment survey changed the birth-death model to incorporate current sample information each month. The change follows the same methodology applied to the April through October 2024 forecasts during the 2024 post-benchmark period (see question 9 in the CES Birth-Death Model Frequently Asked Questions page at www.bls.gov/web/empsit/cesbdqa.htm).
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Table A. Revisions to total nonfarm employment, January to December 2025, seasonally adjusted
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Population Control Adjustments to the Household Survey
The annual population control adjustments that are usually incorporated with the release of January estimates in February will instead be introduced with the release of February 2026 estimates in March. Consequently, the initial January 2026 household survey estimates in this news release continue to use short-term projections of monthly population estimates derived from population adjustments introduced in January 2025 (based on Vintage 2024 population estimates provided by the U.S. Census Bureau). As soon as practicable, BLS plans to revise January 2026 estimates to incorporate the updated population controls. Additional information will be announced at www.bls.gov/cps/documentation.htm#pop.
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Effect of Severe Winter Storms on Employment Estimates
Major winter storms and severe cold weather affected large parts of the country in January 2026, primarily after the reference periods for the establishment and household surveys. These events had no discernible effect on national payroll employment, hours, and earnings from the establishment survey, nor on the national unemployment rate from the household survey. (For information on how weather can affect data on employment and hours estimates, see the Frequently Asked Questions section of this news release.)
The severe weather did impact the collection of household survey data, and the January response rate of 64.3 percent was below average. The collection of establishment survey data was not impacted by severe weather, and the collection rate was within its normal range.
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HOUSEHOLD DATA
Summary table A. Household data, seasonally adjusted
ESTABLISHMENT DATA
Summary table B. Establishment data, seasonally adjusted
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Frequently Asked Questions about Employment and Unemployment Estimates
1. Why are there two monthly measures of employment?
The household survey and establishment survey both produce sample-based estimates of employment, and both have strengths and limitations. The establishment survey employment series has a smaller margin of error on the measurement of month-to-month change than the household survey because of its much larger sample size. An over-the-month employment change of about 122,000 is statistically significant in the establishment survey, while the threshold for a statistically significant change in the household survey is about 650,000. However, the household survey has a more expansive scope than the establishment survey because it includes self-employed workers whose businesses are unincorporated, unpaid family workers, agricultural workers, and private household workers, who are excluded by the establishment survey. The household survey also provides estimates of employment for demographic groups. For more information on the differences between the two surveys, please visit www.bls.gov/web/empsit/ces_cps_trends.htm.
2. Are undocumented immigrants counted in the surveys?
It is likely that both surveys include at least some undocumented immigrants. However, neither the establishment nor the household survey is designed to identify the legal status of workers. Therefore, it is not possible to determine how many are counted in either survey. The establishment survey does not collect data on the legal status of workers. The household survey does include questions which identify the foreign and native born, but it does not include questions about the legal status of the foreign born. Data on the foreign and native born are published each month in table A-7 of The Employment Situation news release.
3. Why does the establishment survey have revisions?
The establishment survey revises published estimates to improve its data series by incorporating additional information that was not available at the time of the initial publication of the estimates. The establishment survey revises its initial monthly estimates twice, in the immediately succeeding 2 months, to incorporate additional sample receipts from respondents in the survey and recalculated seasonal adjustment factors. For more information on the monthly revisions, please visit www.bls.gov/web/empsit/cestn.htm#Revisions-Between-Preliminary-and-Final-Data.
On an annual basis, the establishment survey incorporates a benchmark revision that re-anchors estimates to nearly complete employment counts available from unemployment insurance tax records. The benchmark helps to control for sampling and modeling errors in the estimates. For more information on the annual benchmark revision, please visit www.bls.gov/web/empsit/cesbmart.htm.
4. Does the establishment survey sample include small firms?
Yes. About 46 percent of the establishment survey sample is comprised of business establishments with fewer than 20 employees. The establishment survey sample is designed to maximize the reliability of the statewide total nonfarm employment estimate; firms from all states, size classes, and industries are appropriately sampled to achieve that goal.
5. Does the establishment survey account for employment from new businesses?
Yes. Monthly establishment survey estimates include an adjustment to account for the net employment change generated by business births and deaths. The adjustment comes from an econometric model that forecasts the monthly net jobs impact of business births and deaths based on the actual past values of the net impact that can be observed with a lag from the Quarterly Census of Employment and Wages. The establishment survey uses modeling rather than sampling for this purpose because the survey is not immediately able to bring new businesses into the sample. There is an unavoidable lag between the birth of a new firm and its appearance on the sampling frame and availability for selection. BLS adds new businesses to the survey twice a year. More information on business births and deaths in the establishment survey is available at www.bls.gov/web/empsit/cesbd.htm.
6.Is the count of unemployed people limited to just those receiving unemployment insurance benefits?
No. The estimate of unemployment is based on a monthly sample survey of households. All people who are without jobs and are actively seeking and available to work are included among the unemployed. (People on temporary layoff are included even if they do not actively seek work.) There is no requirement or question relating to unemployment insurance benefits in the monthly survey.
7. Does the official unemployment rate exclude people who want a job but are not currently looking for work?
Yes. However, there are separate estimates of people outside the labor force who want a job, including those who are not currently looking because they believe no jobs are available (discouraged workers). In addition, alternative measures of labor underutilization (some of which include discouraged workers and other groups not officially counted as unemployed) are published each month in table A-15 of The Employment Situation news release. For more information about these alternative measures, please visit www.bls.gov/cps/lfcharacteristics.htm#altmeasures.
8. How can unusually severe weather affect employment and hours estimates?
In the establishment survey, the reference period is the pay period that includes the 12th of the month. Unusually severe weather is more likely to have an impact on average weekly hours than on employment. Average weekly hours are estimated for paid time during the pay period, including pay for holidays, sick leave, or other time off. The impact of severe weather on hours estimates typically, but not always, results in a reduction in average weekly hours. For example, some employees may be off work for part of the pay period and not receive pay for the time missed, while some workers, such as those dealing with cleanup or repair, may work extra hours.
It is not possible to precisely quantify the effect of extreme weather on payroll employment estimates. In order for severe weather conditions to reduce employment estimates, employees have to be off work without pay for the entire pay period. Employees who receive pay for any part of the pay period, even 1 hour, are counted in the payroll employment figures. For more information on how often employees are paid, please visit www.bls.gov/ces/publications/length-pay-period.htm.
In the household survey, the reference period is generally the calendar week that includes the 12th of the month. People who miss the entire week's work for weather-related events are counted as employed whether or not they are paid for the time off. The household survey collects data on the number of people who had a job but were not at work due to bad weather. It also provides a measure of the number of people who usually work full time but had reduced hours due to bad weather.
Current and historical data are available on the household survey's most requested statistics page, please visit data.bls.gov/toppicks?survey=ln.
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Technical Note
This news release presents statistics from two major surveys, the Current Population Survey (CPS; household survey) and the Current Employment Statistics survey (CES; establishment survey). The household survey provides information on the labor force, employment, and unemployment that appears in the "A" tables, marked HOUSEHOLD DATA. It is a sample survey of about 60,000 eligible households conducted by the U.S. Census Bureau for the U.S. Bureau of Labor Statistics (BLS).
The establishment survey provides information on employment, hours, and earnings of employees on nonfarm payrolls; the data appear in the "B" tables, marked ESTABLISHMENT DATA. BLS collects these data each month from the payroll records of a sample of nonagricultural business establishments. Each month the CES program surveys about 119,000 businesses and government agencies, representing approximately 622,000 individual worksites, in order to provide detailed industry data on employment, hours, and earnings of workers on nonfarm payrolls. The active sample includes approximately 26 percent of all nonfarm payroll jobs.
For both surveys, the data for a given month relate to a particular week or pay period. In the household survey, the reference period is generally the calendar week that contains the 12th day of the month. In the establishment survey, the reference period is the pay period including the 12th, which may or may not correspond directly to the calendar week.
Coverage, definitions, and differences between surveys
Household survey. The sample is selected to reflect the entire civilian noninstitutional population. Based on responses to a series of questions on work and job search activities, each person 16 years and over in a sample household is classified as employed, unemployed, or not in the labor force.
People are classified as employed if they did any work at all as paid employees during the reference week; worked in their own business, profession, or on their own farm; or worked without pay at least 15 hours in a family business or farm. People are also counted as employed if they were temporarily absent from their jobs because of illness, bad weather, vacation, labor-management disputes, or personal reasons.
People are classified as unemployed if they meet all of the following criteria: they had no employment during the reference week; they were available for work at that time; and they made specific active efforts to find employment sometime during the 4-week period ending with the reference week. People laid off from a job and expecting recall need not be looking for work to be counted as unemployed. The unemployment data derived from the household survey in no way depend upon the eligibility for or receipt of unemployment insurance benefits.
The civilian labor force is the sum of the employed and unemployed. Those people not classified as employed or unemployed are not in the labor force. The unemployment rate is the number unemployed as a percent of the labor force. The labor force participation rate is the labor force as a percent of the population, and the employment-population ratio is the employed as a percent of the population. Additional information about the household survey can be found at www.bls.gov/cps/documentation.htm.
Establishment survey. The sample establishments are drawn from private nonfarm businesses such as factories, offices, and stores, as well as from federal, state, and local government entities. Employees on nonfarm payrolls are those who worked or received pay for any part of the reference pay period, including people on paid leave. People are counted in each job they hold. Hours and earnings data are produced for the private sector for all employees and for production and nonsupervisory employees. Production and nonsupervisory employees are defined as production and related employees in manufacturing and mining and logging, construction workers in construction, and non-supervisory employees in private service-providing industries.
Industries are classified on the basis of an establishment's principal activity in accordance with the 2022 version of the North American Industry Classification System. Additional information about the establishment survey can be found at www.bls.gov/ces/.
Differences in employment estimates. The numerous conceptual and methodological differences between the household and establishment surveys result in important distinctions in the employment estimates derived from the surveys. Among these are:
* The household survey includes agricultural workers, self-employed workers whose businesses are unincorporated, unpaid family workers, and private household workers among the employed. These groups are excluded from the establishment survey.
* The household survey includes people on unpaid leave among the employed. The establishment survey does not.
* The household survey is limited to workers 16 years of age and older. The establishment survey is not limited by age.
* The household survey has no duplication of individuals, because individuals are counted only once, even if they hold more than one job. In the establishment survey, employees working at more than one job and thus appearing on more than one payroll are counted separately for each appearance.
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Seasonal adjustment
Over the course of a year, the size of the nation's labor force and the levels of employment and unemployment undergo regularly occurring fluctuations. These events may result from seasonal changes in weather, major holidays, and the opening and closing of schools. The effect of such seasonal variation can be very large.
Because these seasonal events follow a more or less regular pattern each year, their influence on the level of a series can be tempered by adjusting for regular seasonal variation. These adjustments make nonseasonal developments, such as declines in employment or increases in the participation of women in the labor force, easier to spot. For example, in the household survey, the large number of youth entering the labor force each June is likely to obscure any other changes that have taken place relative to May, making it difficult to determine if the level of economic activity has risen or declined. Similarly, in the establishment survey, payroll employment in education declines by about 20 percent at the end of the spring term and later rises with the start of the fall term, obscuring the underlying employment trends in the industry. Because seasonal employment changes at the end and beginning of the school year can be estimated, the statistics can be adjusted to make underlying employment patterns more discernible. The seasonally adjusted figures provide a more useful tool with which to analyze changes in month-to-month economic activity.
Many seasonally adjusted series are independently adjusted in both the household and establishment surveys. However, the adjusted series for many major estimates, such as total payroll employment, employment in most major sectors, total employment, and unemployment are computed by aggregating independently adjusted component series. For example, total unemployment is derived by summing the adjusted series for four major age-sex components; this differs from the unemployment estimate that would be obtained by directly adjusting the total or by combining the duration, reasons, or more detailed age categories. Percentage distributions of unemployment by reason and duration are derived from the sum of the independently seasonally adjusted component series and will not necessarily match calculations made using the seasonally adjusted total unemployment level. Additional information about seasonal adjustment in the household survey can be found at www.bls.gov/cps/documentation.htm#sa.
For both the household and establishment surveys, a concurrent seasonal adjustment methodology is used in which new seasonal factors are calculated each month using all relevant data, up to and including the data for the current month. In the household survey, new seasonal factors are used to adjust only the current month's data. In the establishment survey, however, new seasonal factors are used each month to adjust the three most recent monthly estimates. The prior 2 months are routinely revised to incorporate additional sample reports and recalculated seasonal adjustment factors. In both surveys, 5-year revisions to historical data are made once a year.
Reliability of the estimates
Statistics based on the household and establishment surveys are subject to both sampling and nonsampling error. When a sample, rather than the entire population, is surveyed, there is a chance that the sample estimates may differ from the true population values they represent. The component of this difference that occurs because samples differ by chance is known as sampling error, and its variability is measured by the standard error of the estimate. There is about a 90-percent chance, or level of confidence, that an estimate based on a sample will differ by no more than 1.6 standard errors from the true population value because of sampling error. BLS analyses are generally conducted at the 90-percent level of confidence.
For example, the confidence interval for the monthly change in total nonfarm employment from the establishment survey is on the order of plus or minus 122,000. Suppose the estimate of nonfarm employment increases by 50,000 from one month to the next. The 90-percent confidence interval on the monthly change would range from -72,000 to +172,000 (50,000 +/- 122,000). These figures do not mean that the sample results are off by these magnitudes, but rather that there is about a 90-percent chance that the true over-themonth change lies within this interval. Since this range includes values of less than zero, we could not say with confidence that nonfarm employment had, in fact, increased that month. If, however, the reported nonfarm employment rise was 250,000, then all of the values within the 90-percent confidence interval would be greater than zero. In this case, it is likely (at least a 90-percent chance) that nonfarm employment had, in fact, risen that month. At an unemployment rate of around 6.0 percent, the 90-percent confidence interval for the monthly change in unemployment as measured by the household survey is about +/- 425,000, and for the monthly change in the unemployment rate it is about +/- 0.3 percentage point.
In general, estimates involving many individuals or establishments have lower standard errors (relative to the size of the estimate) than estimates which are based on a small number of observations. The precision of estimates also is improved when the data are cumulated over time, such as for quarterly and annual averages.
The household and establishment surveys are also affected by nonsampling error, which can occur for many reasons, including the failure to sample a segment of the population, inability to obtain information for all respondents in the sample, inability or unwillingness of respondents to provide correct information on a timely basis, mistakes made by respondents, and errors made in the collection or processing of the data.
For example, in the establishment survey, estimates for the most recent 2 months are based on incomplete returns; for this reason, these estimates are labeled preliminary in the tables. It is only after two successive revisions to a monthly estimate, when nearly all sample reports have been received, that the estimate is considered final.
Another major source of nonsampling error in the establishment survey is the inability to capture, on a timely basis, employment generated by new firms. To correct for this systematic underestimation of employment growth, an estimation procedure with two components is used to account for business births. The first component excludes employment losses from business deaths from sample-based estimation in order to offset the missing employment gains from business births. This is incorporated into the samplebased estimation procedure by simply not reflecting sample units going out of business, but imputing to them the same employment trend as the other firms in the sample. This procedure accounts for most of the net birth/death employment.
The second component is an ARIMA time series model designed to estimate the residual net birth-death employment not accounted for by the imputation. The historical time series used in the ARIMA model is derived from the unemployment insurance universe micro-level database and reflects the actual residual net of births and deaths over the past 5 years. In addition to this time series of actual residual net of births and deaths series, the ARIMA-based component of the birth-death model includes current sample information to inform the forecasts. More information on business births and deaths in the establishment survey is available at www.bls.gov/web/empsit/cesbd.htm.
The sample-based estimates from the establishment survey are adjusted once a year (on a lagged basis) to universe counts of payroll employment obtained from administrative records of the unemployment insurance program. The difference between the March sample-based employment estimates and the March universe counts is known as a benchmark revision, and serves as a rough proxy for total survey error. Benchmarks also incorporate changes in the classification of industries when necessary. The absolute average benchmark revision for total nonfarm employment over the prior 10 years is 0.2 percent. Over this time, revisions ranged from -0.4 percent to 0.3 percent.
Other information
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HOUSEHOLD DATA
Table A-1. Employment status of the civilian population by sex and age
Table A-2. Employment status of the civilian population by race, sex, and age
Table A-2. Employment status of the civilian population by race, sex, and age -- Continued
Table A-3. Employment status of the Hispanic or Latino population by sex and age
Table A-4. Employment status of the civilian population 25 years and over by educational attainment
Table A-5. Employment status of the civilian population 18 years and over by veteran status, period of service, and sex, not seasonally adjusted
Table A-6. Employment status of the civilian population by sex, age, and disability status, not seasonally adjusted
Table A-7. Employment status of the civilian population by nativity and sex, not seasonally adjusted
Table A-8. Employed people by class of worker and part-time status
Table A-9. Selected employment indicators
Table A-10. Selected unemployment indicators, seasonally adjusted
Table A-11. Unemployed people by reason for unemployment
Table A-12. Unemployed people by duration of unemployment
Table A-13. Employed and unemployed people by occupation, not seasonally adjusted
Table A-14. Unemployed people by industry and class of worker, not seasonally adjusted
Table A-15. Alternative measures of labor underutilization
Table A-16. People not in the labor force and multiple jobholders by sex, not seasonally adjusted
ESTABLISHMENT DATA
Table B-1. Employees on nonfarm payrolls by industry sector and selected industry detail
Table B-1. Employees on nonfarm payrolls by industry sector and selected industry detail -- Continued
Table B-1. Employees on nonfarm payrolls by industry sector and selected industry detail-- Continued
Table B-1. Employees on nonfarm payrolls by industry sector and selected industry detail -- Continued
Table B-2. Average weekly hours and overtime of all employees on private nonfarm payrolls by industry sector, seasonally adjusted
Table B-3. Average hourly and weekly earnings of all employees on private nonfarm payrolls by industry sector, seasonally adjusted
Table B-4. Indexes of aggregate weekly hours and payrolls for all employees on private nonfarm payrolls by industry sector, seasonally adjusted
Table B-5. Employment of women on nonfarm payrolls by industry sector, seasonally adjusted
Table B-6. Employment of production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted1
Table B-7. Average weekly hours and overtime of production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted1
Table B-8. Average hourly and weekly earnings of production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted1
Table B-9. Indexes of aggregate weekly hours and payrolls for production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted1
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View original text plus charts and tables here: https://www.bls.gov/news.release/pdf/empsit.pdf