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Email from Texas Demographic Center       MONTHLY DATA UPDATE Happy Holidays from the Texas Demographic Center! As we wrap up the year, we’re grateful for the opportunity to serve Texans with data tha

HUD’s Office of Policy Development and Research (PD&R) is pleased to announce that CHAS (Comprehensive Housing Affordability Strategy) data, are now available via an application programming interface (API). With this API, developers can easily access and customize CHAS data for use in existing applications or to create new applications. To create an account and get an access token, please visit the API page here: https://www.huduser.gov/portal/dataset/chas-api.html. News There are no substantive changes to the format/content of the tables from the 2021 CHAS release. Enhanced disclosure avoidance protections continue to be enforced by Census resulting in some previously-available estimates being suppressed, as was the case starting with the 2018 tables. The following tables have changed compared to pre-2018 releases: Table 1: The "Other (including multiple races, non-Hispanic)" race/ethnicity category is now suppressed. The "Cost burden cannot be computed, none of the above problems" housing unit problems category is now combined with the "Has none of the 4 housing problems" category. Table 2: The "Other (including multiple races, non-Hispanic)" race/ethnicity category is now suppressed. The "Cost burden cannot be computed, none of the above problems" severe housing unit problems category is now combined with the "Has none of the 4 severe housing problems" category. Table 7: The "Cost burden cannot be computed, none of the above problems" category is now suppressed. Table 12: The "Cost burden cannot be computed, none of the above problems" category is now suppressed. Please use caution when referencing estimates using programming code developed for pre-2018 versions of CHAS or when making year-to-year comparisons, as variable names and definitions may have changed. About the CHAS Each year, the U.S. Department of Housing and Urban Development (HUD) receives custom tabulations of American Community Survey (ACS) data from the U.S. Census Bureau. These data, known as the "CHAS" data (Comprehensive Housing Affordability Strategy), demonstrate the extent of housing problems and housing needs, particularly for low income households. The CHAS data are used by local governments to plan how to spend HUD funds, and may also be used by HUD to distribute grant funds. For more background on the CHAS data, including data documentation and a list of updates and corrections to previously released data, click here: Background. Access the data HUD has created a simple web-based table generator (also known as a query tool) that provides some of the most commonly used CHAS figures (click here for the CHAS query tool). Data users who are comfortable working with large datasets and have appropriate data management software (such as SAS or SPSS) can download the complete set of data files (click here for the data download page). The data download tool includes data from every ACS release from 2006-2008 through 2018-2022, for a variety of geographic summary levels. HUD has also created new analytical tools to support HUD grantees preparing their Consolidated Plans. The eCon Planning Suite and CPD Maps are pre-loaded with CHAS data. Access to the eCon Planning Suite is limited to CPD grantees, but CPD Maps is available to the general public. Older versions of CHAS data, from the 2000 Census and the 2005-2007 ACS, are available below. These data are different from more recent versions, and are not in the data download tool. CHAS 2000 CHAS 2005-2007 Analysis HUD will periodically post publications, presentations, and working papers using CHAS data. Joice, Paul. CHAS Affordability Analysis. US Department of Housing and Urban Development, working paper. May 20, 2013. Joice, Paul. Measuring Housing Affordability. Cityscape: A Journal of Policy Development and Research, 16(1). 2014.

Delaney O’Kray-Murphy, EBRC Research Economist

STATE POPULATION INCREASES BY 19,200 IN FISCAL YEAR 2024-2025 FOR IMMEDIATE RELEASE: CONTACT: H.D. Palmer (916) 323-0648 December 19th, 2025 Walter Schwarm (916) 323-4086 SACRAMENTO—California’s population grew by about 19,200, or 0.05 percent, in the year ending July 1, 2025, reaching 39,529,000 people, according to new data released today by the California Department of Finance. The 0.05-percent increase marks the third year of population growth for the state following two years of consecutive declines during the pandemic and reflects the combination of several factors: - International immigration continued to rebound from pandemic lows, with the largest gain in fiscal year 2024 of 260,000 persons—the highest level since 2018. Net international migration increased in recent years due to the rebound in legal immigrants after the pandemic and the expansion of international humanitarian migration programs between 2021 and 2024. In 2025, most of the humanitarian migration programs were terminated. As a result, net international migration for 2024-25 declined to 126,000 persons—approximately half of the 2023-24 level. - Greater domestic in-migration and slowed domestic out-migration helped to bring net loss in domestic migration down to 140,000 persons in 2023-24 from nearly 250,000 persons in 2022-23. Net domestic migration from California became more negative in 2024-2025, increasing to a loss of 216,000 persons, which is consistent with levels in 2018 and 2019. - Natural increase—the net result of births minus deaths— contributes an increase of 108,300 persons in 2024-25 as births are stable and deaths have returned to the state’s pre-pandemic trend. For over 20 years, California has experienced negative net domestic migration, in which the number of people moving out of the state in a year exceeds the number moving in. Since 2016, with the exception of 2023-24, net domestic outmigration has exceeded net international migration, leaving natural increase as the only source of population growth. Natural increase is constrained by continuing fertility declines and increased deaths from an aging population. Net international migration to California reached 126,000 people in the year ending July 1,2025, a significant positive for overall population growth. However, negative net domestic migration still outweighed these gains, resulting in a net total migration loss of over 89,000 residents. With change in policy for international humanitarian migration and deaths returning to long-term trends, California is likely to experience slower growth over the coming several years. Other highlights of the July 1, 2025, county population report include: - California’s 58 counties range in size from Alpine County, with just over 1,150 residents, to Los Angeles County with 9.9 million residents. The population increased in 28 counties, with most growth in the Central Valley and the Inland Empire. Population gains largely reflect natural increase exceeding the losses in net migration. Only Placer, Yuba, and Glenn counties experienced positive population contributions from natural increase, net international migration, and net domestic migration. - The state’s ten largest counties remain Los Angeles, San Diego, Orange, Riverside, San Bernardino, Santa Clara, Alameda, Sacramento, Contra Costa, and Fresno, with each having more than one million residents. These ten counties represent 72 percent of California’s population. Seven of the ten counties with one million or more people have positive population growth, leaving Contra Costa, Los Angeles, and Orange as counties with population loss. - Los Angeles County’s population had the largest numeric decline of almost 28,500 persons in the fiscal year 2025. The decrease is driven by higher domestic migration due to impacts of wildfires, especially the Palisades and Eaton fires, and a significant decrease in net international migration. In January 2025, Los Angeles County experienced nine destructive wildfires out of 14 such wildfires in Southern California. - Population growth rates range from a high of 0.73 percent in Yuba County to a low of negative1.61 percent in Lassen County. The next fastest-growing counties in terms of percentage growth were Madera (0.66 percent), Sutter (0.62 percent), Merced (0.56 percent), Sacramento (0.55 percent), and Fresno (0.52 percent), all largely driven by intra-state moves, continuing a pre-pandemic trend. - Although natural increase was a main source of population growth in the state, 25 counties experienced natural decrease—more deaths than births. Among those counties only Napa and Plumas experienced overall growth thanks to positive net migration, especially net domestic migration. Background Information Population estimates produced by the California Department of Finance are mandated by the California Constitution and various codes. Estimates are used by state agencies, California counties, academic institutions, private research organizations, the media, and the public. Primary uses include budgeting, needs assessment, program planning and evaluation, distribution of state funds, and the calculation of rates (such as birth, death, and incarceration). The California Department of Finance estimates population each year based on changes in births, deaths, domestic migration, and international migration. Estimates are developed using aggregate data from a variety of sources, including birth and death counts provided by the Department of Public Health, driver's license data from the Department of Motor Vehicles, housing unit data from local governments, school enrollment data from the Department of Education, and federal income tax return data from the U.S. Internal Revenue Service. This particular series of estimates was unable to incorporate tax return data and Census Bureau county proportions due to the federal government shutdown which started on October 1 and ended on November 12. As a result, future revisions may be more significant than normal. These statistical reports of administrative records do not disclose any information about individuals. The July 2025 population estimates employ an improved method for estimating net international migration. The California Department of Finance has added a new administrative data component – asylum seekers and people who arrived in the United States on various temporary protected status programs between 2020 to 2024. The resulting net immigration estimates for the 2021-2024 period have increased by 321,000 relative to the previous estimates published in December 2024. As usual, we also updated prior years of the population estimates to reflect the changes in method of estimating international migration. In this release, revised data are for all years from 2020 to 2024. Due to this revision, population in the July 2023 and July 2024 estimates were also revised upward from the previous December 2024 publication. County ranking tables, maps, and the E-2 (California County Population Estimates and Components of Change by Year, July 1, 2020-2025) methodology and data tables are included. The E-2 and companion reports E-6 (Population Estimates and Components of Change by County, July 1, 2020-2025) and E-7 (California Population Estimates, with Components of Change and Crude Rates, July 1, 1900-2025), are available on the Department's website: http://www.dof.ca.gov/Forecasting/Demographics/Estimates. # # # MACRO USED: H:\Prod\Template\Dof-Ltrhd.dotm July 1, 2025 County Estimates Ranked by Size, Numeric and Percent Change since July 1, 2024 Rank County July 1, 2025 Estimate Percent of State Numeric Rank County Numeric Change Percent Rank County Percent Change California 39,528,899 100.00% California 19,242 California 0.05% 1 Los Angeles 9,867,045 24.96% 1 San Diego 10,807 1 Yuba 0.73% 2 San Diego 3,336,081 8.44% 2 Sacramento 8,756 2 Madera 0.66% 3 Orange 3,174,565 8.03% 3 Fresno 5,374 3 Sutter 0.62% 4 Riverside 2,485,007 6.29% 4 Riverside 5,050 4 Merced 0.56% 5 San Bernardino 2,205,940 5.58% 5 Santa Clara 3,748 5 Sacramento 0.55% 6 Santa Clara 1,930,033 4.88% 6 San Bernardino 3,463 6 Fresno 0.52% 7 Alameda 1,665,356 4.21% 7 Kern 3,142 7 Placer 0.51% 8 Sacramento 1,613,481 4.08% 8 San Joaquin 3,137 8 San Benito 0.51% 9 Contra Costa 1,161,681 2.94% 9 Alameda 2,144 9 Yolo 0.42% 10 Fresno 1,035,799 2.62% 10 Placer 2,135 10 Monterey 0.41% 11 Kern 923,402 2.34% 11 Monterey 1,811 11 Glenn 0.40% 12 San Francisco 842,457 2.13% 12 Tulare 1,775 12 San Joaquin 0.39% 13 Ventura 828,474 2.10% 13 Merced 1,636 13 Tulare 0.37% 14 San Joaquin 809,701 2.05% 14 Stanislaus 1,357 14 Plumas 0.37% 15 San Mateo 746,770 1.89% 15 Santa Barbara 1,274 15 Napa 0.36% 16 Stanislaus 556,444 1.41% 16 Madera 1,069 16 Kern 0.34% 17 Tulare 486,876 1.23% 17 Yolo 951 17 San Diego 0.32% 18 Sonoma 482,261 1.22% 18 Yuba 627 18 Kings 0.32% 19 Solano 451,147 1.14% 19 Sutter 622 19 Santa Barbara 0.29% 20 Santa Barbara 446,252 1.13% 20 Napa 492 20 Stanislaus 0.24% 21 Monterey 439,168 1.11% 21 Kings 490 21 Riverside 0.20% 22 Placer 424,595 1.07% 22 San Mateo 397 22 Santa Clara 0.19% 23 Merced 293,741 0.74% 23 San Benito 342 23 San Bernardino 0.16% 24 San Luis Obispo 278,422 0.70% 24 San Francisco 283 24 Alameda 0.13% 25 Santa Cruz 263,039 0.67% 25 Glenn 115 25 Colusa 0.10% 26 Marin 252,756 0.64% 26 Plumas 70 26 San Mateo 0.05% 27 Yolo 225,059 0.57% 27 Colusa 23 27 San Francisco 0.03% 28 Butte 206,659 0.52% 28 Sonoma 17 28 Sonoma 0.00% 29 El Dorado 189,127 0.48% 29 Alpine -10 29 Imperial -0.04% 30 Imperial 185,710 0.47% 30 Sierra -22 30 Orange -0.05% 31 Shasta 180,850 0.46% 31 Modoc -37 31 Mendocino -0.06% 32 Madera 164,083 0.42% 32 Mono -44 32 San Luis Obispo -0.09% 33 Kings 154,306 0.39% 33 Mendocino -55 33 Contra Costa -0.09% 34 Napa 136,105 0.34% 34 Trinity -74 34 Ventura -0.19% 35 Humboldt 132,708 0.34% 35 Mariposa -76 35 Santa Cruz -0.23% 36 Sutter 101,052 0.26% 36 Imperial -82 36 Solano -0.23% 37 Nevada 99,772 0.25% 37 Inyo -89 37 El Dorado -0.24% 38 Mendocino 89,411 0.23% 38 Calaveras -167 38 Shasta -0.27% 39 Yuba 85,987 0.22% 39 San Luis Obispo -250 39 Los Angeles -0.29% 40 San Benito 66,962 0.17% 40 Tehama -258 40 Butte -0.32% 41 Lake 66,446 0.17% 41 Del Norte -260 41 Mono -0.34% 42 Tehama 64,671 0.16% 42 Lake -348 42 Calaveras -0.38% 43 Tuolumne 52,564 0.13% 43 Siskiyou -348 43 Marin -0.38% 44 Calaveras 44,269 0.11% 44 Amador -430 44 Tehama -0.40% 45 Siskiyou 42,530 0.11% 45 El Dorado -449 45 Modoc -0.44% 46 Amador 39,715 0.10% 46 Lassen -449 46 Mariposa -0.45% 47 Glenn 28,957 0.07% 47 Shasta -489 47 Trinity -0.47% 48 Lassen 27,458 0.07% 48 Santa Cruz -608 48 Inyo -0.48% 49 Del Norte 26,557 0.07% 49 Butte -663 49 Lake -0.52% 50 Colusa 22,160 0.06% 50 Nevada -673 50 Humboldt -0.55% 51 Plumas 18,851 0.05% 51 Tuolumne -673 51 Nevada -0.67% 52 Inyo 18,549 0.05% 52 Humboldt -733 52 Sierra -0.70% 53 Mariposa 16,720 0.04% 53 Marin -969 53 Siskiyou -0.81% 54 Trinity 15,733 0.04% 54 Contra Costa -1,044 54 Alpine -0.86% 55 Mono 12,718 0.03% 55 Solano -1,049 55 Del Norte -0.97% 56 Modoc 8,452 0.02% 56 Orange -1,430 56 Amador -1.07% 57 Sierra 3,109 0.01% 57 Ventura -1,602 57 Tuolumne -1.26% 58 Alpine 1,156 0.00% 58 Los Angeles -28,484 58 Lassen -1.61% California County Rankings by Size, Numeric and Percent Change: July 1, 2024 -July 1, 2025 County Size Rank Numeric Change Rank Percent Change Rank County Alameda 7 9 24 Alameda Alpine 58 29 54 Alpine Amador 46 44 56 Amador Butte 28 49 40 Butte Calaveras 44 38 42 Calaveras Colusa 50 27 25 Colusa Contra Costa 9 54 33 Contra Costa Del Norte 49 41 55 Del Norte El Dorado 29 45 37 El Dorado Fresno 10 3 6 Fresno Glenn 47 25 11 Glenn Humboldt 35 52 50 Humboldt Imperial 30 36 29 Imperial Inyo 52 37 48 Inyo Kern 11 7 16 Kern Kings 33 21 18 Kings Lake 41 42 49 Lake Lassen 48 46 58 Lassen Los Angeles 1 58 39 Los Angeles Madera 32 16 2 Madera Marin 26 53 43 Marin Mariposa 53 35 46 Mariposa Mendocino 38 33 31 Mendocino Merced 23 13 4 Merced Modoc 56 31 45 Modoc Mono 55 32 41 Mono Monterey 21 11 10 Monterey Napa 34 20 15 Napa Nevada 37 50 51 Nevada Orange 3 56 30 Orange Placer 22 10 7 Placer Plumas 51 26 14 Plumas Riverside 4 4 21 Riverside Sacramento 8 2 5 Sacramento San Benito 40 23 8 San Benito San Bernardino 5 6 23 San Bernardino San Diego 2 1 17 San Diego San Francisco 12 24 27 San Francisco San Joaquin 14 8 12 San Joaquin San Luis Obispo 24 39 32 San Luis Obispo San Mateo 15 22 26 San Mateo Santa Barbara 20 15 19 Santa Barbara Santa Clara 6 5 22 Santa Clara Santa Cruz 25 48 35 Santa Cruz Shasta 31 47 38 Shasta Sierra 57 30 52 Sierra Siskiyou 45 43 53 Siskiyou Solano 19 55 36 Solano Sonoma 18 28 28 Sonoma Stanislaus 16 14 20 Stanislaus Sutter 36 19 3 Sutter Tehama 42 40 44 Tehama Trinity 54 34 47 Trinity Tulare 17 12 13 Tulare Tuolumne 43 51 57 Tuolumne Ventura 13 57 34 Ventura Yolo 27 17 9 Yolo Yuba 39 18 1 Yuba E-2. California County Population Estimates and Components of Change Revised July 1, 2024 and preliminary July 1, 2025 Table 1. Total Population Change 2024-2025 Components of Change County Revised July 1, 2024 Preliminary July 1, 2025 Number Percent Births Deaths Natural Increase Net Migration Net Immigration Net Domestic Migration Alameda 1,663,212 1,665,356 2,144 0.13 15,991 10,453 5,538 -3,394 8,691 -12,085 Alpine 1,166 1,156 -10 -0.86 10 15 -5 -5 0 -5 Amador 40,145 39,715 -430 -1.07 268 496 -228 -202 19 -221 Butte 207,322 206,659 -663 -0.32 1,998 2,313 -315 -348 197 -545 Calaveras 44,436 44,269 -167 -0.38 393 588 -195 28 9 19 Colusa 22,137 22,160 23 0.10 278 183 95 -72 32 -104 Contra Costa 1,162,725 1,161,681 -1,044 -0.09 10,741 8,422 2,319 -3,363 5,183 -8,546 Del Norte 26,817 26,557 -260 -0.97 240 352 -112 -148 9 -157 El Dorado 189,576 189,127 -449 -0.24 1,483 1,860 -377 -72 208 -280 Fresno 1,030,425 1,035,799 5,374 0.52 13,009 7,507 5,502 -128 748 -876 Glenn 28,842 28,957 115 0.40 335 281 54 61 23 38 Humboldt 133,441 132,708 -733 -0.55 1,074 1,520 -446 -287 96 -383 Imperial 185,792 185,710 -82 -0.04 2,105 1,288 817 -899 915 -1,814 Inyo 18,638 18,549 -89 -0.48 129 218 -89 0 9 -9 Kern 920,260 923,402 3,142 0.34 11,645 6,949 4,696 -1,554 1,675 -3,229 Kings 153,816 154,306 490 0.32 2,079 950 1,129 -639 191 -830 Lake 66,794 66,446 -348 -0.52 640 908 -268 -80 65 -145 Lassen 27,907 27,458 -449 -1.61 264 299 -35 -414 -5 -409 Los Angeles 9,895,529 9,867,045 -28,484 -0.29 89,111 68,114 20,997 -49,481 30,303 -79,784 Madera 163,014 164,083 1,069 0.66 2,190 1,209 981 88 116 -28 Marin 253,725 252,756 -969 -0.38 2,042 2,117 -75 -894 460 -1,354 Mariposa 16,796 16,720 -76 -0.45 129 198 -69 -7 9 -16 Mendocino 89,466 89,411 -55 -0.06 823 881 -58 3 98 -95 Merced 292,105 293,741 1,636 0.56 3,775 1,935 1,840 -204 521 -725 Modoc 8,489 8,452 -37 -0.44 74 122 -48 11 -9 20 Mono 12,762 12,718 -44 -0.34 112 77 35 -79 8 -87 Monterey 437,357 439,168 1,811 0.41 5,147 2,751 2,396 -585 970 -1,555 Napa 135,613 136,105 492 0.36 1,147 1,295 -148 640 237 403 Nevada 100,445 99,772 -673 -0.67 755 1,198 -443 -230 48 -278 Orange 3,175,995 3,174,565 -1,430 -0.05 30,682 22,394 8,288 -9,718 13,173 -22,891 Placer 422,460 424,595 2,135 0.51 4,119 3,764 355 1,780 920 860 Plumas 18,781 18,851 70 0.37 123 213 -90 160 -2 162 Riverside 2,479,957 2,485,007 5,050 0.20 26,813 19,772 7,041 -1,991 5,204 -7,195 Sacramento 1,604,725 1,613,481 8,756 0.55 17,730 13,090 4,640 4,116 9,913 -5,797 San Benito 66,620 66,962 342 0.51 782 394 388 -46 163 -209 San Bernardino 2,202,477 2,205,940 3,463 0.16 25,295 16,261 9,034 -5,571 4,636 -10,207 San Diego 3,325,274 3,336,081 10,807 0.32 35,287 23,183 12,104 -1,297 12,548 -13,845 San Francisco 842,174 842,457 283 0.03 7,145 6,140 1,005 -722 3,746 -4,468 San Joaquin 806,564 809,701 3,137 0.39 9,477 6,168 3,309 -172 2,648 -2,820 San Luis Obispo 278,672 278,422 -250 -0.09 2,435 2,635 -200 -50 219 -269 San Mateo 746,373 746,770 397 0.05 7,225 4,927 2,298 -1,901 2,805 -4,706 Santa Barbara 444,978 446,252 1,274 0.29 5,351 3,470 1,881 -607 644 -1,251 Santa Clara 1,926,285 1,930,033 3,748 0.19 18,626 10,819 7,807 -4,059 10,799 -14,858 Santa Cruz 263,647 263,039 -608 -0.23 2,124 1,984 140 -748 462 -1,210 Shasta 181,339 180,850 -489 -0.27 1,702 2,430 -728 239 119 120 Sierra 3,131 3,109 -22 -0.70 13 35 -22 0 -1 1 Siskiyou 42,878 42,530 -348 -0.81 341 669 -328 -20 18 -38 Solano 452,196 451,147 -1,049 -0.23 4,476 3,783 693 -1,742 714 -2,456 Sonoma 482,244 482,261 17 0.00 4,216 4,433 -217 234 974 -740 Stanislaus 555,087 556,444 1,357 0.24 6,628 4,587 2,041 -684 1,844 -2,528 Sutter 100,430 101,052 622 0.62 1,188 930 258 364 808 -444 Tehama 64,929 64,671 -258 -0.40 702 830 -128 -130 88 -218 Trinity 15,807 15,733 -74 -0.47 77 161 -84 10 20 -10 Tulare 485,101 486,876 1,775 0.37 6,564 3,494 3,070 -1,295 548 -1,843 Tuolumne 53,237 52,564 -673 -1.26 404 711 -307 -366 133 -499 Ventura 830,076 828,474 -1,602 -0.19 8,362 6,516 1,846 -3,448 1,579 -5,027 Yolo 224,108 225,059 951 0.42 1,819 1,503 316 635 744 -109 Yuba 85,360 85,987 627 0.73 1,169 756 413 214 179 35 California 39,509,657 39,528,899 19,242 0.05 398,862 290,551 108,311 -89,069 126,471 -215,540 E-2. California County Population Estimates and Components of Change Revised July 1, 2023 and revised July 1, 2024 Table 2. Total Population Change 2023-2024 Components of Change County Revised July 1, 2023 Revised July 1, 2024 Number Percent Births Deaths Natural Increase Net Migration Net Immigration Net Domestic Migration Alameda 1,654,952 1,663,212 8,260 0.50 15,914 10,388 5,526 2,734 13,115 -10,381 Alpine 1,166 1,166 0 0.00 11 17 -6 6 0 6 Amador 40,177 40,145 -32 -0.08 297 475 -178 146 32 114 Butte 206,478 207,322 844 0.41 2,088 2,241 -153 997 306 691 Calaveras 44,615 44,436 -179 -0.40 352 505 -153 -26 24 -50 Colusa 22,099 22,137 38 0.17 250 186 64 -26 65 -91 Contra Costa 1,156,632 1,162,725 6,093 0.53 11,000 8,554 2,446 3,647 8,087 -4,440 Del Norte 26,301 26,817 516 1.96 258 391 -133 649 12 637 El Dorado 189,160 189,576 416 0.22 1,509 1,764 -255 671 345 326 Fresno 1,021,339 1,030,425 9,086 0.89 13,121 7,834 5,287 3,799 11,189 -7,390 Glenn 28,599 28,842 243 0.85 338 273 65 178 138 40 Humboldt 134,332 133,441 -891 -0.66 1,081 1,367 -286 -605 155 -760 Imperial 182,901 185,792 2,891 1.58 2,306 1,272 1,034 1,857 3,482 -1,625 Inyo 18,742 18,638 -104 -0.55 131 248 -117 13 12 1 Kern 913,030 920,260 7,230 0.79 12,024 7,003 5,021 2,209 4,805 -2,596 Kings 152,717 153,816 1,099 0.72 2,099 928 1,171 -72 452 -524 Lake 66,586 66,794 208 0.31 612 888 -276 484 140 344 Lassen 28,135 27,907 -228 -0.81 244 292 -48 -180 16 -196 Los Angeles 9,853,995 9,895,529 41,534 0.42 90,484 68,553 21,931 19,603 75,539 -55,936 Madera 161,159 163,014 1,855 1.15 2,170 1,176 994 861 917 -56 Marin 254,171 253,725 -446 -0.18 2,115 2,162 -47 -399 1,016 -1,415 Mariposa 16,858 16,796 -62 -0.37 134 206 -72 10 14 -4 Mendocino 89,534 89,466 -68 -0.08 824 934 -110 42 202 -160 Merced 289,346 292,105 2,759 0.95 3,721 2,060 1,661 1,098 1,525 -427 Modoc 8,542 8,489 -53 -0.62 77 121 -44 -9 29 -38 Mono 12,968 12,762 -206 -1.59 107 74 33 -239 28 -267 Monterey 436,767 437,357 590 0.14 5,296 2,854 2,442 -1,852 1,941 -3,793 Napa 135,369 135,613 244 0.18 1,153 1,272 -119 363 809 -446 Nevada 100,505 100,445 -60 -0.06 773 1,176 -403 343 97 246 Orange 3,161,317 3,175,995 14,678 0.46 30,511 22,270 8,241 6,437 20,430 -13,993 Placer 415,664 422,460 6,796 1.63 3,810 3,809 1 6,795 1,530 5,265 Plumas 19,050 18,781 -269 -1.41 123 249 -126 -143 6 -149 Riverside 2,460,447 2,479,957 19,510 0.79 26,882 19,482 7,400 12,110 11,240 870 Sacramento 1,589,157 1,604,725 15,568 0.98 17,129 13,155 3,974 11,594 14,889 -3,295 San Benito 66,168 66,620 452 0.68 806 403 403 49 256 -207 San Bernardino 2,189,838 2,202,477 12,639 0.58 24,928 16,200 8,728 3,911 11,451 -7,540 San Diego 3,304,441 3,325,274 20,833 0.63 35,843 23,095 12,748 8,085 19,580 -11,495 San Francisco 836,950 842,174 5,224 0.62 6,804 6,072 732 4,492 6,252 -1,760 San Joaquin 797,357 806,564 9,207 1.15 9,691 6,156 3,535 5,672 6,422 -750 San Luis Obispo 279,014 278,672 -342 -0.12 2,430 2,791 -361 19 657 -638 San Mateo 741,747 746,373 4,626 0.62 7,209 4,908 2,301 2,325 6,066 -3,741 Santa Barbara 443,026 444,978 1,952 0.44 5,382 3,301 2,081 -129 1,881 -2,010 Santa Clara 1,906,555 1,926,285 19,730 1.03 18,360 10,913 7,447 12,283 17,392 -5,109 Santa Cruz 264,276 263,647 -629 -0.24 2,121 1,963 158 -787 636 -1,423 Shasta 180,417 181,339 922 0.51 1,816 2,306 -490 1,412 199 1,213 Sierra 3,162 3,131 -31 -0.98 14 44 -30 -1 2 -3 Siskiyou 43,101 42,878 -223 -0.52 363 621 -258 35 28 7 Solano 449,474 452,196 2,722 0.61 4,685 3,854 831 1,891 2,397 -506 Sonoma 480,381 482,244 1,863 0.39 4,422 4,303 119 1,744 1,992 -248 Stanislaus 551,038 555,087 4,049 0.73 6,710 4,638 2,072 1,977 3,475 -1,498 Sutter 99,896 100,430 534 0.53 1,207 910 297 237 1,147 -910 Tehama 65,166 64,929 -237 -0.36 729 738 -9 -228 205 -433 Trinity 15,871 15,807 -64 -0.40 95 134 -39 -25 0 -25 Tulare 480,479 485,101 4,622 0.96 6,593 3,424 3,169 1,453 2,458 -1,005 Tuolumne 53,368 53,237 -131 -0.25 430 719 -289 158 42 116 Ventura 829,561 830,076 515 0.06 8,348 6,502 1,846 -1,331 2,953 -4,284 Yolo 221,709 224,108 2,399 1.08 1,849 1,427 422 1,977 970 1,007 Yuba 84,094 85,360 1,266 1.51 1,129 728 401 865 273 592 California 39,279,899 39,509,657 229,758 0.58 400,908 290,329 110,579 119,179 259,321 -140,142 E-2. California County Population Estimates and Components of Change Revised July 1, 2022 and revised July 1, 2023 Table 3. Total Population Change 2022-2023 Components of Change County Revised July 1, 2022 Number Percent Births Deaths Natural Increase Net Migration Net Immigration Net Domestic Migration Alameda 1,652,503 1,654,952 2,449 0.15 16,561 10,785 5,776 -3,327 11,542 -14,869 Alpine 1,177 1,166 -11 -0.93 5 16 -11 0 1 -1 Amador 40,163 40,177 14 0.03 319 539 -220 234 16 218 Butte 206,567 206,478 -89 -0.04 1,908 2,308 -400 311 256 55 Calaveras 44,767 44,615 -152 -0.34 387 592 -205 53 20 33 Colusa 21,970 22,099 129 0.59 275 195 80 49 92 -43 Contra Costa 1,156,404 1,156,632 228 0.02 11,507 8,861 2,646 -2,418 6,425 -8,843 Del Norte 26,466 26,301 -165 -0.62 275 412 -137 -28 12 -40 El Dorado 189,753 189,160 -593 -0.31 1,449 1,815 -366 -227 224 -451 Fresno 1,014,895 1,021,339 6,444 0.63 13,640 7,999 5,641 803 6,701 -5,898 Glenn 28,602 28,599 -3 -0.01 322 317 5 -8 74 -82 Humboldt 134,727 134,332 -395 -0.29 1,141 1,596 -455 60 120 -60 Imperial 181,041 182,901 1,860 1.03 2,470 1,313 1,157 703 2,018 -1,315 Inyo 18,848 18,742 -106 -0.56 141 224 -83 -23 26 -49 Kern 912,801 913,030 229 0.03 12,324 7,571 4,753 -4,524 3,486 -8,010 Kings 151,809 152,717 908 0.60 2,065 1,035 1,030 -122 324 -446 Lake 66,974 66,586 -388 -0.58 652 1,010 -358 -30 125 -155 Lassen 29,681 28,135 -1,546 -5.21 268 333 -65 -1,481 8 -1,489 Los Angeles 9,859,505 9,853,995 -5,510 -0.06 93,329 72,481 20,848 -26,358 56,131 -82,489 Madera 158,538 161,159 2,621 1.65 2,162 1,297 865 1,756 448 1,308 Marin 255,197 254,171 -1,026 -0.40 2,190 2,207 -17 -1,009 853 -1,862 Mariposa 16,941 16,858 -83 -0.49 168 238 -70 -13 8 -21 Mendocino 89,804 89,534 -270 -0.30 827 1,002 -175 -95 186 -281 Merced 286,724 289,346 2,622 0.91 3,811 2,114 1,697 925 1,037 -112 Modoc 8,595 8,542 -53 -0.62 82 129 -47 -6 9 -15 Mono 12,986 12,968 -18 -0.14 114 79 35 -53 18 -71 Monterey 436,872 436,767 -105 -0.02 5,488 2,911 2,577 -2,682 1,299 -3,981 Napa 135,667 135,369 -298 -0.22 1,236 1,299 -63 -235 570 -805 Nevada 100,712 100,505 -207 -0.21 774 1,162 -388 181 90 91 Orange 3,165,309 3,161,317 -3,992 -0.13 30,270 23,044 7,226 -11,218 17,886 -29,104 Placer 411,687 415,664 3,977 0.97 3,805 3,817 -12 3,989 1,277 2,712 Plumas 19,255 19,050 -205 -1.06 147 245 -98 -107 11 -118 Riverside 2,443,147 2,460,447 17,300 0.71 26,952 20,115 6,837 10,463 8,788 1,675 Sacramento 1,581,562 1,589,157 7,595 0.48 18,007 13,452 4,555 3,040 11,327 -8,287 San Benito 66,130 66,168 38 0.06 804 439 365 -327 178 -505 San Bernardino 2,185,609 2,189,838 4,229 0.19 25,837 16,634 9,203 -4,974 8,480 -13,454 San Diego 3,297,225 3,304,441 7,216 0.22 36,513 24,105 12,408 -5,192 14,619 -19,811 San Francisco 835,487 836,950 1,463 0.18 6,843 6,602 241 1,222 5,754 -4,532 San Joaquin 789,694 797,357 7,663 0.97 9,786 6,226 3,560 4,103 4,715 -612 San Luis Obispo 279,912 279,014 -898 -0.32 2,380 2,626 -246 -652 370 -1,022 San Mateo 741,530 741,747 217 0.03 7,276 5,185 2,091 -1,874 4,917 -6,791 Santa Barbara 444,282 443,026 -1,256 -0.28 5,586 3,551 2,035 -3,291 1,148 -4,439 Santa Clara 1,897,531 1,906,555 9,024 0.48 18,673 11,305 7,368 1,656 15,177 -13,521 Santa Cruz 265,746 264,276 -1,470 -0.55 2,216 1,972 244 -1,714 535 -2,249 Shasta 180,642 180,417 -225 -0.12 1,804 2,450 -646 421 147 274 Sierra 3,195 3,162 -33 -1.03 17 50 -33 0 2 -2 Siskiyou 43,382 43,101 -281 -0.65 389 636 -247 -34 29 -63 Solano 448,428 449,474 1,046 0.23 4,719 3,928 791 255 1,684 -1,429 Sonoma 481,041 480,381 -660 -0.14 4,385 4,682 -297 -363 1,519 -1,882 Stanislaus 549,802 551,038 1,236 0.22 6,904 4,862 2,042 -806 2,632 -3,438 Sutter 99,258 99,896 638 0.64 1,219 889 330 308 977 -669 Tehama 65,418 65,166 -252 -0.39 765 817 -52 -200 105 -305 Trinity 15,932 15,871 -61 -0.38 97 181 -84 23 3 20 Tulare 477,303 480,479 3,176 0.67 6,751 3,515 3,236 -60 1,368 -1,428 Tuolumne 53,274 53,368 94 0.18 445 763 -318 412 20 392 Ventura 832,679 829,561 -3,118 -0.37 8,680 6,872 1,808 -4,926 2,256 -7,182 Yolo 221,849 221,709 -140 -0.06 1,881 1,483 398 -538 869 -1,407 Yuba 83,039 84,094 1,055 1.27 1,144 698 446 609 182 427 California 39,220,037 39,279,899 59,862 0.15 410,185 302,984 107,201 -47,339 199,094 -246,433 E-2. California County Population Estimates and Components of Change Revised July 1, 2021 and revised July 1, 2022 Table 4. Total Population Change 2021-2022 Components of Change County Revised July 1, 2021 Preliminary July 1, 2022 Number Percent Births Deaths Natural Increase Net Migration Net Immigration Net Domestic Migration Alameda 1,661,291 1,652,503 -8,788 -0.53 16,972 10,953 6,019 -14,807 7,400 -22,207 Alpine 1,181 1,177 -4 -0.34 13 17 -4 0 0 0 Amador 40,276 40,163 -113 -0.28 329 580 -251 138 13 125 Butte 206,119 206,567 448 0.22 2,035 2,607 -572 1,020 133 887 Calaveras 45,017 44,767 -250 -0.56 386 626 -240 -10 12 -22 Colusa 21,946 21,970 24 0.11 269 185 84 -60 90 -150 Contra Costa 1,163,644 1,156,404 -7,240 -0.62 11,757 9,059 2,698 -9,938 4,397 -14,335 Del Norte 27,291 26,466 -825 -3.02 249 426 -177 -648 11 -659 El Dorado 191,135 189,753 -1,382 -0.72 1,641 1,905 -264 -1,118 172 -1,290 Fresno 1,009,968 1,014,895 4,927 0.49 14,036 9,178 4,858 69 3,445 -3,376 Glenn 28,605 28,602 -3 -0.01 373 345 28 -31 45 -76 Humboldt 134,726 134,727 1 0.00 1,278 1,647 -369 370 67 303 Imperial 179,852 181,041 1,189 0.66 2,616 1,511 1,105 84 1,470 -1,386 Inyo 18,889 18,848 -41 -0.22 183 253 -70 29 14 15 Kern 909,210 912,801 3,591 0.39 12,520 8,328 4,192 -601 2,196 -2,797 Kings 151,553 151,809 256 0.17 2,104 1,224 880 -624 161 -785 Lake 67,163 66,974 -189 -0.28 728 1,003 -275 86 80 6 Lassen 31,077 29,681 -1,396 -4.49 298 399 -101 -1,295 6 -1,301 Los Angeles 9,914,688 9,859,505 -55,183 -0.56 96,527 75,028 21,499 -76,682 39,597 -116,279 Madera 157,514 158,538 1,024 0.65 2,111 1,527 584 440 226 214 Marin 257,802 255,197 -2,605 -1.01 2,370 2,111 259 -2,864 492 -3,356 Mariposa 17,022 16,941 -81 -0.48 146 250 -104 23 8 15 Mendocino 90,733 89,804 -929 -1.02 852 1,041 -189 -740 103 -843 Merced 282,124 286,724 4,600 1.63 3,885 2,312 1,573 3,027 684 2,343 Modoc 8,566 8,595 29 0.34 84 131 -47 76 0 76 Mono 13,128 12,986 -142 -1.08 125 72 53 -195 12 -207 Monterey 437,493 436,872 -621 -0.14 5,677 2,925 2,752 -3,373 922 -4,295 Napa 136,893 135,667 -1,226 -0.90 1,138 1,320 -182 -1,044 373 -1,417 Nevada 101,948 100,712 -1,236 -1.21 802 1,190 -388 -848 42 -890 Orange 3,166,857 3,165,309 -1,548 -0.05 31,085 23,516 7,569 -9,117 10,955 -20,072 Placer 409,100 411,687 2,587 0.63 3,835 4,068 -233 2,820 650 2,170 Plumas 19,650 19,255 -395 -2.01 142 265 -123 -272 2 -274 Riverside 2,430,897 2,443,147 12,250 0.50 28,019 21,773 6,246 6,004 6,060 -56 Sacramento 1,586,714 1,581,562 -5,152 -0.32 18,364 14,335 4,029 -9,181 7,298 -16,479 San Benito 65,256 66,130 874 1.34 891 473 418 456 147 309 San Bernardino 2,184,388 2,185,609 1,221 0.06 26,807 18,725 8,082 -6,861 6,412 -13,273 San Diego 3,287,251 3,297,225 9,974 0.30 38,126 25,560 12,566 -2,592 9,546 -12,138 San Francisco 836,115 835,487 -628 -0.08 7,347 6,385 962 -1,590 4,634 -6,224 San Joaquin 784,882 789,694 4,812 0.61 10,049 6,902 3,147 1,665 2,454 -789 San Luis Obispo 277,812 279,912 2,100 0.76 2,501 2,734 -233 2,333 311 2,022 San Mateo 746,868 741,530 -5,338 -0.71 7,648 5,007 2,641 -7,979 3,667 -11,646 Santa Barbara 437,999 444,282 6,283 1.43 5,689 3,541 2,148 4,135 904 3,231 Santa Clara 1,896,474 1,897,531 1,057 0.06 19,384 11,134 8,250 -7,193 10,340 -17,533 Santa Cruz 263,290 265,746 2,456 0.93 2,280 1,941 339 2,117 420 1,697 Shasta 182,115 180,642 -1,473 -0.81 1,801 2,789 -988 -485 90 -575 Sierra 3,216 3,195 -21 -0.65 22 43 -21 0 0 0 Siskiyou 43,613 43,382 -231 -0.53 388 763 -375 144 13 131 Solano 450,779 448,428 -2,351 -0.52 4,989 4,106 883 -3,234 971 -4,205 Sonoma 483,178 481,041 -2,137 -0.44 4,464 4,538 -74 -2,063 941 -3,004 Stanislaus 551,294 549,802 -1,492 -0.27 7,332 5,430 1,902 -3,394 1,652 -5,046 Sutter 98,872 99,258 386 0.39 1,245 1,047 198 188 360 -172 Tehama 65,687 65,418 -269 -0.41 781 959 -178 -91 53 -144 Trinity 16,007 15,932 -75 -0.47 101 198 -97 22 2 20 Tulare 475,247 477,303 2,056 0.43 6,836 4,205 2,631 -575 976 -1,551 Tuolumne 54,667 53,274 -1,393 -2.55 451 872 -421 -972 10 -982 Ventura 838,557 832,679 -5,878 -0.70 8,779 6,735 2,044 -7,922 1,579 -9,501 Yolo 213,974 221,849 7,875 3.68 1,949 1,553 396 7,479 638 6,841 Yuba 82,435 83,039 604 0.73 1,240 775 465 139 104 35 California 39,260,048 39,220,037 -40,011 -0.10 424,049 318,525 105,524 -145,535 133,360 -278,895 E-2. California County Population Estimates and Components of Change Revised July 1, 2020 and revised July 1, 2021 Table 5. Total Population Change 2020-2021 Components of Change County Revised July 1, 2020 Revised July 1, 2021 Number Percent Births Deaths Natural Increase Net Migration Net Immigration Net Domestic Migration Alameda 1,683,955 1,661,291 -22,664 -1.35 16,738 11,595 5,143 -27,807 -613 -27,194 Alpine 1,202 1,181 -21 -1.75 12 33 -21 0 0 0 Amador 40,417 40,276 -141 -0.35 318 503 -185 44 11 33 Butte 210,236 206,119 -4,117 -1.96 2,001 2,479 -478 -3,639 -91 -3,548 Calaveras 45,253 45,017 -236 -0.52 367 585 -218 -18 11 -29 Colusa 21,870 21,946 76 0.35 295 194 101 -25 14 -39 Contra Costa 1,168,787 1,163,644 -5,143 -0.44 11,751 9,123 2,628 -7,771 1,462 -9,233 Del Norte 27,599 27,291 -308 -1.12 258 386 -128 -180 1 -181 El Dorado 190,736 191,135 399 0.21 1,514 1,862 -348 747 43 704 Fresno 1,007,234 1,009,968 2,734 0.27 13,664 9,574 4,090 -1,356 1,039 -2,395 Glenn 28,786 28,605 -181 -0.63 375 301 74 -255 18 -273 Humboldt 136,242 134,726 -1,516 -1.11 1,223 1,501 -278 -1,238 21 -1,259 Imperial 180,355 179,852 -503 -0.28 2,322 1,902 420 -923 522 -1,445 Inyo 18,955 18,889 -66 -0.35 176 248 -72 6 7 -1 Kern 906,689 909,210 2,521 0.28 12,257 8,390 3,867 -1,346 772 -2,118 Kings 152,147 151,553 -594 -0.39 2,181 1,206 975 -1,569 80 -1,649 Lake 67,380 67,163 -217 -0.32 677 904 -227 10 45 -35 Lassen 31,847 31,077 -770 -2.42 290 341 -51 -719 3 -722 Los Angeles 10,012,587 9,914,688 -97,899 -0.98 94,561 89,114 5,447 -103,346 7,079 -110,425 Madera 156,669 157,514 845 0.54 2,073 1,461 612 233 82 151 Marin 261,061 257,802 -3,259 -1.25 2,185 2,211 -26 -3,233 302 -3,535 Mariposa 17,098 17,022 -76 -0.44 140 222 -82 6 5 1 Mendocino 91,152 90,733 -419 -0.46 907 1,070 -163 -256 43 -299 Merced 281,786 282,124 338 0.12 3,823 2,382 1,441 -1,103 136 -1,239 Modoc 8,684 8,566 -118 -1.36 77 135 -58 -60 1 -61 Mono 13,228 13,128 -100 -0.76 121 63 58 -158 3 -161 Monterey 439,531 437,493 -2,038 -0.46 5,364 3,327 2,037 -4,075 269 -4,344 Napa 137,959 136,893 -1,066 -0.77 1,211 1,301 -90 -976 127 -1,103 Nevada 102,143 101,948 -195 -0.19 796 1,225 -429 234 9 225 Orange 3,190,106 3,166,857 -23,249 -0.73 30,038 26,313 3,725 -26,974 513 -27,487 Placer 405,747 409,100 3,353 0.83 3,577 3,784 -207 3,560 229 3,331 Plumas 19,817 19,650 -167 -0.84 163 268 -105 -62 2 -64 Riverside 2,420,241 2,430,897 10,656 0.44 27,109 24,040 3,069 7,587 1,489 6,098 Sacramento 1,590,013 1,586,714 -3,299 -0.21 17,908 13,987 3,921 -7,220 2,734 -9,954 San Benito 64,301 65,256 955 1.49 751 437 314 641 31 610 San Bernardino 2,185,674 2,184,388 -1,286 -0.06 26,257 21,738 4,519 -5,805 2,103 -7,908 San Diego 3,308,440 3,287,251 -21,189 -0.64 36,662 26,747 9,915 -31,104 405 -31,509 San Francisco 867,927 836,115 -31,812 -3.67 7,536 6,709 827 -32,639 240 -32,879 San Joaquin 781,856 784,882 3,026 0.39 9,664 7,544 2,120 906 916 -10 San Luis Obispo 281,859 277,812 -4,047 -1.44 2,379 2,641 -262 -3,785 -11 -3,774 San Mateo 758,900 746,868 -12,032 -1.59 7,434 5,194 2,240 -14,272 1,081 -15,353 Santa Barbara 447,148 437,999 -9,149 -2.05 5,314 3,703 1,611 -10,760 -1,574 -9,186 Santa Clara 1,925,871 1,896,474 -29,397 -1.53 18,847 11,919 6,928 -36,325 414 -36,739 Santa Cruz 271,673 263,290 -8,383 -3.09 2,178 2,097 81 -8,464 -863 -7,601 Shasta 182,581 182,115 -466 -0.26 1,812 2,616 -804 338 32 306 Sierra 3,232 3,216 -16 -0.50 30 47 -17 1 4 -3 Siskiyou 44,002 43,613 -389 -0.88 416 716 -300 -89 249 -338 Solano 453,847 450,779 -3,068 -0.68 4,899 3,939 960 -4,028 388 -4,416 Sonoma 488,286 483,178 -5,108 -1.05 4,426 4,610 -184 -4,924 457 -5,381 Stanislaus 553,444 551,294 -2,150 -0.39 6,906 5,802 1,104 -3,254 361 -3,615 Sutter 99,291 98,872 -419 -0.42 1,244 948 296 -715 39 -754 Tehama 66,052 65,687 -365 -0.55 749 879 -130 -235 31 -266 Trinity 16,103 16,007 -96 -0.60 118 177 -59 -37 198 -235 Tulare 473,428 475,247 1,819 0.38 6,570 4,165 2,405 -586 150 -736 Tuolumne 55,499 54,667 -832 -1.50 401 767 -366 -466 398 -864 Ventura 844,736 838,557 -6,179 -0.73 8,385 7,360 1,025 -7,204 299 -7,503 Yolo 218,016 213,974 -4,042 -1.85 1,948 1,532 416 -4,458 -1,704 -2,754 Yuba 82,064 82,435 371 0.45 1,105 763 342 29 23 6 California 39,541,742 39,260,048 -281,694 -0.71 412,503 345,080 67,423 -349,117 20,035 -369,152 E-2. California County Population Estimates and Percent Change Revised July 1, 2020 through Preliminary July 1, 2025 Table 6. County Revised July 1, 2020 Revised July 1, 2021 Revised July 1, 2022 Revised July 1, 2023 Revised July 1, 2024 Preliminary July 1, 2025 Alameda 1,683,955 1,661,291 1,652,503 1,654,952 1,663,212 1,665,356 Alpine 1,202 1,181 1,177 1,166 1,166 1,156 Amador 40,417 40,276 40,163 40,177 40,145 39,715 Butte 210,236 206,119 206,567 206,478 207,322 206,659 Calaveras 45,253 45,017 44,767 44,615 44,436 44,269 Colusa 21,870 21,946 21,970 22,099 22,137 22,160 Contra Costa 1,168,787 1,163,644 1,156,404 1,156,632 1,162,725 1,161,681 Del Norte 27,599 27,291 26,466 26,301 26,817 26,557 El Dorado 190,736 191,135 189,753 189,160 189,576 189,127 Fresno 1,007,234 1,009,968 1,014,895 1,021,339 1,030,425 1,035,799 Glenn 28,786 28,605 28,602 28,599 28,842 28,957 Humboldt 136,242 134,726 134,727 134,332 133,441 132,708 Imperial 180,355 179,852 181,041 182,901 185,792 185,710 Inyo 18,955 18,889 18,848 18,742 18,638 18,549 Kern 906,689 909,210 912,801 913,030 920,260 923,402 Kings 152,147 151,553 151,809 152,717 153,816 154,306 Lake 67,380 67,163 66,974 66,586 66,794 66,446 Lassen 31,847 31,077 29,681 28,135 27,907 27,458 Los Angeles 10,012,587 9,914,688 9,859,505 9,853,995 9,895,529 9,867,045 Madera 156,669 157,514 158,538 161,159 163,014 164,083 Marin 261,061 257,802 255,197 254,171 253,725 252,756 Mariposa 17,098 17,022 16,941 16,858 16,796 16,720 Mendocino 91,152 90,733 89,804 89,534 89,466 89,411 Merced 281,786 282,124 286,724 289,346 292,105 293,741 Modoc 8,684 8,566 8,595 8,542 8,489 8,452 Mono 13,228 13,128 12,986 12,968 12,762 12,718 Monterey 439,531 437,493 436,872 436,767 437,357 439,168 Napa 137,959 136,893 135,667 135,369 135,613 136,105 Nevada 102,143 101,948 100,712 100,505 100,445 99,772 Orange 3,190,106 3,166,857 3,165,309 3,161,317 3,175,995 3,174,565 Placer 405,747 409,100 411,687 415,664 422,460 424,595 Plumas 19,817 19,650 19,255 19,050 18,781 18,851 Riverside 2,420,241 2,430,897 2,443,147 2,460,447 2,479,957 2,485,007 Sacramento 1,590,013 1,586,714 1,581,562 1,589,157 1,604,725 1,613,481 San Benito 64,301 65,256 66,130 66,168 66,620 66,962 San Bernardino 2,185,674 2,184,388 2,185,609 2,189,838 2,202,477 2,205,940 San Diego 3,308,440 3,287,251 3,297,225 3,304,441 3,325,274 3,336,081 San Francisco 867,927 836,115 835,487 836,950 842,174 842,457 San Joaquin 781,856 784,882 789,694 797,357 806,564 809,701 San Luis Obispo 281,859 277,812 279,912 279,014 278,672 278,422 San Mateo 758,900 746,868 741,530 741,747 746,373 746,770 Santa Barbara 447,148 437,999 444,282 443,026 444,978 446,252 Santa Clara 1,925,871 1,896,474 1,897,531 1,906,555 1,926,285 1,930,033 Santa Cruz 271,673 263,290 265,746 264,276 263,647 263,039 Shasta 182,581 182,115 180,642 180,417 181,339 180,850 Sierra 3,232 3,216 3,195 3,162 3,131 3,109 Siskiyou 44,002 43,613 43,382 43,101 42,878 42,530 Solano 453,847 450,779 448,428 449,474 452,196 451,147 Sonoma 488,286 483,178 481,041 480,381 482,244 482,261 Stanislaus 553,444 551,294 549,802 551,038 555,087 556,444 Sutter 99,291 98,872 99,258 99,896 100,430 101,052 Tehama 66,052 65,687 65,418 65,166 64,929 64,671 Trinity 16,103 16,007 15,932 15,871 15,807 15,733 Tulare 473,428 475,247 477,303 480,479 485,101 486,876 Tuolumne 55,499 54,667 53,274 53,368 53,237 52,564 Ventura 844,736 838,557 832,679 829,561 830,076 828,474 Yolo 218,016 213,974 221,849 221,709 224,108 225,059 Yuba 82,064 82,435 83,039 84,094 85,360 85,987 California 39,541,742 39,260,048 39,220,037 39,279,899 39,509,657 39,528,899 E-2. California County Numeric Change Revised July 1, 2020 through Preliminary July 1, 2025 Table 7. Numeric Population Change County 2020-2021 2021-2022 2022-2023 2023-2024 2024-2025 Alameda -22,664 -8,788 2,449 8,260 2,144 Alpine -21 -4 -11 0 -10 Amador -141 -113 14 -32 -430 Butte -4,117 448 -89 844 -663 Calaveras -236 -250 -152 -179 -167 Colusa 76 24 129 38 23 Contra Costa -5,143 -7,240 228 6,093 -1,044 Del Norte -308 -825 -165 516 -260 El Dorado 399 -1,382 -593 416 -449 Fresno 2,734 4,927 6,444 9,086 5,374 Glenn -181 -3 -3 243 115 Humboldt -1,516 1 -395 -891 -733 Imperial -503 1,189 1,860 2,891 -82 Inyo -66 -41 -106 -104 -89 Kern 2,521 3,591 229 7,230 3,142 Kings -594 256 908 1,099 490 Lake -217 -189 -388 208 -348 Lassen -770 -1,396 -1,546 -228 -449 Los Angeles -97,899 -55,183 -5,510 41,534 -28,484 Madera 845 1,024 2,621 1,855 1,069 Marin -3,259 -2,605 -1,026 -446 -969 Mariposa -76 -81 -83 -62 -76 Mendocino -419 -929 -270 -68 -55 Merced 338 4,600 2,622 2,759 1,636 Modoc -118 29 -53 -53 -37 Mono -100 -142 -18 -206 -44 Monterey -2,038 -621 -105 590 1,811 Napa -1,066 -1,226 -298 244 492 Nevada -195 -1,236 -207 -60 -673 Orange -23,249 -1,548 -3,992 14,678 -1,430 Placer 3,353 2,587 3,977 6,796 2,135 Plumas -167 -395 -205 -269 70 Riverside 10,656 12,250 17,300 19,510 5,050 Sacramento -3,299 -5,152 7,595 15,568 8,756 San Benito 955 874 38 452 342 San Bernardino -1,286 1,221 4,229 12,639 3,463 San Diego -21,189 9,974 7,216 20,833 10,807 San Francisco -31,812 -628 1,463 5,224 283 San Joaquin 3,026 4,812 7,663 9,207 3,137 San Luis Obispo -4,047 2,100 -898 -342 -250 San Mateo -12,032 -5,338 217 4,626 397 Santa Barbara -9,149 6,283 -1,256 1,952 1,274 Santa Clara -29,397 1,057 9,024 19,730 3,748 Santa Cruz -8,383 2,456 -1,470 -629 -608 Shasta -466 -1,473 -225 922 -489 Sierra -16 -21 -33 -31 -22 Siskiyou -389 -231 -281 -223 -348 Solano -3,068 -2,351 1,046 2,722 -1,049 Sonoma -5,108 -2,137 -660 1,863 17 Stanislaus -2,150 -1,492 1,236 4,049 1,357 Sutter -419 386 638 534 622 Tehama -365 -269 -252 -237 -258 Trinity -96 -75 -61 -64 -74 Tulare 1,819 2,056 3,176 4,622 1,775 Tuolumne -832 -1,393 94 -131 -673 Ventura -6,179 -5,878 -3,118 515 -1,602 Yolo -4,042 7,875 -140 2,399 951 Yuba 371 604 1,055 1,266 627 California (281,694) (40,011) 59,862 229,758 19,242 E-2. California County Percent Change Revised July 1, 2020 through Preliminary July 1, 2025 Table 8. Percent Population Change County 2020- 2021 2021- 2022 2022- 2023 2023- 2024 2024- 2025 Alameda -1.3 -0.5 0.1 0.5 0.1 Alpine -1.7 -0.3 -0.9 0.0 -0.9 Amador -0.3 -0.3 0.0 -0.1 -1.1 Butte -2.0 0.2 0.0 0.4 -0.3 Calaveras -0.5 -0.6 -0.3 -0.4 -0.4 Colusa 0.3 0.1 0.6 0.2 0.1 Contra Costa -0.4 -0.6 0.0 0.5 -0.1 Del Norte -1.1 -3.0 -0.6 2.0 -1.0 El Dorado 0.2 -0.7 -0.3 0.2 -0.2 Fresno 0.3 0.5 0.6 0.9 0.5 Glenn -0.6 0.0 0.0 0.8 0.4 Humboldt -1.1 0.0 -0.3 -0.7 -0.5 Imperial -0.3 0.7 1.0 1.6 0.0 Inyo -0.3 -0.2 -0.6 -0.6 -0.5 Kern 0.3 0.4 0.0 0.8 0.3 Kings -0.4 0.2 0.6 0.7 0.3 Lake -0.3 -0.3 -0.6 0.3 -0.5 Lassen -2.4 -4.5 -5.2 -0.8 -1.6 Los Angeles -1.0 -0.6 -0.1 0.4 -0.3 Madera 0.5 0.7 1.7 1.2 0.7 Marin -1.2 -1.0 -0.4 -0.2 -0.4 Mariposa -0.4 -0.5 -0.5 -0.4 -0.5 Mendocino -0.5 -1.0 -0.3 -0.1 -0.1 Merced 0.1 1.6 0.9 1.0 0.6 Modoc -1.4 0.3 -0.6 -0.6 -0.4 Mono -0.8 -1.1 -0.1 -1.6 -0.3 Monterey -0.5 -0.1 0.0 0.1 0.4 Napa -0.8 -0.9 -0.2 0.2 0.4 Nevada -0.2 -1.2 -0.2 -0.1 -0.7 Orange -0.7 0.0 -0.1 0.5 0.0 Placer 0.8 0.6 1.0 1.6 0.5 Plumas -0.8 -2.0 -1.1 -1.4 0.4 Riverside 0.4 0.5 0.7 0.8 0.2 Sacramento -0.2 -0.3 0.5 1.0 0.5 San Benito 1.5 1.3 0.1 0.7 0.5 San Bernardino -0.1 0.1 0.2 0.6 0.2 San Diego -0.6 0.3 0.2 0.6 0.3 San Francisco -3.7 -0.1 0.2 0.6 0.0 San Joaquin 0.4 0.6 1.0 1.2 0.4 San Luis Obispo -1.4 0.8 -0.3 -0.1 -0.1 San Mateo -1.6 -0.7 0.0 0.6 0.1 Santa Barbara -2.0 1.4 -0.3 0.4 0.3 Santa Clara -1.5 0.1 0.5 1.0 0.2 Santa Cruz -3.1 0.9 -0.6 -0.2 -0.2 Shasta -0.3 -0.8 -0.1 0.5 -0.3 Sierra -0.5 -0.7 -1.0 -1.0 -0.7 Siskiyou -0.9 -0.5 -0.6 -0.5 -0.8 Solano -0.7 -0.5 0.2 0.6 -0.2 Sonoma -1.0 -0.4 -0.1 0.4 0.0 Stanislaus -0.4 -0.3 0.2 0.7 0.2 Sutter -0.4 0.4 0.6 0.5 0.6 Tehama -0.6 -0.4 -0.4 -0.4 -0.4 Trinity -0.6 -0.5 -0.4 -0.4 -0.5 Tulare 0.4 0.4 0.7 1.0 0.4 Tuolumne -1.5 -2.5 0.2 -0.2 -1.3 Ventura -0.7 -0.7 -0.4 0.1 -0.2 Yolo -1.9 3.7 -0.1 1.1 0.4 Yuba 0.5 0.7 1.3 1.5 0.7 California -0.7 -0.1 0.2 0.6 0.0 Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Population 1,156 to 293,741 293,742 to 1,161,681 1,161,682 to 2,485,007 2,485,008 to 3,336,081 9,867,045 0 40 80 120 16020 Miles July 1, 2025 Population Estimates Population Distribution by County Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 California: 39,528,899 Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Percent of State Population 0.00 to 0.74 0.75 to 2.94 2.95 to 8.44 24.96 0 40 80 120 16020 Miles July 1, 2025 Population Estimates County Percentage of California's Population Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Percent Change -1.61 to -0.01 0.00 to 0.39 0.40 to 0.73 0 40 80 120 16020 Miles July 1, 2024 to July 1, 2025 Population Estimates Percent Change Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 California: 0.05 Percent Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Numeric Change -28,484 -28,483 to -430 -429 to -1 0 to 2,144 2,145 to 5,374 5,375 to 10,807 0 40 80 120 16020 Miles July 1, 2024 to July 1, 2025 Population Estimates Numeric Change Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 California: 19,242 Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Natural Increase -728 to -1 0 to 4,696 4,697 to 12,104 20,997 0 40 80 120 16020 Miles July 1, 2024 to July 1, 2025 Population Estimates Natural Increase Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 California: 108,311 Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Net Migration -49,481 to -4,060 -4,059 to -1 0 to 300 301 to 640 641 to 4,116 0 40 80 120 16020 Miles July 1, 2024 to July 1, 2025 Population Estimates Net Migration* Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 California: -89,069 *The sum of net domestic migration and net immigration. Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Net Domestic Migration -79,784 -79,783 to -1,354 -1,353 to -1 0 to 119 120 to 860 0 40 80 120 16020 Miles July 1, 2024 to July 1, 2025 Population Estimates Net Domestic Migration* Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 California: -215,540 *Persons moving to California from another U.S. state minus those moving out of California to another U.S. state. Sierra Sacramento Santa Barbara Calaveras Ventura Los Angeles Sonoma Kings San Diego Placer San Francisco Marin Mariposa Lassen Napa Shasta Monterey Trinity Mendocino Inyo Mono Tuolumne Solano San Bernardino Contra Costa Alpine El Dorado Yolo Yuba San Benito Humboldt Riverside Kern Colusa Del Norte Modoc Fresno Madera Santa Clara Tehama San Joaquin Alameda Nevada Butte Merced Tulare Stanislaus Orange Imperial Sutter Amador Lake Plumas San Mateo Siskiyou Santa Cruz Glenn San Luis Obispo Esri, USGS Net Immigration -9 to -1 0 to 163 164 TO 714 715 to 2,648 2,649 to 30,303 0 40 80 120 16020 Miles July 1, 2024 to July 1, 2025 Population Estimates Net Immigration* Map prepared by: California Department of Finance, Demographic Research Unit, December 2025 California: 126,471 *Persons moving to California from a foreign country minus those leaving the state to live abroad.

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auto!important;} #b327, #b374, #b400{padding:12px 16px!important;} #b327 .mceButtonContainer{width:100%!important;max-width:100%!important;} #b327 .mceButtonLink{padding-top:16px!important;padding-bottom:16px!important;font-size:16px!important;} #b334 .mceTextBlockContainer{padding:0 24px 10px!important;} #b351{padding:0 12px!important;} } @media only screen and (max-width: 640px) { .mceClusterLayout td{padding:4px!important;} } We are excited to announce the release of the 2024 1-year data from the American Community Survey (ACS) through IPUMS USA and IPUMS NHGIS. ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌     ͏ ‌    ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ View this email in your browser Dear , We are excited to announce the release of the 2024 1-year data from the American Community Survey (ACS) through IPUMS USA and IPUMS NHGIS. Read on for the final update of 2025 from IPUMS HQ.   DATA UPDATES IPUMS USA The 2024 1-year American Community Survey (ACS) and Puerto Rico Community Survey (PRCS) Public Use Microdata Sample (PUMS) data are now available via IPUMS USA. This release includes updates to RACE with new detailed codes for Black/African American and White groups. IPUMS NHGIS NHGIS has added the 2024 1-Year ACS Summary File, including over 1,400 data tables for geographic areas with 65,000 or more residents. IPUMS CPS We have updated the Supplemental Poverty Measure variables for the 2014-2016 ASEC samples to use revised versions released by the Census Bureau. These revisions reflect broader changes to the SPM variables that were introduced with the 2017 ASEC. COMING SOON: IPUMS CPS is wrapping up our integration of the November 2025 CPS basic monthly data, which were delayed by the U.S. federal government shutdown and released yesterday by the Census Bureau. Stay tuned to the IPUMS CPS revision history to see when data become available and for a link to a forthcoming blog with important information about the implications of the missing October 2025 data.   CONFERENCES Call for Abstracts: 2026 Data-Intensive Research Conference Abstracts due January 30, 2026 Abstract submissions are now open for the 2026 Data-Intensive Research Conference. The 2026 conference will be held July 22-23 in Minneapolis, MN. The conference theme is Novel Data Linkages and Innovative Life Course Research. Enriching population data through data linkage creates novel data sources that can shed light on life course processes. Linking across time allows for the examination of transitions and trajectories and linking to contextual information situates the experiences of individuals and populations in their environments. Review the call for proposals and submit an abstract.   2025 IPUMS RESEARCH AWARDS Submit your 2025 #poweredbyIPUMS research to our annual research awards competition by Sunday, February 15, 2026. The IPUMS Research Awards honor innovative research using IPUMS data and offer cash prizes to the best published and best student work (published or unpublished). Submit your work for consideration, or nominate the work of a colleague today.   VIRTUAL OFFICE HOURS We invite you to join IPUMS Virtual Office Hours on Wednesday, January 28 from 10:00-11:30am CT. You can drop in anytime, but registration is required for virtual office hours. Stop by with your questions for the data experts who make IPUMS possible.   Use it for good! The IPUMS Team   New Blog Post Historical Supplemental Poverty Measure The Supplemental Poverty Measure (SPM) is an invaluable resource for examining poverty in the United States. However, the Census Bureau only releases SPM data back to the 2010 CPS ASEC. Fortunately, researchers at Columbia University’s Center on Poverty and Social Policy (CPSP) have compiled the data necessary to extend SPM back to 1968, and partnered with IPUMS to make these historical SPM data available via IPUMS CPS. Read our latest blog post to learn more about how CPSP created the historical measures and their “anchored” poverty variables. Read the blog post   IPUMS.ORG | University of Minnesota   Copyright (C) 2025 University of Minnesota, All rights reserved. Our mailing address is: IPUMS 225 19th Ave South Minneapolis, MN 55455 This email was sent to why did I get this? | unsubscribe from this list | update subscription preferences

The purpose of this notice is to allow for 60 days of public comment on the revision of the American Community Survey and Puerto Rico Community Survey, prior to the submission of the information collection request (ICR) to OMB for approval.

Improvements to usability and search are helping decisions move forward The CTPP Data Portal provides online access to the Census Transportation Planning Products (CTPP) data, which is compiled and released by American Association of State Highway and Transportation Officials (AASHTO)’s Census Transportation Solutions program (ACTS). This specialized, user-friendly resource allows transportation planners, researchers, and consultants to query, view, and download detailed special transportation-related tabulations of the U.S. Census Bureau's American Community Survey data. The latest CTPP Data Portal is enhanced to increase the flexibility and utility of its core geographic data. These enhancements are designed to empower transportation planners with more control over their analysis of boundaries and flow patterns, moving beyond standard geographic definitions to support more customized and user-defined options. The geography selection process, the critical step in any CTPP data query, has been redesigned to be easier to use and more intuitive for planners. The change dynamically organizes geographies, actively narrowing the available options at lower-level geographies based on the selections made at higher level geographies. This organized, step-by-step approach streamlines the user's ability to extract highly specific data for local planning and policy analysis. The updated Self-Defined Geography feature allows users to easily create, name, and manage custom study areas for current and future project needs. After selecting a set of geographies, users can save the unique combination as a reusable geography. This custom area can be used for any future query. This capability dramatically increases efficiency by eliminating the need to manually recreate complex geographic areas for recurring or related studies. This enhancement bridges the gap between the CTPP Portal's user-friendly interface and external automated workflows, enabling advanced, programmatic data access. Carrying the selected geographies, including any self-defined areas, into an API (Application Programming Interface) code is now simple and direct. Users can now copy unique geographic identifiers to describe their geographic selection and paste them directly into a target API code. This feature ensures that any custom work performed within the portal is seamlessly and accurately reflected in automated modeling and data retrieval scripts, maximizing consistency and efficiency for users. This powerful enhancement supports more complex commuter flow analysis, a capability essential for understanding origin-destination characteristics like commuter networks. The change expands typical “One-to-All” and “All-to-One” capabilities to “Selected-to-All” and “All-to-Selected” to give the user the additional ability to define their traffic flows. For example, the interface now allows users to choose one or more residence geographies as origins, while all possible workplaces are automatically selected as destinations. This is ideal for analyzing where workers from a specific neighborhood or set of neighborhoods commute. Conversely, users can also choose one or more workplaces as destinations, while all residences are automatically selected as origins. This allows planners to quickly identify the entire commuter shed feeding a major employment center or a series of centers. To explore the powerful, user-friendly CTPP Data Portal, visit https://ctppdata.transportation.org/. A flagship data product from the AASHTO Census Transportation Solutions (ACTS) program, the Census Transportation Planning Product (CTPP) combines a unique focus on residence- and workplace-based data and commuter flows with Census data, including ACS and decennial Census data, to empower more informed transportation planning. The CTPP delivers demographic characteristics, home and work locations, and journey-to-work travel flows by procuring a custom tabulation of Census data every five years. It is specifically designed to support transportation planning and policy applications to help you improve:

In our new series: Chart Toppers 2025, Wilder Research staff look at the most popular charts on Minnesota Compass for 2025. In the first of our series, Jennifer Valorose and Nida Yamin examine the mos...

By Stephanie Richards, Kari Williams, and Sarah Flood The Annual Social and Economic Supplement (ASEC) of the Current Population Survey is the official source of information about poverty in the United States. Since 1968, the ASEC has been used to create the Official Poverty Measure (OPM) and has included the variables needed to create that measure. The Supplemental Poverty Measure (SPM) and the variables needed to create it were first released by the Census Bureau in 2010, reporting the SPM for 20091. In contrast to the OPM, the SPM provides a more complete picture of the economic wellbeing of American households. The value of the SPM is apparent – it is a comprehensive and nuanced measure that accounts for the diversity of living arrangements, variability in cost of living, and a wider array of available financial resources and demands. However, the temporal coverage of SPM is limited; the Census Bureau only has data back to 2010. Over the last ten years, researchers at Columbia University’s Center on Poverty and Social Policy (CPSP) have eliminated this constraint by compiling the data necessary to create SPM and make it available back to 1968, and have shared the data with the research community via the CPSP Historical SPM Data Portal. CPSP researchers have also partnered with IPUMS to disseminate their historical SPM data via IPUMS CPS. This includes the poverty status variables (i.e., SPMPOV and SPMPOVANC12) as well as the inputs and thresholds for creating them. If you know IPUMS, you know that we loooooove the chance to extend a valuable measure back in time. We are incredibly grateful to CPSP for the important work they have done and are thrilled to make it even easier for IPUMS CPS users to access the historical SPM data. In this blog post, we briefly describe differences between the components – family, resources, and needs – used to create OPM and (historical) SPM, preview CPSP’s “anchored” poverty variables that facilitate comparisons over time that reference a set cost-of-living standard, and share suggestions for further reading (because we know you are going to want to learn even more about this!). Defining Poverty In broadest terms, the definition of poverty is whether a family has sufficient resources to meet their basic needs. To determine if a family’s resources can meet their needs, one must first define family, resources, and needs. For each of these, historical SPM extends the logic of the SPM back in time, with creative solutions for adapting the measure to constraints of historical data. Family The official Census definition of a family – which is used in the OPM – is “a group of two people or more (one of whom is the householder) related by birth, marriage, or adoption.” The SPM family, or resource sharing unit, is more inclusive than the OPM family definition. It includes unmarried cohabiting partners and their children, foster children under the age of 22, and any unrelated children under the age of 15 who share resources and expenses together. Historical SPM is faced with two main limitations in identifying families or resource sharing units in early years of the CPS: Cohabiting couples: unmarried partners of the householder are first identified in 1995; with any coresident unmarried partners within a household identified in 2007-forward. Prior to 1995, CPSP uses the adjusted POSSLQ method to capture unmarried partners and create SPM families. Foster children: “foster child” is not an available response for the variable that reports a person’s relationship to householder (i.e., RELATE) prior to 1988, meaning some foster children in these years will not be incorporated into their historical SPM families. There is no way to address this limitation. Resources OPM resources include a family’s total pre-tax cash income from all sources, including wages, retirement, interest and dividends, social security, and veteran’s benefits (FTOTVAL). For the SPM (see SPMTOTRES), OPM cash income is adjusted to account for both additional resources (post-tax income; non-cash benefits) and non-discretionary expenses. Resources added to cash income include the estimated value of food and nutrition program benefits, housing and utility supplements, and tax credits such as the Earned Income Tax Credit (EITC) and Child Tax Credit (CTC). Subtractions from cash income (i.e., non-discretionary expenses) include the cost of federal, state, and payroll taxes, child support paid, childcare and unreimbursed work expenses, and out-of-pocket medical costs. One challenge for the creation of SPMTOTRES in the ASEC prior to 2010 is that the necessary variables for estimating SPM resources are not always collected. In these instances, CPSP imputes values as described in Tables 1 & 2. Table 1: Imputed Resources in Historical SPM Supplemental Nutrition Assistance Program (SNAP) 1968-1979 SNAP was established in 1964 and the program grew over the course of the 1970s; data first gathered in the CPS in 1980 Receipt of benefits imputed with Consumer Expenditure Survey (CE) data; Value of benefits imputed using administrative data on SNAP/Food Stamps caseloads and benefit levels Women, Infants, and Children (WIC)* 1976-2009 WIC pilot program established in 1972 and became permanent in 1974; beginning in 2001, CPS reports number of WIC recipients per household (receipt of benefits imputed by CPSP prior to 2001) Receipt of benefits inferred by identifying income-eligible households then constraining number of individual recipients based on participation in 2001-2010 administrative data; value of benefits imputed using administrative data on average per person WIC expenditures Housing assistance 1968-1975 Versions of federal housing assistance programs date back to at least the New Deal; CPS first asks about reduced price rentals and rental assistance in 1976 First estimate rental payments as 30% of household income and subtract from shelter portion of the threshold, then apply correction factor based on administrative data After-tax income 1968-1979 Census Bureau imputes tax estimates, releasing standalone files for 1980-1990 and incorporating these data directly into the CPS beginning in 1992; imputations in earlier years account for Earned Income Tax Credit (EITC), which was implemented in 1975 National Bureau of Economic Research (NBER) Taxsim model Table 2: Imputed Expenses in Historical SPM Taxes 1968-1979 Census Bureau imputes tax estimates, releasing standalone files for 1980-1990, and incorporates these data directly into the CPS beginning in 1992 NBER Taxsim model Medical out-of-pocket expenses 1968-2010 First included in CPS in 2011 Hot-deck imputation strategy to assign households to MOOP expenditure deciles based on Consumer Expenditure Survey (CE) Childcare expenses 1968-2009 First included in CPS in 2010 Use CE to both predict likelihood of using paid childcare and then apply hot deck imputation to assign households to expenditure deciles Work expenses 1968-2010 Work expenses are not directly collected in the CPS. Census Bureau estimates these from theSurvey of Income and Program Participation (SIPP) SIPP (annual data for 1998-forward; inflation-adjusted value of median work expenditures years before 1998) Thresholds The poverty threshold in both the OPM and SPM are based on the composition of the family unit. The OPM threshold is determined by the number of adults and children in the household and the age of the householder. The original threshold matrix, set in 1963, is adjusted for inflation each year but not otherwise modified. By contrast, SPM thresholds are calculated by the Bureau of Labor Statistics using the Consumer Expenditure Survey (CE) and based on a rolling five-year average of the out-of-pocket costs of living. The original SPM methodology, which CPSP applies to construct historical SPM, specifically accounts for the costs of food, clothing, shelter, and utilities (FCSU2) with adjustment for miscellaneous household expenses. The shelter portion of the threshold varies by household tenure, differentiating between renters and between owners with or without a mortgage, and is adjusted for family composition and geographic differences in the cost of living. There are two areas in which CPSP must address limited data availability for early years of the CPS to create historical SPM thresholds. Expenditures: CPSP uses CE data to impute both expenditures and household tenure (as well as mortgage for 1975-2010) status in early years of the data. Annual CE data are available for 1980-forward, with two additional surveys from 1960/1961 and 1972/1973. For the earliest years, CPSP constructs thresholds using the 1961 and 1972/1973 CE data, then interpolates values for interim years (i.e., 1962-1971 and 1974-1979). For 1980-1983, thresholds are based on one to four years of data instead of the full five-year average. Geographic adjustments: The basic geographic adjustment formula is the median rent for a given geographical area divided by the average national rent. Without a singular source of sufficiently detailed rent information dating back to reference year 1967, CPSP uses the Department of Housing and Urban Development’s Fair Market Rents for the 1985-2010 period and decennial census data (from IPUMS USA!) for earlier years. Anchored Variables By design, the SPM is a “quasi-relative” measure of poverty. This means that changes in the SPM poverty rate over time reflect both changes resulting from the resources that families have and differences in living standards across time. An alternative, which is more similar to the OPM, is a more absolute-style measure of the historical SPM that “anchors” the cost-of-living standard to a given year. CPSP uses the SPM methodology to generate poverty thresholds for a focal year (the anchor year), and then derives thresholds for other years by adjusting the anchor year thresholds for inflation only. The anchored SPM threshold and accompanying variables addresses the question, “what would poverty rates have been across this period when considered against the anchor year’s living standards?” SPMTHRESHANC12 uses the 2012 SPM thresholds and adjusts for inflation SPMPOVANC12 is a dichotomous measure that indicates a household’s poverty status using the 2012 anchored thresholds SPMGEOADJANC12 offers an anchored geographic adjustment factor, which can be used to calculate anchored thresholds that are not adjusted for geographic location. Remember to Cite CPSP If you use IPUMS CPS to access and use these valuable historical SPM data for the 1968 to 2009 period or the anchored SPM measure (for any year!), please acknowledge via citation the substantial efforts of CPSP to create this series. Christopher Wimer, Liana Fox, Sophie Collyer, Irwin Garfinkel, Neeraj Kaushal, Jennifer Laird, Jaehyun Nam, Laura Nolan, Jessica Pac, Ryan Vinh, and Jane Waldfogel. Historical Supplemental Poverty Measure Data. Center on Poverty and Social Policy at Columbia University and Columbia Population Research Center. 2023. www.povertycenter.columbia.edu Learn More Poverty measurement – including the creation of the historical SPM – is a big topic. Check out these resources to learn more. Learn about the history of the SPM and updates to the methodology over time from the BLS page on Research Poverty Thresholds Get more details about Historical SPM data in IPUMS CPS in our user note. Read the paper that introduces the historical SPM (Fox et al., 2015) Understand the geographic cost of living adjustments in historical SPM (Nolan, et al., 2016). Learn about the creation and implication of anchored SPM measures (Wilmer et al., 2016; Fox, 2017) Footnotes This blog post will use survey years for describing availability of SPM variables unless otherwise specified. The Census Bureau collects data to create the SPM via the Annual Social and Economic supplement, or ASEC. The reference period for the ASEC is the previous calendar year, meaning the reference year is the year prior to the survey year. The initial Census Bureau releases of SPM data as stand-alone files used the reference year in naming the files. Since survey year 2020, the SPM data are included in the ASEC data file when the SPM data were originally collected; ASEC files are named according to the survey year. In 2020, the methodology was revised to remove telephone from utilities; telephone and internet are instead treated as separate categories (FSCUti). The revised 2020 methodology also accounts for additional in-kind benefits that are similar to the Supplemental Nutrition Assistance Program (SNAP) benefits included in the original methodology and makes a number of other changes (see this BLS documentation). The 2020 SPM data were released using both the original and the revised methodology.

Broadly slowing labor market is a major factor in falling jobs numbers

Kem C. Gardner Policy Institute I 411 East South Temple Street, Salt Lake City, Utah 84111 I 801-585-5618 I gardner.utah.edu Summary Estimates produced by the Utah Population Committee indicate a total Utah population of 3,551,150 on July 1, 2025, adding 44,351 residents to the state since July 1, 2024. These estimates reflect a continuing moderation of growth since 2023. • Growth Rate - Population growth slowed to 1.3% in 2025, down from 1.5% in 2024. • Components of Change- Net migration played a smaller role in growth than in the past 4 years, contributing 43% to statewide population change. Natural change contributed 57% of new residents. • Natural Change - Natural change was the primary source of population growth, resulting from increases in both births and deaths. Natural change increased for the first time in over a decade outside of changes around COVID-19 trends in 2023. • County Growth - Twenty-four counties grew in 2025, with over half of those counties’ growth driven by net migration. • Fastest Growing Counties - Tooele and Iron counties experienced the fastest population growth (3.0%). Washington, Utah, Grand, and Wasatch counties grew by 2.0% or more. • Most Growth- Utah County added the most population, totaling 15,914 new residents, accounting for approximately 36% of the state’s population growth. State-level Results In 2025, Utah experienced a deceleration in population growth for the second year in a row, from 1.5% in 2024 to 1.3% in 2025. Natural change was the main driver of population growth statewide in 2025. This is a departure from the last four years, where net migration drove the majority of growth. Of the estimated 44,351 new residents added between 2024 and 2025, 57% came from natural change and 43% from net migration. These shifts resulted in a population of 3,551,150 as of July 1, 2025. Utah’s recent shift back to natural change as the primary source of growth represents a return to patterns seen before COVID-19. Figure 1: Utah Population Estimates, 2025 Source: Utah Population Committee, Kem C. Gardner Policy Institute The Utah Population Committee (UPC), chaired and staffed by the Kem C. Gardner Policy Institute, produced Utah’s state and county population estimates for July 1, 2025. The 2025 estimates incorporate the most recent 2020 decennial census data, released in August 2021. This postcensal series will extend from July 1, 2020, until the next decennial census in 2030. The UPC continues to investigate the data and refine the estimates process to accurately reflect the period between July 1, 2020, and July 1, 2025. UPC will continue to monitor the state’s data and conditions into the future. Births Deaths Natural Change Births Deaths Natural Change Cache 145,865 Rich 2,812 Weber 272,929 Davis 381,339 Morgan 13,341 Daggett 959 State Population Estimate Annual Growth Rate Net Migration Natural Change Population Change 3,062,384 3,122,477 3,176,342 3,231,108 3,284,823 3,342,543 3,400,493 3,456,446 3,506,798 3,551,150 1.95% 1.96% 1.73% 1.72% 1.66% 1.76% 1.73% 1.65% 1.46% 1.26% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 2,800,000 2,900,000 3,000,000 3,100,000 3,200,000 3,300,000 3,400,000 3,500,000 3,600,000 % Population G row thTo ta l P op ul at io n 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 1990 1995 2000 2005 2010 2015 2020 2025 46,304 45,463 45,572 46,869 23,292 21,137 21,305 21,751 23,012 24,326 24,267 25,118 10,000 20,000 30,000 40,000 50,000 60,000 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 -20% -15% -10% -5% 0% 5% 10% 15% 20% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 December 2025 I gardner.utah.edu I N F O R M E D D E C I S I O N S TM2 Births Deaths Natural Change Births Deaths Natural Change Cache 145,865 Rich 2,812 Weber 272,929 Davis 381,339 Morgan 13,341 Daggett 959 State Population Estimate Annual Growth Rate Net Migration Natural Change Population Change 3,062,384 3,122,477 3,176,342 3,231,108 3,284,823 3,342,543 3,400,493 3,456,446 3,506,798 3,551,150 1.95% 1.96% 1.73% 1.72% 1.66% 1.76% 1.73% 1.65% 1.46% 1.26% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 2,800,000 2,900,000 3,000,000 3,100,000 3,200,000 3,300,000 3,400,000 3,500,000 3,600,000 % Population G row thTo ta l P op ul at io n 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 1990 1995 2000 2005 2010 2015 2020 2025 46,304 45,463 45,572 46,869 23,292 21,137 21,305 21,751 23,012 24,326 24,267 25,118 10,000 20,000 30,000 40,000 50,000 60,000 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 -20% -15% -10% -5% 0% 5% 10% 15% 20% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Births Deaths Natural Change Births Deaths Natural Change Cache 145,865 Rich 2,812 Weber 272,929 Davis 381,339 Morgan 13,341 Daggett 959 State Population Estimate Annual Growth Rate Net Migration Natural Change Population Change 3,062,384 3,122,477 3,176,342 3,231,108 3,284,823 3,342,543 3,400,493 3,456,446 3,506,798 3,551,150 1.95% 1.96% 1.73% 1.72% 1.66% 1.76% 1.73% 1.65% 1.46% 1.26% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 2,800,000 2,900,000 3,000,000 3,100,000 3,200,000 3,300,000 3,400,000 3,500,000 3,600,000 % Population G row thTo ta l P op ul at io 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 1990 1995 2000 2005 2010 2015 2020 2025 46,304 45,463 45,572 46,869 23,292 21,137 21,305 21,751 23,012 24,326 24,267 25,118 10,000 20,000 30,000 40,000 50,000 60,000 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 -20% -15% -10% -5% 0% 5% 10% 15% 20% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Births Deaths Natural Change Births Deaths Natural Change Cach 145,865 Rich 2,812 Weber 272,929 vis 381,339 Morgan 13,341 Daggett 959 State Population Estimate Annual Growth Rate Net Migration Natural Change Population Change 3,062,384 3,122,477 3,176,342 3,231,108 3,284,823 3,342,543 3,400,493 3,456,446 3,506,798 3,551,150 1.95% 1.96% 1.73% 1.72% 1.66% 1.76% 1.73% 1.65% 1.46% 1.26% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 2,800,000 2,900,000 3,000,000 3,100,000 3,200,000 3,300,000 3,400,000 3,500,000 3,600,000 % Population G row thTo ta l P op ul at io 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 1990 1995 2000 2005 2010 2015 2020 2025 46,304 45,463 45,572 46,869 23,292 21,137 21,305 21,751 23,012 24,326 24,267 25,118 10,00 2 , 3 , 4 , 5 , 6 , 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 -20% -15% -10% -5% 0% 5% 10% 15% 20% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Figure 2: Utah Population and Annual Growth Rates, 2016-2025 Source: Utah Population Committee, Kem C. Gardner Policy Institute Source: Utah Population Committee, Kem C. Gardner Policy Ins itute Births Deaths Natural Change Births Deaths Natural Change Cache 145,865 Rich 2,812 Weber 272,929 Davis 381,339 Morgan 13,341 Daggett 959 State Population Estimate Annual Growth Rate Net Migration Natural Change Population Change 3,062,384 3,122,477 3,176,342 3,231,108 3,284,823 3,342,543 3,400,493 3,456,446 3,506,798 3,551,150 1.95% 1.96% 1.73% 1.72% 1.66% 1.76% 1.73% 1.65% 1.46% 1.26% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 2,800,000 2,900,000 3,000,000 3,100,000 3,200,000 3,300,000 3,400,000 3,500,000 3,600,000 % Population G row thTo ta l P op ul at io 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 1990 1995 2000 2005 2010 2015 2020 2025 46,304 45,463 45,572 46,869 23,292 21,137 21,305 21,751 23,012 24,326 24,267 25,118 10,000 20,000 30,000 40,000 50,000 60,000 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 -20% -15% -10% -5% 0% 5% 10% 15% 20% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Source: Utah Department of Health and Human Services Figure 4: Utah Vital Records, 2016-2025 Figure 5: Utah Vital Records Annual Percent Change, 2016-2025 Source: Utah Department of Health and Human Services Natural Change and Net Migration Natural change increased by 3.5% to 25,118, driving 57% of 2 25’s population growth. Natural change is the difference between the number of annual births and annual deaths. When positive, births are higher than deaths, and negative when deaths outnumber births. This is the first time in over a decade Figure 3: Utah Components of Population Change, 199 -2025 that natural change has increased (outside of the post-COVID-19 rebound from stabilizing deaths). This increase is due to a 2.8% increase in births and a 2.1% increase in deaths. Deaths have annually increased for over a decade and are expected to increase as the population continues aging. Net migration reached 19,233 in 2025, declining from 26,086 in 2024. Net migration accounted for 43% of total state growth this year, declining from 52% in 2024 and 57% in 2023. Net migration’s influence on Utah’s population growth is declining to pre-COVID-19 levels, where it was moderately high but still below natural change. Subtracting out-migration (people moving out of a state or county) from in-migration (people moving into a state or county) provides the net migration value. Net migration is more volatile than natural increase and sensitive to societal and economic situations. Positive net migration is often an indicator of favorable economic conditions, particularly in the western United States.1 Utah’s low, but increasing, unemployment rate and slowing employment growth in 2025 align with the slowing growth and net migration in the July 1, 2025, estimates.2 December 2025 I gardner.utah.edu I N F O R M E D D E C I S I O N S TM3 County-level Results Tooele and Iron counties recorded the fastest growth in the state at 3.0%, similar to last year’s growth of 3.1% and 2.8%, respectively. Washington (2.3%), Utah (2.1%), Grand (2.1%), and Wasatch (2.0%) counties all experienced growth of 2.0% or more. Utah County added the most residents, driven by natural change. Of the 15,914 new residents, natural change contributed 60% (9,582) with net migration representing 40% (6,332). While significantly higher than the second largest population growth county (Salt Lake at 8,281), it was substantially fewer new residents than in 2024. Both Utah and Salt Lake counties experienced substantial decreases in population growth this year, adding 4,000 to 5,000 fewer residents than last year due to declining net migration. Utah County has been the largest contributor to statewide growth for the last six years and accounts for 36% of the population increase in 2025. Salt Lake (19%), Washington (11%), and Tooele (6%) counties also represented large shares of state growth in 2025. Five counties lost population in 2025: Daggett (-2.4%), Piute (-1.5%), Garfield (-0.8%), Wayne (-0.2%), and San Juan (-.03%) counties. In 2025, fewer counties experienced population decline than in 2024. Population estimates for the state and all counties are available in Table 1. Figure 6: Share of Annual Population Growth by Components of Change in Utah, 2016-2025 Beaver Box Elder Carbon Duchesne Emery Grand Iron Juab Kane Gar eld Millard Piute Salt Lake San Juan Sanpete Sevier Summit Tooele Uintah Utah Wasatch Washington Wayne0 -137 -127 -11 1,385 2 8 -24 5,156 436 -262 -459 1,798 -46412,694 617 5,283 28 Cache 605 Rich 81 Weber 1144 Davis -1,184 Morgan -36 Daggett -6 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% State Carbon Kane Sevier Grand Washington Iron Wasatch Tooele Sanpete Morgan Uintah Box Elder Beaver Cache Utah Juab Duchesne Millard Salt Lake Davis Weber Emery Rich Summit Natural Change Net Migration Natural Change Net Migration 57% 53% 55% 52% 51% 41% 40% 43% 48% 57% 43% 47% 45% 48% 49% 59% 60% 57% 52% 43% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Source: Utah Population Committee, Kem C. Gardner Policy Institute Figure 7: Absolute and Percentage Changes in County Population, 2024-2025 Source: Utah Population Committee, Kem C. Gardner Policy Institute Cache 2,383 Rich 8 Weber 1,551 Davis 2,769 Morgan 248 Daggett -24 Cache 1.7% Rich 0.3% Weber 0.6% Davis 0.7% Morgan 1.9% Daggett -2.4% 18.7% Salt Lake 3.5% Weber Rest of State (7.1%) 10.7% Washington 6.2% Davis 5.4% Cache 4.6% Iron 35.9% Utah County 5.6% Tooele 2.6% Box Elder Wasatch 1.8% Sanpete 1.2% Uintah 0.9% Emery 0.0% Rich 0.0% Summit 0.0% Carbon 0.2% Duchesne 0.2% Beaver 0.2% Sevier 0.3% Kane 0.3% Millard 0.2% Morgan 0.6% Juab 0.6% Grand 0.5% Absolute Change Percent Change December 2025 I gardner.utah.edu I N F O R M E D D E C I S I O N S TM4 Figure 8: County Share of State Population Growth, 2024-2025 Beaver Box Elder Carbon Duchesne Emery Grand Iron Juab Kane Gar eld Millard Piute Salt Lake San Juan Sanpete Sevier Summit Tooele Uintah Utah Wasatch Washington Wayne0 -137 -127 -11 1,385 208 -24 5,156 436 -262 -459 1,798 -46412,694 617 5,283 28 Cache 605 Rich 81 Weber 1144 Davis -1,184 Morgan -36 Daggett -6 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% State Carbon Kane Sevier Grand Washington Iron Wasatch Tooele Sanpete Morgan Uintah Box Elder Beaver Cache Utah Juab Duchesne Millard Salt Lake Davis Weber Emery Rich Summit Natural Change Net Migration Natural Change Net Migration 57% 53% 55% 52% 51% 41% 40% 43% 48% 57% 43% 47% 45% 48% 49% 59% 60% 57% 52% 43% 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Note: Daggett, Garfield, Piute, San Juan, and Wayne counties are not included due to population declines Source: Utah Population Committee, Kem C. Gardner Policy Institute Cache 2,383 Rich 8 Weber 1,551 Davis 2,769 Morgan 248 Daggett -24 Cache 1.7% Rich 0.3% Weber 0.6% Davis 0.7% Morgan 1.9% Daggett -2.4% 18.7% Salt Lake 3.5% Weber Rest of State (7.1%) 10.7% Washington 6.2% Davis 5.4% Cache 4.6% Iron 35.9% Utah County 5.6% Tooele 2.6% Box Elder Wasatch 1.8% Sanpete 1.2% Uintah 0.9% Emery 0.0% Rich 0.0% Summit 0.0% Carbon 0.2% Duchesne 0.2% Beaver 0.2% Sevier 0.3% Kane 0.3% Millard 0.2% Morgan 0.6% Juab 0.6% Grand 0.5% Source: Utah Population Committee, Kem C. Gardner Policy Institute Figure 9: Share of Population Growth by Components of Change by County, 2024-2025 December 2025 I gardner.utah.edu I N F O R M E D D E C I S I O N S TM5 Table 1: Utah State and County Population Estimates and Components of Change, 2020-2025 Economic Region/County Utah Population Committee Estimate July 1, 2024 – July 1, 2025 July 1, 2020 July 1, 2021 July 1, 2022 July 1, 2023 July 1, 2024 July 1, 2025 Absolute Change Change Rate Natural Increase Net Migration Net Migration Share of Change State 3,284,823 3,342,543 3,400,493 3,456,446 3,506,798 3,551,150 44,351 1.26% 25,118 19,233 43% Greater Salt Lake 2,847,422 2,892,355 2,940,154 2,987,827 3,030,412 3,066,224 35,813 1.18% 23,533 12,280 34% Box Elder 57,886 59,208 60,607 61,251 61,756 62,911 1,155 1.87% 440 715 62% Cache 133,743 136,945 140,289 141,700 143,482 145,865 2,383 1.66% 1,289 1,094 46% Davis 363,419 367,361 372,262 377,378 378,570 381,339 2,769 0.73% 2,408 361 13% Juab 11,831 12,057 12,438 12,766 13,116 13,364 248 1.89% 170 78 31% Morgan 12,353 12,678 13,016 13,059 13,092 13,341 248 1.90% 82 166 67% Rich 2,517 2,559 2,643 2,725 2,804 2,812 8 0.28% 16 -8 0% Salt Lake 1,188,213 1,197,256 1,206,733 1,220,554 1,232,656 1,240,937 8,281 0.67% 6,902 1,379 17% Summit 42,394 42,837 43,249 43,491 43,301 43,303 2 0.00% 205 -203 0% Tooele 73,149 76,249 77,692 79,408 81,854 84,320 2,466 3.01% 725 1,741 71% Utah 664,258 683,385 705,692 727,751 749,602 765,515 15,914 2.12% 9,582 6,332 40% Wasatch 34,933 35,816 37,075 37,933 38,801 39,588 788 2.03% 211 577 73% Weber 262,727 266,003 268,459 269,811 271,378 272,929 1,551 0.57% 1,503 48 3% Uintah Basin 56,230 56,673 57,472 57,638 57,369 57,860 491 0.86% 220 271 55% Daggett 942.721 962 956 998 984 959 -24 -2.45% -3 -21 0% Duchesne 19,608 19,738 20,095 20,112 20,171 20,266 95 0.47% 70 25 26% Uintah 35,679 35,973 36,422 36,527 36,214 36,634 420 1.16% 153 267 64% West Central 67,073 67,967 69,311 70,082 70,673 71,449 776 1.10% 283 493 64% Millard 13,010 13,211 13,441 13,484 13,609 13,715 106 0.78% 88 18 17% Piute 1,442 1,479 1,495 1,565 1,649 1,625 -24 -1.47% 4 -28 0% Sanpete 28,560 28,978 29,867 30,347 30,900 31,454 553 1.79% 166 387 70% Sevier 21,571 21,795 21,966 22,164 21,972 22,118 146 0.67% 16 130 89% Wayne 2,490 2,504 2,542 2,523 2,543 2,538 -5 -0.21% 9 -14 0% East Central 30,273 30,377 30,664 30,689 30,356 30,461 106 0.35% -31 137 100% Carbon 20,449 20,487 20,737 20,654 20,443 20,539 96 0.47% -53 149 100% Emery 9,824 9,890 9,927 10,035 9,913 9,922 9 0.09% 22 -13 0% Southeast 24,205 24,356 24,668 24,796 24,899 25,103 205 0.82% 54 151 74% Grand 9,664 9,709 9,743 9,842 9,896 10,105 209 2.11% 24 185 88% San Juan 14,541 14,647 14,925 14,954 15,002 14,998 -4 -0.03% 30 -34 0% Southwest 259,621 270,814 278,223 285,413 293,090 300,052 6,961 2.38% 1,063 5,898 85% Beaver 7,076 7,156 7,298 7,314 7,339 7,429 90 1.23% 40 50 56% Garfield 5,084 5,083 5,113 5,141 5,114 5,074 -41 -0.80% 8 -49 0% Iron 57,658 61,128 63,683 66,044 67,896 69,939 2,042 3.01% 416 1,626 80% Kane 7,692 7,919 8,174 8,387 8,363 8,481 118 1.41% -6 124 100% Washington 182,111 189,527 193,956 198,528 204,378 209,129 4,751 2.32% 605 4,146 87% Note: The 2020 Census reflects April 1, 2020. Sources: U.S. Census Bureau (April 1, 2020); Utah Population Committee, Kem C. Gardner Policy Institute (2020-2025) Natural Change and Net Migration Natural change and net migration have had a stable relationship at the state level, but there is more variation at the county level. Typically, slower-growing counties are fueled by natural change, with less or negative net migration, and faster- growing counties are fueled more by net migration. In 2025, net migration drove growth in 13 counties, an increase from last year (11). Of the 13 counties with large shares of net migration, nine had growth rates higher than the state. Three counties, Carbon, Kane, and Daggett, experienced natural decrease (more deaths than births) between 2024 and 2025, ranging from declines of 3 to 53 residents. Despite this, two of the three counties experienced population growth in 2025, with positive net migration offsetting the natural decrease. In ten counties - Utah, Juab, Duchesne, Millard, Salt Lake, Davis, Weber, Emery, Rich, and Summit - the share of growth from net migration was lower than the state (see Figure 9). Net migration in Salt Lake and Utah counties declined in 2025, and natural change became the main driver of population growth for both counties. December 2025 I gardner.utah.edu I N F O R M E D D E C I S I O N S TM6 Endnotes 1. Li, W.L. 1976. A Note on Migration and Employment. Demography 13(4): 565-570. 2. Utah Department of Workforce Services; QCEW (Quarterly Census of Employment and Wages); CES(Current Employment Statistics); Local Area Unemployment Statistics Utah Population Committee (UPC) Members: Mallory Bateman, UPC Chair, Kem C. Gardner Policy Institute Nicole Bissonette, Utah Department of Health and Human Services Aaron Brough, Utah State Board of Education Laura Hanson, Governor’s Office of Planning and Budget Gwen Kervin, Department of Workforce Services David Landward, Enbridge Energy Jacoba Larsen, Utah State Tax Commission Carrie Mayne, Utah System of Higher Education Eric Reither, Utah State University Andrea Wilko, Office of the Legislative Fiscal Analyst Conclusion In 2025, Utah’s population grew primarily due to natural change, with lower net migration and overall growth. Compared to 2024, Utah experienced slowing population growth, with a decline in net migration compared to the last 4 years. Natural change increased for the first time in 10 years. These estimates reflect a slowing growth rate compared to the high growth exhibited at the beginning of the decade. About the Utah Population Committee (UPC) The Utah Population Committee (UPC) prepares state and county-level estimates of the usual resident population for the state of Utah. The U.S. Census Bureau produces annual national, state, and county-level estimates, but their methods lack a contextual understanding of each state. This motivates many states, including Utah, to calculate their own estimates to create a more precise view and explanation of population change each year. State statute determines the composition of UPC membership and the utilization of committee-produced population estimates. The Kem C. Gardner Policy Institute chairs and provides technical staff for the committee. (DE) UPC Estimates Dec2025 Kem C. Gardner Policy Institute I 411 East South Temple Street, Salt Lake City, Utah 84111 I 801-585-5618 I gardner.utah.edu Kem C. Gardner Policy Institute Staff and Advisors Leadership Team Natalie Gochnour, Associate Dean and Director Jennifer Robinson, Chief of Staff Mallory Bateman, Director of Demographic Research Phil Dean, Chief Economist and Senior Research Fellow Shelley Kruger, Director of Accounting and Finance Colleen Larson, Associate Director of Administration Nate Lloyd, Director of Economic Research Dianne Meppen, Director of Community Research Laura Summers, Director of Public Policy Research Nicholas Thiriot, Communications Director James A. Wood, Ivory-Boyer Senior Fellow Staff Eric Albers, Senior Natural Resources Policy Analyst Samantha Ball, Dignity Initiative Research Director Parker Banta, Public Policy Analyst Melanie Beagley, Senior Health Research Analyst Kristina Bishop, Research Economist Andrea Thomas Brandley, Senior Education Analyst Kara Ann Byrne, Senior Health and Human Services Analyst Nate Christensen, Research Economist Moira Dillow, Housing, Construction, and Real Estate Analyst John C. Downen, Senior Research Fellow Dejan Eskic, Senior Research Fellow and Scholar Kate Farr, Monson Center Maintenance Specialist Chance Hansen, Communications Specialist Emily Harris, Senior Demographer Michael T. Hogue, Senior Research Statistician Mike Hollingshaus, Senior Demographer Madeleine Jones, Dignity Initiative Field Director Jennifer Leaver, Senior Tourism Analyst Maddy Oritt, Senior Public Finance Economist Levi Pace, Senior Research Economist Praopan Pratoomchat, Senior Research Economist Heidi Prior, Public Policy Analyst Megan Rabe, Demography Research Associate Natalie Roney, Research Economist Shannon Simonsen, Research Coordinator Paul Springer, Senior Graphic Designer Gaby Velasquez, Monson Center Special Events Coordinator Cayley Wintch, Monson Center Building Manager David Witt, Dignity Initiative Program Associate Senior Advisors Jonathan Ball, Office of the Legislative Fiscal Analyst Ari Bruening, Community-at-Large Silvia Castro, Suazo Business Center Gary Cornia, Marriott School of Business Beth Jarosz, Population Reference Bureau Pamela S. Perlich, University of Utah Chris Redgrave, Community-at-Large Juliette Tennert, Community-at-Large Kem C. Gardner Policy Institute Advisory Board Conveners Michael O. Leavitt Mitt Romney Board Scott Anderson, Co-Chair Gail Miller, Co-Chair Doug Anderson Deborah Bayle Roger Boyer Michelle Camacho Sophia M. DiCaro Cameron Diehl Kurt Dirks Lisa Eccles Spencer P. Eccles Christian Gardner Kem C. Gardner Kimberly Gardner Natalie Gochnour Brandy Grace Jeremy Hafen Clark Ivory Ann Marie McDonald Derek Miller Ann Millner Sterling Nielsen Jason Perry Ray Pickup Gary B. Porter Taylor Randall Jill Remington Love Josh Romney Charles W. Sorenson James Lee Sorenson Vicki Varela Ex Officio (invited) Governor Spencer Cox Speaker Mike Schultz Senate President Stuart Adams Representative Angela Romero Senator Luz Escamilla Mayor Jenny Wilson Mayor Erin Mendenhall Partners in the Community The following individuals and entities help support the research mission of the Kem C. Gardner Policy Institute. Legacy Partners The Gardner Company Christian and Marie Gardner Family Intermountain Health Clark and Christine Ivory Foundation KSL and Deseret News Larry H. & Gail Miller Family Foundation Mountain America Credit Union Salt Lake City Corporation Salt Lake County University of Utah Health Utah Governor’s Office of Economic Opportunity WCF Insurance Zions Bank Executive Partners The Boyer Company Clyde Companies Sustaining Partners Enbridge Salt Lake Chamber Staker Parson Materials and Construction Wells Fargo

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