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TwitterThis annual study provides migration pattern data for the United States by State or by county and are available for inflows (the number of new residents who moved to a State or county and where they migrated from) and outflows (the number of residents who left a State or county and where they moved to). The data include the number of returns filed, number of personal exemptions claimed, total adjusted gross income, and aggregate migration flows at the State level, by the size of adjusted gross income (AGI) and by age of the primary taxpayer. Data are collected and based on year-to-year address changes reported on U.S. Individual Income Tax Returns (Form 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, U.S. Population Migration Data.
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This dataset shows the state-to-state migration in the United States from 2010 to 2019.
The columns in this dataset are: - current state: Current state that people reside in the year of the measurement (include District of Columbia and Puerto Rico) - year: Year of the measurement - population: Population of the current state in the year of the measurement - same house: Number of people reside in the same house as 1 year ago - same state: Number of people reside in the same state as 1 year ago - from different state Total: Total number of people from different states migrate to the current state - abroad Total: Total number of people from abroad migrate to the current state - from: Place from where people migrate to the current state. This includes 50 states, District of Columbia, Puerto Rico, US Island Area, and Foreign Country - number of people: number of people from a different place (from column) migrate to the current state
Data source: US Census
Where do people go from/to each year? What are the factors that correlate with the migration into that state (combine with other datasets)?
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TwitterMigration flows are derived from the relationship between the location of current residence in the American Community Survey (ACS) sample and the responses given to the migration question "Where did you live 1 year ago?". There are flow statistics (moved in, moved out, and net moved) between county or minor civil division (MCD) of residence and county, MCD, or world region of residence 1 year ago. Estimates for MCDs are only available for the 12 strong-MCD states, where the MCDs have the same government functions as incorporated places. Migration flows between metropolitan statistical areas are available starting with the 2009-2013 5-year ACS dataset. Flow statistics are available by three or four variables for each dataset starting with the 2006-2010 5-year ACS datasets. The variables change for each dataset and do not repeat in overlapping datasets. In addition to the flow estimates, there are supplemental statistics files that contain migration/geographical mobility estimates (e.g. nonmovers, moved to a different state, moved from abroad) for each county, MCD, or metro area.
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These migration data come from the Census 2000 long-form questions about residence in 1995 and provide the number of people who moved between counties. There are two files, one for inflows from every county in the United States and another re-sorted by outflows to every county. Each file contains data for all 50 states and the District of Columbia, sorted by FIPS state and county codes.
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Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Centre County, PA (DISCONTINUED) (NETMIGNACS042027) from 2009 to 2020 about Centre County, PA; State College; migration; flow; PA; Net; 5-year; and population.
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TwitterThis app shows the inbound and outbound flow of population to and from every state in the U.S., between 2015 and 2016. This is based on tax returns filed through the IRS. Click on any state to see information about population flows. The brightest, thickest lines have the most population moving along that flow line. The circles indicate the total population inbound or outbound. The chart is sorted by distance to the state, and lets you instantly compare the inflow and outflow of population between 2015 and 2016. The visualization was created from the Distributive Flow Lines tool to depict the flow of population in different directions throughout the country. To see your state or other states, click here. The data comes from the Internal Revenue Service (IRS) migration data based on tax stats. According to the U.S. Population Migration Data: Strengths and Limitations, if a state had less than 3 tax returns from another state, the value is suppressed. This is stated within the pop-up for these cases.
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Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Philadelphia County/city, PA (DISCONTINUED) (NETMIGNACS042101) from 2009 to 2020 about Philadelphia County/City, PA; migration; Philadelphia; flow; PA; Net; 5-year; population; and USA.
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The study of the patterns and evolution of international migration often requires high-frequency data on migration flows on a global scale. However, the presently existing databases force a researcher to choose between the frequency of the data and its geographical scale. Yearly data exist but only for a small subset of countries, while most others are only covered every 5 to 10 years. To fill in the gaps in the coverage, the vast majority of databases use some imputation method. Gaps in the stock of migrants are often filled by combining information on migrants based on their country of birth with data based on nationality or using ‘model’ countries and propensity methods. Gaps in the data on the flow of migrants, on the other hand, are often filled by taking the difference in the stock, which the ’demographic accounting’ methods then adjust for demographic evolutions.
This database aims to fill this gap by providing a global, yearly, bilateral database on the stock of migrants according to their country of birth. This database contains close to 2.9 million observations on over 56,000 country pairs from 1960 to 2020, a tenfold increase relative to the second-largest database. In addition, it also produces an estimate of the net flow of migrants. For a subset of countries –over 8,000 country pairs and half a million observations– we also have lower-bound estimates of the gross in- and outflow.
This database was constructed using a novel approach to estimating the most likely values of missing migration stocks and flows. Specifically, we use a Bayesian state-space model to combine the information from multiple datasets on both stocks and flows into a single estimate. Like the demographic accounting technique, the state-space model is built on the demographic relationship between migrant stocks, flows, births and deaths. The most crucial difference is that the state-space model combines the information from multiple databases, including those covering migrant stocks, net flows, and gross flows.
More details on the construction can currently be found in the UNU-CRIS working paper: Standaert, Samuel and Rayp, Glenn (2022) "Where Did They Come From, Where Did They Go? Bridging the Gaps in Migration Data" UNU-CRIS working paper 22.04. Bruges.
https://cris.unu.edu/where-did-they-come-where-did-they-go-bridging-gaps-migration-data
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The IRS Statistics of Income Division (SOI), in collaboration with the U.S. Census Bureau, has released migration data for the United States for several decades. These data are an important source of information detailing the movement of individuals from one location to another. SOI bases these data on year-to-year address changes reported on individual income tax returns filed with the IRS. They present migration patterns by State or by county for the entire United States and are available for inflows—the number of new residents who moved to a State or county and where they migrated from, and outflows—the number of residents leaving a State or county and where they went. The data are available for Filing Years 1991 through 2016 and include:
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Net County-to-County Migration Flow (5-year estimate) for Miami-Dade County, FL was -47071.00000 Persons in January of 2020, according to the United States Federal Reserve. Historically, Net County-to-County Migration Flow (5-year estimate) for Miami-Dade County, FL reached a record high of -5052.00000 in January of 2010 and a record low of -47345.00000 in January of 2018. Trading Economics provides the current actual value, an historical data chart and related indicators for Net County-to-County Migration Flow (5-year estimate) for Miami-Dade County, FL - last updated from the United States Federal Reserve on November of 2025.
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Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Hancock County, GA (DISCONTINUED) (NETMIGNACS013141) from 2009 to 2020 about Hancock County, GA; migration; flow; GA; Net; 5-year; and population.
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Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Thurston County, WA (DISCONTINUED) (NETMIGNACS053067) from 2009 to 2020 about Thurston County, WA; Olympia; migration; flow; WA; Net; 5-year; and population.
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Net County-to-County Migration Flow (5-year estimate) for Ohio County, IN was 28.00000 Persons in January of 2020, according to the United States Federal Reserve. Historically, Net County-to-County Migration Flow (5-year estimate) for Ohio County, IN reached a record high of 106.00000 in January of 2009 and a record low of -225.00000 in January of 2014. Trading Economics provides the current actual value, an historical data chart and related indicators for Net County-to-County Migration Flow (5-year estimate) for Ohio County, IN - last updated from the United States Federal Reserve on November of 2025.
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Migration data for the United States are based on year-to-year address changes reported on individual income tax returns filed with the IRS. They present migration patterns by State or by county for the entire United States and are available for inflows—the number of new residents who moved to a State or county and where they migrated from, and outflows—the number of residents leaving a State or county and where they went. The data are available for Filing Years 1991 through 2016 and include:
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TwitterAre international migration flows racially biased? Despite widespread consensus that racism and xenophobia affect migration processes, no measure exists to provide systematic evidence on this score. In this research note, I construct such a measure— the migration deviation. Migration deviations are the difference between the observed migration between states, and the flow that we would predict based on a racially blind model that includes a wide variety of political and economic factors. Using this measure, I conduct a descriptive analysis and provide evidence that migrants from majority black states migrate far less than we would expect under a racially blind model. These results pave a new way for scholars to study international racial inequality.
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TwitterVITAL SIGNS INDICATOR Migration (EQ4)
FULL MEASURE NAME Migration flows
LAST UPDATED December 2018
DESCRIPTION Migration refers to the movement of people from one location to another, typically crossing a county or regional boundary. Migration captures both voluntary relocation – for example, moving to another region for a better job or lower home prices – and involuntary relocation as a result of displacement. The dataset includes metropolitan area, regional, and county tables.
DATA SOURCE American Community Survey County-to-County Migration Flows 2012-2015 5-year rolling average http://www.census.gov/topics/population/migration/data/tables.All.html
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Data for migration comes from the American Community Survey; county-to-county flow datasets experience a longer lag time than other standard datasets available in FactFinder. 5-year rolling average data was used for migration for all geographies, as the Census Bureau does not release 1-year annual data. Data is not available at any geography below the county level; note that flows that are relatively small on the county level are often within the margin of error. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area, in addition to the primary MSAs for the nine other major metropolitan areas, by aggregating county data based on current metropolitan area boundaries. Data prior to 2011 is not available on Vital Signs due to inconsistent Census formats and a lack of net migration statistics for prior years. Only counties with a non-negligible flow are shown in the data; all other pairs can be assumed to have zero migration.
Given that the vast majority of migration out of the region was to other counties in California, California counties were bundled into the following regions for simplicity: Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, Sonoma Central Coast: Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz Central Valley: Fresno, Kern, Kings, Madera, Merced, Tulare Los Angeles + Inland Empire: Imperial, Los Angeles, Orange, Riverside, San Bernardino, Ventura Sacramento: El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba San Diego: San Diego San Joaquin Valley: San Joaquin, Stanislaus Rural: all other counties (23)
One key limitation of the American Community Survey migration data is that it is not able to track emigration (movement of current U.S. residents to other countries). This is despite the fact that it is able to quantify immigration (movement of foreign residents to the U.S.), generally by continent of origin. Thus the Vital Signs analysis focuses primarily on net domestic migration, while still specifically citing in-migration flows from countries abroad based on data availability.
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Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Murray County, GA (DISCONTINUED) (NETMIGNACS013213) from 2009 to 2020 about Murray County, GA; Dalton; migration; flow; GA; Net; 5-year; and population.
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Net County-to-County Migration Flow (5-year estimate) for Big Stone County, MN was -43.00000 Persons in January of 2020, according to the United States Federal Reserve. Historically, Net County-to-County Migration Flow (5-year estimate) for Big Stone County, MN reached a record high of 78.00000 in January of 2011 and a record low of -291.00000 in January of 2016. Trading Economics provides the current actual value, an historical data chart and related indicators for Net County-to-County Migration Flow (5-year estimate) for Big Stone County, MN - last updated from the United States Federal Reserve on November of 2025.
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Net County-to-County Migration Flow (5-year estimate) for Delta County, TX was -252.00000 Persons in January of 2020, according to the United States Federal Reserve. Historically, Net County-to-County Migration Flow (5-year estimate) for Delta County, TX reached a record high of 189.00000 in January of 2018 and a record low of -357.00000 in January of 2013. Trading Economics provides the current actual value, an historical data chart and related indicators for Net County-to-County Migration Flow (5-year estimate) for Delta County, TX - last updated from the United States Federal Reserve on December of 2025.
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Net County-to-County Migration Flow (5-year estimate) for District of Columbia was -3655.00000 Persons in January of 2020, according to the United States Federal Reserve. Historically, Net County-to-County Migration Flow (5-year estimate) for District of Columbia reached a record high of -2610.00000 in January of 2010 and a record low of -8193.00000 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for Net County-to-County Migration Flow (5-year estimate) for District of Columbia - last updated from the United States Federal Reserve on November of 2025.
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TwitterThis annual study provides migration pattern data for the United States by State or by county and are available for inflows (the number of new residents who moved to a State or county and where they migrated from) and outflows (the number of residents who left a State or county and where they moved to). The data include the number of returns filed, number of personal exemptions claimed, total adjusted gross income, and aggregate migration flows at the State level, by the size of adjusted gross income (AGI) and by age of the primary taxpayer. Data are collected and based on year-to-year address changes reported on U.S. Individual Income Tax Returns (Form 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, U.S. Population Migration Data.