VITAL 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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UCB Projection: Net International Migration data was reported at 1,118,000.000 Person in 2060. This records an increase from the previous number of 1,116,000.000 Person for 2059. UCB Projection: Net International Migration data is updated yearly, averaging 1,095,000.000 Person from Jun 2017 (Median) to 2060, with 44 observations. The data reached an all-time high of 1,118,000.000 Person in 2060 and a record low of 997,000.000 Person in 2017. UCB Projection: Net International Migration data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.G089: Immigration: Projection: US Census Bureau.
VITAL 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.
https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de446531https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de446531
Abstract (en): 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. All persons living in housing units in the United States in 2000. self-enumerated questionnaireFor each county in the state, the number of migrants who moved to that county from another county is listed. These files contain records for FIPS state code in 2000, FIPS county code in 2000, county and state name in 2000 (current residence), FIPS state code in 1995, FIPS county code in 1995, county and state name in 1995 (previous residence), and the number of migrants who moved between those two counties (inflow).For each county in the state, the number of migrants who moved away from that county to another county is listed. These files contain records for FIPS state code in 1995, FIPS county code in 1995, county and state name in 1995 (previous residence), FIPS state code in 2000, FIPS county code in 2000, county and state name in 2000 (current residence), and the number of migrants who moved between those two counties (outflow).The data for Puerto Rico are not included in this version of the collection.
Migration Summary (2011-2020) Infographic to be embedded in 2022 BBTN Migration Story Map. Data for maps and tables was retrieved from: Internal Revenue Service, Statistics of Income Division Migration Data, 2011 - 2020.
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Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for El Paso County, TX (DISCONTINUED) (NETMIGNACS048141) from 2009 to 2020 about El Paso County, TX; El Paso; migration; flow; Net; TX; 5-year; and population.
Projected Net International Migration by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: 2016-2060 // Source: U.S. Census Bureau, Population Division // There are four projection scenarios: 1. Main series, 2. High Immigration series, 3. Low Immigration series, and 4. Zero Immigration series. // Note: Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. // For detailed information about the methods used to create the population projections, see https://www2.census.gov/programs-surveys/popproj/technical-documentation/methodology/methodstatement17.pdf. // Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The Population Estimates and Projections Program provides additional information on its website: https://www.census.gov/programs-surveys/popproj.html.
https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/
Dataset contains counts for territorial authority local board area (TALB) of usual residence by TALB of usual residence address one year ago and five years ago, and by life cycle age group, for the census usually resident population count, 2023 Census.
This dataset compares usual residence at the 2023 Census with usual residence one and five years earlier to show population mobility and internal migration patterns of people within New Zealand.
‘Usual residence address’ is the address of the dwelling where a person considers that they usually live.
‘Usual residence one year ago address’ identifies an individual’s usual residence on 7 March 2022, which may be different to their current usual residence on census night 2023 (7 March 2023).
‘Usual residence five years ago address’ identifies an individual’s usual residence on 6 March 2018, which may be different to their current usual residence on census night 2023 (7 March 2023).
Note: This dataset only includes usual residence address information for individuals whose usual residence address one year ago and five years ago is available at TALB.
Life cycle age groups are categorised as:
This dataset can be used in conjunction with the following spatial files by joining on the TALB code values:
Footnotes
Geographical boundaries
Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.
Subnational census usually resident population
The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.
Population counts
Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.
Rows excluded from the dataset
Rows show TALB of usual residence by TALB of usual residence one year ago and five years ago, by life cycle age group. Cells with a number less than six have been confidentialised. Responses to categories unable to be mapped, such as response unidentifiable, not stated, and Auckland (not further defined), have also been excluded from this dataset.
About the 2023 Census dataset
For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.
Data quality
The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.
Quality rating of a variable
The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.
Age quality rating
Age is rated as very high quality.
Age – 2023 Census: Information by concept has more information, for example, definitions and data quality.
Census usually resident population quality rating
The census usually resident population count is rated as very high quality.
Census usually resident population count – 2023 Census: Information by concept has more information, for example, definitions and data quality.
Usual residence address quality rating
Usual residence address is rated as high quality.
Usual residence address – 2023 Census: Information by concept has more information, for example, definitions and data quality.
Usual residence one year ago quality rating
Usual residence one year ago area is rated as high quality.
Usual residence one year ago – 2023 Census: Information by concept has more information, for example, definitions and data quality.
Usual residence five years ago quality rating
Usual residence five years ago area is rated as high quality.
Usual residence five years ago – 2023 Census: Information by concept has more information, for example, definitions and data quality.
Using data for good
Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.
Confidentiality
The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.
Symbol
-999 Confidential
Inconsistencies in definitions
Please note that there may be differences in definitions between census classifications and those used for other data collections.
Data represents migration flow into/out of each county as well as intra-county movers and nonmovers
"Counties or equivalent areas in the non-New England States; the District of Columbia; and minor civil divisions in the States of Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, and Connecticut"
https://www.broward.org/Terms/Pages/Default.aspxhttps://www.broward.org/Terms/Pages/Default.aspx
Migration, the movement of people from one location to another, is a key part in population change and provides useful insights that local governments utilize in the planning and development of areas; such as housing supply and demand, job markets, economic health, and resource allocations among others. Domestic migration is defined as the movement of a population within a country. There are two components: in-migrants, people moving into an area, and out-migrants, people moving out of an area. Although these movements occur in response to individual economic, lifestyle and lifecycle choices, in aggregate they show patterns of domestic migration that can change over time.
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Census: Number of Migrants: Odisha data was reported at 15,421,793.000 Person in 03-01-2011. This records an increase from the previous number of 11,054,202.000 Person for 03-01-2001. Census: Number of Migrants: Odisha data is updated decadal, averaging 11,054,202.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 15,421,793.000 Person in 03-01-2011 and a record low of 8,429,297.000 Person in 03-01-1991. Census: Number of Migrants: Odisha data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.
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Census: Number of Migrants: Rajasthan data was reported at 7,224,514.000 Person in 03-01-2011. This records a decrease from the previous number of 16,385,715.000 Person for 03-01-2001. Census: Number of Migrants: Rajasthan data is updated decadal, averaging 12,666,382.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 16,385,715.000 Person in 03-01-2001 and a record low of 7,224,514.000 Person in 03-01-2011. Census: Number of Migrants: Rajasthan data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.
https://www.icpsr.umich.edu/web/ICPSR/studies/8471/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/8471/terms
Gross in- and out-migration statisitcs are provided in this file for each county (or county equivalent) in the United States. Migrant data are stratified by age, race, and sex. Included for each race/sex/age group are data on college attendance, military status, group quarters status, residence abroad in 1975, and total population. Data on country of birth are listed for race/sex strata.
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Graph and download economic data for Net County-to-County Migration Flow (5-year estimate) for Rowan County, NC (DISCONTINUED) (NETMIGNACS037159) from 2009 to 2020 about Rowan County, NC; migration; flow; NC; Net; 5-year; and population.
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Census: Number of Migrants: Assam data was reported at 10,644,234.000 Person in 03-01-2011. This records an increase from the previous number of 6,792,826.000 Person for 03-01-2001. Census: Number of Migrants: Assam data is updated decadal, averaging 6,792,826.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 10,644,234.000 Person in 03-01-2011 and a record low of 5,407,547.000 Person in 03-01-1991. Census: Number of Migrants: Assam data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.
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This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show the number and percentages of migration by census tract in the Atlanta region.
The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.
The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.
For further explanation of ACS estimates and margin of error, visit Census ACS website.
Naming conventions:
Prefixes:
None
Count
p
Percent
r
Rate
m
Median
a
Mean (average)
t
Aggregate (total)
ch
Change in absolute terms (value in t2 - value in t1)
pch
Percent change ((value in t2 - value in t1) / value in t1)
chp
Change in percent (percent in t2 - percent in t1)
Suffixes:
None
Change over two periods
_e
Estimate from most recent ACS
_m
Margin of Error from most recent ACS
_00
Decennial 2000
Attributes:
SumLevel
Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)
GEOID
Census tract Federal Information Processing Series (FIPS) code
NAME
Name of geographic unit
Planning_Region
Planning region designation for ARC purposes
Acres
Total area within the tract (in acres)
SqMi
Total area within the tract (in square miles)
County
County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)
CountyName
County Name
Pop1P_e
# Population ages 1 year and over, 2017
Pop1P_m
# Population ages 1 year and over, 2017 (MOE)
SameHouse_e
# Living in the same house as 1 year ago, 2017
SameHouse_m
# Living in the same house as 1 year ago, 2017 (MOE)
pSameHouse_e
% Living in the same house as 1 year ago, 2017
pSameHouse_m
% Living in the same house as 1 year ago, 2017 (MOE)
DiffHouseInUS_e
# Living in a different house in the U.S. 1 year ago, 2017
DiffHouseInUS_m
# Living in a different house in the U.S. 1 year ago, 2017 (MOE)
pDiffHouseInUS_e
% Living in a different house in the U.S. 1 year ago, 2017
pDiffHouseInUS_m
% Living in a different house in the U.S. 1 year ago, 2017 (MOE)
SameCounty_e
# Living in a different house in the same county 1 year ago, 2017
SameCounty_m
# Living in a different house in the same county 1 year ago, 2017 (MOE)
pSameCounty_e
% Living in a different house in the same county 1 year ago, 2017
pSameCounty_m
% Living in a different house in the same county 1 year ago, 2017 (MOE)
DiffCounty_e
# Living in a different county 1 year ago, 2017
DiffCounty_m
# Living in a different county 1 year ago, 2017 (MOE)
pDiffCounty_e
% Living in a different county 1 year ago, 2017
pDiffCounty_m
% Living in a different county 1 year ago, 2017 (MOE)
SameState_e
# Living in a different county, same state 1 year ago, 2017
SameState_m
# Living in a different county, same state 1 year ago, 2017 (MOE)
pSameState_e
% Living in a different county, same state 1 year ago, 2017
pSameState_m
% Living in a different county, same state 1 year ago, 2017 (MOE)
Diff_State_e
# Living in a different state 1 year ago, 2017
Diff_State_m
# Living in a different state 1 year ago, 2017 (MOE)
pDiff_State_e
% Living in a different state 1 year ago, 2017
pDiff_State_m
% Living in a different state 1 year ago, 2017 (MOE)
Abroad_e
# Living abroad 1 year ago, 2017
Abroad_m
# Living abroad 1 year ago, 2017 (MOE)
pAbroad_e
% Living abroad 1 year ago, 2017
pAbroad_m
% Living abroad 1 year ago, 2017 (MOE)
Moved_e
# Moved in the last year, 2017
Moved_m
# Moved in the last year, 2017 (MOE)
pMoved_e
% Moved in the last year, 2017
pMoved_m
% Moved in the last year, 2017 (MOE)
last_edited_date
Last date the feature was edited by ARC
Source: U.S. Census Bureau, Atlanta Regional Commission
Date: 2013-2017
For additional information, please visit the Census ACS website.
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Census: Number of Migrants: Maharashtra data was reported at 57,376,776.000 Person in 03-01-2011. This records an increase from the previous number of 41,715,711.000 Person for 03-01-2001. Census: Number of Migrants: Maharashtra data is updated decadal, averaging 41,715,711.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 57,376,776.000 Person in 03-01-2011 and a record low of 25,462,420.000 Person in 03-01-1991. Census: Number of Migrants: Maharashtra data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.
TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.
Gross in- and out-migration statisitcs are provided in this file for each county (or county equivalent) in the United States. Migrant data are stratified by age, race, and sex. Included for each race/sex/age group are data on college attendance, military status, group quarters status, residence abroad in 1975, and total population. Data on country of birth are listed for race/sex strata. (Source: downloaded from ICPSR 7/13/10)
Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08471.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.
The 1990 Enhanced Migration Files portion of the Archive of Census Related Products (ACRP) contains migration data derived from the U.S. Census Bureau's Summary Tape File (STP-28). The data includes counts by race and hispanic origin within each county, county to county, and state to state. This portion of the ACRP is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
VITAL 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.