Migration Trends
v3.2
*** To see what's new in the Migration Trends feed, please refer to the Migration Trends v3.2 - Cities and Towns
Use the Placer.ai Migration Trends Data-Feed to analyze the people migration overtime for any region in the US. Analyze the net-migration, migration source, and destination, easily aggregated by ZCTA, DMA, MSA, County, city/town or State.
Placer’s migration data helps understand population trends and changes across the US. To ascertain a migration, we utilize our extensive roster of panelists and follow home region changes. A migration is defined when a panelist is assigned a new home region for at least two months. Please note that this differs from the census definition, but will allow a near real time understanding of the trends in the market. For example, this will identify a student panelist moving to a new location for a semester.
Important
Please note - migration is defined when a panelist is assigned a new home region for at least two consecutive months. To accurately determine migration, the calculation for a given month takes into account data for that month and the following month. Therefore at any given time a report will reflect migration data for the month prior to the last full calendar month. e.g. A report delivered in June will reflect migration trends up to the end of April.
Files Delivery
Once enabled, files will be uploaded to your cloud bucket (AWS/GCS) or delivered via email (see Delivery Details) once a month.
- Files will be located under this path:
/export/analytics/migration-trends/monthly/- upload date, example: 2020-01-11
- Each delivery includes a folder for each of the following region types: CBSA, DMA, county, citytown, state, ZCTA. In
each folder: migration[region_type]ab.csv, migration[region_type]net.csv,
migration[region_type]_metadata.csv - Delivery is done until the 15th of each month, each delivery includes full data-history going back to 2018.
- Each file is GZip compressed
Data Retention and Usage
Placer's algorithms and data constantly improve, therefore we include all the history in every monthly export. We strongly suggest not to use data provided in old exports with new ones to avoid data anomalies.
Zipcodes are actually ZCTAs
ZIP Code Tabulation Areas (ZCTAs) are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas used by the US Census and are considered a common practice when analyzing Zip code population. For more information see this.
A Note about MS Excel
In order to display the data correctly, it's recommended to import the file to Excel, rather than opening it. Opening the file with Excel will work too, but some values may be displayed differently than expected (e.g ZCTAs that start with a zero such as '01003' may appear as 1003)
Schema Overview - migration_[region_type]_net.csv
Each row provides monthly net-migration results per region type per month.
Important!
The adjusted_population for each month shows the sum of adjusted_population for the previous month as well as domestic migration, natural growth and international migration.
For example: The adjusted_population for November 2020, will be the adjusted_population for Oct 2020 + domestic migration throughout Oct 2020 + natural growth throughout Oct 2020 + international migration throughout Oct 2020.
The adjusted_population for January 2018 is used as a baseline.
The total_migration field shows the domestic migration between the named month and the next one. For example:
- The total_migration for November 2020, will include the number of people who migrated between November and December.
- The report for December 2020 will be released in January 2021 and will include the adjusted population up to December 2020. However, the 'total_migration' field will have values until November 2020, representing the migration between November and December.
The latest adjust_population reflects the population counted up to the end of the previous calendar month.
| Column | Description | Type | Example |
|---|---|---|---|
| [region_code] | The numeric code of the region. region_code can be one of: cbsa_code, dma_code, county_code, state_code, zipcode | string | '78705' |
| month | Net-Migration month | YYYY-MM | 2019-01-01 |
| adjusted_population | The adjusted region population. Placer uses the ACS-2018 1 yearaverage as a baseline on which Placer applies the migration trends analysis. This field includes the adjusted population estimation for the relevant month. | integer | 34598 |
| migration_percent | A percentage of the adjusted region population who migrated within the US on the relevant month. Number could be positive or negative. | float | 0.71 |
| population_growth_percent | A percentage of the adjusted region population which shows the population's natural growth (Births/Deaths) in the relevant month. Number could be positive or negative. | float | 4.32 |
| international_migration_percent | A percentage of the adjusted region population which migrated internationally in the relevant month. Number could be positive or negative. | float | 0.66 |
| total_pop_change | The total change in adjusted region population during that month. Number could be positive or negative. | integer | 10498 |
| total_migration | The estimated net number of people who migrated domestically to the region during that month. Number could be positive or negative. | integer | 690 |
Schema Overview - migration_[region_type]_ab.csv
Important
Since a migration is defined when a panelist is assigned a new home region for at least two months, the _ab files include information no more recent than one month before the last full month. For example: if the feed is generated and delivered in May, it will include Migration data until March.
Each row provides monthly domestic migration results for a pair of source/destination region types and month.
| Column | Description | Type | Example |
|---|---|---|---|
| month | Migration month | YYYY-MM | 2019-01 |
| [region_code]_a | region code A region_code can be one of: cbsa_code, dma_code, county_code, state_code, zipcode | string | '90210' |
| [region_code]_b | region code B region_code can be one of: cbsa_code, dma_code, county_code, state_code, zipcode | string | '90065' |
| [region_code]_a_adjusted_population | The adjusted region A population. region_code can be one of: cbsa_code, dma_code, county_code, state_code, zipcode | integer | 21000 |
| percentage_migrated_a_to_b | The percentage of population migrated from 'Region A' to 'Region B' on the relevant month | float | 0.47 |
| percentage_migrated_b_to_a | The percentage of population migrated from 'Region B' to 'Region A' during the relevant month | float | 4.25 |
| a_to_b | The number of people that migrated from 'Region A' to 'Region B' during the relevant month | integer | 1567 |
| b_to_a | The number of people that migrated from 'Region B' to 'Region A' during the relevant month | integer | 345 |
Schema Overview - migration_[region_type]_metadata.csv
Each row includes metadata for a region.
Note the 'seasonal_magnitude' warning to improve analysis quality.
| Column | Description | Type | Example |
|---|---|---|---|
| [region_code] | region_code can be one of: cbsa_code, dma_code, county_code, state_code, zipcode | string | '90210' |
| [region_name] | region_name can be one state_name, cbsa_name, dma_name, county_name, zipcode_name | string | ‘Los Angeles’ |
| baseline_population | Derived from the ACS 2018 1 year population average. Used as the baseline for the 'adjusted population estimates'. | integer | 19500 |
| lat | Region’s center latitude | double | 34.100835 |
| lng | Region’s center longitude | double | -118.41417 |
| insufficient_data | regions with very low population, will have insufficient_data=true | boolean | False |
| seasonal_magnitude | Ranges from 0.0 to 1.0 and used to measure the seasonality bias of the region (e.g. due to a University or a summer vacation destination). | double | 0.017317 |
Schema Sample File
Please find HERE migration trends feed's files with a limited data for schema evaluation.
Updated 6 days ago