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We are trying to understand the difference between employees and daytime population. It looks like some of the population may be double counted. Can you explain what rows are used for the 2014 Total Daytime population #.
Methodologies are different for Employees and Daytime Population.
Employees & Establishments in Business Summary are sourced from the D&B Business list and summarized to a geographic level although delivered in the Experian CAPE release. The employee counts are as accurate as the D&B employee value but are also subject to block centroid allocation used for population.
Employment fields from the Occupation & Employment folder are based upon the American Community Survey, modeled to a current year value and are part of CAPE.
Daytime Population is sourced from Experian and are compiled values using several CAPE fields. The excerpt below is pulled from the Tech Overview delivered to clients.
Daytime PopulationDaytime Population – Current Year Estimates (CYE)
The Daytime Population database is created using a variety of methodologies applicable for different subsets of the Total Daytime Population. These subsets are then added together to create the Total Daytime Population.
The process starts by identifying key subsets of the residential population that are assumed to stay in or close to their home location during the day. In particular, the following subsets of population are assumed to remain in the same Block Group during the day as the Block Group in which they live (or reside):
Residential Population : Children aged less than or equal to 2
Residential Population : Civilian aged 16+ population that are unemployed
Residential Population : Civilian aged 16+ population that work at home
Residential Population : Population aged 65+ who are retired
Residential Population : Population aged 16+ who are homemakers
Residential Population : Population aged 16+ who are in the Armed Forces
All of the above variables can be directly obtained from previously calculated CAPE – Demographics – Current Year Estimate (CYE) residentially-based variables, except for the ‘Residential Population : Population aged 16+ who are homemakers’. This variable is calculated by applying suitable localized proportions to the existing ‘larger population’ variable of the ‘Civilian aged 16+ population who are ‘Not in Labor Force’. Applying these proportions determines the subset of this ‘larger population’ that are estimated to be homemakers.
Once these initial subsets of Daytime Population who are assumed to stay in their residential Block Group during the daytime are defined and accounted for, then the daytime location of other population types are modelled. It is assumed that these remaining population types are much more likely to travel out of their residential Block Group to reach their typical daytime location than is the case for the population groups previously accounted for. However, flows from home address to daytime address that occur completely within the same Block Group are also possible for these types.
First, the estimate of daytime population at place of work that has already been modelled for the Mosaic Workplace database is accounted for. This variable is:
Daytime Population, Civilian 16+, at WorkplaceAfter the above, the main population groups left to be modelled are:
Within the work to create Mosaic Workplace, this variable is estimated using Census Tract-to-Tract flows of workers from residence to workplace, and National Business Database data to update these flows and allocate them from Tract level to Block Group level.
Daytime Population, Students : Prekindergarten to 8th grade
Daytime Population, Students : 9th grade to 12th grade
Daytime Population, Students : Post-secondary students
Daytime Population: Any remaining Civilian aged 16+ population that are ‘Not in Labor Force’ and have not yet been accounted for.
All of the three student populations are modelled using a variety of data from the National Center for Education Statistics (NCES) and also information from key institutions (i.e. universities/colleges) themselves. After making allowance for students registered at an institution but very unlikely to travel to that institution on a typical day (for example, students undertaking online courses), this information is compiled and modelled to create an initial estimate of the typical number of students that spend the day at the location (or campus) of each institution. These figures are then calibrated so that the initial estimates of students who spend a typical day at the location of each institution, and those who stay within their residential Block Group during a typical day, are balanced to equal the national number of students within each category (i.e. Prekindergarten to 8th grade, 9th grade to 12th grade, Post-secondary students).
Once all students have been accounted for, current estimates of each relevant daytime population sub-group are tallied and compared to the national estimate of ‘Residential Population: Civilian aged 16+ population that are Not in Labor Force’. The above work does not yet account for a proportion of this population group. The, as yet unaccounted for, proportion of this group is therefore calculated and assumed to spend a typical day within the Block Group in which they live.
Having allocated all of the relevant subsets of residential population to either the Block Group in which they reside, or to another Block Group which they are estimated to travel to in order to spend a typical day, then the two final variables in the database are calculated:
Daytime Population Aged 16+
Total Daytime Population (i.e. all ages)
Census data is calculated based on census designated boundaries which range in increasing size from Blocks - Block Groups - Tracts - Counties - etc. However, when solving most business issues, custom polygons are often used. Since custom polygons almost never perfectly mirror Census Blocks, a method to subdivide Blocks must be created. Block Centroid Retrevial
Alteryx utilizes Block Centroid Retrieval when allocating demographic data to irregular polygons such as custom radii, ZIP Codes, and custom trade areas. For the US datasets, this retrieval is based on the centroids of the US Census 2010 Blocks. Each record is tagged with the percent of the household and population it represents as a fraction of its associated block group. Development changes in the years since the census are not reflected in this inventory of block centroids.
To address this requirement, Alteryx designed a methodological approach to update block groups to reflect areas of growth. By utilizing the Experian household database of 127 million U.S. consumer households in conjunction with the Census Bureau, Alteryx has created additional points, within the block inventory dataset, utilized by Allocate to represent population and household growth during the time since the previous census.