Smbliq C 044 Opportunity Insights Economic Tracker Data Documentation 2020 10

Summary

Opportunity Insights Economic Tracker Data Documentation, last updated on 2020-10-13, which provides an overview of the sources and processing applied to each data series within the tracker. It describes the Consumer Spending series, using aggregated and anonymized credit and debit card spending data from Affinity Solutions, and the Small Business Revenue and Small Businesses Open series, with Womply listed as the data source. It also describes a Job Postings series from Burning Glass Technologies. Each series entry gives its summary, data source, update frequency, date range, indexing type, geographies and breakdowns by industry and ZIP code income, with notes on data limitations.

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Opportunity Insights Economic Tracker
Data Documentation
last updated on 2020-10-13

1 Overview

This document provides an overview of the sources and processing applied to each data series
within the Opportunity Insights Economic Tracker. The documentation is organized sequentially
by series in the tracker, then broken down into categories of information describing each series,
its source data, and our processing steps.
You can refer to additional documentation published by Opportunity Insights for complementary
information:

• The Economic Tracker’s Data Dictionary lists each data file and variable available for
public use, with short descriptions of the contents of each variable.
• The accompanying paper provides detailed information about the methodology used to
construct the series.

Please note that both the data and this data documentation is updated regularly and that the
following information is subject to change.

2 Data Series

2.1 Consumer Spending

Summary: Aggregated and anonymized purchase data from consumer credit and debit card
spending. Spending is reported based on the ZIP code where the cardholder lives, not the ZIP
code where transactions occurred.
Data Source: Affinity Solutions
Update Frequency: Weekly
Date Range: January 13th until the most recent date available.
Data Frequency: Data is daily until the final two weeks of the series, and the daily data is
presented as a 7 day lookback moving average. For the final two weeks of the series, the data is
weekly and presented as weekly data points.
Index Period: January 4th - January 31st
Indexing Type: Seasonally adjusted change since January 2020. Data is indexed in 2019 and
2020 as the change relative to the January index period. We then seasonally adjust by dividing

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year-over-year, which represents the difference between the change since January observed in
2020 compared to the change since January observed since 2019. We account for differences in
the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align
the holidays before performing the year-over-year division.
Geographies: National, State, County, Metro
Breakdowns:

• By Industry. Industries are constructed by grouping merchant codes that are used by
Affinity Solutions to identify the category of merchant and merchant activity.

– Apparel and General Merchandise
– Entertainment and Recreation
– Grocery
– Health Care
– Resturants and Hotels
– Transportation

• By Consumer Zip Code Income. Transactions are linked to zip codes where the consumer
lives and zip codes are classified into income cateogories based on measurements of median
household income and population provided by the American Community Survey (2014 -
2018).

– High Income (median household income greater than $78,000 per year)
– Middle Income (median household income between $46,000 per year and $78,000 per
year)
– Low Income (median household income less than $46,000 per year)

Notes: The raw data contains discontinuous breaks caused by entry or exit of credit card
providers from the sample. We generally correct for this using a method outlined in the paper.
However, at the county-level when are there more than one structurual breaks the data is too
noisy to correct for these breaks and counties with multiple breaks are dropped from the sample.
Additionally Affinity solutions suppresses any cut of the data with fewer than five transactions.

2.2 Small Business Revenue

Summary: Small business transactions and revenue data aggregated from several credit card
processors. Transactions and revenue are reported based on the ZIP code where the business is
located.
Data Source: Womply
Update Frequency: Weekly
Date Range: January 15th until the most recent date available.
Data Frequency: Daily, presented as a 7-day moving average
Indexing Period: January 4th - January 31st
Indexing Type: Seasonally adjusted change since January 2020. Data is indexed in 2019 and
2020 as the change relative to the January index period. We then seasonally adjust by dividing
year-over-year, which represents the difference between the change since January observed in
2020 compared to the change since January observed since 2019. We account for differences in

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the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align
the holidays before performing the year-over-year division.
Geographies: National, State, County, Metro
Breakdowns:

• Industry, by NAICS supersector.

– Education and Health Services
– Leisure and Hospitality
– Retail and Transportation

• Business Zip Code Income. Transactions are linked to ZIP codes where the business is
located and ZIP codes are classified into income categories based on measurements of
median household income and population provided by the American Community Survey
(2014 - 2018).

Notes:
Small businesses are defined as those with annual revenue below the Small Business Adminstra-
tion’s thresholds. Thresholds vary by 6 digit NAICS code ranging from a maximum number of
employees between 100 to 1500 to be considered a small business depending on the industry.
County-level and metro-level data and breakdowns by High/Middle/Low income ZIP codes have
been temporarily removed since the August 21st 2020 update due to revisions in the structure
of the raw data we receive. We hope to add them back to the OI Economic Tracker soon.

2.3 Small Businesses Open

Summary: Number of small businesses open, as defined by having had at least one transaction
in the previous 3 days.
Data Source: Womply
Update Frequency: Weekly
Date Range: January 15th until the most recent date available.
Data Frequency: Daily, presented as a 7-day moving average
Indexing Period: January 4th - January 31st
Indexing Type: Seasonally adjusted change since January 2020. Data is indexed in 2019 and
2020 as the change relative to the January index period. We then seasonally adjust by dividing
year-over-year, which represents the difference between the change since January observed in
2020 compared to the change since January observed since 2019. We account for differences in
the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align
the holidays before performing the year-over-year division.
Geographies: National, State, County, Metro

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We exclude counties with a total average revenue of less than $250,000 during the indexing period
(January 4-31). Additionally we omit spending categories for a small number of geographies
that are extreme positive outliers, and we cap a small number of extreme negative outliers at 0
revenue.
Breakdowns:

• Industry, by NAICS supersector.

– Education and Health Services
– Leisure and Hospitality
– Retail and Transportation

Notes: Small businesses are defined as those with annual revenue below the Small Business
Adminstration’s thresholds. Thresholds vary by 6 digit NAICS code ranging from a maximum
number of employees between 100 to 1500 to be considered a small business depending on the
industry.
County-level and metro-level data and breakdowns by High/Middle/Low income ZIP codes have
been temporarily removed since the August 21st 2020 update due to revisions in the structure
of the raw data we receive. We hope to add them back to the OI Economic Tracker soon.

2.4 Job Postings

Summary: Weekly count of new job postings, sourced from over 40,000 online job boards. New
job postings are defined as those that have not had a duplicate posting for at least 60 days
prior.
Data Source: Burning Glass Technologies
Update Frequency: Weekly
Date Range: January 17th until the most recent date available.
Data Frequency: Weekly data points, with each week ending on Friday.
Indexing Period: January 4th - January 31st
Indexing Type: Change relative to the January 2020 index period, not seasonally adjusted.
Geographies: National, State, Metro.
Breakdowns:

• Industry, by NAICS supersector.

– Educational and Health Services
– Financial Activities and Services

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– Leisure and Hospitality
– Manufactoring
– Professional and Business Services

• Education Requirement, by ONET Jobzone’s Education Requirement Classification.

– Minimal - Jobzone 1
– Some - Jobzone 2
– Moderate - Jobzone 3
– Considerable - Jobzone 4
– Extensive - Jobzone 5

2.5 Employment

Summary: Number of active employees, aggregating information from multiple data providers.
This series is based on firm-level payroll data from Paychex and Intuit, worker-level data on
employment and earnings from Earnin, and firm-level timesheet data from Kronos.
Data Source: Paychex, Intuit, Earnin, Kronos
Update Frequency: Weekly
Date Range: January 15th until the most recent date available. The most recent date available
for the full series depends on the combination of Paychex, Intuit and Earnin data. We extend
the national trend for the Low Income employment subgroup by using Kronos timecard data to
forecast beyond the end of the Paychex, Intuit and Earnin data.
Data Frequency: Daily, presented as a 7-day moving average
Indexing Period: January 4th - January 31st
Indexing Type: Change relative to the January 2020 index period, not seasonally adjusted.
Geographies: National, State, County, Metro
To prevent the introduction of new Paychex clients from artificially creating noise in the
employment series overtime, in the underlying raw data we suppress county x industry x firm
size cells that both (i) experience a large anomalous change in employment and (ii) made up a
large share of a county’s total employment at any point in the current year. For more details on
the specifics of these thresholds see the appendix of the accompanying paper.
Breakdowns:

• Wage.

– High Income (wage greater than $60,000 per year)
– Middle Income (wage between $27,000 per year and $60,000 per year)
– Low Income (wage less than $27,000 per year)

• Industry, by NAICS supersector.

– Professional and Business Services
– Education and Health Services
– Retail and Transportation
– Leisure and Hospitality

Notes:

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• For low income workers, the change in employment is calculated using Paychex and Earnin
data. For medium and high income workers, the change in employment is calculated using
Paychex and Intuit data.
• We forecast the national trend in employment for the Low Income subgroup past the most
recent data from Paychex and Earnin using data from Kronos. The Kronos timestamp
data tracks closely with low-income employment constructed from payroll data, but for
payroll data there is a lag in reporting until the end of a payroll cycle. To get information
closer to real time we use the Kronos timestamp data, which is reported more frequently
with a shorter lag. We predict low-income employment using a distributed lag model,
regressing a given week’s low income employment measure on the corresponding week’s
and 3 previous lagged weeks’ Kronos timestamp measure.

2.6 Unemployment Claims

Summary: Weekly unimployment insurance claims counts and rates (as a share of the 2019
labor force) for all states, as well as initial unemployment insurance claims for select counties
where the data is publicly available.
Data Source: State-level and national statistics are reported by the U.S. Department of
Labor.
The county-level series is only available for states whose respective state agencies publish county
level data:

• Alabama: Alabama Department of Labor
• Arizona: Arizona Commerce Authority
• California: Employment Development Department of California
• Colorado: Colorado Department of Labor and Employment
• Georgia: Georgia Department of Labor
• Hawaii: Hawaii Department of Labor
• Idaho: Idaho Department of Labor
• Illinois: Illinois Department of Employment Security
• Indiana: Indiana Department of Workforce Development
• Iowa: State of Iowa
• Kentucky: Kentucky Center for Statistics
• Maryland: Maryland Department of Labor
• Massachusetts: Masschusetts Department of Unemployment Assistance
• Missouri: State of Missouri
• Nebraska: NEworks (Government of Nebraska)
• Nevada: Nevada Department of Employment; Training and Rehabilitation
• New York: New York State Department of Labor
• Ohio: Ohio Department of Job and Family Services
• Pennsylvania: Government of Pennsylvania
• Washington: Washington State Employment Security Department
• Wisconsin: Wisconsin Department of Workforce Development
• Wyoming: Wyoming Department of Workforce Services

Update Frequency: Weekly (where available, in the case of county-level data)
Date Range: January 18th until the most recent date available.
Data Frequency: Weekly data points, with each week ending on Saturday.

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Note that county-level claims in California, Georgia, Kentucky, and Illinois are reported at
the monthly level and imputed to weekly data points for the county-level series. For more
information about the imputation methodology, see the accompanying paper
Indexing Period: No indexing applied, the published numbers directly report quantities.
Indexing Type: No indexing applied, the published numbers directly report quantities.
Geographies: National, State, County, Metro.
Breakdowns:

• Initial Claims

– Regular Claims
– PUA Claims
– Combined Claims

• Continued Claims

– Regular Claims
– PUA Claims
– PEUC Claims
– Combined Claims

Notes: Unemployment claims rates are calculated by dividing unemployment claims counts by
the Bureau of Labor Statistics labor force estimates from 2019.
Under the CARES Act, all states provide 13 additional weeks of federally funded Pandemic
Emergency Unemployment Assistance (PEUC) benefits to people who exhaust their regular
state benefits. Under the Act, through the end of 2020, some people who exhaust all these
benefits, and others who have lost their jobs for reasons arising from the pandemic but who are
not normally eligible for UI in their state, are eligible for Pandemic Unemployment Assistance
(PUA). “Combined Claims” are defined as the sum of regular, PUA and PEUC unemployment
benefit claims.

2.7 Online Math Participation

Summary: Number of students using an online math curriculum, Zearn Math, among schools
that already used Zearn Math in course instruction before the pandemic.
Data Source: Zearn
Update Frequency: Weekly, except during summer and winter school breaks.
Date Range: January 6th to May 3rd 2020. The data series is not being updated during the
summer. Updates will resume during the fall semester.
Data Frequency: Weekly data points, with each week ending on Sunday.
Indexing Period: January 6th - February 7th
Indexing Type: Change relative to the January 2020 index period, not seasonally adjusted.
Geographies: National, States, County, Metro
To ensure privacy, the data we obtain are masked such that any county with fewer than two
districts, fewer than three schools, or fewer than 50 students on average using Zearn Math is
excluded. Where possible, masked county levels values are replaced by commuting zone means.

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Breakdowns:

• School Zip Code Income. Schools are linked back to their ZIP code and ZIP codes are
classified into income categories based on measurements of median household income and
population provided by the American Community Survey (2014 - 2018).

Notes: We exclude schools who did not use Zearn Math for at least one week from January 6
to February 7 and schools that never have more than five students using Zearn Math during our
analysis period.

2.8 Student Progress in Math

Summary: Number of lessons completed by students each week using Zearn Math, among
schools that already used Zearn Math in course instruction before the pandemic.
Data Source: Zearn
Update Frequency: Weekly, except during summer and winter school breaks.
Date Range: January 6th to May 3rd 2020. The data series is not being updated during the
summer. Updates will resume during the fall semester.
Data Frequency: Weekly data points, with each week ending on Sunday.
Indexing Period: January 6th - February 7th
Indexing Type: Change relative to the January 2020 index period, not seasonally adjusted.
Geographies: National, States, County, Metro
To ensure privacy, the data we obtain are masked such that any county with fewer than two
districts, fewer than three schools, or fewer than 50 students on average using Zearn Math is
excluded. Where possible, masked county levels values are replaced by commuting zone means.
Breakdowns:

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2.9 COVID-19 Cases, Deaths and Tests

Summary: The daily count and rate per 100,000 people of confirmed COVID-19 cases, deaths
or tests performed.
Data Source: New York Times COVID-19 Data, The COVID Tracking Project.
Update Frequency: Daily
Date Range: January 22th until the most recent date available.
Data Frequency: Daily, presented as a 7-day moving average
Indexing Period: No indexing applied, the published numbers directly report quantities.
Indexing Type: No indexing applied, the published numbers directly report quantities.
Geographies: National, State, Country, Metro
Note that testing counts and rates are only available at the national and state level, not at the
county or metro levels.
Breakdowns:

• New Cases, Deaths, or Tests (presented as a 7-day moving average)
• Total Cases, Deaths, or Tests

2.10 Time Outside Home

Summary: Time spent away from home, estimated using cellphone location data from Google
users who have enabled the Location History setting.
Data Source: Google COVID-19 Community Mobility Reports, American Time Use Survey
Update Frequency: When released by Google, typically every 4-7 days.
Date Range: February 24th until the most recent date available.
Data Frequency: Daily
Indexing Period: January 3rd to February 5th
Indexing Type: Change relative to the January 2020 index period, not seasonally adjusted.
Geographies: National, State, County, Metro
Breakdowns:

• Time Away From Home
• Retail and Restaurants
• Transit
• Parks
• Grocery
• Workplace

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Notes: Google does not release data for geographies where their internal quality and privacy
thresholds are not met. Therefore some geographic areas are omitted from the series for certain
finer breakdowns while the release of others can be delayed while under review. When data
is missing for 1 or 2 consecutive days we linearly interpolate the missing values and construct
the 7 day moving average including these interpolated values. If data is missing for 3 or more
consecutive days, the corresponding 7 day moving average is also recorded as missing whenever
it overlaps with the missing data.
Time Away From Home is calculated by multiplying the mean time spent inside home from the
American Time Use Survey by the percent change in time spent at residential locations reported
by Google. For more information about this imputation, see the accompanying paper.

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