In March 2020, Mayor Carter announced the Saint Paul Bridge Fund to provide emergency relief for families and small businesses most vulnerable to the economic impacts of the COVID-19 pandemic. The program was funded through $3.25 million dollars from the Saint Paul Housing and Redevelopment Authority along with contributions from philanthropic, corporate and individual donors. Through these additional contributions, the fund provided $4.1 million to families and small businesses in Saint Paul.Data previously shared in this space included only the 380 recipients funded through "Phase 1". This dataset includes all three phases that were ultimately rolled out through the Bridge Fund for Small Business program.Nearly 2,000 unique applications applied for a small business grant of $7,50036% were from ACP50 areas (Areas of Concentrated Poverty where 50% or more of the residents are people of color)The applications were reviewed in order of a random number assigned at application close. Of these applications:633 small businesses were awarded a $7,500 grant36% of applications in the city were from ACP50 areas86% of applicants in the city cited they were ordered closed under one of the Governor’s Executive OrdersThis is a dataset of the small businesses that applied for the Bridge Fund and includes:Self-reported survey responsesAward informationGeographic information Additional information about the Saint Paul Bridge Fund may be found at stpaul.gov/bridge-fund.

US Covid-19 Cases, Deaths and Mobility by State/County

Analyzing the Impact of the Pandemic on Low-Income Populations

By Liz Friedman [source]

About this dataset

Welcome to the Opportunity Insights Economic Tracker! Our goal is to provide a comprehensive, real-time look into how COVID-19 and stabilization policies are affecting the US economy. To do this, we have compiled a wide array of data points on spending and employment, gathered from several sources.

This dataset includes daily/weekly/monthly information at the state/county/city level for eight types of data: Google Mobility; Low-Income Employment and Earnings; UI Claims; Womply Merchants and Revenue; as well as weekly Math Learning from Zearn. Additionally, three files- Accounting for Geoids-State/County/City provide crosswalks between geographic areas that can be merged with other files having shared geographical levels.

Our goal here is to enable data users around the world to follow economic conditions in the US during this tumultuous period with maximum clarity and precision. We make all our datasets freely available so if you use them we kindly ask you attribute our work by linking or citing both our accompanying paper as well as this Economic Tracker at https://tracktherecoveryorg By doing so you are also agreeing to uphold our privacy & integrity standards which commit us both to individual & business confidentiality without compromising on independent nonpartisan research & policy analysis!

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How to use the dataset

This dataset provides US COVID-19 case and death data, as well as Google Community Mobility Reports, on the state/county level. Here is how to use this dataset:

• Understand the file structure: This dataset consists of three main files: 1) US Cases & Deaths by State/County, 2) Google Community Mobility Reports, and 3) Data from third-parties providing small business openings & revenue information and unemployment insurance claim data (Low Inc Earnings & Employment, UI Claims and Womply Merchants & Revenue).
• Select your Subset: If you are interested in particular types of data (e.g., mobility or employment), select the corresponding files from within each section based on your geographic area of interest – national, state or county level – as indicated in each filename.
• Review metadata variables: Become familiar with the provided variables so that you can select which ones you need to explore further in your analysis. For example, if analyzing mobility trends at a city level look for columns such as ‘Retailer_and_recreation_percent_change’ or ‘Transit Stations Percent Change’; if focusing on employment decline look for columns such pay or emp figures that align with industries of interest to you such as low-income earners (emp_{inclow},pay_{inclow}).
• Unify dateformatting across row values : Convert date formats into one common unit so that all entries have consistent formatting if necessary; for exampe some entries may display dates using YYYY/MM/DD notation while others may use MM//DD//YY format depending on their source datasets; make sure to review column labels carefully before converting units where needed..

• Merge datasets where applicable : Utilize GeoID crosswalks to combine multiple sets with same geographical coverageregionally covering ; example might be combining low income earnings figures with specific county settings by reference geo codes found in related documents like GeoIDs-County .
  6 . Visualise Data : Now that all the different measures have been reviewed can begin generating charts visualize findings . This process may include cleaning up raw figures normalizing across currency formats , mapping geospatial locations others ; once ready create bar graphs line charts maps other visual according aggregate output desired Insightful representations at this stage will help inform concrete policy decisions during outbreak recovery period..

  Remember to cite

Research Ideas

• Estimating the Impact of the COVID-19 Pandemic on Small Businesses - By comparing county-level Womply revenue and employment data with pre-COVID data, policymakers can gain an understanding of the economic impact that COVID has had on local small businesses.
• Analyzing Effects of Mobility Restrictions - The Google Mobility data provides insight into geographic areas where...

Local authorities have received and distributed funding to support small and medium businesses in England during coronavirus. The datasets cover schemes managed by local authorities: Additional Restrictions Support Grant (ARG) Restart Grant - closed June 2021 Local Restrictions Support Grants (LRSG) and Christmas support payments - closed 2021 Small Business Grants Fund (SBGF) - closed August 2020 Retail, Hospitality and Leisure Business Grants Fund (RHLGF) - closed August 2020 Local Authority Discretionary Grants Fund (LADGF) - closed August 2020 The spreadsheets show the total amount of money that each local authority in England: received from central government distributed to SMEs 20 December 2021 update We have published the latest estimates by local authorities for payments made under this grant programme: Additional Restrictions Grants (up to and including 28 November 2021) The number of grants paid out is not necessarily the same as the number of businesses paid. The data has not received full verification.

This dataset includes anonymized information about all of CSBDF's closed loans that were utilized in the lending economic impact analysis for FY21 (July 1, 2020 through June 30, 2021). The data contain anonymized information on all lending transactions during the period, including the socioeconomic characteristics of the recipient small businesses and their owner(s).

The Paycheck Protection Program (PPP) is a nearly $1 trillion business loan program started in 2020 under the Trump administration to provide relief to businesses struggling due to the Coronavirus epidemic.

This program that was managed by the Small Business Administration (SBA) offers loans to companies based on current payroll expense. The exact amount a business qualifies for depends on a number of factors including corporate structure, but generally follows the guidelines below:

Average monthly payroll (using a maximum annual salary per employee of $100,000) * 2.5

in 2020, a judge ordered the SBA to release all data on PPP loans, even those loans made for less than $150,000.

This dataset represents only businesses who received loans of more than $150,000, and presents an interesting opportunity for researchers in the data science community. Some potential projects are listed below: - Exploring loan amounts industries and business types - Using this data as features to predict business metrics such as company size, revenue, risk of bankruptcy. - Tracking important demographic statistics related to loan amounts and any potential bias in the program.

This dataset consolidates public U.S. Small Business Administration (SBA) Economic Injury Disaster Loan (EIDL) data released during the COVID-19 pandemic.

It contains loan-level records issued between April and November 2020, documenting the scale and timing of emergency relief for small businesses across all U.S. states and territories.

The files were retrieved from the SBA’s open-data portal and standardized for analysis in Python (Pandas) and visualization in Tableau.

Fields include: • Loan amount (face value or obligation) • Approval date • State of recipient • Recipient identifier

Analytical use: This data supports exploration of post-COVID economic recovery patterns, showing how federal loan programs helped stabilize small businesses by region and time period.

Source: U.S. Small Business Administration Open Data

Last updated: November 2020

Prepared by: Christopher White (@cwhiteprofessional)

License: U.S. Government Works — This dataset is derived from public SBA data and is not subject to copyright protection under 17 U.S.C. §105. It may be freely reused and shared.

Data on the number and value of grants to small and medium sized businesses (SMEs) in response to the coronavirus pandemic. The spreadsheet shows the total amount of money that each local authority and parliamentary constituency in England has: received from central government distributed to SMEs as at 5 July 2020 31 July 2021: coronavirus grant schemes Local Restrictions Support Grant (LRSG): (Open) Local Restrictions Support Grant (LRSG): (Closed) Additional Restrictions Grant (ARG) - scheme open until 31 March 2022. A final update will be released afterwards Christmas Support Payment (CSP) Restart 5 July 2020: coronavirus grant schemes: Small Business Grants Fund (SBGF) scheme Retail, Hospitality and Leisure Business Grants Fund (RHLGF) Local Authority Discretionary Grant Fund (LADGF)

Business Needs Survey 2022 – Impact of the Covid-19 pandemic on the needs of businesses in the City. The City conducted the 2020 Business Needs Survey following the first lockdown initiated in response to Covid-19. The survey aimed to provide insight into the needs of small business operators to determine the best approach in supporting them to remain economically viable. The City has conducted 2021 and 2022 Covid-19 Business Needs Surveys. The responses document how organisations, industry sectors and members were impacted by the pandemic immediately before the 2021 four-month lockdown. See previous surveys

This dataset includes small business loans or grants issued for emergency COVID-19 financial assistance. Underlying data is provided by the Department of Small Business Services (SBS). Dollar amounts are in actual dollars.

The Paycheck Protection Program (PPP) established by the CARES Act, is implemented by the Small Business Administration (SBA) with support from the Department of the Treasury. The program provided small businesses with funds to pay up to 8 weeks of payroll costs including benefits. Funds could also be used to pay interest on mortgages, rent, and utilities This dataset details New York State recipients of PPP funds.

The datasets come from two surveys of Jamaican businesses conducted between May and June 2020. Two sets of self-administered surveys were conducted using Survey Monkey. A very small sample of financial institutions was surveyed to gain perspective on the challenges facing financiers as a result of the pandemic, and their efforts to respond to such challenges. Nine financial institutions completed this survey, and the results were used to complement the information derived from the second and major survey. The second survey targeted non-financial businesses operating in Jamaica. The sample of firms was selected from a list of all registered Jamaican firms, obtained from the Companies Office of Jamaica. A stratified random sample was used based on firm type, region, and sector. Some firms may have also participated in the study through contact made by their respective affiliations, which were approached to endorse the study and encourage their members to engage. A total of 390 firms completed the second survey. A significant degree of representation was achieved across size, type and age of business, sector and location of operation. Good gender representation was also achieved.

The Paycheck Protection Program (PPP) is a $953-billion business loan program established by the United States federal government, led by the Donald Trump administration in 2020 through the Coronavirus Aid, Relief, and Economic Security Act (CARES Act) to help certain businesses, self-employed workers, sole proprietors, certain non-profit organizations, and tribal businesses continue paying their workers.

The Paycheck Protection Program allows entities to apply for low-interest private loans to pay for their payroll and certain other costs. The amount of a PPP loan is approximately equal to 2.5 times the applicant's average monthly payroll costs. In some cases, an applicant may receive a second draw typically equal to the first. The loan proceeds may be used to cover payroll costs, rent, interest, and utilities. The loan may be partially or fully forgiven if the business keeps its employee counts and employee wages stable. The program is implemented by the U.S. Small Business Administration. The deadline to apply for a PPP loan was March 31, 2021.

Some economists have found that the PPP did not save as many jobs as purported and aided too many businesses that were not at risk of going under. They noted that other programs, such as unemployment insurance, food assistance, and aid to state and local governments, would have been more efficient at strengthening the economy. Opponents to this view note that the PPP functioned well to prevent business closures and cannot be measured on the number of jobs saved alone.

According to a 2022 study, the PPP: cumulatively preserved between 2 and 3 million job-years of employment over 14 months at a cost of $169K to $258K per job-year retained. These numbers imply that only 23 to 34 percent of PPP dollars went directly to workers who would otherwise have lost jobs; the balance flowed to business owners and shareholders, including creditors and suppliers of PPP-receiving firms. Program incidence was ultimately highly regressive, with about three-quarters of PPP funds accruing to the top quintile of households. PPP's breakneck scale-up, its high cost per job saved, and its regressive incidence have a common origin: PPP was essentially untargeted because the United States lacked the administrative infrastructure to do otherwise. Harnessing modern administrative systems, other high-income countries were able to better target pandemic business aid to firms in financial distress. Building similar capacity in the U.S. would enable improved targeting when the next pandemic or other large-scale economic emergency inevitably arises.

Additional Information Field: Value Created: April 5, 2022 Format: CSV License: Other (Public Domain) Size: 428.6 MiB

SB: AZ: COVID-19 Impact: Moderate Negative Effect data was reported at 42.100 % in 11 Apr 2022. This records an increase from the previous number of 38.300 % for 04 Apr 2022. SB: AZ: COVID-19 Impact: Moderate Negative Effect data is updated weekly, averaging 43.200 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 45.600 % in 14 Mar 2022 and a record low of 36.000 % in 22 Nov 2021. SB: AZ: COVID-19 Impact: Moderate Negative Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).

SB: AZ: COVID-19 Impact: Moderate Positive Effect data was reported at 5.700 % in 11 Apr 2022. This records a decrease from the previous number of 8.400 % for 04 Apr 2022. SB: AZ: COVID-19 Impact: Moderate Positive Effect data is updated weekly, averaging 8.000 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 10.100 % in 22 Nov 2021 and a record low of 5.700 % in 11 Apr 2022. SB: AZ: COVID-19 Impact: Moderate Positive Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).

This dataset includes small business loans or grants issued for emergency COVID-19 financial assistance. Underlying data is provided by the Department of Small Business Services (SBS). Dollar amounts are in actual dollars. This dataset will be refreshed on a quarterly basis.

Context

The Paycheck Protection Program (PPP) was passed by congress to give relief to businesses negatively impacted by Covid-19 in order to maintain pay for employees. The program gives forgivable loans to businesses that continue paying employees during the pandemic. The PPP quickly ran out of funds, limiting which businesses received relief. Some controversy around the program arose from large, publicly traded companies applying for and receiving PPP funds while many small businesses were unable to access relief.

Content

This dataset released by the treasury department on July 6 shows all loans above $150K given through the Paycheck Protection Program.

Acknowledgements

This dataset was posted by GovTrades, a mission-oriented organization working to increase transparency and accountability in policymaking. Check out GovTrades.org for data on stocks that elected officials buy and sell.

The number of community banks in the United States has fallen from more than 13,000 in the mid-1980s to less than 5,000 today. These community-focused banks have consolidated mainly as a result of competitive pressures. Research shows that community banks are essential to maintaining economically fruitful communities, and losing these banks could be a significant blow to local infrastructure.

One example of the importance of community banks was their role in distributing Paycheck Protection Program (PPP)1 loans during the Covid-19 pandemic. The PPP was designed to help small businesses keep their workers employed during the pandemic by providing funds through a short-term loan backed by the Small Business Administration (SBA). Preliminary research by CSBS shows that state-chartered banks were the primary distributor of PPP loans, and that community banks played an outsized role in the distribution of PPP funds.

CSBS is providing complete loan-level PPP data [available here (full file, 300MB), here (sample data) and here (data definitions)] that combines the publicly available files made available on sba.gov. To allow for analysis on depository institutions, CSBS will also be adding FDIC Certificate numbers to this file. When the institution is a bank, the FDIC Certificate number will allow participants to link the PPP data to the quarterly Call Report of Income and Condition, which can be accessed here. CSBS is also providing a sample dataset that can be updated and examined in Excel. Questions regarding the data can be sent to data@csbs.org. CERT number is based on originating lender, not servicing lender. Field Name Field Description LoanNumber Loan Number (unique identifier) DateApproved Loan Funded Date SBAOfficeCode SBA Origination Office Code ProcessingMethod Loan Delivery Method (PPP for first draw; PPS for second draw) BorrowerName Borrower Name BorrowerAddress Borrower Street Address BorrowerCity Borrower City BorrowerState Borrower State BorrowerZip Borrower Zip Code LoanStatusDate Loan Status Date - Loan Status Date is blank when the loan is disbursed but not Paid In Full or Charged Off LoanStatus Loan Status Description - Loan Status is replaced by 'Exemption 4' when the loan is disbursed but not Paid in Full or Charged Off Term Loan Maturity in Months SBAGuarantyPercentage SBA Guaranty Percentage InitialApprovalAmount Loan Approval Amount (at origination) CurrentApprovalAmount Loan Approval Amount (current) UndisbursedAmount Undisbursed Amount FranchiseName Franchise Name ServicingLenderLocationID Lender Location ID (unique identifier) ServicingLenderName Servicing Lender Name ServicingLenderAddress Servicing Lender Street Address ServicingLenderCity Servicing Lender City ServicingLenderState Servicing Lender State ServicingLenderZip Servicing Lender Zip Code RuralUrbanIndicator Rural or Urban Indicator (R/U) HubzoneIndicator Hubzone Indicator (Y/N) LMIIndicator LMI Indicator (Y/N) BusinessAgeDescription Business Age Description ProjectCity Project City ProjectCountyName Project County Name ProjectState Project State ProjectZip Project Zip Code CD Project Congressional District JobsReported Number of Employees NAICSCode NAICS 6 digit code Race Borrower Race Description Ethnicity Borrower Ethnicity Description UTILITIES_PROCEED Note: Proceed data is lender reported at origination. On the PPP application the proceeds fields were check boxes. PAYROLL_PROCEED MORTGAGE_INTEREST_PROCEED RENT_PROCEED REFINANCE_EIDL_PROCEED HEALTH_CARE_PROCEED DEBT_INTEREST_PROCEED BusinessType Business Type Description OriginatingLenderLocationID Originating Lender ID (unique identifier) OriginatingLender Originating Lender Name OriginatingLenderCity Originating Lender City OriginatingLenderState Originating Lender State Gender Gender Indicator Veteran Veteran Indicator NonProfit 'Yes' if Business Type = Nonprofit Organization or Nonprofit Childcare Center or 501(c) Nonprofit ForgivenessAmount Forgiveness Amount ForgivenessDate Forgiveness Paid Date CERT Community Bank Flag State vs. National Charter

Source - https://www.csbs.org/

United States SBP: WT: COVID-19 Impact: Little or Number Effect data was reported at 15.800 % in 04 Oct 2020. This records an increase from the previous number of 15.000 % for 27 Sep 2020. United States SBP: WT: COVID-19 Impact: Little or Number Effect data is updated weekly, averaging 12.300 % from Apr 2020 (Median) to 04 Oct 2020, with 18 observations. The data reached an all-time high of 16.000 % in 13 Sep 2020 and a record low of 7.700 % in 26 Apr 2020. United States SBP: WT: COVID-19 Impact: Little or Number Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S036: Small Business Pulse Survey: by Sector: Weekly, Beg Sunday (Discontinued).

This dataset contains payment amounts for first and second applications and the items that were reimbursed through the Small Business Hardship Scheme that operated during 2021-2022 as part of ACT Government COVID-19 response.

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