Complete set of loan-level data on the recipients of Paycheck Protection Program loans

An aggregated dataset of PPP (Paycheck Protection Program) SBA (Small Business Administration) loans involving 3 million businesses would be a comprehensive collection of financial information, aimed at analyzing the distribution and impact of these loans. This dataset would include key details such as the names of the businesses, loan amounts, loan disbursement dates, and the terms of the loans. Additionally, the dataset would contain information on board members of these businesses, providing insights into the governance structures and potential networks influencing the flow of SBA funds. This aspect of the dataset can be crucial for understanding the distribution patterns of PPP loans, identifying trends in funding allocation among different types of businesses, and examining any correlations between board composition and loan receipt. Such a dataset would be valuable for various analyses, including: Financial Analysis: Assessing the financial health and stability of businesses that received PPP loans, and understanding how these loans have impacted their operations during challenging economic times. Governance Analysis: Evaluating the role of board members in acquiring PPP loans, and whether certain types of governance structures were more successful in securing funds. Economic Impact Assessment: Measuring the broader economic impact of the PPP loans, such as job retention, business survival rates, and sector-wise distribution of funds. Network Analysis: Mapping the connections between different businesses and their board members to identify any potential networks or clusters that may have influenced the flow of funds. Policy Evaluation: Providing data-driven insights to policymakers for assessing the effectiveness of the PPP program and for planning future economic relief measures.

This dataset is published by the Atlanta Regional Commission Research & Analytics group to show Paycheck Protection Program Loans for Georgia summarized by ZIP Code. Source: US Department of Treasuryhttps://home.treasury.gov/policy-issues/cares-act/assistance-for-small-businesses/sba-paycheck-protection-program-loan-level-data

The Paycheck Protection Program (PPP) loans provide small businesses with the resources they need to maintain their payroll, hire back employees who may have been laid off, and cover applicable overhead. This data set includes businesses in Connecticut that received PPP funding, how much funding the employer received & how many jobs the employer claims they saved. The NAICS (National Industry Classification) was provided by the loan recipient. This dataset includes loans under $150,000 and loans of $150,000 and above made to Connecticut businesses through August 8, 2020. Please see attached document for more details.

This dataset provides values for GDP PER CAPITA PPP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The average for 2024 based on 177 countries was 27291 U.S. dollars. The highest value was in Singapore: 132570 U.S. dollars and the lowest value was in Burundi: 836 U.S. dollars. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.

Paycheck Protection Program loans are SBA loans that helps businesses keep their workforce employed during the Coronavirus (COVID-19) crisis, specific to Colorado. Includes < $150,000 loans and > $150,000 loans. Current law dictates that the Paycheck Protection Program (PPP) close at the end of August 8, 2020.

Russia had the highest GDP per capita based on purchasing-power-parity (PPP) among the presented Eurasian countries between 2010 and 2023 and was forecast to remain in the leading position in the following years. However, Kazakhstan was predicted to close the gap with Russia slowly by 2029. What are the largest economies in Eurasia? At an estimated *** trillion U.S. dollars, Russia had the largest GDP among the Eurasian countries in 2024. The country generated most of its wealth through its energy sector, given that a high percentage of its industrial and agricultural sectors was privatized in the 1990s. Ranking second and third were Kazakhstan and Ukraine, whose GDP amounted to approximately *** billion U.S. dollars and *** billion U.S. dollars, respectively. Looking at national debt, Ukraine demonstrated the highest ratio to GDP, at over ** percent in 2024. Despite exhibiting the second-lowest figure in the region, Russia’s national debt was forecast to increase in the years until 2029. Inflation in Eurasia The highest inflation rate in Eurasia was recorded in Uzbekistan, at around ** percent in 2024. It was followed by Kazakhstan and Russia, where consumer prices were estimated to grow by approximately *** percent and *** percent relative to the previous year, respectively. As of January 2024, monthly expenses on the basic food basket occupied around ** percent of the official minimum wage in Moldova. At the same time, in Uzbekistan, the minimum wage was just enough to cover basic food expenses.

The average for 2024 based on 37 countries was 55142 U.S. dollars. The highest value was in Luxembourg: 128182 U.S. dollars and the lowest value was in Colombia: 18504 U.S. dollars. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.

This dataset features PPP loan data distributed across the City of Los Angeles as of January 25, 2022. Data comes from SBA.gov.

This dataset provides values for GDP PER CAPITA PPP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_GDP_-PPP-. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

This dataset is extracted from https://en.wikipedia.org/wiki/List_of_regions_by_past_GDP_-PPP-. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_past_and_projected_GDP_-PPP-. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

The extract lists Paycheck Protection Program (PPP) loans across North Carolina from April through August 2020. The data is based on information submitted by lenders to the Small Businesses Administration (SBA). Data is available for the aforementioned period in two separate categories of loans: those under and above $150,000. The temporal resolution is daily and the spatial resolution is at the zip code level.

The Paycheck Protection Program (PPP) loans provide small businesses with the resources they need to maintain their payroll, hire back employees who may have been laid off, and cover applicable overhead. This data set includes businesses in New Jersey who received PPP funding, how much funding the employer received & how many jobs the employer claims they saved. The NAICS (National Industry Classification) was provided by the loan recipient.

Note: As per SBA, The Paycheck Protection Program (PPP) ended on May 31, 2021 so no updates has been made on this dataset.

Please see attached document on landing page for more details.

This dataset provides values for GDP PER CAPITA PPP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This Excel file provides detailed crosswalks from the EU Table of Contents (SANCO/10181/2013) for plant protection product (PPP) dossiers to IUCLID 6 v8. It includes two spreadsheets, containing the mappings for active substance (as laid out in Commission Regulation (EU) No 283/2013) and representative product (Commission Regulation (EU) No 284/2013):

• EU_PPP_ActiveSubstance: mapping between the "KCA" ToC and IUCLID 6 v8 working context "EU PPP Active substance information"
• EU_PPP_Product: mapping between the "KCP" ToC and IUCLID 6 v8 working context "EU PPP Active substance application (product)"

The spreadsheets map each section of the original EU ToC to:

• IUCLID section: name of the section in IUCLID where to input the corresponding data/information
• Endpoint study record: name of the document template used to report individual studies of the section (if exists). These usually correspond to OECD Harmonised Templates (OHT).
• Endpoint summary: name of the document template used to report the summary information of the studies presented in the section (if available)
• Other IUCLID document: name of any other document template in IUCLID used to report information of the section (if available)
• OHT: name/id of the OECD Harmonised Template used for the endpoint study record document (if available)
• Additional context: fulI IUCLID paths indicating the section of the respective document where information needs to be provided and/or specific values to be indicated. If more than one path is provided, these are separated by ";". Operators "=" and "!=" are used to indicate values to be used and to be avoided, respectively. When more than one value is possible, "IN" and "NOT IN" operators are used, followed by the exhaustive list of possible values. This nomenclature was defined with the aim of making contents machine-readable.

Version 5 includes changes in the table of contents of IUCLID 6 v8.

This dataset provides values for GDP PPP CURRENT INTERNATIONAL DOLLAR WB DATA.HTML. reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The average for 2024 based on 52 countries was 6829 U.S. dollars. The highest value was in the Seychelles: 29242 U.S. dollars and the lowest value was in Burundi: 836 U.S. dollars. The indicator is available from 1990 to 2024. Below is a chart for all countries where data are available.