*** Authors: J.A. Slootweg ***

Supervisors : Prof. dr. J.H. Slinger, Dr. S.T.H. Storm 
TU Delft, Faculty of Technology, Policy and Management, Department of Values, Technology and Innovation

***General Introduction*** This dataset contains DGGF data used for the Master Thesis “Impacting SDG 8 in Developing Countries Through the use of Blended Finance”  (July 2022): http://resolver.tudelft.nl/uuid:6919bb25-bf6e-4552-8de8-750e72c3385b
 It is being made public both to act as supplementary data for publications and the Master Thesis thesis of Alexander Slootweg and in order for other researchers to use this data in their own work. 
The data in this data set was contains Investment data from the year 2015-2021 for the DGGF fund, and was obtained via Invest International
***Purpose of the data***
 The data was used to analyse a number of hypotheses through t-tests
***Description of the data in this data set*** The data included in this data set has been organised per anonymised company, it is an Excel spreadsheet in a table for filtering the data with both numerical and monetary data

Country: Country in which the company is located

Country Classification: World Bank income group classification of the country

Sector: Sector of the Company operations

Financing type: The type of financing a company received, either a loan or a loan guarantee

Before intervention employees: Number of employees before investment

M: Male

F: Female

Employees target: The amount of employees targeted at the end of the investment

Employees realised as of 31-12-2021: Number of employees at that data

Jobs created: difference between employees before intervention and at 31-12-2021

Difference with target: difference between employees at 31-12-2021 and employees targeted

Outgrowers: Indirect job creation, again target, realisation and difference

Trained outgrows: Indirect jobs trained, again target, realisation and difference, less relevant for research
Total job creation: Number of jobs created in total, direct and indirect

Total investment: total size of investment in the company

Expected jobs per million per year: Direct jobs created per million invested, per year of project runtime and multiplied by the reverse probability of default of the company in jobs/euros/year

Start year: Start year of investment in year

End year, either 2021 for active investments or year in which the investment ended in year 

Project duration: Total runtime for project in years

Risk rating start: Risk rating of company at start of investment

Rev% start: Reverse probability of default at start of investment in %

Risk rating as of 2021: Risk rating currently

Rev%final: Reverse probability of default currently for active investments at end of investment for completed projects
Absolute risk difference: difference between start and end risk absolute value in %

Relative risk rating change per year: risk rating chance absolute difference divided by project runtime in %/year

Jobs created per million per year: Jobs created per million euros invested divided by runtime in jobs/millioneuros/year

*** Other Sheets***
All other sheets are results of two sample t-test, assuming unequal variances and a mean difference of 0 at 95% confidence
