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Collecting the dataset
1: The list will be updated once per year with new companies.
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Identifying startups and vetting the data
Approximately 5.300 startups were identified from the following sources:
Definition of a startup: A startup is defined as a company with a scalable and innovative product or service, pursuing rapid and global expansion. Additionally, it includes ventures that have secured venture capital investments.
The list of startups includes also startup companies that were definitely startups before, but have already grown to a large size. In the analyzes we can slice the data by for example analyzing only young startups or startups with a revenue less than certain threshold.
Validating the data: Data validation involved researching most of the identified startups through online searches and assessing their business model based on available website information.
Caveats in the data: Since we started compiling data only recently, it's likely that some short-lived startups, for example those from the early 2010s, may have been overlooked. The dataset may also overstate growth rates, as it includes surviving startups while excluding those that failed. However, failed startups are typically smaller in scale, thus minimally impacting metrics such as employment or turnover data.
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Linking startups to registry data
Finnish Startup Community sent a list of 2.767 business IDs of startups to Statistics Finland. These were linked to Statistics Finland's research database without endangering the anonymity of individuals or businesses.
In the registry datasets, each business and individual person have pseudonymized identification numbers (IDs from here on) and only Statistics Finland has keys to transform these IDs to real business ids and personal identification numbers.
ID numbers enables researchers to merge different datasets together. For example the financial statements can be merged with employment relationships data which makes it possible to identify which individuals are working in startups.
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Enterprise Warehouse Data
The first registry data we are analyzing is the so called Enterprise Warehouse Data (Firm_enter) that covers all enterprises, corporations and private practitioners of trade with value added tax liability or that have paid employees.
Enterprises which have been active for more than half a year in the reference year and employed more than one-half of a person or whose balance sheet exceeds 170 000 euros or had a turnover in excess of an annually specified limit for statistics compilation (EUR 11 376 in 2017) are selected into the statistics.
Industry A (agriculture, forestry and fishing) include farms whose income from agriculture in the statistical year has exceeded the yearly defined limit for statistics compilation. The only comprehensive data provided by agriculture are personnel data. Industry 02 includes units whose revenue from forestry exceeds the limit for statistics compilation. In regards to financial and insurance activities (Sectors 64, 65, 66), only the number of enterprises and personnel data are published.
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From the 2.767 business IDs sent to Statistics Finland, 2.683 were identified from the Enterprise Warehouse research data.
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Number of startups increasing
Source Enterprise Data Warehouse (Firm_enter) & startup list (validated at Q1 of 2024)
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Number of new startups in the dataset
Source: Enterprise Data Warehouse & startup list (validated at Q1 of 2024)
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Revenue in startups is growing fast
Sources: Enterprise Data Warehouse (Firm_enter) & startup list (validated at Q1 of 2024)
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Full-time employees in startups is at record levels
Sources: Enterprise Data Warehouse (Firm_enter) & startup list (validated at Q1 of 2024)
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Which individuals are employed in startups?
Using the list of startups that were identified in previous analysis and Statistics Finland employment data (FOLK employment) we are able to identify which persons have had an employment relationship with a startup company during a specific year.
The employment data module contains data on person's employment. Data on employment are both for the person's employment relationship during the last week of the year (TVM) and for the longest employment relationship of the year (ATV). The dataset is available since 1987.
Dataset includes information about each person's employment including the business IDs of employer. Using the business IDs that were identified in the Statistics Finland enterprise registry we can collect the identification numbers from the employment registry.
Employment data was used from years 2013 until the latest year available, which was 2020 when this analysis was done.
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28%
Of the startup workforce are females in 2020
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21%
Of the startup workforce are immigrants in 2021
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Different growth stages
Let’s categorize startups to different groups based on their total revenue.
Early Stage: Revenue less than or equal to 1 million euros per year
Scaleup: Startups has revenue more than 1 million euros but less than 10 million euros per year.
Grownup: if startup has a revenue more than 10 million euros
By dividing startups in different growth stages, we can analyse how the growth stage of a company affects the way
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Share of women across different growth stages over time
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Share of immigrants across different growth stages over time
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Employment levels increasing faster in younger startups
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Startups employ highly skilled workers in Finland
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