CREAT: Census Research Exploration and Analysis Tool

Technifying Ventures

July 2025

Working Paper Number:

CES-25-49

Abstract

How do advanced technology adoption and venture capital (VC) funding impact employment and growth? An analysis of data from the US Census Bureau suggests that while both advanced technology use and VC funding matter on their own for firm outcomes, their joint presence is most strongly correlated with higher employment levels. VC presence is linked with a high increase in employment, though primarily among a limited subset of firms. In contrast, technology adoption is associated with a smaller rise in employment, yet it influences a considerably larger number of firms. A model of startups is created, focusing on decisions to use advanced technology and seek VC funding. The model is compared with firm-level data on employment, advanced technology use, and VC investment. Several thought experiments are conducted using the model. Some experiments assess the importance of advanced technology and VC in the economy. Others examine the reallocation effects across firms with different technology choices and funding sources in response to shifts in taxes and subsidies.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
investment, enterprise, technological, acquisition, entrepreneurial, venture, entrepreneur, entrepreneurship, investor, innovation, patent, technology adoption, economically, revenue, founder

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
:
Total Factor Productivity, Survey of Manufacturing Technology, IBM, Longitudinal Business Database, Initial Public Offering, Economic Census, North American Industry Classification System, Census Bureau Disclosure Review Board, Business Dynamics Statistics, Census Bureau Business Dynamics Statistics, National Center for Science and Engineering Statistics, Annual Business Survey

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