Measuring Entrepreneurship (Blog Post)

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Blog Post
Title Measuring Entrepreneurship (Blog Post)
Author Dylan Dickens
Series Entrepreneurship 101
Content status Tabled
Publication date
©, 2016


Short blog post examining the current measurable determinants, and some of the potential issues in measuring, entrepreneurship.


Starting with the formal definitions of early 18th century Irish economist Richard Cantillon, the word "entrepreneur" has existed in the economic lexicon for literal centuries now(1) . Regardless of its long-standing theoretical history with economics, only in more recent years has a more quantitative and empirical definition of the term been sought(2). Due to its wide reaching consequences convoluted internal mechanisms, and array of sources, the very nature of entrepreneurship defies detailed empirical definition. While not necessarily a huge problem in strictly economic terms, this poses a massive problem in a large and ever-increasing field related to entrepreneurship: policy.

Researchers from the Organisation for Economic Co-operation and Development outline the issue as follows, "Where there are policy references to entrepreneurship, most simply equate it with small and medium sized enterprises in general, or even numbers of self-employed. Neither of which fully captures the totality of entrepreneurship(3)," They further elaborate that the lack of predefined empirical entrepreneurship indicators compounds the general ambiguity of entrepreneurship when discussed in policy arenas. This ambiguity was the spark for an array of research on a pressing question, what is entrepreneurship in a measurable policy-friendly sense?

The OECD aims to define entrepreneurship through a wide array of indicators, wisely demonstrating that no one single factor can accurately measure and compare entrepreneurship across various nations. The six core indicators used are employer enterprise births, rate of high-growth firms based on employment growth, rate of high-growth firms based on turnover growth, Gazelle rates based on employment, Gazelle rates based on turnover, and employer enterprise deaths. The logic behind these indicators revolves around the nature of entrepreneurship to birth firms, employ many individuals, lead to the turnover of many individuals in the sector, generate high-growth firms, or Gazelles, which hire and fire many individuals, and the nature of entrepreneurship to fail. While these indicators are in no means exhaustive, as admitted by the Organisation for Economic Co-operation and Development itself, there are other interesting prospects for measurement which have been suggested. Academics from the Research Institute of Industrial Economics in Stockholm, Sweden, purport that by measuring self-made billionaires who became wealthy by founding new firms(4). Their results, in a study of 996 billionaires across 50 nations over 14 years yielded some interesting results. Predictably, countries with higher income, higher trust, lower taxes, more venture capital investment and lower regulatory burdens had higher entrepreneurship rates as measured by self-made billionaires. This high entrepreneurship high billionaire nations scored lower however on seemingly related measures such as self-employment, small business ownership and firm startup rates.

The above research shows that while much work has been done on the empirical measures of entrepreneurship, there still remains an ambiguity that could be problematic in policy crafting. Perhaps the lesson to be drawn is one of understanding, that while it is understandable for policy makers to desire succinct, empirical, indicators to generate entrepreneurship goals around, the data is often times more convoluted and ambiguous than any stakeholder would like. Perhaps with this understanding, and further support into the research on entrepreneurship, a more empirically backed and beneficial future can be generated for all.

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