If getting things done requires too many steps, there will be fewer entrepreneurs. That seems to be something of a consensus in the economics and social science literature regarding conceptual linkages between regulation and entrepreneurship.
This all has lessons for public policy. As the World Bank stated in its well-known and wide-ranging annual Doing Business survey, “[Hernando] de Soto’s conjecture, which turned out to be right, was that measuring and reporting would create pressure for improvements in the efficiency of government.”
The Doing Business report ranks nations on business climate with respect to “regulation that affects small and medium-size enterprises, operating in the largest business city of an economy.” The report also presents “quantitative indicators on the regulations that apply to firms at different stages of their life cycle” (The report “relies on four main sources of information: the relevant laws and regulations, Doing Business [survey] respondents, the governments of the economies covered and the World Bank Group regional staff.”)
Doing Business underscores, on an internationally comparative basis, the dramatic effect the number of steps involved in starting a business can have. There are 11 core quantitative measures of business regulation, among them:
- hurdles in starting a business,
- dealing with construction permits
- Registering property
- Getting credit
- Trading across borders
- Enforcing contracts
- Resolving insolvency
- and labor market regulation
Nations now seek to do better and “compete” with one another on fostering an entrepreneurial environment, and in turn the Doing Business report has become a major tool of researchers studying entrepreneurship. Much of the emphasis has been on the Doing Business-style independent variables like procedures and permitting complexity and economic freedom measures.
There are likewise seemingly endless ways to select and study dependent variables, our measures of proxies for entrepreneurship. The OECD’s Entrepreneurship at a Glance, for example, lists the following indicators (some highly developed in the literature, some less so since, such data is not collected everywhere) “for measuring the state of entrepreneurship”:
- New enterprise creations
- Enterprise exits
- Outlook and prospects of job creation
- Enterprises by size
- Employment by enterprise size
- Value added by enterprise size
- Turnover by enterprise size
- Compensation of employees by enterprise size
- Labor productivity by enterprise size
- Birth rate of enterprises
- Death rate of enterprises
- Survival of enterprises
- Employment creation and destruction by enterprise births and deaths
- High-growth enterprises rate
- Incidents of traders
- Trade concentration
- Exports and imports by enterprise size
- Market proximity
- Exports and imports by enterprise ownership
- Self-employment by gender
- Self-employment among the youth
- Earnings from self-employment
- Inventors by gender
- Perception of entrepreneurial risk
- Venture capital investments
Like the OECD Glance data, one can find related projects attempting to capture entrepreneurial activity (the dependent variable). One example is the United Kingdom’s Office of National Statistics’ “Trends in Self-Employment” report. Others include the Eurostat-OECD entrepreneurship indicator program (EIP) which began in 2007 to “collect internationally comparable statistics to enable the ‘measurement’ of entrepreneurship.” Another is the non-profit World Economic Forum’s Global Competitiveness Report.
Putting “measurement” in quotes makes sense in the EIP or any other program. As regulatory cost measurement is imperfect and in many ways impossible, so too is gauging causality. Researchers generally freely acknowledge limitations (note the appendix compilation in Anna Maria Zárate Moreno’s “Regulation, Innovation & Entrepreneurship,” for example). While startups/births are a major examined variable, correlations that could be proposed and tested as independent variables affecting entrepreneurship indicators on a list like the OECD’s Entrepreneurship at a Glance seem unlimited. Even the OECD’s list of indicators alone exceeds the number of letters in the Alphabet.
Furthermore, the regulation of entrepreneurship proceeds from many fronts: state, province, local, national and international. Once one pulls a thread, there is no stopping, hence the perpetual calls for “future research.” In immersing myself in this topic preparing a chapter for the Fraser Institute’s book Demographics and Entrepreneurship, this became increasingly apparent to me.
Feel like getting busy, or need a dissertation or thesis topic? My list immediately below covers, in no particular order, a sample of potential variables/avenues for future research on linkages between the business/political environment and entrepreneurship:
- Inertia analysis. That is, the speed of permitting/processing matters (consider pharmaceuticals compared to releasing an Android app);
- Stringency of regulatory enforcement; Or, conversely, are there well-developed systems of internalized competitive discipline (or “self regulation”) in a given country?
- Startup rates by sector are something just beginning to be explored; but where exactly within what sectors is there entrepreneurship, and where is there not?
- Some argue government investment plays a positive role in entrepreneurship. But investment can range from the arguable public good necessity special case on the one hand, to nationalization;
- Relatedly, research could examine whether a heavy government contracting sector means the nearby artificially fattened entrepreneurs (some perhaps rent seekers) may be injured less by regulation (say, startups right outside Washington DC, home of some of the richest counties in America);
- Heavy differences in entrepreneurship might also be expected given adjacent complementary or competitive industries, whether or not government has a large presence;
- Certain foreign investment in developing nations, such as that by China in Africa, or large-scale infrastructure interventions such as a consortium potentially operating a fleet of stratospheric Internet balloons, may play measurable roles in entrepreneurship;
- Are certain areas tax havens? That would matter, as would the kinds of firms that can be located in nations (differences in corporate vs proprietorship settings);
- Financial variables’ effect on entrepreneurship are ripe for study after global banking reforms. These might include absolute magnitudes or changes in bank loans (themselves influenced by regulation), and IPOs vs. private placements and other access-to-capital metrics (for example, access to the rise in Kickstarter-like funding campaigns);
- Country household-level metrics like income levels, savings rates, changes in per-capita income and more could get further treatment in explaining entrepreneurship rates today compared to entrepreneurs of the past in a far poorer world;
- Country social metrics like size of the welfare state, dual vs. single income families, percentage of working-age youth living at home, child care and family structure generally, (especially as governments influence these with social policies), number of paid holidays, average retirement age and the like could increasingly figure in cross-country comparisons (I addressed the worrisome the trial balloon of the universal basic income, or UBI, recently elsewhere);
- The influence of emergent global societal developments surrounding the changing nature of work, including workweek flexibility, telecommuting, networking and the sharing economy create interesting challenges for researchers studying entrepreneurship (such as teasing out the differences between part-time work driven by lifestyle and technology changes from regulation-induced reactions). Researchers may find they should distinguish between entrepreneurship that requires hiring full-time vs. part-time vs. the use of contractors as these are increasingly influenced by the transformational capabilities of the networked/Internet economy;
- The spectrum of pre-college education, business-specific education or university entrepreneurship programs, and preponderance of business-school graduates;
- Available national transportation and communications/Internet infrastructure, and the speed of expanding them, navigable waterways, presence of a thriving tourism industry, proximity to cities;
- Local mobility, such as availability of automobiles and other transport;
- As international trade and mobility of goods and services compound, the presence of multinational firms in smaller countries should grow, so measuring human mobility by such metrics as ease of acquiring worker visas may be important.
- Economic crises also seem to have measurable effect, such as OECD’s noting of the smaller average size of new enterprises in 2013 compared to pre-crisis year 2008;
- Electricity access is measured by Doing Business, but also relevant are what in the west were transformational labor-saving devices like washing machines or air conditioning (the invention of which “shaped global productivity, migration, and even politics”);
- Participation in treaties restricting access to energy will be a future measurable, likely making “fossil fuels … more expensive across the board.”
- Further exploration of patents as a signifier of entrepreneurial activity would be worthwhile. One study in the above-noted Zárate Moreno survey noted fewer patents issued when the cost of business is higher. On the other hand, finding classical liberals skeptical of patents or intellectual property rights is not difficult.
- Measures for political and social instability matter. As described in Pranab Bardhan’s “Institutions Matter, But Which Ones?,” economies at early stages of development are “beset with coordination failures and collective action problems.” These economies benefit from going beyond property rights concerns (traditional economic freedom measures) to even more difficult-to-quantify institutions such as voter participation rights that may more directly affect literacy or other human development indicators, and in turn indirectly the usual entrepreneurship indicators such as income or startups.
Complexity in measuring regulation’s effect on entrepreneurship is further heightened by the preeminence of the formal legal environment and escalation of litigation, as economies grow wealthier; and research has also outlined the spread of categories of laws and regulations affecting small business.
Understanding the sources of wealth creation and human flourishing is worthwhile. But complicated. Need a Ph.D.? Get started!
(Note: The introductory portion of this article describing entrepreneurship research resources is in part based on a portion of my chapter in the Fraser Institute’s new book Demographics and Entrepreneurship. One may read the chapters at the volume’s landing-page here.)