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Macroeconomics and Entrepreneurship in 2005

May 2005 Corporate

There are many paradigms through which people measure the level of entrepreneurship. One paradigm examines entrepreneurship as the event that occurs when capital, marketable ideas, and managerial talent are combined. Another paradigm attempts to explain entrepreneurship as a cultural phenomenon, with certain cultures more apt to foster entrepreneurs while others which readily punish entrepreneurial attempts. Yet one other examines entrepreneurship as the outcome of business networks that enable entrepreneurs to launch their business. Each of these paradigms provides a level of intellectual satisfaction, supporting the initiatives and viewpoints of different actors within the entrepreneurial world. Yet none would be complete without a discussion of the economics of entrepreneurship.

Economics provides perhaps the most accurate lenses through which to examine the level of entrepreneurship. According to fundamental economic precepts, humans seek to participate in economic activities that will provide them with greater benefits in comparison to all other economic activities. In the context of entrepreneurship, people become entrepreneurs to improve their own welfare over that of traditional employment arrangements. This would imply that entrepreneurs perceive the financial opportunities provided through entrepreneurship are greater than those provide traditional employment.

Low Success Rate, High Success Payoff

Financially, entrepreneurship is a risky behavior. Dr. Schrager of The University of Chicago is often quoted for stating that 9 out of 10 new companies fail to survive. To put this in context, a casino gambler is more likely to succeed than an entrepreneur on a given day. Despite the poor odds of success for the entrepreneur, those who do succeed are likely to receive extremely high payouts. That is, they expect to earn a proportionately greater return than that which they could have earned through traditional employment such that the dismal odd of success are countered by the value of success when achieved.

Macroeconomics and Entrepreneurship

Expectations and perception have much to do with the choice of becoming an entrepreneur. An entrepreneur must expect to succeed despite the statistical odds against their achievement. Furthermore, their perception of all other opportunities must be such that those other opportunities are less desirable than attempting to create a business on their own.

External factors will shape these expectations. When external factors indicate the likelihood of success through entrepreneurship or the unlikelihood of success through traditional employment, an individual will be more likely to select entrepreneurship. Indicators of each of these factors can be found in macroeconomic statistics.

Growing Economies Favor Entrepreneurship

Growing economies are more hospitable to business than declining economies. The macroeconomic indicator of a health of the economy is the Gross Domestic Product (GDP). A Growing GDP indicates a growing economy, while a shrinking GDP indicates a shrinking economy. On a state by state basis, the equivalent metric is the Gross State Product (GSP). The Bureau of Economic Analysis tracks each state’s GSP.

Because individuals will have an increased tendency to expect success when the economy is growing rather than shrinking, we can expect there to exist a positive correlation between the state level GSP and the state level of entrepreneurship.

Reynolds et al have demonstrated statistically in a cross national study that growth in GDP is positively correlated to levels of entrepreneurship. In analogy, we can expect that state level GSP is likewise correlated with levels on entrepreneurship at the state level. A statistical analysis presented later supports this claim.

Unemployment Favors Entrepreneurship

High levels of unemployment lower the opportunities available in the traditional employment market. During periods of relatively high unemployment, the traditional employment market will offer many individuals with the prospect of an extended period of unemployment or its counterpart of underemployment, wherein a person takes a position that does not maximize their potential productivity. For these individuals, neither unemployment nor underemployment will provide the same perceived level of opportunity as that which could be gained through entrepreneurship.

Reynolds et al have demonstrated statistically in a cross national study that unemployment levels are positively correlated to levels of entrepreneurship. In analogy, we can expect that state level unemployment is likewise correlated with state levels of entrepreneurship. The Bureau of Labor Statistics tracks each state’s unemployment level. A statistical analysis presented later supports the claim that unemployment is positively correlated with entrepreneurship.

Measuring Entrepreneurship

As a measurement of the level of entrepreneurship within a state, we solicited from The Secretary of State offices the number of new businesses filings within their state.

We requested for a count of both corporations and LLCs. LLCs are relatively new types of business filings. In prior decades, new businesses would file as a corporation. In the 90’s, most states changed their state law to enable the establishment of LLCs. LLCs typically provide for similar legal protection and pass through taxation as corporations, but require less paperwork and lower filing fees. The key distinction between LLCs and corporations is between the allowable number of owners. Typically, companies with more than 75 shareholders are required to file as corporations. Because most small businesses do not have a large number of owners, LLCs have become highly acceptable entities for many entrepreneurs. This is reflected in the high percentage of new LLCs as a portion of all new businesses in various states. See Exhibit 1.

Exhibit 1

State LLC as a Percentage of New Business Filings
CA 33%
TX 55%
IL 28%
NY 35%
OH 69%

As a note of areas for errors, the number of new business filings is not a completely accurate measurement of entrepreneurship, but it is better than all others that can be gained with the same level of ease. (See Footnote 1.)

Modeling Entrepreneurship

The above discussion provides us with the framework for analytically modeling entrepreneurship. Entrepreneurship, as measured by the number of new business filings from the Secretary of State can be examined in comparison to state level GSP and Unemployment.

We have tracked entrepreneurship of the State of Illinois over the 1999 to 2004 time frame. See Exhibit 2.

Exhibit 2



The Green Line is the number of new business filings within Illinois charted against the right axis. The Blue Line is the GSP of IL in millions of dollars charted against the left axis. The Red Line is the number of unemployed individuals in Illinois charted also against the left axis. We can visually see from Exhibit 2 that increases in unemployment or GSP both yield an increase in the level of entrepreneurship for IL.

A regression analysis of the number of new business filings against the GSP and the number of unemployed individuals reveals the strength of these effects. According to our regression analysis, every $10 million increase in GSP is associated with the establishment of one new business. Furthermore, for every 100 individuals that join the ranks of the unemployed, 7 individual will establish a new business. Combined, changes in GSP and unemployment account for 88% of all new business creation over this period. (See Footnote 2.)

Types of Entrepreneurship

While most of the level of entrepreneurship can be accounted for by examining macroeconomic factors, this examination fails to predict which industries entrepreneurs will choose to enter. Clearly, new businesses that market highly valuable products and services are more desirable to foster than those which market low value products and services. To examine the factors that lead to high valued activities over low valued activities though, we must leave macroeconomics and return to one of the popular paradigms.

References

1. P. Reynolds, W. Bygrave, E. Autio, L. Cox, and M. Hay, Global Entrepreneurship Monitor 2002 Executive Report, Ewing Marion Kauffman Foundation, 2002.
2. A. Zacharakis, P. Reynolds, W. Bygrave, Global Entrepreneurship Monitor National Assessment: United States of America 1999 Executive Report, Babson College 1999.
3. Ohio Secretary of State’s Office, IL Secretary of State’s Office, NY Secretary of State’s Office, CA Secretary of State’s Office, TX Secretary of State’s Office for the number of filings for new Corporations and LLCs.
4. US Census Bureau for Estimated Population Data
5. U.S. Department of Labor, Bureau of Labor Statistics for Estimated Unemployment Data
6. U.S. Department of Commerce Bureau of Economic Analysis for Estimated Gross State Product Data

Footnotes
Footnote1
The number of new business filings within a state is less than fully accurate due to two mentionable factors, the definition of entrepreneurship and the requirements for new business filings.

With respect to definition, many businesses operate in the “gray” market. The grey market lies between the illicit business activities, such as those practiced in the “black market, and those fully reported and fully legal, such as those practiced in the “white” market. Common examples of grey market activities would include baby sitters, maids, and contractors which perform services on a cash basis and do not fully report their earnings. Accurate statistics on the establishment of grey market businesses are naturally fraught with the challenge of getting the entrepreneur to report their less than fully legal activities. The “grey” market entrepreneurs and others who do not incorporate will not be represented in the recorded new business filings with the Secretary of State. This source of error will negatively bias the state level statistics.

With respect to the requirements for new business filings, individuals and businesses can file for the establishment of a new business in states that they do not live within. For instance, many individuals will seek to establish their business in the state of Delaware even though they live outside of that state due to favorable tort law within Delaware. This can leave the number of new business filings to be either positively or negatively biased as a metric for entrepreneurship. Further complicating the use of state recorded new business filings as a metric of entrepreneurship is the fact that businesses can file for the establishment of a new business. A business which is established by another business is not an entrepreneurial activity, rather it represents the expansion of an existing business. This source of error will positively bias the state level statistics.

Our analysis accepts these sources of error in using the Secretary of State records of new business filings as a measurement of entrepreneurial activity. We anticipate that these sources of error have relatively little significance resulting overall analysis.

Footnote 2
The regression equation for the establishment of new businesses in IL against GSP and state wide unemployment is

New Co = – 28108 + 0.117 GSP + 0.0762 Unemployed

With an R Squared of 88.1%. The T stat for the coefficients of both the GSP and unemployed are indicate these coefficients are statistically significant, with a T stat for the GSP coefficient of 1.35 and a T stat for the Unemployed coefficient of 2.08. That for the constant term indicates that the constant is not significantly different from zero.



About the author

Tim J. Smith, PhD is the Managing Principal of Wiglaf Pricing, and an Adjunct Professor at DePaul University of Marketing and Economics. His most recent book is Pricing Strategy: Setting Price Levels, Managing Price Discounts, & Establishing Price Structures.

Tim J. Smith, PhD
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