More than you think: An inclusive estimate of business entries

ELSEVIER

MORE T H A N Y O U THINK: A N INCLUSIVE ESTIMATE OF BUSINESS ENTRIES WILLIAM J. DENNIS, JR. N F I B Education Fotmdation

The Wells" Fargo/NFIB Series on Business Entries and Exits' collected data throughout 1995 from 36,000 households regarding the business formation SUMMARY activity occurring among adults within those households. After adjusting for the 1.37 owners per firm and the 10% ~f households with more than one entry, there were an estimated 4.553-million business entries in the 12-month period involving 6.211 million active owners'. Seventy-eight and one-half (78.5) percent of those businesses were de n o v o starts, 20.0% purchases, and the remainder other fi)rms of entry (including missing responses). Most of the entries were quite small whether started or purchased. The number of business entries is significantly larger than prior estimates. However, the 4.553-million figure, when dissected into component parts, is consistent with other measures" of business entry. The primary reason for the larger estimate is that this" research was able to capture the signtficant number of very small entries that either do not appear in other databases or appear only after a substantial delay. These new data offer a significantly expanded view of the American business population and its dynamics. More specifically, they provide quantification of the smaller end of the entry scale, thereby introducing new population distributions and raising fundamental research and marketing questions about the unit of analysis (What is a business?) What constitutes a reasonable survey sample? To what population do we generalize survey data ? What are the market segments" of the small-business population, and how do they differ? What are the public policy requirements" tff these segments', and how do they coincide and conflict? And, what do real entry numbers" tell us about the operation of the American economy on both a secular and cyclical basis? The foregoing are obvious. However, there are more subtle and perhaps more interesting questions. For example, the more people try to go into business for themselves, the more our collective (American) experience is influenced by the experience of business ownership. Small business draws enormous empathy .from the American public; few Americans institutions are as popular. This is obviously a complex phenomenon. However, one explanation for its popularity is that so many Americans are exposed to business ownership either personally or through someone they know. Part of this research not yet published shows that small-business ownership pervades every class, income category, racial grouping, etc. The penetration of business formation into the American experience, therefore, is not only deep, it is

EXECUTIVE

Address correspondence to William J. Dennis, Jr., NFIB Education Foundation. 600 Maryland Avenue S.W.. #700, Washington, DC 20024. The author wishes to thank the Wells Fargo Bank of San Francisco for its support of this research. He also wishes to thank Bruce Kirchhoff, Bruce Phillips, and Paul Reynolds for their continuing interest and commentary. and an anonymous referee for several helpful suggestions. Journal of Business Venturing 12, 175-196 © 1997 Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010

0883-9026/97/$17.0() PII S0883-9026(96)00060-2

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also broad. A n d when its dimensions are so great, the remaining issue is not the existence of influence but its degree. I f there are more starts than previously recognized, there must also be more exits. And, if there are more exits, the dynamics o f the business entry-exit process become even more tumultuous than previously recognized. Particularly for those interested in either policy or management, the question becomes, "Why is exit so common ?" One path of inquiry leads to motivation for entry, including career alternatives and income supplementation. To what extent do people intend to grow their businesses and to what extent do they intend their businesses to fill financial, occupational, or time gaps until something better comes along? Another path o f inquiry leads to resources. Do resource constraints or constraints o f other natures impede business development? Then there is the issue o f preparation. How well-prepared are entrants? And, what reasonable steps can be taken to improve their assessments o f potential opportunities or to effectively implement plans to capitalize on them? These are not necessarily new issues. But they become more conspicuous and pressing when the large number of exits is appreciated. The technique used to capture these data at a reasonable cost is called an "omnibus" or "caravan" survey. This survey technique is not well-known outside the commercial survey industry, but it presents considerable opportunity for researchers either with limited budgets or desirous of asking fewer than 10-15-minutes ' worth o f questions from a sample of the adult population. Its advantage is financial. Multiple sponsors can ask a limited number o f proprietary questions at their own expense. But they then share the costs and results of reaching respondents and of asking the demographic questions, for example, age or sex of respondent. The current research posed two screen questions to all 36,000 households interviewed. The sponsors paid for those 72,000 questions. But only about 2,000 respondents passed one o f the screens. These respondents were led through several more questions. Thus, the sponsors paid just for the screen questions and those questions administered to the 2,000. A n extensive set of demographic data about the respondents was thrown in "free." © 1997 Elsevier Science Inc.

INTRODUCTION Alvin Star and Chem Narayana concluded their 1983 article, "Do We Really Know the Number of Small Business Starts," with the following commentary: "The precise number of annual business starts remains elusive--small business researchers and policy analysts must rely upon gross estimates" (Star and Narayana 1983, p. 48). A contemporary assessment of the same issue would yield the same conclusion. There still isn't a reliable estimate for the number of business entries, and we still must rely on gross estimates. Assessments of the business entry population are regrettably few, and their results vary significantly. One half to one million annually seems to be the popular range. Kirchhoff (1994) and Armington (1986) occupy the lower end. Using U.S. Small Business Administration (SBA) data sets developed from Dun & Bradstreet's DMI files, they separately conclude that 10%-12% of all firms in any year represent the entries. Translated, that number becomes about 450,000 to 500,000 firms. This end of the range corresponds to decade-old "conventional wisdom's" 400,000 new businesses annually (Star and Narayana). Birch occupies the high end when he casually mentions that "millions of enterprises are formed each year" (Birch 1987, p. 3). Since he also investigates a derivative of D&B's DMI files, he obviously compensates for some of the files' deficiencies and judgmentally inflates the estimate beyond his numbers. SBA employs a different data set to arrive at 807,000 new firms and 944,000 new and successor firms for 1994 (U.S. Small Business Administration, 1995). The agency does point out that these are new firms with employees. Dun & Bradstreet's New Incorporations series (nearly 750,000 in 1994) sometimes is used to estimate the number of starts. More typically, it is employed directly or indirectly as a proxy for new business activity. The Bureau of Economic Analysis at the

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D e p a r t m e n t of Commerce constructed a Business Formation Index (recently taken over by the Conference Board) from New Incorporations and "other component data •.. not available to the public." The other component data are associated with business telephone connections or listings. This Index, once part of the government's Index of Leading Indicators, represented the government's "official" indicator of new business activity• It is still reported regularly in the Survey of Current Business despite its recent loss of status• But, the index has always provided a trend in formation, never an absolute level. Dun & Bradstreet also produced a Business Starts series registering about 250,000 annually in the mid-1980s. The series, which counted new business locations, was discontinued in 1986, through D&B is currently attempting to reinstitute it. This brief review summarizes the business entry numbers from which we can choose• The supply is limited, and the differences among the limited supply vary by 50%-100%• Yet, how reliable are any of them? And, if the existing numbers are not reliable, what is a reliable figure? The remainder of this article is structured as follows: The first portion addresses in some detail the data sets currently used to make estimates of business entry and why they are either fragmentary or inappropriate for the task. The second focuses on the research methodology used to obtain a reliable estimate of business entry• The third presents results and checks them for consistency with other data. Conclusions constitute the final portion•

THE DATA CURRENTLY BUSINESS ENTRIES

U S E D TO E S T I M A T E

Two fundamental problems exist with the figures now put forward as the number of entries or as proxy for the number of entries. First, the data sets on which they are often based miss a substantial number of new and very small firms. They are fragmentary. While some missing businesses will eventually be incorporated into the files, many will not. In either case (late or never), the data lead to misinformation about the extent and/ or timing of entries. The second problem is definition. At least two of the data sets used to measure entries (i.e., ES-202 and new incorporations) were designed for other purposes. They may measure phenomena for which they were intended and may even be reasonable proxies for the course of business entries, but they do not directly substitute for the p h e n o m e n o n we seek to gauge.

Fragmentary D a t a Sets Birley (1984), Aldrich et al. (1989), and Busenitz and Murphy (1996) participated in a line of inquiry that attempted to identify the most comprehensive source of new business data. They approached the problem in a similar fashion. These investigators located potentially useful data sets (at least one of which required considerable prior field work), and then counted and compared firm listings in each. The three focused their research on a single county (St. Joseph Co., IN; Durham Co., NC; and Montgomery Co., TX, respectively), and all included data from D&B's DMI file, the state's ES-202 (unemploy-

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m e n t c o m p e n s a t i o n ) file, 1 and a t e l e p h o n e directory. Aldrich et al. also e m p l o y e d a C h a m b e r of C o m m e r c e directory, which was quickly shown to be i n a d e q u a t e for their purposes, and e n u m e r a t i o n in which businesses were identified t h r o u g h field observation. Busenitz and M u r p h y a d d e d a state sales tax registrations file. [Earlier, Star and N a r a y a n a (1983) played with the idea of using the Illinois Retailers' O c c u p a t i o n a l tax data modified by various federal data sets.] A key finding shared by three studies is that no single data set can be considered inclusive. 2 Birley (1984), excluding the wholesale and retail industries, d e t e r m i n e d that " n e w " business in the D M I files contained only a small fraction ( 8 % ) of the ES-202 entries. Further, only a b o u t three-quarters of similar listings in the ES-202 files could be f o u n d in the white and yellow pages of the t e l e p h o n e directory. W h e n Aldrich et al. (1989) reviewed the c o m b i n e d n u m b e r of new firms in the three data sets that were eventually c o m p a r e d ( D M I , ES-202, and e n u m e r a t i o n / d i r e c t o r y ) , the m o s t inclusive set (i.e., e n u m e r a t i o n / d i r e c t o r y ) only a c c o u n t e d for 78% of the new firms they could identify by any m e t h o d . T h e count missed at least 22% of D u r h a m C o u n t y ' s new firms and possibly more. T h e o t h e r two data sets m o r e c o m m o n l y used to yield entry estimates fared m u c h worse. T h e D M I files contained only 38% of all entries, and ES-202 contained 43%. Busenitz and M u r p h y (1996) f o u n d that sales tax registrations were also vastly superior to D M I or ES-202 files in locating new businesses. T h e authors d e t e r m i n e d that 81% of the new firms f o u n d in any of the three sources were c o n t a i n e d in the sales tax files, c o m p a r e d to 22% in the ES-202 files and 8% in the D M I files. Just 12% of that universe were listed in the t e l e p h o n e directory. A survey of new businesses in the sales tax file d e t e r m i n e d that only two of three fit the a u t h o r ' s 19-month definition of "new," including those that had ownership transferred during the period; the others were f o r m e d earlier. U n f o r t u n a t e l y , Busenitz and M u r p h y did not collect an e n u m e r a t i o n / directory data set similar to A l d r i c h et al.'s. W h i c h of the two would have p r o v e d m o r e c o m p r e h e n s i v e is an interesting question. H o w e v e r , in a follow-up survey of new firms in the sales tax files, the investigators f o u n d 58% were located in h o m e dwellings and 17% in residential n e i g h b o r h o o d s , suggesting sales tax files are m o r e inclusive than enumeration/directory. E v e n if e n u m e r a t i o n / d i r e c t o r y or sales tax files are reasonably inclusive, c o s t - a m o n g o t h e r c o n s i d e r a t i o n s - - e l i m i n a t e s t h e m as viable options for nationally counting new businesses on a regular basis. Just the e n u m e r a t i o n for D u r h a m C o u n t y required four m a n - m o n t h s of effort prior to the t e l e p h o n e calls and o t h e r forms of c o m m u n i c a tion required to d e t e r m i n e if these were new firms, h o w e v e r defined. T h e sales-tax-registrations a p p r o a c h appears m o r e practical, but it has its own problems. S o m e states will Employers must complete a form listing their employees, hours, wages, etc., each month and file it with the state agency responsible for administration of the unemployment compensation program. Each state compiles these data and submits them to the U,S. Department of Labor. The form submitted by the state to Washington is the ES-202, For current purposes, the data developed from this cooperative process is referenced as ES-202 data. 2Birley (1984) and Busenitz and Murphy (1996) actually made no judgment about the comprehensiveness of telephone listings. To do so, they would have had to make a large number of calls from the directory to locate "new businesses." Aldrich et al. (1989) combined the directory with enumeration by taking those visually identified and not appearing in the directory published six months earlier. While the telephone directory may appear to be the greatest potential source of new businesses, the major telephone companies have known for years that many business owners use personal telephone numbers for business purposes. The data collected for the Wells Fargo/NFIB Series on Business Entries and Exits (discussed subsequently in the text) indicates that half of all entries do not have a business telephone in their first month of operation.

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census data are also not useful in gauging the number of business entries in manufacturing, let alone across the broader economy. In sum, an assessment of the m a n y data sets employed to m a k e estimates of business entries consistently shows that they are fragmentary. F r a g m e n t a r y data sets yield undercounts. These undercounts vary by data set used, but appear severe even among the most comprehensive.

Inappropriate Data Sets O t h e r data sets should not be used to measure entries simply because they measure related activities, not entries. They possibly can serve as a directional proxy for the entry p h e n o m e n o n , but they do not gauge levels. The ES-202 files, new incorporations, and the Current Population Survey (CPS) are three examples. The ES-202 files have deficiencies for counting business entries, as has already been noted. But the ES-202 files were never intended to measure entries. The government form was intended to keep records for purposes of u n e m p l o y m e n t compensation eligibility. As a result, it is a file of employers. Entries without employees other than the owner(s) are by definition excluded. The population covered immediately suggests a severe undercount of entries. But, a second and counter influence on the ES-202 count also occurs. The data are collected state by state. If an existing firm starts operations in a different state, the owner must file another ES-202 in the new state. Those circumstances result in the file adding an entry. The consequence is to overcount them. A timing p r o b l e m also arises when a self-employed business owner adds his first employee. The business is not new, but it enters the file as if it were. The net effect of these three characteristics is therefore not totally clear. But we do know that the ES-202 file is an overcount of employers and an undercount of entries. The new incorporations series produced by D u n & Bradstreet is also sometimes taken to represent entries. But D u n & Bradstreet has always been clear: The data are counts of incorporations collected from the Secretary of State (or its equivalent) in each state; they are not counts of new businesses. The c o m p a n y describes its series as a "key indicator to the trend in new business formations and an often used measure of the level of business activity" (Dun & Bradstreet 1996, p. 20). Since most businesses never b e c o m e corporations, the new incorporations series by definition omits the majority of entries. The series presents other problems as well. A business may have existed for decades as a proprietorship or partnership before the owner decides to incorporate; such a business is counted as newly incorporated. ( D u n & Bradstreet officials could provide no estimate of the proportion of new incorporations that fall into this category.) In addition, a single business can have parts incorporated for legal purposes. One example is a contractor who may incorporate individual blocks of housing in a larger development. Thus, the new incorporations data are not helpful as a measure of the level of new business activity. Finally, the Current Population Survey (CPS), conducted by the U.S. Bureau of the Census, has infrequently been used by researchers interested in small business and entrepreneurship. Evans and Leighton (1989) and Segal (1996) are important exceptions. Since the sampling pattern for the data set includes reinterviews at a one-year interval of a fraction of the approximately 60,000 monthly observations, the CPS could be employed to investigate a number of questions related to self-employment and busi-

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ness entry. However, estimating the number of business entries is n o t one of them. The unit of analysis for the CPS is the individual, not the business, and the individual is classified as business owner only when self-employment is the longest held job (economic activity) during a year. If the individual changes employment status between years, the change is recorded. But if the individual maintains the same status, no change is noted. Closing a business and starting another is irrelevant for these data if the occupation/job the individual holds is the same. Opening a second business has no effect, either. Thus, the CPS is both inappropriate and fragmentary for current purposes.

The Inadequacy of Currently Employed Data Sets Table 1 summarizes the salient characteristics of the data sets currently employed to estimate new business entry. It presents each data set by its definition of new business entry: its method of identification of a new business, including the information source, legal compulsion to provide, and the timeliness of data collected; its primary liability as a new business measure (i.e., fragmentary or inappropriate); and, relevant considerations unique to the set. The odd data set on the table, enumeration, isn't so much a data set as a methodology. However, it is highly relevant and included for comparative purposes. Even a casual review of Table 1 reveals one startling fact: The data set usually defines business entry and hence its count. Consider the column titled "Definition of business entry." Four of the eight sets evaluated (i.e., DMI, LED, Sales Tax Registrations, and Telephone Directory) define business entry as entry into the data file. Yet, none of the four files capture all generally recognized entries. They miss entries because the data sets are not designed for the purpose of finding them. While the sets may eventually capture an entry initially missed, the lag is often considerable. Note in the column titled "Timing between event and file entry" the lag can be months or even years. Nor does the number of entries missed appear trivial. Data collected in 1993 involving a small sample of entries indicates that few paid their first state unemployment compensation taxes, paid their first FICA taxes, filed their first federal income tax return (business return), or believed they were in the Dun & Bradstreet files at entry (Carter, Gartner, and Reynolds, 1996; Reynolds 1995). Even the compulsory nature of sales tax registrations does not guarantee coincidence of the two (Busenitz and Murphy 1996). It is clear that entry into the file is not the equivalent to entry. Counts based on entry into the file are, therefore, fragmentary, measuring only selected, securable entries. Three of the data sets (i.e., ES-202, New Incorporations, and CPS) do define their unit of analysis reasonably well. Their problem for present purposes is that the unit of analysis cannot be construed to be business entries. It is something else. The ES-202 defines entry as a "new employer" within a state; New Incorporations is a newly incorporated entity; and the CPS focuses on individuals, not businesses. (See Table 1, column headed "Definition of business entry.") While any of the three might serve as reasonable proxies for entry trends, none captures entry levels, and levels is the phenomenon attempting to be measured. Allowing the data set to dictate definitions and, therefore, counts has been a matter of convenience and cost. That strategy is understandable, but it is also backward. The preferable technique is to begin with a definition and then develop methodologies designed to obtain the desired information. The definition of entry should be intuitively satisfactory, rather than exclusively a convenience. The methodology should capture the

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T A B L E 1 S u m m a r y o f S a l i e n t C h a r a c t e r i s t i c s o f D a t a Sets E m p l o y e d to E s t i m a t e B u s i n e s s Entry by Data Set Identification of business entry

Data set

Definition of business entry

Source of information

Provided by Timing between legal event and file compulsion entry

Principal liability as data set

ES-202

New employer in a state

Employer regis- Yes, for em- Few weeks lag ters for state ployers UC prog. only

Inappr.

D & B ' s New Incorps.

New incorporation

Files with state

Immediate; reporting lag

Inappr.

D & B ' s DMI

Entry into the file

Trade credit ap- No plication, tele. dir., and others

Can be months, years, or never

Frag.

CPS

No None/occupation Survey of ranof individual domly selected households Entry into the Survey--IRS No file files sampling frame

18 mos. maximum if captured

Inappr.

LED

Sales tax reg- Entry into the istrations sales tax file

Files with state tax officials

Telephone directory

Entry into the di- Business telerectory phone hookup

Enumeration/ phone book

Start-up from scratch; takeover

Physical sighting-confirmed by tele.

No

Up to five years Frag. after IRS illing; some never

For most, Not clear but not all entries No U p to year to get in dir. after hook-up

Frag.

Not applicable

Frag.

U p to year when tel. directory used

Frag.

Misc. Double counts interstate employers Most businesses not incorp. Smallest entries most often missed Individual is unit of analysis Manufacturers only; data on smallest-unreliable Not available in all states About half don't have bus. tele. at entry Too expensive for practical use

defined phenomenon, and capture it in a timely fashion. Moreover, the entire procedure must be financially possible. Aldrich et al. (1989) attempted to follow the preferred technique with their enumeration methodology. They began with their idea of a business entry, and developed a methodology to obtain the desired information, including reasonable precision in timing entry. But, they were not successful for present purposes. Their results were fragmentary because the methodology effectively omitted starts without a public physical location. Many businesses, including many viable businesses, begin in the home or some non-public place. The data collection supporting this paper indicates that a majority

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of starts are home-based, and a significant number of employing businesses begin there as well. In sum, the data sets now available to estimate the number of business entries over any defined period are simply not up to the task. They are fragmentary or inappropriate. Investigators must look elsewhere, develop new tools, or both.

Research Objectives Given this background and the similar condition surrounding business exits data, the Wells Fargo Bank of San Francisco agreed to sponsor primary research regarding business entries and exits. The Wells Fargo/NFIB Series on Business Entries and Exits, 4 described below, is the result. The research has three fundamental purposes. The first and most important is to estimate (i.e., measure) the number of business entries in the United States by calendar quarter. The second purpose is to profile the personal characteristics of the entrant population. The third is to learn something about the businesses that are formed. This article centers on the first purpose, although it incorporates data collected for the third.

METHODOLOGY AND THE OMNIBUS SURVEY The ability to estimate the number of entries for any defined period is conceptually simple: Ask (survey) a sample of adult Americans about their entry activity, and extrapolate their responses to the population. This procedure allows the researcher to avoid the principal problems inherent in previous attempts to estimate the population. He can define (1) entry as he wishes--not let the data set define it for him, (2) capture all entries--not just those that identify themselves, and (3) obtain a time of e n t r y - - n o t a time of entry into a file that is constructed for some other purpose. The problem occurs when the researcher must ask such a large number of people that the cost becomes prohibitive, particularly if the intent is to produce estimates periodically.

Data Collection The resolution of the cost issue is tied to a form of survey syndication. Known as the "omnibus" or "caravan" survey, the technique involves the sale of individual survey questions to different customers/clients/researchers, with the data from a general set of demographic questions shared by all. Thus, the enormous expense of screening as many as 20 people who have experienced no recent entry activity for every one who has can be reduced significantly. Though various commercial polling firms maintain such a service, the author engaged The Gallup Organization of Princeton, New Jersey, to participate in the project. Every month Gallup conducts three omnis consisting of 1,000 respondents each. One is conducted early in the month, a second at mid-month, and a third toward the end of the month. Over the course of a year, Gallup conducts 36,000 interviews. The sampling frame for each is the universe of households in the United States. The sample is collected through a random digit dial technique, and all interviewing is conducted 4 The series has recently been renamed the Wells Fargo/NFIB Series on Business Starts and Stops to make it subject matter more comprehensible to the general public.

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by employees of Gallup. The data are weighted to reflect the underrepresentation of some groups.

Potential R e s p o n s e Bias The response rate on Gallup's omnis averages about 50% on a seven-call pattern. While a decent rate given the need to have all interviews concluded by month's end, the immediate concern is potential response bias. This is a particular concern when one of the groups to be measured is composed of people who recently formed a business and are likely to be working long hours. Working long hours presumes that the individual will be home less often to respond to a telephone inquiry, or, even if at home, will be less likely to participate in a survey. To address this concern, the researcher compared the number of calls required to obtain an interview with respondents who indicated that they or someone else in the household had recently entered a business, and the number of calls required to obtain an interview with all other respondents. The two should be virtually identical if response bias does not exist, and indeed that is what happened for all practical purposes. The author obtained the average "call-back" data for the nine months AprilDecember, 1995, and found that the two groups fell within 0.1 calls of one another. Of the successfully concluded interviews, it took an average of 1.74 calls to interview respondents with no business entry activity in the household, 1.87 calls to interview those who reported that they had participated in an entry, and 1.75 calls to interview those reporting on the entry activity of someone else in the household. Combining the two groups with entry activity on a weighted basis results in 1.82 calls, 0.07 calls more than for the population with none. If bias exists, it is in the expected direction, that is, an undercount of new business activity. The second means to address the issue of potential response bias is to determine who in the household responded about business entry activity. The questionnaire asked qualifying respondents who (what individual) engaged in entry activity, the respondent or another member of the household. There are 1.98 adults per household in the United States. Thus, the a priori expectation is that in roughly half the cases, the respondent would be the business owner; in the other half the cases, the respondent would be reporting on another person in the household. The data showed that the respondent reported on himself in 58% of the cases (unweighted monthly average). It appears either that respondents were more likely to r e m e m b e r they started a business in the last six months than they were to remember a similar activity of another adult member of the household, or that people who engage in starts are more likely to be at home than another adult is. The author will report later that two of three starts are home-based. The presumption is that these home-based entrants are more likely to be at home and answer the telephone (only half of the total and less than half at home have business telephone numbers.) The result is to modify the a priori expectation; a higher proportion of the respondent population probably should be reporting on themselves than reporting on others. But, what proportion should be expected? There is no basis on which to develop a precise expected figure, though the 58% appears reasonable. These data, along with the call-back comparison, do not prove the absence of response bias. However, they strongly suggest that one potentially severe negative impact on our data, namely, the failure of entrants to respond, probably has little or no effect.

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Since the failure of entrants to respond represents the greatest potential threat to data quality, the major issue involving response bias appears resolved. What these data do not resolve, however, is the distribution of respondents. For example, if we were to miss a comparatively high proportion of those with large starts because they spend so much time away from home, the total number of entrants would be little affected. Large starts represent only a small portion of all starts. However, we could incorrectly draw the conclusion that new starts are smaller on average (or in frequency) than they actually are. A higher response rate than the one obtained is obviously desirable. However, given that the existing survey format provides only a 10-day window to complete the interviews, a higher response rate would be very difficult to achieve without extraordinary and expensive follow-up. The implication is that a more fully mined sample would be able to provide more precise data on a one-time basis, but would be of little value in allowing longitudinal examination of the fundamental research question.

Survey Questionnaire The definition of "new business" or "entry" is inclusive for data collection purposes. The strategy is to locate the p h e n o m e n o n using the minimum criteria reasonable; then, collect a level of detail on each that allows researchers to adopt a definition to meet their varying needs. The survey contains a single initial screen to distinguish those who have recently entered from those who have not. It reads, "In the last six months, have you or has another adult in your household, alone or with others, started or purchased a business, one with sales or income?" Note, the critical element is whether the respondent thinks he is in business; it is not an event or events, actions, activities, or processes. There are two reasons for this simple definition of entry: No single event or action or sequence defines entry (Carter et al. 1996; Reynolds, 1995). If we know of none, why establish a screen containing a series of possibly tangential criteria? Moreover, screening people employing an action-driven definition of "business" would entail several additional questions. The increased expense of these questions would make the project financially prohibitive. The phrase "with sales or income" is the sole control on the respondent's discretion within the question. Businesses can start without immediate sales or income, for example, a high-tech firm started with venture capital that is still in a research mode. However, there is evidence that new businesses almost always are characterized by some sales (Carter et al. 1996; Reynolds, 1995). Thus, a swap occurred between a limited restriction on a respondent's definition of "business" created by the phrase "sales or income" and the loss of isolated entries having no sales. The initial screen also contained the phrase "started or purchased." While a subsequent question specifically asks the method of entry (i.e., start or purchase), the initial screen contained the inclusive language to ensure that the respondent understands information on both forms is sought. Some researchers feel purchases are an entry: others consider only de novo starts to be legitimate. The question's structuring implies no prejudice on the issue. The questionnaire focuses on the household as its primary unit for data collection. The household rather than the individual creates analytic problems, as will be noted later. However, the household was necessary to provide the researcher sufficient "in"

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to obtain the desired sampling error over the desired time frames. The individual as the unit of data collection provides information on 36,000 adults; the household provides it on almost 72,000. The screen question asks for activity within the last six months. The length of the reference period creates possible recall problems, and earlier a brief discussion provided some evidence on the matter. Prior to drafting the final questionnaire, three test questions employed reference periods of "six months," "12 months," and "one year." The longer period (differentially described) did not work well, as evidenced by the modestly greater number of positive responses over twice the length of time (Dennis, Dunkelberg, and Dial 1995). Even a six-month reference period appears to produce a modest winnowing of cases toward the end, except for the final month. The luxury of reducing the reference period to perhaps the prior three months was not possible as the number of cases becomes too few to produce reliable figures. If a recall issue exists, however, the effect is to depress the final estimates.

Calculation of the Estimate The first step in calculating an estimate for business entries is to verify that the business actually entered during the prior six months. A positive response was omitted if it occurred prior to the six-month reference period, or if no month or season was identified. (Decision rules are discussed subsequently.) Approximately 16% of those who passed the original screen were dropped because they could not establish an eligible entry date. The second step is to transform the data into usable form. Eligible positive responses divided by all responses result in the percentage of households where at least one adult entered a business in the prior six months. Unfortunately, it is not possible to derive the estimate of business entries from the percentage of households with entry activity multiplied by the number of households in the country. Two critical pieces of data complicate the calculation. The first is active partners outside the household and the second is multiple starts within the same household. If a business has more than one person who is not a member of the household actively involved in the entry, any sampling procedure will yield more people than businesses. The result of simply multiplying the two variables is an inflated number of businesses. Nor is this a trivial consideration. An average of 1.37 people formed a business (a conservative count for reasons discussed later). Thus, the author had to adjust for multiple owners. Multiple starts in the same household present the opposite problem. If more than one entry comes from a single household, a direct extrapolation based on the number of households experiencing such behavior will result in an undercount. This is no trivial consideration, either. About one in 10 households reported multiple entries. The unit of analysis was another consideration. It can be either the household or the individual, but all units must correspond. The household was selected because the focus of the interviews was the household. That means that the number of partners (individuals) have to be converted to household equivalents before a final calculation can be made. There are an average of 1.98 adults per household. Hence, the number of "partners" (individuals) is divided by 1.98 to transform units from individuals to households. Entries must be annualized from events that occurred during the seven-month time frame in which respondents could form businesses eligible to be counted. The easiest way to accomplish this task is to divide by seven, thereby obtaining a monthly figure.

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The monthly figure multiplied by 12 annualizes it. The result is multiplication of totals by 12/7. After converting units to entries per household and annualizing figures, the general strategy for the calculation is to consolidate households with the same number of entries into groups. For example, one group consists of the number of households with an entry having one partner (two people forming the business) subtracted from the number of household with two entries (one person per business). The author then adds the group with one entry per household to those with two per household (twice, since there are two entries in the household), etc. Since the resulting number represents those entrants located by the survey, it must be divided by all survey respondents (one per household) to obtain an incidence. The incidence can then be multiplied by the 98-million American households. The formula employed to make the calculation is 12/7[E1 + 2 ( E 2 - P]1"98) + 3(E3-P2/l'98) +4(-p3/1"98)]/* H Ps

(1)

where Entries per household, Pl..3 = Partners (in addition to respondent) per business, Ps = Sample population, H = Households, 1.98 = Average adults per household. The decision rules governing data use are very conservative. The result is to minimize the entry estimate. While there are too many decision rules to report here, the most important involve the treatment of nonresponse, the reference period, partners, and multiple entries. Nonresponse is treated as a negative response for purposes of the estimate. If respondents are not certain about entry, they are treated as if providing a negative answer. If they cannot provide an eligible month or at least an eligible season for their entry, they are eliminated. A more difficult problem with the reference period comes with the term "last six months." As noted earlier, Gallup conducts its omnies throughout each month. Thus, a respondent in late January may consider July within the last six months since there may have been little chance for activity in the year's first month. Someone responding early in January may adopt a different view. Therefore, the author makes eligible all cases in the month of the survey and the prior six months. Finally, caps are placed on the number of active partners allowed in any business and the number of starts any household can produce. A handful of respondents provided outlying answers that, if used as reported, would have distorted all calculations. The author could find no literature on which to make decisions and therefore arbitrarily chose a limit of four active owners (three partners) and three business entries from one household. El... 3 =

Sampling Error The sampling error (i.e., the plus or minus) is not presented here in the conventional sense. Too many decision rules had to be adopted in order to feel comfortable placing an upper and lower bound on the estimate and assigning a confidence level to the interval. However, the fundamental data are presented.

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The initial stage of this research captured the incidence of new business activity in a household. Sampling error on 36,000 interviews regarding the activities of almost 72,000 adults is _+ 0.4% at the 95% confidence level. However, calculation of the final estimates include data on multiple entries and the number of multiple entries in a household as well as the number of active owners in a business. Those calculations are based on the number of positive responses to the incidence measure, implying the sampling of error on those data is based on about 1,200 respondents. The plus or minus on 1,200 is _+ 2.8%. The latter figure constitutes the error as conventionally presented. The foregoing are survey sampling errors. There are other possible places for errors to enter the estimate. For example, a series of decision rules had to be established. Some were more arbitrary than others; all the rules affected the calculation. Throughout the calculation, numbers were rounded to two decimals. Rounding also influences the final estimate.

O t h e r Issues

The Wells Fargo/NFIB Series on Business Entries and Exits also estimates the number of people involved in the process. It does so by averaging the number of owners per business and multiplying by the number of businesses. This procedure undercounts the number of people actively involved in formation of the business because it assumes one person per respondent household per business. For example, if a husband and wife jointly are active in an entry, the number of people counted is one; if two neighbors do the same, the count is two. If a husband and wife in the respondent's household and a husband and wife in another household are jointly active and entered, the number is three. The reasons for the failure to count multiple active owners in the same household (unless there is more than one entry) are the special problems defining "active" and "ownership" for those living together, and the number of survey questions necessary to make the appropriate distinctions. Thus, the "people" estimate must be recognized as the absolute floor of those actively involved. The data for this series were collected monthly throughout calendar 1995. Since the numbers are developed from a reference period of up to 6 months prior, they do not provide a direct estimate for the calendar year. For example, January's interviews only include data for 1 month in 1995 and 6 in 1994; February's, for 2 months in 1995 and 5 in 1994. But July's interviews include data only for 1995. At the same time, the only data collected about December 1995 activity comes from the December 1995 survey. Thus, the data collected in calendar 1995 provide a 12-month estimate, with 1995 serving as its focus. The author nonetheless refers to 1995 for convenience and ease of communication.

RESULTS A N D DISCUSSION The United States produced 4.553-million business entries in 1995; 6.219-million people were actively involved. Three-and-one-half-million entries were de novo starts, and 910,000 were purchases? The remainder were other forms of entry (e.g., inheritance), or 5Press accounts of this research report modestly different figures than the totals presented here. For example, see Michael Selz, "Business Starts Were Surprisingly High in '95," Wall Street Journal, August 23, 1996, p. B2. The discrepancy is due to the time period measured. This paper employs data collected in 1995; news reports are based on data of events actually occurring in 1995.

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TABLE 2 Business Entries by Form of Entry*--1995 * Businesses Starts (de novo) Purchases Other/N A People Starts (de novo) Purchases Other/NA

Number *

Percent

4,552,574 3,573,771 910,515 68289 6,218,816 4,874,624 1261,974 83,995

100.0 78.5 20.0 1.5 100.0 78.4 20.3 1.4

Distributions of entry forms are based on the first entry in a household. * See text for definition of 1995. *Total does not add due to rounding.

the respondent did not provide an entry method (Table 2). By way of comparison, more business entries occurred (1995) than there were corporate income tax returns filed (1993); more than there were proprietorships filing income taxes in California, Texas, and New York combined (1993); and almost as many as there were businesses in the United States employing someone other than the owners (1990). There was a greater likelihood of locating someone starting a business in 1995 than locating a male undergraduate student (1992); more than twice the chance than of locating an elementary or secondary teacher (1994); and almost as great a chance as locating a public-sector union member (1990). The number of entries is huge, multiples of prior estimates. It is six to seven times larger than the most frequently cited figures. Obviously, a re-estimation of this size has enormous consequences for our understanding of the business-formation process in the United States. But before claiming to provide a significant new perspective on the business-entry population, it is well to carefully examine the numbers developed by the Wells Fargo/NFIB Series in light of other available data. Earlier, the author demonstrated that most of the current popular numbers are substantially too small. Their inaccuracy does not mean that the higher Wells Fargo/ NFIB numbers are correct or even better. But if the author can demonstrate that the results obtained are consistent with what has been learned from other data sources, then these new estimates can be accepted with greater confidence.

Consistency Among Data Sets The Wells Fargo/NFIB estimate of small-business starts is remarkably consistent with other data measuring business formation and related phenomenon. The following discusses its correspondence with five known data sources; ES-202 files, Dun & Bradstreet's New Incorporations series, SBA's Small Business Data Base (SBDB) developed from D&B's DMI files, Reynolds' estimates of nascent entrepreneurs, and the Current Population Survey measures of change in occupation/employment status.

ES-202-Based Data SBA's new formations series yields a number of 807,000 starts in 1994 (latest data available). This series is based on employer filings of ES-202s. The reader will recall that ES-202s provide a count of new employing organizations, although they exaggerate the number because any business expanding into a new state must file with that state. The

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files also may not accurately reflect the timing of entry because non-employing organizations becoming employers are counted as new. A "successor" file, different from the new formations series and vastly inferior to it, supposedly captures the transfer of ongoing organizations whether by sale, inheritance, or some other means, Thus, the ES-202 count covers new employers only, overstates that number to some extent, and separately counts successors. The Wells Fargo/NFIB Series estimates 3.574-million de novo starts, with 21.6% reporting employees other than the owners. Those are the firms that presumably must appear on ES-202s. Multiplying the two Wells Fargo/NFIB figures (3,574,000 × 0.216) yields 772,000 entries, 35,000 or about 5% short of the ES-202's 807,000 figure. The discrepancy between the two sets is easily explained by the double counting in the ES202 file. Thus, the two data sets produce remarkably similar results when they measure the same phenomenon. Less consistent is the "successor" firm number from the ES-202 file with the purchases number from the Wells Fargo/NFIB Series. The former totaled 137,000 (1994) while the latter was calculated to be 357,000 (1995). Several factors explain parts of the gap. Whether they can explain it away is another issue. The most important of these factors focuses on the successor data itself. They are highly suspect. The primary evidence to support that contention is that the number of successor firms in the ES-202data has declined consistently since the early 1980s and by a total of 25% while the total number of de novo starts has grown over 25%. Further, the result of ES 202's new firm data added to its successor firm data often is a lower figure than the exit total. Every other data set available shows the population increasing. There are also specific reasons why successor firms may be undercounted. Businesses changing ownership are supposed to file ownership changes. However, that might not occur. Certain tax advantages accrue to the sale of assets rather than businesses. From the seller's perspective, the method of sale could be the difference between capital gains and ordinary income; from the buyer's perspective, the method of sale could mean (until 3 years ago) having to include "good will" in the value of the business for tax purposes and not being able to amortize it. No sale of the business technically takes place in such cases. This is a common procedure, though no data quantifies its frequency. Other reporting issues are possible. For example, the new ownership could have dismissed the employees (at purchase) who would appear in the file as a termination rather than a succession. The transfer itself may not be captured if the business remains essentially unchanged. There is also the possibility of changes in the ownership structure that conceivably is captured by the Series but not by the ES-202. These explanations are unsatisfying, however, leaving the successor firm data the only data inconsistent with that produced by the entire Series. New Incorporations

Dun & Bradstreet's New Incorporations series measures precisely what the title indicates: new incorporations. The series counted 741,657 new incorporations in 1994. Directly, these data do not help validate the Wells Fargo/NFIB estimate. But if the author can calculate the ratio of new businesses that are incorporated to those that are not, he can make a "ballpark" estimate of the number of entries (Star and Narayana, 1983). The Statistics of Income (SOI) produced by the Internal Revenue Service show just over six partnerships and proprietorships with less than $500,000 in gross receipts

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for every corporation of the same size (U.S. Internal Revenue Service 1992). Lowering that gross receipts figure to $100,000, a sales volume closer to an entry than the $500,000 figure, increases the ratio to almost ten to one. Assume that distribution of active businesses reflects the distribution of entries in terms of legal form. Given the number of new incorporations, those ratios provide a lower bound of 4.36 million (6 × 741,657) and an upper bound of 7.42 million (10 × 741,657). While D&B's New Incorporations series measures new incorporations, it does not necessarily mean that the incorporation is a business entry. Earlier discussion provided several reasons for the lack of identity. Suffice it to say that the 741,657 new incorporations carries considerable double-counting and some counting of operating businesses as new. The effect of adjusting down that 741,657 figure for the purpose of measuring entries in the corporate legal form is to adjust down the interval used to compare with the Wells Fargo/NFIB estimate. A lower interval makes the fit between the two even more comfortable.

D M I Files Using the Dun's Market Indicator (DMI) files of the Dun & Bradstreet Corporation as cleaned by the U.S. Small Business Administration to produce the Small Business Data Base (SBDB), Kirchhoff calculated 814,190 entries for 1977-78 (Kirchhoff 1994, chap. 9). The annualized figure is therefore half. In effect, Kirchhoff developed his number by counting all businesses that entered the file for the first time during the two-year span after downward adjustments for such things as successor firms, large corporate spin-offs, and so forth. The DMI file is primarily a credit-reporting file. As noted earlier, many new and very small firms entered the file substantially after their birth or not at all. This was particularly true prior to the early 1980s, when D&B made a major effort to fashion a comprehensive file. Any comparison between Kirchhoff's SBDB based results and those of the Wells Fargo/NFIB Series suffer from a 15-year time gap. Still, if we compare the most substantial businesses from the Series (i.e., those most likely to appear in the Dun & Bradstreet file) with Kirchhoff's number, there is a similarity. The most substantial businesses in the Wells Fargo/NFIB Series are defined as those that have a business telephone number and employ someone other than the owner(s). That amounts to just over 400,000 de novo starts and 650,000 total entries. Given natural growth in the population since 1977-78 and the inherent problems in identifying (and therefore purging from the file) successor firms, the Kirchhoff calculation is consistent with estimates from the Wells Fargo/NFIB Series.

Nascent Entrepreneurs Paul Reynolds and a series of co-investigators used sample surveys similar to Wells Fargo/NFIB's to explore the prevalence of people trying to start businesses in the general adult population. H e dubbed these individuals "nascent entrepreneurs" or "entrepreneurs in gestation." To formally qualify as a nascent entrepreneur, an individual must report that he is trying to start a business and has already exhibited at least two behaviors (e.g., looked for facilities/equipment) that are typical of start-up activity. A Wisconsin sample and a national sample separately found the prevalence of nascent entrepreneurs

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to be about 4% (Reynolds 1995). In other words, at any point in time, about 7.5 to 8million adults are actively taking steps to go into business for themselves. Reynolds re-interviewed nascent entrepreneurs 12-18 months after the initial interview. The purpose was to determine the disposition of their plans and to obtain data on the sequencing and timing of additional start-up behaviors. He found the average planning time for the entire population (entrants and resignations) is somewhat over one year. Assuming one year, 7.5 to 8-million people a year are planning businesses. Two-thirds are entrants and one-third resignations. Thus, Reynolds numbers suggest over 5-million entrants (people) in a year, about 1.0 million fewer than Wells Fargo/NFIB. A precise numerical comparison between Reynolds' survey results and the Wells Fargo/NFIB data is tenuous at best. The Reynolds samples are quite small and therefore subject to large standard errors. Nonetheless, the two produce remarkably similar results. The difference is only about 15%, with small changes in any number of variables eliminating that gap.

Current Population Survey Segal calculated from CPS data that between 1983 and 1993 an average of 16% of all self-employed people (includes owners of corporations) were not self-employed the prior year. With 13-million self-employed people in 1993, the number of people who moved from other employment, unemployment, or out of the labor force into self-employment amounted to just over 2-million individuals. That is one-third the number of people estimated from data collected by the Wells Fargo/NFIB Series. The CPS data contains two characteristics important for present purposes as earlier reported: the data refer to the occupational/employment status that consumes the individual's activity throughout most of the year. That usually means their full-time activity for most of the year. In other words, 2-million people shifted into full-time business ownership during the year. The Wells Fargo/NFIB Series on Business Entries and Exits obtained data on the amount of hours/week an owner worked in his business during its first 30 days of operation. Just 45% claimed to work 40 hours per week or more. As a result, no more than about 2.8 million would be considered full-time. The resulting gap between the CPS and Wells Fargo/NFIB data is about 800,000. While the two concepts of full-time are not consistent between the data sets, reference to similar phenomena demonstrate that the CPS does not count a sizeable share of people entering business as self-employed, that is, as business owners. A second characteristic of the CPS is that the data do not pick up entries by individuals already self-employed. Thus, turnover (i.e., moving from one business to another and additional businesses formed by someone already in business cannot be located from CPS numbers. To account for the 800,000 gap requires that either turnover or multiple businesses affect one of every 16-full-time business owners. We do not know how many entries fit these two categories. However, Cooper et al. (1990) indicates that 14% or one in seven of his new business sample worked in their own business prior to opening their current venture. That alone accounts for approximately half of the 800,000 difference. Fourteen percent of the CPS base figure amounts to about 300,000. Thus, though the data sets are very different, their results are similar.

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TABLE 3 Form of Entry by Substance of Business Form of entry Business substance

Start

1. 2. 3. 4.

Bus tel, employer, not in home Bus tel, employer, in home Bus tel, not employer, not in home No bus tel, not employer, in home, works <40 hrs/wk in business

Purchase

Total*

8.1% 6.1 14.1

23.2% 8.4 7.6

11.2% 6.6 12.9

26.8

24.1

26.3

" The total includes the 1.5% who either asserted a different entry form or did not answer.

Why the Larger Entry Estimate? The principal difference between the results of the Wells Fargo/NFIB Series and prior attempts to measure business entry is that the former has been able to capture a segment of the entry population not previously measured. By locating and measuring formerly uncounted organizations, the Series is more comprehensive than prior efforts. Most of these previously uncounted organizations are very small. For example, less than half (47.5%) of the entries had a separate and distinct business telephone number in the first 30 days of operation; two out of three began in the home; three of four employed no one other than the owners (see Table 3). The table contains entries by various definitions of business "substance." The most substantial entries are those that employ someone other than the owner(s), are located outside the home, and have a business telephone number. The least substantial are those that are located in the home, have no separate telephone number, and employ no one other than the owner(s). In addition, the owner(s) must work less than 40 hours per week in the business. In between are various gradations, though the table does not present every permutation and combination. Only 11% of all entries fall into the most substantial class. The figure drops to 8% if only de n o v o starts are considered. Though firms in this class are the most substantial of the entry population, they are not necessarily very large. The most rigorous requirement for inclusion is that a firm employs someone other than the owner(s), and that could be just one other person. The last group contains the least substantial businesses. Not only do these businesses not have separate business telephone numbers, not employ anyone other than the owners, and conduct operations from the owner's home, but the owner must have worked in the business less than 40 hours per week during the first month of operation. Over one quarter of total entrants or l.l-million businesses fit this classification. It would be wrong to conclude that the exclusive reason the Wells Fargo/NFIB Series counts so many more entries than other sets is that it alone captures the smallest firms. The Series also counts more because it captures firms on a contemporaneous basis. If the population is growing as it presently is, counting entry on a contemporaneous basis rather than on a lag increases the relative number. If, on the other hand, the population is declining, the opposite occurs. Moreover, only the Wells Fargo/NFIB Series is likely to capture an entry with a rapid exit regardless of size. CONCLUSION There are vastly more business entries in the United States than is commonly believed. The number approximates 4.5 million compared to most prior estimates of less than

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1.0 million. The discrepancy lies primarily in the frenetic activity at the lowest end of the business size distribution. Figuratively, millions of unrecorded, and therefore uncounted, efforts are being made to form businesses. The Wells Fargo/NFIB Series captures them simply because it approaches the issue from a different perspective. It seeks to locate these businesses rather than waiting for their owners to self-report, often when they have no legal obligation to do so. These new numbers portray a significantly more intense business entry dynamic than previously thought. Birch (1987) once used the metaphor of a cloud to represent the dynamics of the business population. H e described it as a large, dark cloud drifting across the sky, but inside the placid, slow-moving exterior, chaos reigns. The Wells Fargo/NFIB data illustrate the extent of those chaotic conditions, at least the business entry-exit portion of them. The new numbers also provide a static result that was not necessarily sought. They emphasize the extent to which the size distribution of the business population is skewed to the bottom. Most of the time we ignore the millions of these small entries, whether for research or other purposes. They are difficult to locate, and we do not know how many there are. But, the data in the Wells Fargo/NFIB Series effectively sides with the more comprehensive counts, such as the IRS's Statistics of Income, over other government sources as being the most accurate reflection of the population. This result necessitates a more careful definition of the term "business" in everything from academic surveys to market segmentation of commercial activity. Over 6 million adults started a business in 1995. That is equivalent to 5% of the adult population. Some percentage of these, perhaps even a large percentage, have done so before. The Characteristics of Business Owners (U.S. Bureau of the Census survey 1992) indicates that about 15% of the self-employed (in the legal sense) previously owned at least one other business. Cooper et al. (1990), whose data included C-corporation owners, found that 26% in their sample of new business owners reported their highest level of management experience prior to their current business was ownership of another firm. These data indicate that a large portion involve first-time entrants. However, the compounding effect of even small annual percentages who have entered at least once before, imply that a significant portion of adult Americans have at some point in their lives attempted to start a business. The precise number is an empirical question, as is the percentage of people who have not personally tried to start a business, but who have lived in a household with someone undergoing the experience. All this suggests that business entry is a familiar experience for large segments of the American population, and that common experience must produce effects of which we are now little informed. If there are more starts than previously recognized, there are also more exits. And if there are more exits, questions associated with their cause become more conspicuous and pressing--and so do questions associated with their consequences. These are not new issues. Entrepreneurship education, for example, is clearly a growth industry and is intended to help people assess potential entry opportunities and avoid at least the most disastrous exits. But when placed in the context of the new entry data, a need arises to revisit questions concerning the distribution of resources. Our understanding of the population from an empirical perspective is very different than we thought it was. That alone urges a re-examination. The larger issue these new data reflect is the restructuring of the American economy and, in its wake, the American society. They argue that the restructuring is oc-

MORE THAN YOU THINK: AN INCLUSIVE ESTIMATE 195 curring even faster and more tumultuously than previously realized. They also argue that the restructuring is more pervasive than most imagine. Yet, what are the consequences? With that question we can let our imaginations wander unimpeded, and we still might not be able to develop a reasonably comprehensive list of the plausible possibilities. Think: Do we see the demise of economically rational man? Will wealth be traded for life-style? Will most of us become independent contractors? Has the traditional idea of "employee" and "employer" outlived its usefulness? Is economic security as we know it a dead issue? From where will personal and national economic stabilizing systems come? What will those systems be? How small can our businesses become and still be economically competitive, both on a national and individual basis? How will "career paths" change? Will business ownership prove "family friendly" or "family hostile"? Will increased entries induce us as a people to become more civic-minded, or less? Are the "basics" to be taught in our educational system compatible with the needs of an entrepreneurial society? How do we teach change in institutions that largely have not changed in a thousand years'? What is lifetime education for entrepreneurs and how will it be financed? Will our personal mobility be affected by increased self-employment? Where will population growth occur: nice places to live or places with synergy and traditional economic advantage? Will the most efficient mechanisms that ensure capital reaches the sector change? What happens to those who cannot adapt to accelerated change, less economic security, and a more entrepreneurial environment? Researchers have begun to document both the changes that are occurring in selfemployment and in business formation and their ties with associated phenomena such as employment change. An understanding of the implications of these changes is still a long way off.

A Final Note The Wells Fargo/NFIB Series on Business Entries and Exits contains a number of variables not discussed in this article. Most are related to personal characteristics of the individual involved, for example, income and education. The series is midway through its second year of data collection. New questions were added in 1996 to investigate additional financing issues. They focus on the amount of money saved, borrowed, or otherwise raised to open the business and on the amount of time it took to procure that money. In addition, one question requests the precise month in which the first positive cash flow was attained and the relative importance of financing in the entry process. The author also expects to gather more useful industry information than has been obtained to date. The title of this data series contains the word "Exits." A set of questions paralleling the entry questions are posed of people who have closed, sold, transferred, or allowed a business to become inactive over the last six months. The results of these data should be accessible shortly. The micro-data of this series are available to researchers who wish to study the entry and exit process.

REFERENCES Aldrich, H., Kalleberg, A., Marsden, P., and Cassell, J. 1989. In pursuit of evidence: Sampling procedures for locating new businesses. Journal of Business Venturing 4(6):367-386.

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Armington, C. 1986. Entry and exit of firms: An internationalcomparison. Paper presented at the U.K. Conference on Job Formation and Economic Growth, London, March. Mimeo. Birch, D. 1987. Job Creation in America: How Our Smallest Companies Put the Most People to Work. New York: The Free Press. Birch, D. 1979. The Job Generation Process. Cambridge, MA: M.I.T. Program on Neighborhood and Regional Change. Mimeo. Birley, S. 1984. Finding the new firm. Proceedings of the Academy of Management Meetings 47:64-68. Busenitz, L., and Murphy, G. 1996. New evidence in the pursuit of locating new businesses. Journal of Business Venturing 11(3):221-231. Carter, N., Gartner, W., and Reynolds, P. 1996. Exploring start-up event sequences. Journal of Business Venturing 11(3):151-166. Cooper, A., Dunkelberg, W., Woo, C., and Dennis, W. 1990. New Business in America: The Firms & Their Owners. Washington, DC: The NFIB Foundation. Davis, S., Haltiwanger, J., and Schuh, S. 1993. Small business and job creation: Dissecting the myth and reassessing the facts. Working Paper No. 4492. Cambridge, MA: National Bureau of Economic Research. Dennis, W., Dunkelberg, W., and Dial, T. 1996. Measuring business formations and dissolutions: A new time series. In W. D. Bygrave, et al., eds., Frontiers"of Entrepreneurship Research. Wellesley, MA: Center for Entrepreneurial Studies, Babson College. Dun & Bradstreet Corporation, New Business Incorporations, monthly, mimeo. Dun & Bradstreet Corporation. 1996. Business Failure Record, 1994. Wilton, CT: Dun & Bradstreet Corporation. Dunne, T., and Roberts, M. 1991. The duration of employment opportunities in U.S. manufacturing. The Review of Economic and Statistics 21(2):216-227. Dunne, T., Roberts, M., and Samuelson, L. 1988. Patterns of firm entry and exit in U.S. manufacturing industries. RAND Journal of Economics 19(4):495-515. Evans, D., and Leighton, L. 1989. Small-Business Formation by Unemployed Workers. Washington, DC: U.S. Small Business Administration, Office of Advocacy. Mimeo. Kirchhoff, B. 1994. Entrepreneurship and Dynamic Capitalism: The Economics of Firm Formation and Growth. Westport, CT: Praeger. Reynolds, P. 1995. The national study of U.S. business start-ups: Background and progress report. Paper presented at the Conference on Dynamics of Employment and Industry Evolution, January 19-21. Mannheim, Germany. Mimeo. Reynolds, P. In press. Who starts new firms? Preliminary explorations of firms-in-gestation.Small Business Economics. Segal, L. 1996. Flexible employment: Composition and trends. Journal of Labor Research XVII(4);525-542. Star, A., and Narayana, C. 1983. Do we really know the number of small business starts. Journal of Small Business Management 21(4):44---48. U.S. Bureau of the Census. 1996. Statistical Abstract of the United States, 1995. Washington, DC: Government printing office. U.S. Bureau of the Census. 1992.1987-Characteristics of Business Owners. CBO87-1. Washington, DC: Government Printing Office. U.S. Internal Revenue Service. Statistics oflncome. Washington, DC: Government Printing Office. U.S. Small Business Administration. 1995. State of Small Business: A Report to the President. Washington, DC: Government Printing Office.