TECHNICAL REPORT UCED 2005/06-11

NASCENT ENTREPRENEURSHIP PREVALENCE IN RURAL AREAS

UNIVERSITY OF NEVADA, RENO

NASCENT ENTREPRENEURSHIP PREVALENCE IN RURAL AREAS

Elizabeth Fadali Thomas R. Harris

Elizabeth Fadali is a Research Associate in the University Center for Economic Development and the Department of Resource Economics at the University of Nevada, Reno. Thomas R. Harris is a Professor in the Department of Resource Economics and Director of the University Center for Economic Development at the University of Nevada, Reno.

October 2004

UNIVERSITY OF NEVADA RENO

The University of Nevada, Reno is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, color, religion, sex, age, creed, national origin, veteran status, physical or mental disability, and in accordance with university policy, sexual orientation, in any program or activity it operates. The University of Nevada employs only United States citizens and aliens lawfully authorized to work in the United States.

This publication, Nascent Entrepreneurship in Rural Areas, was published by the University Center for Economic Development in the Department of Resource Economics at the University of Nevada, Reno. Funds for this publication were provided by the University of Nevada Agricultural Research Station and the United States Department of Commerce Economic Development Administration under University Centers Program contract #07-66-05671. This publication's statements, findings, conclusions, recommendations, and/or data represent solely the findings and views of the authors and do not necessarily represent the views of the University of Nevada Agricultural Research Station, the U.S. Department of Commerce, the Economic Development Administration, University of Nevada, Reno, or any reference sources used or quoted by this study. Reference to research projects, programs, books, magazines, or newspaper articles does not imply an endorsement or recommendation by the authors unless otherwise stated. Correspondence regarding this document should be sent to:

Thomas R. Harris, Director University Center for Economic Development University of Nevada, Reno Department of Resource Economics Mail Stop 204 Reno, Nevada 89557-0105 Phone: 775/784-6499

UCED University of Nevada, Reno Nevada Cooperative Extension Department of Resource Economics

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Nascent Entrepreneurship Prevalence in Rural Areas This article examines prevalence rates of entrepreneurship in various types of rural counties in the United States, using the Panel Study of Entrepreneurial Dynamics dataset and county codes developed by the Economic Research Service of the USDA. In addition, rates of entrepreneurship are calculated and compared for each of the four Census regions. The Panel Study of Entrepreneurial Dynamics provides a national database that systematically examines the business start-up process. An initial screening of 64,622 households was used to locate people who were starting new businesses. Detailed followups of those individuals who fit the profile of nascent entrepreneur were then carried out. For the purposes of this article only the screening portion of the database is used. The screening portion of the database can be used to find the proportion of the population involved in entrepreneurial activities1. The Economic Research Service of the USDA has created several different county coding systems for rural counties. One, the so-called Beale code, assigns a number from 1 to 9 to each county in the United States based on its place in an urban to rural continuum. The county typology codes, on the other hand, assign rural counties to such economic types as farming, mining, services and so forth. In addition, the typology codes assign rural counties to different policy types such as “retirement destination” or “federal lands”.2 The rural-urban continuum codes use the Office of Management and Budget (OMB) official assignment of counties to metro or non-metro status as a starting point. The OMB definitions are in turn developed using population and commuting information from the 2000 Census. The rural-urban continuum codes then use the population size of a metro area to classify metro counties into one of three categories: 1 for counties in a metro area with a population of 1 million or more, 2 for counties in a metro area with a population in the range of 250,000 to 1 million and 3 for counties in a metro area with a population less than 250,000. Population size is defined by the population in the associated Metropolitan Statistical Area. The rural part of the continuum, used to classify the OMB non-metro counties, is somewhat more complex. It takes into account the size of the urban population in the county as well as whether or not the county is considered to be functionally adjacent to a metro area. Adjacency is defined as physical adjacency to a metro area combined with at least a 2% commuting rate of the county labor force to the adjacent metro area. Category 4 corresponds to a non-metro county with an urban population of at least 20,000 adjacent to a metro area. Category 5 denotes a non-metro county with urban population of at least 20,000 that is not adjacent to a metro area, category 6, an urban population from 2500 to 19,999 adjacent to a metro area, 7 an urban 1

See Reynolds, P., N.M. Carter, W.B. Gartner, P.G. Greene and L.W. Cox. 2002. "The Entrepreneur Next Door, Characteristics of Individuals Starting Companies in America, An Executive Summary of the Panel Study of Entrepreneurial Dynamics." Ewing Marion Kauffman Foundation. Data and documentation for the project is available on-line at http://projects.isr.umich.edu/psed/index.cfm. 2 See Beale, C. 2003. "Measuring Rurality: Rural-urban Continuum Codes." Economic Research Service, United States Department of Agriculture. and Economic Research Services. 2003a. "Measuring Rurality: County Typology Codes." United States Department of Agriculture.

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population from 2500 to 19,999 not adjacent to a metro area, 8, an urban population of 2500 or less adjacent to a metro area and finally, category 9 denotes a county with an urban population of 2500 or less that is not adjacent to a metro area. County typology codes classify rural counties by primary economic activities and by policy type. These codes are defined only for counties that were defined as non-metro in 1993. Counties can be designated by only one of the six different primary economic activity codes. All but seventeen of the non-metro counties have been assigned an economic code. The seventeen without an economic code could not be coded because of data suppression issues. The different economic types are as follows: farming-dependent, mining-dependent, manufacturing-dependent, government-dependent, services-dependent and non-specialized counties. This last category includes all categorizable non-metro counties that did not fit the definitions for any of the other economic types. Policy type codes, in contrast to the economic type codes, are non-exclusive, that is, a county may have more than one policy type designation. The different policy types distinguished by the code are retirement destination counties (15% or greater increase in population over 60 years of age from 1980 to 1990 due to in-migration), Federal lands counties (Federally-owned lands make up 30% or more of the county land area in 1987), commuting counties (over 40% of workers in 1990 commuting to jobs in other counties), persistent poverty counties (poverty rates of 20% or higher in 1960, 1970 and 1990) and transfers-dependent counties (economies heavily dependent on government transfer payments such as social security, unemployment insurance, welfare benefits and so forth). In addition to the county types discussed above, the difference in prevalence rates by region is examined. For this purpose the four Census Regions defined by the Census Bureau are used: Northeast, South, Midwest and West. See Figure 1 for a map of the states in each region. Figure 2 is a map of the United States showing which counties have been defined as metropolitan by the OMB. In determining prevalence rates for business start-ups, this article follows the definition used in Reynolds, et al. 2002. Nascent entrepreneurs are defined as respondents who answer yes to either of the following questions during the telephone screening survey: 1. Are you, alone or with others, now trying to start a new business? 2. Are you, alone or with others, now starting a new business or new venture for your employer? An effort that is part of your job assignment? In addition, the respondent must satisfy two other criteria, namely that they have been active in start-up activities during the last 12 months and that they will own all or part of the new business.3 3

The variable in the PSED dataset that encapsulates this definition is SUOWNACT. 2010 observations from one of the control subgroups are dropped because they have no data on business start-up activity. Existing weights are then recentered as described in Curtin, R. 2003. "Computation of Weights Presentation, Panel Study of Entrepreneurial Dynamics." University of Michigan.

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Figure 1. Map of Four Census Regions4

Findings In general, counties classified as metropolitan had higher prevalence rates for nascent entrepreneurship. Using the 2003 definitions, counties classified as metropolitan had a 6.15% prevalence rate compared to a rate of 4.75% in counties classified as nonmetropolitan (Figure 1). The difference was significant at the .01% level. Prevalence rates across the rural-urban continuum codes show a general trend downward as the size of the metropolitan or urban population in the county decreases (Figure 2). The exception is the final category nine, counties with an urban population of 2500 or less not adjacent to a metropolitan area. However, confidence intervals are especially large for these last two categories because of the smaller number of observations available, so the difference is not statistically significant. Using the .05 criteria, category one counties (metropolitan area with greater than one million population) have a significantly higher percentage of nascent entrepreneurs than all other categories of counties.

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Map created on the U.S. Census Bureau website with American Factfinder at http://factfinder.census.gov/servlet/ReferenceMapFramesetServlet?_lang=en.

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Figure 2. Map of Metro and Non-metro Counties5

Figure 3. Prevalence Rate of Nascent Entrepreneurs in Metropolitan and Non-Metropolitan Counties 6.50

6.15

%Nascent Entrepreneurs

6.00

5.50

5.00

4.75 4.50 nonmetro

metro

Metro Versus Non-Metro Counties 2003 Cases weighted by WTEXPERI

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Map from Economic Research Service at http://www.ers.usda.gov/Briefing/Rurality/WhatisRural/

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Figure 4. Prevalence Rates of Nascent Entrepreneurs By County Rural Urban Continuum Codes 7.00 6.64

6.50

% Nascent Entrepreneurs

6.00 5.50

5.55 5.30

5.32

5.00 4.91

4.77

4.50

4.51

4.41

4.00 3.91 3.50 1

2

3

4

5

6

7

8

9

2003 Rural-urban Continuum Code Cases weighted by WGTBEAL

Figure 5. 95% Confidence Intervals for Nascent Entrepreneurship By Rural Urban Continuum Code for County of Residence .080

95% CI % Nascent Entrpreneurs

.070

.060

.050

.040

.030 .020 1

2

3

4

5

6

7

8

9

2003 Rural-urban Continuum Code Cases weighted by WGTBEAL

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Table 1. Confidence Intervals for Prevalence Rates of Nascent Entrepreneurs by Rural Urban Continuum Weighted Observations 2003 RuralUrban Continuum Code

Entrepreneur

1 2 3 4 5 6 7 8 9

Total

1,918 727 375 211 69 185 111 27 43

% Entrepreneurs

28,879 13,084 7,077 3,960 1,454 4,095 2,505 690 870

95% Confidence Interval Lower Upper Bound Bound

6.64% 5.55% 5.30% 5.32% 4.77% 4.51% 4.41% 3.91% 4.91%

6.35% 5.16% 4.77% 4.62% 3.67% 3.88% 3.61% 2.46% 3.47%

6.93% 5.95% 5.82% 6.02% 5.87% 5.15% 5.22% 5.36% 6.35%

Prevalence rates of nascent entrepreneurship in rural counties of differing economic type are shown in Figure 4. Non-metropolitan counties whose economies are dominated by the government sector have the highest prevalence of nascent entrepreneurs. Confidence intervals are shown in Figure 5. Both services and government dependent counties are not significantly different from the metropolitan counties in percentage of nascent entrepreneurs. Metropolitan counties have a higher prevalence rate than unclassified, farm, mine, manufacturing-dependent or non-specialized counties. Figure 6. Prevalence Rates of Nascent Entrepreneurs By County Economic Type

% Nascent Entrepreneurs

7.00 6.00

6.25

6.16 5.37

5.00

4.88 4.52

4.00

4.19

4.20

3.00 2.00 1.90 1.00

ed

g rin tu

ifi

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ve go

ss la

ac uf an m

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rm fa

tc no

County Economic Types Cases weighted by WGTECON

8

95% CI %Nacent Entrepreneurs

Figure 7. 95% Confidence Intervals for Nascent Entrepreneurship By County Economic Type .08

.06

.04

.02

0.00 -.02

t

rin

en

tu

ed ifi

g

ro et ed m liz ia ec sp nno s

e ic rv se

ac

nm

uf

e

an

in

rm

r ve go

m

m

fa

ss la tc no

Economic Types Cases weighted by WGTECON

Table 2. 95% Confidence Intervals for Prevalence Rates of Nascent Entrepreneurs by County Economic Type Economic Type Not Classified Farm Mine Manufacturing Government Services Nonspecialized Metro

Weighted Observations Entrepreneur Total

% Entrepreneurs

3 60 34 211 119 159 167

144 1,427 813 4,657 1,899 2,956 3,421

1.90% 4.19% 4.20% 4.52% 6.25% 5.37% 4.88%

2912

47,295

6.16%

95% Confidence Interval Lower Upper Bound Bound -0.36% 4.16% 3.15% 5.23% 2.81% 5.58% 3.93% 5.12% 5.16% 7.34% 4.56% 6.19% 4.88% 5.60% 5.94%

6.37%

Below the prevalence rate of nascent entrepreneurs for counties of various policy types is compared. Rates in all but the transfers-dependent counties are higher than the average for non-metro counties (note that not all non-metro counties are assigned to a policy type).6 An examination of the 95% confidence intervals in Table 3 indicates that the transfers-dependent counties are the only policy type that can be said to have a significantly lower prevalence of nascent entrepreneurs than metropolitan counties.

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The 1993 definition of metropolitan and non-metropolitan counties is used here to more closely fit the policy definitions.

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10.00% 9.00% 5.92% 6.03% 5.46% 8.00% 5.57% 4.72% 6.16% 7.00% 4.90% 6.00% 5.00% 4.00% 3.00% 2.00% 1.00% 0.00% N on

et

an

s-

nt

93

en

r ty

nd

ve

pe

19

De

g

ds

Po

in

ro

er

te

ut

t

an

en

lL

et m

ro

sf

is rs

m om

M

Tr

Pe

C

m

ra

ir e

de

et

Fe

R

% Nascent Entrepreneurs

Figure 8. Prevalence Rates of Nascent Entrepreneurs By County Policy Type

t

County Policy Type

Table 3. 95% Confidence Intervals for Prevalence of Nascent Entrepreneurs by County Economic Type Weighted Observations Policy Types Retirement Federal Lands Commuting Persistent Poverty Transfers-Dependent Metro Nonmetro 1993

Entrepreneur 92 100 105 134 91 2,912 751

Total 1,653 1,690 1,742 2,453 1,928 47,295 15,317

% Entrepreneurs 5.57% 5.92% 6.03% 5.46% 4.72% 6.16% 4.90%

95% Confidence Interval Lower Bound Upper Bound 4.46% 6.67% 4.79% 7.05% 4.92% 7.16% 4.57% 6.37% 3.75% 5.64% 5.94% 6.37% 4.57% 5.24%

The definitions of metropolitan and non-metropolitan counties in 1993 and 2003 have changed quite substantially. Because the analysis above used both the 2003 and 1993 definitions, in keeping with the definitions for rural-urban continuum codes and the typology codes respectively, we offer a closer look at the differences with respect to prevalence rates below. A total of 298 formerly non-metro counties have been reclassified as metro both because of changes in the OMB definitions and because of population growth. 45 metro counties have been reclassified as non-metropolitan, mainly because of changes in the classification rules. The rule change with the most influence with regard to these counties was an increase in the level of commuting required for classification as an outlying metro

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county from 15% to 25% of the workforce.7 Table 4 shows that the lowest percentage of entrepreneurs are in counties that were formerly classified as metro but are now nonmetropolitan (4.33%) and the highest percentage of entrepreneurs are found in the counties that have maintained the metro classification throughout (6.19%). Counties that were formerly classified as non-metropolitan in 1993 but that are now classified as metropolitan have a prevalence rate of 5.55%. Overall, prevalence rates for nonmetropolitan areas are smaller (4.75% for 2003 versus 4.9% for 1993) using the 2003 definition. The 2003 definitions may more closely reflect which counties are now metropolitan in character when the PSED data was collected in 1998 and 1999 but the influence of the definition change is hard to quantify. Table 4. Prevalence Rates of Nascent Entrepreneurs by 2003 and 1993 Metropolitan Classification Weighted Observations 2003 Metro

1993 Metro

Nonmetro 2003

Nonmetro 1993 Metro 1993 Total Nonmetro 2003 Nonmetro 1993 Metro 1993 Total Metro 2003 Nonmetro 1993 Metro 1993 Total

Metro 2003

Total

Entrepreneurs

Total

95% Confidence Interval Lower Upper Bound Bound 4.41% 5.15%

611

12,794

% Nascent Entrepreneurs 4.78%

34 645

779 13,573

4.33% 4.75%

2.90% 4.39%

5.76% 5.11%

140

2,523

5.55%

4.66%

6.45%

2,878 3,018

46,516 49,039

6.19% 6.15%

5.97% 5.94%

6.41% 6.37%

751

15,317

4.90%

4.56%

5.25%

2,912 3,663

47,295 62,612

6.16% 5.85%

5.94% 5.67%

6.37% 6.03%

Regional Differences Clear differences in prevalence rates of nascent entrepreneurs were apparent in comparing metropolitan and non-metropolitan counties of different regions. Within the metro counties the highest prevalence rate is in the West (7.24%) and the lowest is in the Midwest (4.99%). Similarly, within non-metro counties, the highest prevalence rate is in the West (6.36%) and the lowest is in the Midwest (3.96%). In each of the four regions, metro areas had a greater prevalence rate of nascent entrepreneurs than non-metro areas although the difference was not significant for the Western and Northeastern Regions. The largest difference in prevalence rates between a region’s metropolitan and nonmetropolitan counties occurred in the South (6.63% versus 4.80%).

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Economic Research Services. 2003b. "Measuring Rurality: New Definitions in 2003." United States Department of Agriculture.

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Figure 9. Prevalence Rates of Nascent Entrepreneurs By Region, Metro and Non-metro

% Nascent Entrepreneur

8.00 7.00

7.24 6.63

6.36

6.00 5.50

5.00

5.05

4.99

4.80

4.00 3.96 3.00 t es W t ro es et W M ro et -m t on es N w t id M es w ro id et M M ro et -m on th N u So h ro ut et So M ro et -m st on ea h N t st or ea N ht ro or et N M ro et -m on

N

Metro and Non-metro by Region Cases weighted by REGNWGT

95% CI Nascent Entrepreneur

Figure 10. 95% Confidence Intervals for Nascent Entrepreneurship By Region, Metro and Nonmetro .09 .08 .07 .06 .05 .04 .03 t es W t ro es et W M ro et -m t on es N w id t M es w ro id et M M ro et -m on N th u So h ro ut et So M ro et t -m as on e th st or ea N

ro et

ro et

N

-m on

M

N

N

th or

Metro and Non-metro by Region Cases weighted by REGNWGT

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Table 5. 95% Confidence Intervals for Prevalence of Nascent Entrepreneurs by County Economic Type Weighted Observations Region Non-metro Northeast Metro Northeast Non-metro South Metro South Non-metro Midwest Metro Midwest Non-metro West Metro West

98 607 259 1,076 179 531 110

1,943 11,020 5,388 16,231 4,520 10,650 1,722

5.05 5.50 4.80 6.63 3.96 4.99 6.36

95% Confidence Interval Lower Bound Upper Bound 4.07 6.02 5.08 5.93 4.23 5.37 6.25 7.02 3.39 4.53 4.58 5.40 5.21 7.52

806

11,138

7.24

6.76

Entrepreneur

Total

% Entrepreneurs

7.72

References Beale, C. 2003. "Measuring Rurality: Rural-urban Continuum Codes." Economic Research Service, United States Department of Agriculture. Curtin, R. 2003. "Computation of Weights Presentation, Panel Study of Entrepreneurial Dynamics." University of Michigan. Economic Research Services. 2003a. "Measuring Rurality: County Typology Codes." United States Department of Agriculture. ---. 2003b. "Measuring Rurality: New Definitions in 2003." United States Department of Agriculture. Reynolds, P., N.M. Carter, W.B. Gartner, P.G. Greene and L.W. Cox. 2002. "The Entrepreneur Next Door, Characteristics of Individuals Starting Companies in America, An Executive Summary of the Panel Study of Entrepreneurial Dynamics." Ewing Marion Kauffman Foundation.

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