entrepreneurship and employment

1

Entrepreneurship and Employment

Michael Fritsch

3rd Summer School on “Knowledge Dynamics, Industry Evolution, and Economic Development”, Nice (France)

July 11, 2014

Contact: Prof. Dr. Michael Fritsch, Friedrich Schiller University Jena, Carl-Zeiss-Str. 3, Room 5.12Phone (03641) 9 – 432 20, [email protected]://www.wiwi.uni-jena.de/uiw/index.html

Fritsch: Entrepreneurship and Economic Development, 3rd KID Summer School, Nice, July 11, 2014

mailto:[email protected]

This lecture is based on

Basic source: Fritsch, Michael (2013): New business formation and regional development - A Survey and Assessment of the Evidence. Foundations and Trends in Entrepreneurship, 9, 249–364.

Recent research papers:

Fritsch, Michael and Florian Noseleit (2013): Investigating the Anatomy of the Employment Effect of New Business Formation. Cambridge Journal of Economics, 37, 349-377.

Fritsch, Michael and Florian Noseleit (2013): Start-Ups, Long- and Short-Term Survivors, and their Contribution to Employment Growth. Journal of Evolutionary Economics, 23, 719–733.

Fritsch, Michael and Florian Noseleit (2013): Indirect Employment Effects of New Business Formation Across Regions: The Role of Local Market Conditions. Papers in Regional Science, 92, 361-382.

Fritsch: Entrepreneurship and Economic Development, 3rd KID Summer School, Nice, July 11, 2014 2

3

Main topics

1. Development of the research field

2. Theoretical and conceptual considerations

3. Results of empirical research

4. Implications for entrepreneurship policy

5. Avenues for further research


Joseph A. Schumpeter

Schumpeter wanted to identify the sources of economic growth. He identified entrepreneurs who revolutionized the economy by introducing radical innovation. But these Schumpeterian entrepreneurs are very, very few!

My question: What is the effect of new business formation in general on economic development?


5

The ‚Birch‘-debate

Initiated by a study of David Birch: The Job Generation Process, Boston 1979: MIT (mimeo).

Main statements of this study:

Large firms in the USA have massively reduced employment during the 1970s.

In the same time period small firms in the USA have created many new jobs.

A relatively large contribution to employment growth came from the service sector and from new businesses.

The Birch-Study induced many empirical analyses of job generation by small and new firms and a long-lasting debate about the role of small businesses, particularly new businesses, in the economy.


6

New business formation and the market process

Start-ups or market entries

Market process (selection)

Exiting capacities: Decline or closure of

incumbents

New capacities:

Development of new

businesses

Supply-side effects:

Securing efficiency

Acceleration of structural change

Amplified innovation

Greater variety

Improvedcompetitiveness

Growth


New businesses

Growth

Incumbent firms

Direct effect

Indirect effect

Direct and indirect effects of new businesses on growth


7

Hypothesis: The indirect effect of new business formation is much larger and more important than the direct effect (= development of the start-ups).

Direct and indirect effects of new business formation on economic development

A positive effect of new business formation on employment can only result from the supply-side effects which occur rather indirectly.

If competition does not work according to a survival of the fittest scenario then the supply-side effect of new business formation can well be negative.

Not all start-ups will have the same effect on economic growth. It is particularly those start-ups that exert a strong challenge on incumbents (e.g. innovative start-ups) that have a main effect on growth.

The indirect effect will be the larger, the more productive / innovative the reaction of the incumbents.

The effects may be rather different across industries and regions.


8

Factors that may determine the effect of new business formation on regional development


9

New businesses

Regional growth

Incumbent firms

Qualification of the workforce

Stage of the industry

lifecycle

Size of the region and density of

actors

Regional knowledge base

Quality of other inputs

Industry-specific conditions

Entry and exit

barriers

Regional environment

Location and accessibility

Supportive infrastructure for start-ups

Regional ‘culture’ of entrepreneurship

Number and size of

regional competitors

Market structure and intensity of competition

Thickness of local input

markets

10

Approaches to analyze the effect of new firm formation on economic development empirically

Cohort analysis.

Correlation and regression analysis (cross section, longitudinal) of the relationship between new firm formation rate and growth

at an industry level

at a regional level

Including new firm formation / entrepreneurship into a regional production function.

Dependent variable: employment, GDP, productivity (for smaller regions the available information on employment is most reliable).


Number of firms

Time

Number of firms

Number of exits

Number of entries

Net entry

Shake out

‘Entrepreneurial‘ regime ‘Routinized‘ regime

Stylized paths in the numbers of entries, exits, and firms over the industry lifecycle



Analyzing the lag-structure of the effect of new businesses on employment – basic approach (Fritsch &

Mueller, 2004)

Regional employment change (%) t0 =

a + b1 start-up rate t0 + b2 start-up rate t-1

+ b3 start-up rate t-2 + b4 start-up rate t-3 + …

+ b11 start-up rate t-10 + cn Xn + u

Xn = further determinants,

u = stochastic error term

Method: Fixed-effects panel regression.

13

Effects of new firm formation on employment change over time – third-order polynomial

0

Impa

ct o

f new

firm

form

atio

n on

em

ploy

men

t cha

nge

0 1 2 3 4 5 6 7 8 9 10

Lag (year)

I

II

IIINew capacities

Supply-side effects

Exiting capacities

Source: Fritsch and Mueller (2004).Fritsch: Entrepreneurship and Economic Development, 3rd KID Summer School, Nice, July 11, 2014


Evolution of employment in entry cohorts (all private industries)

employment

survival

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

Per

cent

age

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Age (Year) Source: Schindele and Weyh (2011).


Direct effect

Regional data about employment cohorts of new businesses is used to analyze the direct effect.

Largest impact on total employment changewhen the new businesses enter the market.

Small positive contribution one year after start-up.

Slightly negative impact in later periods.


Indirect effectsEmpirical strategy:

Regress employment change of incumbents on start-up rate of the year t=0 and of each of the preceding ten years (t-1 to t-10) indirect effect

Compute the average percentage employment change of the indirect effect“Reassemble” the overall effect

17


Fritsch & Noseleit (2013): The employment effect of short-term and long-term survivors on regional growth


Results and conclusions

Indirect effects are quantitatively much larger than direct effects. A large part of the “Birch-debate” was misleading.

The effect may differ by type of start-up.

Short-term survivors have no significant positive effect.

The effect differs considerably by the size of the entry.

Positive effects of new business formation on economic development occur with a considerable time-lag. Long-term policy orientation needed!

Policy should not interfere with the process of market selection. No significant subsidization of new businesses after start-up!

Presumably, the quality of start-ups with regard to challenging the incumbents is important for their effects. Try to increase the quality of start-ups and/or focus on higher quality start-ups!

What makes the “quality” of a start-up?

Tautological definition: The higher the challenge for the incumbents the higher the quality of the start-up.

The quality of a new business is indicated by:

Ex ante indicators:

Innovativeness of the supplied goods and services (e.g., high tech manufacturing, knowledge intensive services, etc.) ;

Qualification of the entrepreneur (e.g., academic start-ups);

Main motivation for starting a business (e.g., ‘opportunity’ versus ‘necessity’ entrepreneurship; part time versus full time entrepreneurship);

Growth ambitions (e.g., growth oriented versus non-growth oriented new businesses);

19


What makes the “quality” of a start-up? (continued)

Ex ante indicators (continued):

Amount and quality of the employed resources (e.g. size of start-up, team start-up, ability to attract VC, …);

Productivity of start-up as compared to incumbents;

…

Ex post indicators:

Survival over a certain period of time;

Growth (e.g. ‘gazelles), size, market share after a certain time period ;

…

20


21

The relationship between start-up rate and regional employment change

-4-2

02

4

Ave

rage

cha

nge

of e

mpl

oym

ent i

n %

4 6 8 10

Average start-up rate

Oberland

Oberfranken-OstEmscher-Lippe

Ingolstadt

Dortmund

Brunswick

Cologne

Duisburg

Munich Bonn

Median value

Median value-4

-20

24

Ave

rage

cha

nge

of e

mpl

oym

ent i

n %

4 6 8 10

Average start-up rate

Oberland

Oberfranken-OstEmscher-Lippe

Ingolstadt

Dortmund

Brunswick

Cologne

Duisburg

Munich Bonn

Median value

Median value


22

Effects of new firm formation on employment change in different types of region (West Germany)

Source: Fritsch and Mueller (2008).


Agglomeratedregions

Moderatelycongested regions

Ruralregions

-0.40

-0.20

0.00

0.20

0.40

Impa

ct o

f ne

w b

usi

ness

form

atio

non

em

plo

ymen

t ch

ange

0 1 2 3 4 5 6 7 8 9 10Lag (year)

Agglomeratedregions

Moderatelycongested regions

Ruralregions

-0.40

-0.20

0.00

0.20

0.40

Impa

ct o

f ne

w b

usi

ness

form

atio

non

em

plo

ymen

t ch

ange

0 1 2 3 4 5 6 7 8 9 10Lag (year)

23

Impact of new firm formation on employment change – England vs. Scotland and Wales

Scotland

England

Wales-0.9

-0.6

-0.3

0.0

0.3

0.6

0.9

1.2

1.5

Imp

act

of

ne

w f

irm

form

atio

no

n e

mp

loym

en

t ch

ang

e

t t-1 t-2 t-3 t-4 t-5 t-6 t-7 t-8Start-up rate

Scotland

England

Wales-0.9

-0.6

-0.3

0.0

0.3

0.6

0.9

1.2

1.5

Imp

act

of

ne

w f

irm

form

atio

no

n e

mp

loym

en

t ch

ang

e

t t-1 t-2 t-3 t-4 t-5 t-6 t-7 t-8Start-up rate

Source: Mueller, van Stel and Storey (2008).



The effect of new business formation on regional employment in urban and rural in the Netherlands

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

0 1 2 3 4 5 6 7 8

Urban Rural

Source: Van Stel & Suddle (2008)


Regional differences I

Direct effect


Regional differences II

Indirect effects


Why Does the Effect of New Business Formation Differ Across Regions ? Estimation approach (Fritsch

& Schroeter, 2011)

Eit=0 / Eit-2 = a + b1 * average start-up rateit

+ b2 * average start-up rate2it

+ b3 * control variableit

+ b4 * control variableit * average start-up rateit

+ b5 * control variableit

+ b6 * control variableit * average start-up rateit

+ b7 * average start-up rate in adjacent regions it + u.

Pure cross-section regressions using regional average values.


Marginal effect of start-ups on employment change -.

01

0.0

1.0

2

Marg

inal e

ffect of st

art

-up r

ate

5 6 7 8 9Start-up rate

Marginal effect of start-up rate 95% Confidence interval

Dependent variable: employment change

Marginal effect of start-up rate on employment change

Source: Fritsch & Schroeter (2011)


Marginal effect of start-ups on employment change with different levels of population density

-.005

0.0

05

.01

.015

.02

Marg

inal e

ffect

of st

art

-up r

ate

4 5 6 7Population density

Marginal effect of start-up rate 95% Confidence interval

Dependent variable: employment change

Marginal effect of start-up rate on employment change as the population density changes

Source: Fritsch & Schroeter (2011)


The Role of Local Market Conditions for the Indirect Employment Effects (Fritsch & Noseleit, 2013)

Results

The indirect employment effect of new business formation is more pronounced

in areas with relatively high population density than in less density regions.

in small business regions than in large business regions.

in regions characterized by a high concordance between the industry structures of start-ups and local incumbents than in regions where the correspondence of the industry structure of newcomers and incumbent firms is relatively low.

in small business regions where there is also high similarity between the industry structure of start-ups and incumbents than in large business regions with high similarity.


Speculations: Why are the indirect effects so much higher in agglomerations ?

Higher share of high quality start-ups in agglomerations because of

higher qualification of the workforce?

higher level of knowledge spillovers?

higher level of cultural, technological and economic creativity?

better supply of inputs?

…

Higher intensity of competition leading to higher quality of surviving start-ups and incumbents? − Could explain higher productivity and competitiveness of agglomerations.

Competition on input or on output markets?

Safeguard that competition works according to a survival of the fittest. Do not interfere with this kind of selection.

Focus on stimulating high quality start-ups.

A main part of the measures for stimulating high-quality new businesses should be region-specific.

A policy that aims at stimulating entrepreneurship needs a long-term perspective.

…


Policy Implications

Using other performance indicators than employment: GDP, productivity, innovation, …

Analyzing direct employment effects / fast growing firms (gazelles)

Identifying and analyzing the indirect effects of new business formation

The effect of entries of different quality

The role of new businesses for the generation and dissemination of innovation and knowledge (spin-offs)

Universities and other research institutions as incubators (entrepreneurial university)

The role of non-innovative entry

Developing and analyzing indicators for the formation of growth-relevant new businesses


Some avenues for further research

The role of the conditions on input and on output markets for the effects of new business formation on economic development

Effects of entry on competition in input markets and output markets

The role of the institutional environment

The role of regional characteristics

The role of the level of new business formation

The role of the economic development level/ effects of new business formation on economic development in developing countries

Entry as a cause or as a symptom of growth?

Longer-run effects of new business formation on regional development

Entrepreneurship policy (effectiveness, recommendations, etc.)Fritsch: Entrepreneurship and Economic Development, 3rd KID Summer School, Nice, July 11, 2014 34

Some avenues for further research (continued)

35

Thank you for your attention !



The effect of new business formation on regional employment in US-MSAs (Acs & Mueller, 2008)

0.0

0.5

1.0

1.5

2.0

2.5

Impa

ct o

f ne

w b

usi

ness

fo

rmatio

no

n e

mp

loym

en

t ch

an

ge

t t-1 t-2 t-3 t-4 t-5 t-6Start-up rate

0.0

0.5

1.0

1.5

2.0

2.5

Impa

ct o

f ne

w b

usi

ness

fo

rmatio

no

n e

mp

loym

en

t ch

an

ge


Source: Acs & Mueller (2008)

All start-ups



0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Impa

ct o

f n

ew

bu

siness

fo

rmatio

non e

mplo

ymen

t ch

an

ge


0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Impa

ct o

f n

ew

bu

siness

fo

rmatio

non e

mplo

ymen

t ch

an

ge



Small start-ups



-7.0

-6.0

-50.

-4.0

-3.0

-2.0

-1.0

0.0

Impa

ct

of

ne

w b

usin

ess f

orm

ation

on e

mp

loym

en

t ch

an

ge


-7.0

-6.0

-50.

-4.0

-3.0

-2.0

-1.0

0.0

Impa

ct

of

ne

w b

usin

ess f

orm

ation

on e

mp

loym

en

t ch

an

ge



Large start-ups


Regression results for high and low population regions

High populated regions Low populated regions

Employment change

Independent variables

Total Incum-bents

New busi-nesses

Total Incum-bents

New busi-nesses

(I) (II) (III) (IV) (V) (VI)

Average sector-adjusted start-up rate (log), t-1

0.243*** 0.211*** 0.0323 0.164*** 0.100*** 0.0631* (0.0516) (0.0498) (0.0259) (0.0292) (0.0346) (0.0361)

Share of highly qualified 0.183*** 0.150*** 0.0336** 0.0296** 0.0221 0.00758 employees (log), t-1 (0.0264) (0.0255) (0.0133) (0.0134) (0.0173) (0.0110)

Population density (log), t-1

0.0357 0.0328 0.00292 -0.00085 -0.0103 0.00950

(0.0685) (0.0661) (0.0206) (0.0415) (0.0401) (0.0412)

Market potential (log), t-1 0.681* 0.101 0.580*** 1.298*** 1.159*** 0.139 (0.350) (0.338) (0.156) (0.301) (0.338) (0.250)

Constant -7.466* -0.498 -6.968*** -15.68*** -14.16*** -1.522 (4.973) (3.510) (1.992) (3.726) (4.213) (3.109)

Year dummies Yesa Yesa Yesa Yesa Yesa Yesa Control for industry structure

Yesa Yesa Yesa Yesa Yesa Yesa

R-squared (within) 0.72 0.635 0.666 0.843 0.728 0.571


Regression results for regions with high and low shares of small business employment

Small business regions Large business regions

Employment change


Total Incum-bents

New busi-nesses

Total Incum-bents

New busi-nesses

(I) (II) (III) (IV) (V) (VI)


0.205*** (0.053)

0.198*** (0.043)

0.0317 (0.042)

0.189*** (0.047)

0.0991** (0.042)

0.0758** (0.030)

Share of highly qualified employees (log), t-1

0.0624*** 0.0347* 0.0295** 0.0767*** 0.0644 0.0132

(0.021) (0.018) (0.012) (0.022) (0.065) (0.012) Population density (log), t-1

0.0223 0.0452 0.00148 -0.0712 -0.0591 -0.0315

(0.074) (0.055) (0.055) (0.064) (0.068) (0.024) Market potential (log), t-1 0.611* -0.0309 0.309 0.495 0.168 0.241

(0.31) (0.24) (0.20) (0.38) (0.30) (0.23) Constant -6.980* -3.369 -3.611 -5.042 -1.493 -2.305

(3.67) (3.16) (2.46) (4.64) (3.65) (2.96)



R-squared (within) 0.84 0.73 0.65 0.71 0.62 0.60


Regression results for high and low correspondence of industry structure between entries and incumbents

High correspondence of

industry structure Low correspondence of industry

structure Employment

change


Total Incum-bents

New busi-nesses

Total Incum-bents

New busi-nesses

(I) (II) (III) (IV) (V) (VI)


0.211*** 0.223*** -0.0114 0.171*** 0.115*** 0.0563

(0.051) (0.049) (0.025) (0.038) (0.034) (0.043) Share of highly qualified employees (log), t-1

0.121*** 0.123*** -0.00153 0.0529*** 0.0260* 0.0269*

(0.025) (0.024) (0.012) (0.019) (0.015) (0.013) Population density (log), t-1

0.0780 0.0912 -0.0132 -0.0452 -0.0304 -0.0148

(0.060) (0.059) (0.030) (0.067) (0.044) (0.064) Market potential (log), t-1 0.628 0.0811 0.547*** 1.085*** 0.773* 0.312

(0.42) (0.41) (0.21) (0.33) (0.40) (0.28) Constant -7.341 -0.583 -6.757*** -12.68*** -9.245* -3.439

(5.23) (5.08) (2.57) (4.14) (5.04) (3.52)



R-squared (within) 0.71 0.61 0.64 0.86 0.75 0.59


Small business regions with high correspondence of

industry structure between start-ups and incumbents

Small business regions with low correspondence of

industry structure between start-ups and incumbents

Employment change

Total Incum-bents

New busi-

nesses Total

Incum-bents

New busi-

nesses

Independent variables (I) (II) (III) (IV) (V) (VI)

Average sector-adjusted 0.349*** 0.344*** 0.00488 0.239* 0.185* 0.0287 start-up rate (log), t-1 (0.085) (0.083) (0.046) (0.13) (0.094) (0.10)

Share of highly qualified 0.0817* 0.0770 0.00471 0.0640** 0.0115 0.0552*** employees (log), t-1 (0.046) (0.047) (0.021) (0.024) (0.025) (0.019)

Population density 0.163** 0.189** -0.0266 0.0121 -0.0638 0.0157 (log), t-1 (0.072) (0.080) (0.033) (0.12) (0.054) (0.10)

Market potential (log), t-1 1.206** 0.924* 0.282 -0.191 -0.163 0.0457 (0.46) (0.47) (0.25) (0.71) (0.48) (0.50)

Constant -14.55** -11.27* -3.280 3.221 3.653 -0.432 (5.63) (5.89) (3.04) (8.74) (7.13) (6.17)



R-squared (within) 0.84 0.74 0.67 0.88 0.79 0.68 No. of regions/years 19/16 19/16 19/16 19/16 19/16 19/16

Regression results for small business regions

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