by m.g. calza, p. cella, f. oropallo, s. rossetti, c. viviano istat-eurostat-oecd workshop on...

By M.G. Calza, P. Cella, F. Oropallo, S. Rossetti, C. Viviano

ISTAT-Eurostat-OECD Workshop on Entrepreneurship Indicators

Rome, December 6-7, 2006

Performance, Impact and Context Analysis

Data Integration for Entrepreneurship Indicators in Italy

OutlineISTAT-Eurostat-OECD

Workshop on Entrepreneurship

Indicators

Rome, December 7, 2006

1. Objectives

2. Background

3. Data Integration Issues

4. Framework of analysis

5. Entrepreneurship Performance Indicators

6. Entrepreneurship Impact Indicators

7. Entrepreneurship Determinants:• Barriers to competition• Profiles of new entrepreneurs and associated outcomes

8. An Entrepreneurship Scoreboard

9. Conclusions


The objective of this work is to contribute to research on entrepreneurship indicators by:

1. Building indicators on new/young firms

2. Developing indicators which focus on factors that hinder new entries and, more generally, competition

3. Using FOBS data to characterize the profiles of new entrepreneurs and associated outcomes

ObjectivesISTAT-Eurostat-OECD


Indicators


Data on new/young firms are needed for various entrepreneurship indicators.

Currently, there are two main sources of data :

1) The Business Demography database: It permits to identify real births and real deaths, and to calculate performance indicators, e.g. rate of new firms, business churn, survival rates

2) The Factor of Business Success Survey: It helps us to uncover the socio-demographic characteristics of new entrepreneurs and to understand their motivations and difficulties

The main drawbacks with both sources are:

(i) their “thin” coverage of economic variables

(ii) the hitches allied to their linkage with SME (PMI) survey data, since new firms are inadequately represented in the latter

For this reasons it is useful and indeed rewarding to integrate the information on new entrepreneurship with data from other sources

Background (1)ISTAT-Eurostat-OECD


Indicators


The development of new entrepreneurship is deeply influenced by market entry barriers and the regulatory context

Market barriers and competition are believed to be important factors in the study of the Italian economy

Since these phenomena are multifaceted, their study requires different indicators and data sources

To this effect Data integration is of paramount importance

Background (2)ISTAT-Eurostat-OECD


Indicators


Data integration issues (1)

ISTAT-Eurostat-OECD Workshop on

Entrepreneurship Indicators

Advantages:- exploit existing statistical or administrative information - enhance the statistical information system on new firms- provide more and better information for policy making- open up new vistas for economic analysis

Drawbacks:- confidentiality problems related to the access to micro data- administrative data are customarily collected for different purposes- they may refer to legal units not statistical units


Data integration issues (2)



Matching different data sources (statistical/administrative) means tackling a host of issue, e.g.:

Identifying business unitsi.e. find an identifying variable which is a unique key that is a natural join between different sources. In almost all firm databases we choose the fiscal code

Dealing with Matching Problemsi.e. whenever a key variable is unavailable or is not sufficient to identify the statistical unit. In case of mis-matches or when sources do not contain the same unit

Identifying changes in business units Changes involving a single unit (changes in kind of business classification, in legal form or localisation)

Changes in the number of units (death, birth, breaks up and splits off, mergers and acquisitions)

Addressing sampling problems When merging survey data with exhaustive data from a subset of the population

Reconciling definitions and values among sourcesWhenever a variable has not the same definition or value across different sources

Handling data editing and data reconstruction issuesMeasurement Errors, Missing data, Outliers etc.


Framework of analysis (1)



Following the OECD (Davis 2006) three types of entrepreneurship indicators can be distinguished:

- Performance: which measure how a country performs in terms of entrepreneurship. Most of these indicators can be calculated using Business Register and Business Demography

- Impact: which measure the outcome(s) of entrepreneurship.To focus our attention on these indicators we need to “expand” the information on new/young businesses and integrate it with information from other sources

- Determinants/Context: which measure various aspects of the conditions and qualities that foster or hinder entrepreneurship.We focus our attention on two subgroups: barriers to competition and entrepreneurs profiles


Framework of analysis (2)



Units of analysisNew firms: real births from the Business Demography Young firms: four-year surviving from Business DemographyIncumbent firms: taken as “benchmark firms”, i.e. standing on markets for at least 5 years

Analyzed indicators- Rate of new firm start-ups - Business churn- Survival rate for new businesses- Turnover of new firms- Number of SMEs in total economy- Importance of SMEs in total economy- Share of employment in SMEs

- Growth rate of employment of young firms- Growth rate of turnover of young firms - Contribution of new firms to productivity growth - Share of new/young firms that export - Exports per employee of new/young firms- Return on sales (Ros) for new/young firms- Share of labour cost for new/young firms- Financial burden on sales

- Barriers to competition - Profiles of new entrepreneurs and associated outcomes

SourcesBusiness Register, Business Demography, SBS data, Foreign Trade Statistics, Fiscal Data, Balance Sheets

Performance

Impact

Determinants


Entrepreneurship Performance Indicators



NF : real births from Business DemographyNF(t,t+n): young firms (t-year surviving from Business Demography)DF : real deaths from Business DemographyTF : All firms from Business RegisterSME: Small-medium firmsT_ : Turnover…E_ : Employment…

Breakdown by sector Nace, legal form, geographical area, size class …

Performance indicators

Description Formula Source Nace Coverage

Rate of new firm start-ups NF/TF Business Register and Demography C-K

Business churn (NF+DF)/TF Business Register and Demography C-KSurvival rate for new businesses NF(t,t+n)/NF(t) Business Register and Demography C-KTurnover of new firms T_NF/T_TF Business Register and Demography C-KNumber of SMEs in total economy SME/TF Business Register and Demography C-KImportance of SMEs in total economy T_SME/T_TF Business Register and Demography C-KShare of employment in SMEs E_SME/E_TF Business Register and Demography C-K


Entrepreneurship Impact indicatorsISTAT-Eurostat-OECD


Indicators

NF : real births from Business DemographyNF(t,t+n): young firms (t-year surviving from Business Demography)T_ : Turnover…E_ : Employment Exp_: ExportsOS_: Operating SurplusLC_: Labour CostsTC_: Total CostsIP_: Interest PaymentsP : Labour Productivity measured by Turnover on Employment: Share of employment

Breakdown by sector Nace, legal form, geographical area, size class …

Entrepreneurship impact IndicatorsDescription Formula Source Nace Coverage

Growth rate of employment of young firms E_NF(t,t+n)/E_NF(t)-1 Business Register and Demography C-K

Growth rate of turnover of young firms T_NF(t,t+n)/T_NF(t)-1 Business Register and Demography C-K

Contribution of entries and exits to productivity growth

Business Register and Demographyand SBS data

D-F,G-K

Share of new/young firms that export NF(exp)/NFBusiness Register, Demography and Foreign Trade data

C-K

Exports per employee of new/young firms Exp_NF/E_NFBusiness Register, Demography and Foreign Trade data

C-K

Return on sales (Ros) for new/young firms OS_NF/T_NFBusiness Register, Demography and Fiscal data

D-F,G-I,K,M,N

Share of labour cost for new/young firms LC_NF/TC_NFBusiness Register, Demography and Fiscal data

D-F,G-I,K,M,N

Financial burden on sales for new/young firms IP_NF/T_NFBusiness Register, Demography and Fiscal data

D-F,G-I,K,M,N

NFi

tit

ti Pp )( sec


Entrepreneurship Impact indicators



When Business Register, Business Demography, Foreign Trade, Balance Sheets and SBS are integrated a great deal of new opportunities open up

- Growth rate of employment of young firms- Growth rate of turnover of young firms - Contribution of new firms to productivity growth - Share of new/young firms that export - Exports per employee of new/young firms

Population:B.R. & B.D.

Linked with

Foreign Trade Exporting/Imp. firms

Balance Sheets corporate firms

SBS (sample) domain level analysis

T-n

T-1

Archives

Foreign Trade* Balance Sheets**

All Units

Representative Units

* Enterprises involved in foreign markets

** Corporate firms (Their account system is regulated by EU directives)

Survey Sources

B.RegisterB.Demography

Structural Business Statistics

Large

Sm

all

Med

ium

fir

ms



Growth rate of turnover and employment of young firms



213.3

177.1

217.5

177.4193.2

140.0

93.8

129.3141.8 148.0

122.4 120.9

99.3 97.6

71.0 70.1 68.2 62.6

40.6

66.8

0

50

100

150

200

250

Scaleintensive

Specialisedsuppliers

Transp.Telecom.

Supplierdominated

Sciencebased

Construction Hotels BusinessServices

Trade Total

Turnover Employment

settExitsi

ktit

kti

NewFirmsi

tit

titi

Incumbentsiit

Incumbentsiisett EPpPpPppP

)()()( secsecsecsec

-4.0

-13.8

-8.1

-4.3

-8.8

6.7

-17.5

8.7

-0.6 -1.3

-30

-20

-10

0

10

20

30

Supplierdominated

Specialisedsuppliers

Science based Scale intensive Construction Trade Hotels Transp.Telecom.

BusinessServices

Total

-30

-20

-10

0

10

20

30Within Betw een Entries Exits Changes in B.U. Total


Contribution of entries and exits to productivity growth of micro firms


Entrepreneurship Indicators Entrepreneurship Impact indicators


Share of new, young and incumbent firms that export (%)



8.19.9

4.05.3

7.39.9

13.9 13.4

8.010.1

26.2

32.3

16.7

21.3

24.6

0

5

10

15

20

25

30

35

Supplier dominated Specialisedsuppliers

Science based Scale intensive Total manufacturing

New firms Young firms Incumbents


Exports per employee in firms at birth, after four years (young firms) and in incumbent firms (thousand €)



21.6 26.6

145.1

19.7 24.927.3 28.3

152.8

46.238.8

31.923.2

75.2

58.1

42.7

0

20

40

60

80

100

120

140

160

180

Supplier dominated Specialisedsuppliers

Science based Scale intensive Total manufacturing






Opportunities that open up when Fiscal data are integrated

Fiscal survey purpose To support Tax Admin. control action

on small and medium firms (Turnover less than 5 million €)

(Coverage: all business sectors except Energy (E),Financial (J), Social (O)

Available information:sectors from D to I and M: 48 balance-sheets-comparable variables sectors K and N: excluded from the analysis since available variablesare not comparable

Ros=Return on salesLCI=Share of labour cost

IPS=Financial burden on sales

Population % Linked

New firms 69

Young firms 73

Incumbents 81


ROS (%) - Profitability



7.8

13.2

7.2

1.5

7.0

8.68.1

12.2

8.1

6.77.8

9.09.9

13.0

10.8

12.0

8.6

10.8

0

2

4

6

8

10

12

14

D - Manufact. F - Constr. G - Trade H - Hotels I -Transp. &Telec.

Total



Share of labour cost (%) on total costs



18.4

12.9

4.7

18.6

16.2

11.0

19.7

17.3

6.0

19.817.7

13.1

21.8

18.9

7.2

23.3

19.0

14.9

0

5

10

15

20

25


Total



IPS=Financial burden on sales (%)


Entrepreneurship Indicators Entrepreneurship Impact indicators:

1.1 1.1

0.7

1.7

0.7

1.0

1.6

1.3

0.9

1.6

1.11.2

1.81.6

1.1

2.0

1.21.4

0.0

0.5

1.0

1.5

2.0

2.5


Total



Entrepreneurship Determinants



For the analysis of entrepreneurship determinants more complex methodologies have to be applied

Entrepreneurship DeterminantsDescription Methodology Source Nace Coverage

Barriers to compettion Composite IndicatorBusiness Register, Demography, SBS, Balance sheets

D-K

Profiles of new entrepreneurs and associated outcomes

Cluster AnalysisFOBS, Business Register, Demography and Fiscal data

C-K


Entrepreneurship Determinants: Barriers to competition



Barriers to competition: Barriers to entry are an essential condition to the existence of non-competitive behaviour

Several indices relating to the existence of entry barriers have been computed (at 3-digit level of aggregation):

- Herfindahl index (H) (Sum of squared market sale shares) - Concentration Ratio (CR5) (Cumulative market sale share of the largest 5 firms)

- Share of advertising expenses (AE) (Advertising costs on sales)

- Share of Fixed assets (FA) (Fixed assets on total Assets)

- Dominant firm size (Size class that represents at least 50% of workers)

Sources: Business Register, Structural Business Statistics, Balance Sheets

Coverage: D-K (Nace rev. 1.1)

Anything that prevents new firms from actually entering a market

As a proxy for monopolistic competition due to product differentiation


Entrepreneurship Determinants:Barriers to competition



To measure the intensity of entry barriers for each market, a composite index (summing up indicators re-scaled by their own mean values) is computed

To avoid redundancy, indicators have been selected on the basis of the correlation matrix below:

Market Barriers Intensity = CR5/m(CR5)+AE/m(AE)+FA/m(FA)

Thanks to the above index, markets can be ranked and distinguished for example according to their dominant size (micro, small, medium and large)

Herfindahl Concentration R.5 Share of adv. Share of Fixed assetsHerfindahl 100%Concentration R.5 80% 100%Share of adv. -10% 0% 100%Share of Fixed assets 26% 22% 0% 100%

Context: Barriers to competition




Market Barriers Intensity Index in 1999 (violet) and 2003 (beige)

in all micro (dominant size) business sectors

0 1 2 3 4 5 6 7 8

K-Real estate services on a fee or contract basis

D-Other food products

D-Animal and vegetable oils and fats

K-Renting services of personal and household goods n

K-Renting services of other transport equipment

H-Camping sites and other short-stay accommodation s

H-Beverage serving services

F-Renting services of construction or demolition equ

K-Letting services of ow n property

I-Travel agency and tour operator services; tourist

K-Other computer-related services

D-Metal secondary raw materials

K-Advertising services

H-Food serving services

D-Medical and surgical equipment and orthopaedic app

K-Renting services of other machinery and equipment

G-Retail trade services of second-hand goods in stor

K-Miscellaneous business services n.e.c.

J-Services auxiliary to f inancial intermediation, ex

D-Furs; articles of fur

G-Sales on a fee or contract basis

G-Other w holesale trade services

K-Data processing services

D-Cut, shaped and f inished ornamental and building s

G-Trade, maintenance and repair services of motorcyc

G-Retail trade services of pharmaceutical and medica

D-Builders' joinery and carpentry, of w ood

G-Retail trade services not in stores

J-Services auxiliary to insurance and pension fundin

G-Other retail trade services of new goods in specia

G-Retail trade services of motor fuel

G-Maintenance and repair services of motor vehicles

G-Repair services of personal and household goods

G-Wholesale trade services of agricultural raw mater

K-Maintenance and repair services of off ice, account

G-Trade services of motor vehicle parts and accessor

K-Legal, accounting, book-keeping and auditing servi

K-Hardw are consultancy services

G-Retail trade services of food, beverages and tobac

K-Research and experimental development services on

K-Real estate services w ith ow n property

F-Building installation w ork

F-Site preparation w ork

K-Architectural, engineering and related technical c

F-Building completion w ork

F-Works for complete construction or parts thereof;




The Italian FOBS survey (a sample of 6 th. records) allows to sketch the following identity of the “average” entrepreneur

Entrepreneurship Determinants: Profiles of new entrepreneurs and associated outcomes

Male 39 years old

secondary education with previous working experience-

-in the same sector of activity

Given the vast array of information on entrepreneurs and their characteristic gathered with the survey, different profiles, not just one, are likely to coexist

Multidimensional techniques (e.g. cluster analysis) can be used to group entrepreneurs into homogeneous clusters subject to the following conditions: - the within clusters distance should be as small as possible - the between clusters distance should be as large as possible

Each cluster will define an entrepreneur’s profile




Steps of the clustering procedure

1. Choice of variablesOnly a set of demo-social variables has been considered (such as geog. area, Nace, occupation prior to starting-up enterprise, age, gender, educational background , branch experience, a synthetic measures of the motivations at start-up and a synthetic measure of the difficulties at enterprise start-up)

2. Distance measure between units: Gower’s dissimilarity formula

3. Cluster algorithm: Ward’s minimum variance method (it minimizes the within group variance and maximizes the between groups variance)

4. Choice of the number of clusters: 6 clusters have been chosen according to the results of pseudo t-test and pseudo f-test

5. Ex-post characterization of the cluster with economic information from B.R. and Fiscal data: per capita turnover, employment variation and ROS, LCI and IPS






The empirical analysis leads to portrait the following profiles:

1st cluster (7% of tot Fobs) 2nd cluster (30%) 3rd cluster (26%)

Experienced female with some difficulties Senior experienced male Young experienced male

97% Female 97% Male 97 % Male

80 % with branch experience 94 % with experience as entrepreneur 98 % with branch experience

46 % declares more difficulties at start-up 51 % secondary education 37% works in the industry

43 is the average age 47 is the average age 38 is the average age

4th cluster (18%) 5th cluster (10%) 6th cluster (9%)

South youngs previously unemployed North inexperienced female with lower ed. Higher educated

42% South and Islands 44% North West 47% South and Islands

98% without experience 97% Female about 40 years old 76 % business service (sect. K)

71 % secondary education 96% without experience 95% higher degree

36 is the average age 40% with lower secondary education 41 % declares more motivations at start-up


How does each profile perform?



Entrepreneurship Determinants : Profiles of new entrepreneurs and associated outcomes

23.8

14.4

7.710.1 8.8

15.2

87

74

5350

55

83

16.7

0

10

20

30

40

50

60

70

80

90

100

1) ExperiencedFemale

2) Seniorexperienced

3) Youngexperienced

4) South youngs 5) Northinexperienced

6) Highereducated

Total

Fast grow ing f irms (% - empl. grow th more than 100%) Per capita turnover (Keuro)

129


How does each profile perform?



Entrepreneurship Determinants : Profiles of new entrepreneurs and associated outcomes

7.0 6.6

10.9 10.6

7.9

-2.3

7.6

18.7

11.1

15.9

14.9

18.2

20.2

17.4

0.8

1.1

1.41.2

1.41.3

1.0

-5

0

5

10

15

20

25

1) ExperiencedFemale

2) Seniorexperienced

3) Youngexperienced

4) South youngs 5) Northinexperienced

6) Highereducated

Total

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6Ros (%) Share of Labour Cost (%) Financial burden on sales (%) (rhs)


0 5 10 15 20 25 30 35 40 45 50

Rate of new firm start-ups

Business churn

Survival rate for new businesses (4 years)

Turnover of new firms

Number of SMEs (micro firms) in total economy

Share of employment in SMEs (micro firms)

Importance of SMEs (micro) in total economy

Growth rate of employment of young firms (4 years)

Growth rate of turnover of young firms (4 years)

Contrib. of entries and exits to product. growth (4 years)

Share of young firms that export

Exports per employee of young firms (th. euro)

Return on sales (Ros) for young firms

Share of labour cost for young firms

Financial burden on sales for young firms

Average Concentration Ratio of markets

New entrepreneur with tertiary education

50 100 150ISTAT-Eurostat-OECD


Indicators Towards an entrepreneurship scoreboard

19992003

Perform

ance

Impact

Determinants 1999

2003

Data Integration for Entrepreneurship Indicators in Italy: Performance, Impact and Context Analysis

CONCLUDING REMARKS AND PUZZLES:

• We have tried to contribute to the “entrepreneurship debate” focusing on selected “key concepts” and measuring them for Italy

• We have shown the potential of data integration. A wide range of indicators can be developed, but further work is needed in other areas (e.g. credit access)

• Looking ahead, further analysis is needed on the assessment and selection of indicators on grounds of their relevance and other quality criteria (e. g., robustness, coherence, accurateness …) to better support policies with “evidence”

• From our analysis new/young firms appear to perform well. How does this impact on the overall economy? What policy implications can be drawn?

AND ABOVE ALL• How an effective tool the Entrepreneurship Scoreboard can be

expected to be?


by m.g. calza, p. cella, f. oropallo, s. rossetti, c. viviano istat-eurostat-oecd workshop on...

Documents

oecd workshop

data sourcesto

effect data integration

main sources of data

different indicators

new vistas

new entries

rate of new firms