International Entrepreneurship and Innovation Scorecards: Examining the Data

7/27/2019 International Entrepreneurship and Innovation Scorecards: Examining the Data

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INTERNATIONAL ENTREPRENEURSHIPAND INNOVATION SCORECARDS

Examining the Data

Dane Stangler andJared Konczal

Ewing Marion Kauffman Foundation

October 2013


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INTERNATIONAL ENTREPRENEURSHIP

AND INNOVATION SCORECARDSExamining the Data

Dane Stangler andJared Konczal

Ewing Marion Kauffman Foundation

October 2013


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INTERNATIONAL ENTREPRENEURSHIP AND INNOVATION SCORECARDS

Examining the Data

INTRODUCTION

The purpose of this report is to demonstrate a scorecard approach for distilling differentindicators of entrepreneurship and innovation. We reviewed popular international

indices and indicators in an attempt to distill a large sample of indicators into a set ofthose that closely complement one another. It was presumed that honing in on a smallerset of indicators might be useful for policymakers, and might also help highlight areasdeserving further attention from researchers.

This report lists the selected countries, discusses the selection process for indicatorsand scorecard approach, and presents the resulting scorecards. The methodologyunderpinning the final presented values represents a good faith effort to compile

accurate scorecards, but relies on a number of assumptions to produce comparabledata values from non-standardized sets of indicators. Thus, we present these findingsas exploratory and preliminary. We strongly advise against using this report to comparereported country charts or values, but instead hope that it will serve as a platform fordiscussions of how to improve entrepreneurship data collection.

This report, produced in parallel with efforts by the U.S. Government to support andpromote entrepreneurship, coincides with the announcement of the Global

Entrepreneurship Research Network (GERN), an international collaboration oforganizations working to gain a better understanding of policy barriers and the rightpolicies for fostering entrepreneurship.


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Selected Countries

OECD BelgiumOECD DenmarkOECD JapanOECD MexicoOECD NetherlandsOECD NorwayOECD SloveniaOECD Spain

OECD United States of AmericaNon-OECD BangladeshNon-OECD Dominican RepublicNon-OECD El SalvadorNon-OECD GhanaNon-OECD IndiaNon-OECD IndonesiaNon-OECD LatviaNon-OECD NigeriaNon-OECD PakistanNon-OECD PeruNon-OECD Russian FederationNon-OECD Zambia

Selected Indicators1

GII.Score Global Innovation IndexDF.Start.Score Distance to FrontierStarting a BusinessDF.Contract.Score Distance to FrontierEnforcing Contracts


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INDICATOR SELECTION PROCESS

Based on a review of international statistics on entrepreneurship and innovation, weanalyzed ten different assessments of innovation and entrepreneurship across a widerange of countries. Some assessments represent indexes that aggregate many differentsub-indicators, and some represent standalone statistics. For example, one might focuson new firm formation, another on regulatory barriers, and another on the quality andfluidity of labor markets. Our selection of these particular indicators (see below) is areflection of the important and insightful work done by the various organizations thatcompile them. They have established a strong platform for future research and, in

particular, further work on data collection in entrepreneurship and innovation. 2

In concert with the Global Entrepreneurship Summit, we attempted to compilesomething manageable for policymakers, simultaneously demonstrating the amount ofwork yet to be done on global entrepreneurship and innovation.

These ten assessments and their sub-indicators represent seventy-one measures ofentrepreneurship and innovation for anywhere from thirty-one to 186 countries.3 Weperformed correlation analysis for these seventy-one measures to determine whichones were most related to one another and, in particular, which ones were most relatedto the World Banks data on new firm density. Based on the initial sample andcorrelation results, we ended up with a reduced sample of forty-five countries with justnine different measures (most measures are not available for all countries). Last, weadded the United States to our sample.4

COUNTRY RESULTS

In addition to the United States, we randomly selected twenty of these forty-fivecountries to build the composite scorecards presented in this report. We elected to


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Likewise, the purpose of the scorecard is not to facilitate country-to-countrycomparisons. We do not view the scorecard effort in this report as final in any sense,

and is partly why we only selected twenty random countries rather than the entiresample of forty-five. We have simply found that these selected measures trend togetherand appear to be related, and we should like to investigate this further. This effortshould serve primarily as an illustration of how to view a countrys entrepreneurship andinnovation environment.

Most importantly, this exercise demonstrates the need for improvements instandardized entrepreneurship data collectionboth within and across countriesas

well as longitudinal studies of entrepreneurs and new businesses. Several innovativeefforts at precisely this are occurring around the world, and one goal of the GlobalEntrepreneurship Research Network (GERN), is to support such efforts and enablepolicymakers to have access to sufficient data on entrepreneurship. Lastly, the datasynthesis exercise in this report underscores another GERN objective: substantial gapsremain in the worlds understanding of entrepreneurship, and more research is neededto buttress the emerging entrepreneurship movement around the world.


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RADAR CHARTS

The following charts are not designed to provide prescriptions of what a country shouldor should not do. Broadly speaking, research has shown that implementing reforms onthe cost and procedures required to register a business can influence new firm entry.6While we recognize there is demand for recommendations that individual countriesshould take to improve their entrepreneurship and innovation economies, this requires adepth of analysis beyond the scope of this report. We are only able to cite research thatbroadly demonstrates that regulatory reforms to reduce burdens can matter, and thatmany regulatory issues factor into the scores on the various selected indicators.

0%

50%

100%

150%

200%

250%

300%

t-4 t-3 t-2 t-1 t t+1 t+2Percentofnewlyregisteredfirmscompared

topre-reformy

ear(t-1)

I l t ti f R f

Bangladesh

Chile

Kenya

Morocco

Sweden

Rwanda


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0.010.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score

GEDI.ScoreGITR.Score

GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Belgium

90.0

100.0

GII.Score

Denmark


9/20

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Japan

90.0

100.0

GII.Score

Mexico


10/20

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Netherlands

90.0

100.0

GII.Score

Norway


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0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Slovenia

90.0

100.0

GII.Score

Spain


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0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.090.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

United States


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0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Bangladesh

90.0

100.0

GII.Score

Dominican Republic


14/20

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

El Salvador

90.0

100.0

GII.Score

Ghana


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0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

India

90.0

100.0

GII.Score

Indonesia


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0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Latvia

90.0

100.0

GII.Score

Nigeria


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0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Pakistan

90.0

100.0

GII.Score

Peru


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0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

GII.Score

DF.Start.Score

DF.Contract.Score

DF.Insolve.Score


GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score

Russian Federation

90.0

100.0

GII.Score

Zambia


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APPENDIX: COMPILED DATA

Table 1: Compiled Scores (non-scaled values)

Country

Distance toFrontierWB2013Starting aBusiness

Distance toFrontierWB2013EnforcingContracts

Distance toFrontierWB2013ResolvingInsolvency

GII 2013main score

GEDI20122013(Index)

GITR 2013NetworkedReadinessIndex 2013,17 (best)

GCI 5thpillar: Highereducationand training,17 (best)

GCI 9th pillar:Technologicalreadiness,17 (best)

New FirmDensity*

Latvia 91.2 74.7 63.7 45.2 0.35 4.43 4.78 4.73 7.89

Norway 91.1 76.5 96.2 55.6 0.55 5.66 5.61 5.78 4.41

Peru 86.3 54.5 30.5 36.0 0.29 3.39 4.05 3.57 2.27

Japan 82.0 70.7 98.3 52.2 0.35 5.24 5.28 5.70 1.07

Pakistan 78.5 38.0 39.0 23.3 0.14 3.35 2.99 2.90 0.03

Netherlands 89.1 74.4 94.1 61.1 0.58 5.81 5.79 5.98 3.13

Nigeria 73.5 56.3 30.6 26.6 0.21 3.27 3.31 3.08 0.79Dominican Republic 81.1 60.0 10.2 33.3 0.23 3.62 3.69 3.68 0.74

Belgium 94.3 77.0 94.0 52.5 0.53 5.10 5.81 5.57 2.66

Zambia 84.6 59.3 32.3 26.8 0.15 3.19 3.07 2.96 1.06

Spain 77.0 60.3 81.2 49.4 0.39 4.51 5.02 5.29 2.46

Denmark 92.4 66.7 92.3 58.3 0.63 5.58 5.59 6.17 4.41

Russian Federation 83.6 73.1 46.5 37.2 0.23 4.13 4.59 4.13 1.81

Slovenia 95.1 50.2 53.2 47.3 0.43 4.53 5.20 4.96 3.98

Mexico 88.2 60.2 71.6 36.8 0.26 3.93 4.11 3.80 0.88

Indonesia 71.3 33.7 15.9 32.0 0.21 3.84 4.17 3.56 0.23

El Salvador 78.5 59.2 34.8 31.3 0.17 3.53 3.45 3.26 0.47

Ghana 84.6 63.6 29.2 30.6 0.16 3.51 3.40 3.13 1.06Bangladesh 82.6 19.3 27.8 24.5 0.09 3.22 2.88 2.74 0.08

India 62.4 22.2 28.3 36.2 0.18 3.88 3.97 3.36 0.08

United States 89.8 74.7 86.5 60.3 0.67 5.57 5.72 5.84 1.70*

*New Firm Density score for the United States is computed from a three-year average of the Census Bureaus Business Dynamics Statistics.Allother country scores are based on a three-year average of the World Banks New Firm Density measure.


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Table 2: Compiled Scores (scaled values)

Country GII.ScoreDF.Start.Score

DF.Contract.Score

DF.Insolve.Score GEDI.Score GITR.Score

GCI.Edu.Score

GCI.Tech.Score

Firm.Density.Score*

Latvia 58.1 91.2 74.7 63.7 45.4 63.3 68.2 67.5 84.8

Norway 85.0 91.1 76.5 96.2 79.5 80.8 80.1 82.5 47.6

Peru 34.3 86.3 54.5 30.5 35.1 48.4 57.8 51.0 24.9

Japan 76.2 82 70.7 98.3 45.4 74.8 75.4 81.5 12.1

Pakistan 1.5 78.5 38 39 9.5 47.8 42.7 41.5 1.0

Netherlands 99.2 89.1 74.4 94.1 84.6 83.0 82.7 85.4 34.1

Nigeria 10.0 73.5 56.3 30.6 21.5 46.7 47.3 43.9 9.1

Dominican Republic 27.4 81.1 60 10.2 24.9 51.7 52.7 52.5 8.5

Belgium 77.0 94.3 77 94 76.1 72.8 83.0 79.6 29.0

Zambia 10.6 84.6 59.3 32.3 11.2 45.6 43.8 42.3 11.9

Spain 69.0 77 60.3 81.2 52.2 64.4 71.7 75.6 26.9

Denmark 92.0 92.4 66.7 92.3 93.2 79.7 79.9 88.1 47.7

Russian Federation 37.4 83.6 73.1 46.5 24.9 58.9 65.6 59.1 19.9

Slovenia 63.6 95.1 50.2 53.2 59.0 64.8 74.3 70.8 43.1

Mexico 36.4 88.2 60.2 71.6 30.0 56.1 58.7 54.3 10.0

Indonesia 24.0 71.3 33.7 15.9 21.5 54.9 59.6 50.8 3.1

El Salvador 22.2 78.5 59.2 34.8 14.7 50.5 49.3 46.6 5.7

Ghana 20.4 84.6 63.6 29.2 12.9 50.2 48.6 44.8 12.0

Bangladesh 4.6 82.6 19.3 27.8 1.0 46.0 41.1 39.2 1.6

India 34.9 62.4 22.2 28.3 16.4 55.5 56.7 48.0 1.5

United States 97.2 89.8 74.7 86.5 100.0 79.6 81.7 83.4 18.7*

*New Firm Density score for the United States is computed from a three-year average of the Census Bureaus Business Dynamics Statistics. Allother country scores are based on a three-year average of the World Banks New Firm Density measure.

International Entrepreneurship and Innovation Scorecards: Examining the Data

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