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									Micro, Small, and Medium Enterprises: A Collection of Published Data
Marta Kozak, International Finance Corporation (IFC), Washington, D.C. Date of last update: May 17, 2005

Country SME Characteristics
SME Definitions (number of employees, unless otherwise noted)a Structure of the SME Sector (% of all SMEs) SME Participation in the Economy

Business Environment
Leasing Investment

Economy

Income Group

Year of Source SME of SME Data Data

Micro

Small

Medium

Micro

Small

Medium

SMEs

Leasing as Investment SME SMEs per employme % of total Climate Index 1,000 (0-100), nt as % of priv. credit, people b c total 2002 2003
17.3 18.8 26.4 11.0 54.0 33.1 7.2 2.5 42.2 67.0 7.4 9.7 27.1 28.3 63.0 35.7 6.3 19.6 19.3 194.2 38.1 42.2 79.3 24.0 42.4 41.8 1.4 36.4 72.2 15.7 43.8 15.0 77.6 24.6 77.8 37.2 52.0
d

Albania Algeria Argentina Armenia Australia Austria Azerbaijan Belarus Belgium Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Canada Chile China Colombia Costa Rica Czech Republic Denmark Egypt, Arab Rep. El Salvador Estonia Finland France Georgia Germany Greece Guatemala Hong Kong, China Hungary Indonesia Ireland Italy Jamaica

Lower middle Lower middle Upper middle Lower middle High High Lower middle Lower middle High Lower middle Lower middle Upper middle Lower middle Lower middle High Upper middle Lower middle Lower middle Upper middle Upper middle High Lower middle Lower middle Upper middle High High Lower middle High High Lower middle High Upper middle Lower middle High High Lower middle

2001 2001 1994 2001 2000 2003 2001 2001 2003 1995 2001 2003 2001 2001 2000 1997 2000 1990 2000 2001 2003 2002 1998 2001 2003 2003 2001 2003 2003 1999 2000 2001 2000 2003 2003 1996

UNECE NAED FUNDES UNECE OECD EC UNECE UNECE EC FUNDES UNECE BCSO IBGE UNECE OECD FUNDES APEC
g

1 s ≤ 170,000 0-9 0-9 0-9 0-9 0-10 0-9 0-4
f

2-10 s ≤ 1,000,000 10-99 10-49 < 50 10-49 10-49 11-19 10-49 5-49 10-49 10-49 10-99 5-49 10-49 11-30 10-49 10-49 5-49 10-49 10-49 10-49 10-49 10-49 10-49 11-25 5-19 10-49 5-19 10-49 10-49 3-4

> 10 < 250 s ≤ 8,300,000 < 100 100-499 50-249 50-249 50-249 50-249 20-49 50-249 50-99 50-249 50-249 100-499 50-199 50-199 31-100 50-249 50-249 < 99 50-99 50-249 50-249 50-249 50-249 50-249 50-249 26-60 20-99 50-249 20-99 50-249 50-249 5-9

94.3 91.4 73.0 86.9 80.1 68.6 93.4 99.7 85.3 57.4 92.9 92.6 75.2 82.8 96.1 79.7 97.4 87.8 97.3 77.8 93.7 93.2 48.7 88.3 97.5 77.7 87.4 85.1 85.6 95.6

3.8 7.8 24.8 11.2 29.0 5.7 0.2 11.3 40.1 6.2 5.8 23.1 15.1 3.9 20.3 2.1 10.2 2.6 18.7 5.4 5.8 38.2 10.2 2.1 16.7 7.7 12.2 12.4 4.0

1.9 0.8 2.2 1.9 19.9 2.3 0.9 0.1 3.4 2.5 0.9 1.6 1.7 2.1

54,142 580,000 891,300 34,000 1,075,000 267,000 58,623 25,404 437,000 501,333 30,000 16,466 4,667,609 224,211 1,994,000 522,106 8,000,000 684,646 73,518

75.0 70.2
d

20 41 39 1.47 1.64 65 71 49

25.8 50.0 66.1 2.7
e

69.3 53.0

1.53

70 37 51

0-9 0-9 0-9 0-4 0-9 0-10 0-9 0-9 0-4 0-9 0-9 0-9 0-9 0-9 0-9 0-10 0-4 0-9 1-5 0-9 0-9 1-2
g

56.5 64.7 60.0 86.5 78.0 67.2
d

1.07 1.73 0.84 0.12 4.10 2.76 11.23 1.20

33 44 73 57 37 30 46 70 31 44

FUNDES FUNDES UNECE EC NAED FUNDES UNECE EC EC UNECE EC EC FUNDES APEC APEC EC EC IADB UNECE
g

54.3 64.3 78.4
d

0.5 2.0 0.1 3.5 0.9 1.0 13.1 1.5 0.3 5.6 4.9 2.7 2.0 0.4

1,985,004 205,000 2,500,000 476,900 32,801 221,000 2,495,000 7,257 3,008,000 771,000 173,699 292,000 153,107 16,000,000 97,000 4,486,000 93,110

65.3 59.2 62.7 70.4 74.0
d

16.54 1.72 1.78 1.68 1.24 0.49 11.22 1.04 2.28 57 32 72 52 67 65 70 48 29

7.3
d d

32.3 61.0 45.9 88.0 72.1 73.0
d d

100.0

Japan Korea, Rep. Kyrgyz Republic Latvia Lithuania Macedonia, FYR Malawi Malaysia Mexico Moldova Morocco Netherlands New Zealand Nicaragua Norway Panama Paraguay Peru Philippines Poland Portugal Romania Russian Federation Serbia and Montenegro Singapore Slovak Republic Slovenia South Africa Spain Sweden Switzerland Tanzania Thailand Ukraine United Kingdom United States Uzbekistan Vietnam
k

High High Low Upper middle Upper middle Lower middle Low Upper middle Upper middle Low Lower middle High High Low High Upper middle Lower middle Lower middle Lower middle Upper middle High Lower middle Lower middle Lower middle High Upper middle High Lower middle High High High Low Lower middle Lower middle High High Low Upper middle Low

2000 2000 2001 2001 2001 2000 2000 2000 1998 2001 2002 2003 2003 1996 2003 1998 1997 1994 2000 2001 2003 2001 2003 2001 2000 2001 2001 1997 2003 2003 2003 1996 2000 2001 2003 2002 2003 2000 2000

APEC APEC

g g

0-4 0-4 0-9 0-9 0-4

5-19 5-19 10-49 10-49 5-20

20-99 20-99 50-249 50-249 21-50 Manuf. <100, nonmanuf. < 50 101-500 < 200

57.2 73.4 73.0 80.3 91.3

35.2 18.0 22.3 16.0 8.5

7.5 8.6 4.7 3.7 0.2

6,139,735 2,700,000 22,670
h

48.4 57.4 4.6 13.8 16.1 63.6 72.5 0.8 29.3 4.8 15.2 35.2 73.5 5.6 52.2 14.8 1.8 10.1 10.7 42.8 68.0 18.0 58.9 6.0 13.4 11.5 24.6 22.0 65.1 54.2 46.7 32.8 5.8 4.8 37.6 19.6 9.0 0.5 2.5

78.0 73.0 63.2 20.6 31.6 64.3 38.0 12.0 48.5

0.89 0.67

64 54

UNECE UNECE UNECE UNECE MNSO APEC
g

32,571 56,214 128,802
h

52 29 0.21 1.75 2.76 59 40 39

747,396 19,000

FUNDES UNECE NAED EC NZMED IADB EC FUNDES IADB IADB APEC PME EC UNECE RSMERC UNECE APEC
g g

0-30 0-19 0-9 0-9 0-9 i ≤ 150,000 1-5 0-10 0-4 0-9 0-9 0-9 FE & IE 0-9 0-4 0-9 0-9 0-9 0-9 0-9 0-9 1-5
j j i

31-100 20-75 10-49 10-99 10-49 i ≤ 1,000,000 6-20 11-49 5-19 10-49 10-49 10-49 < 100 10-49 5-19 10-49 10-49 10-49 10-49 10-49 10-49 6-20 5-19 < 50 10-49 10-99 11-40 11-50 < 30

96.0 80.3

3.1 19.7 7.5 7.0 7.1 13.7 16.6 3.3 8.2 5.6 6.9 10.6 9.4 24.9 13.8 13.1 7.0 5.8 5.6 9.3 18.5 9.0 19.9 76.9

0.9

2,786,011 20,518 450,000

50-249 100-499 ≤ 100 50-249 i ≤ 2,500,000 21-100 50-199 20-99 50-249 50-249 50-249 < 250 50-249 20-99 50-249 50-249 50-100 50-249 50-249 50-249 20-99 50-249 100-499 41-100 51-100 <200
j

90.7 92.6 91.6 83.5 77.5 95.8 91.4 99.2 93.5 91.5 60.0 87.0 68.9 81.7 82.7 92.0 93.5 93.6 89.2 79.4 89.7 79.3

1.6 0.4 1.3 2.8 5.9 0.9 0.4 0.8 0.9 1.5 29.5 3.6 6.2 4.5 4.2 1.0 0.7 0.8 1.7 2.0 1.4 0.8 23.1

570,000 294,714 25,301 238,000 40,985 8,858 235,995 817,976 1,654,822 693,000 402,359 8,441,000 63,732 54,000 61,689 48,541 900,683 2,674,000 485,000 343,000 1,000,000 350,000 233,607 2,226,000 5,644,063 229,600 11,314 200,000

58.5

d

0.75 0.73 1.62

75 68 28 67 47

75.9 78.6 61.5 72.0 67.9
d

77.0
d

3.98 4.41 1.42 25.30 3.13

34 43 45 57 38 32 75

66.0 61.8 81.6
d

40.2 49.0 52.0 32.1 20.3 39.0 76.0 56.5
d

UNECE UNECE NTSA EC EC EC ESRF APEC EC USCB IFC FUNDES APEC
g g

10.81 5.92 59 43 1.28 5.62 15.94 60 67 70 24 52 36 0.86 1.39 69 70 30

75.3 25.0 18.0 5.4 56.4
d

0-4 0-9 0-9 0-10 0-10

UNECE

50.2 57.0 85.0

Venezuela, RB

Note: For information on sources and methodology, see the companion note.
a. s = annual sales (in U.S. dollars); i = annual gross income (in U.S. dollars). b. Leasing is a form of financing in which one party provides another an asset for use for a specified period for specified payments (for a more detailed explanation of the indicator, see the companion note). c. Index based on a set of key investment climate indicators (for a more detailed explanation of the indicator, see the companion note). The higher the index, the better the investment climate. d. Data are from "Small and Medium Enterprises Across the Globe: A New Database," by Meghana Ayagari, Thorsten Beck, and Asli Demirguc-Kunt. They are an average for the 1990s and based on the official country definition of SMEs. e. Data are for small enterprises only. f. Includes working proprietors and unknown. g. Data are APEC's best guess for 2000 or the latest available data (1998-2000). h. All enterprises in the economy.

i. FE = farm enterprises; IE = individual enterprises. j. Except in the mining, electricity, manufacturing, and construction sectors. k. The SME definitions apply only to manufacturing.

Companion note (PDF, 53KB)

Micro, Small, and Medium Enterprises: A Collection of Published Data
Marta Kozak, International Finance Corporation (IFC), Washington, D.C. Date of last update: May 17, 2005

The database “Micro, Small, and Medium Enterprises: A Collection of Published Data” presents secondary data. Using these data for precise country rankings may therefore be inappropriate. The user understands that there may be errors and discrepancies within this database because of differences in the way the sources gather data and in the definitions of micro, small, and medium enterprises (MSMEs) they use in doing so. Because of the discrepancies in these definitions, harmonizing the data is costly and difficult and no attempt has been made to do so. Moreover, the MSME definitions used by each data source are not comparable over time. Accordingly, only the most recent data available are included. The user understands that no claims, implicit or explicit, are made for the database and that any conclusions or inferences drawn from the data are wholly the responsibility of the user. No conclusions or inferences drawn from the data or accompanying materials should be attributed to the World Bank Group, its Board of Executive Directors, its management, or any of its member countries without their express written consent. Please click on the "MSMEbeen prepared for the database “Micro, Small, and Medium Enterprises: A A companion note has Database" tab at the bottom of the page to view the data. Collection of Published Data.” When citing the database, please use its full title. Companion note (PDF, 53KB)

# of SMEs vs. Income
# of SMEs per 1,000 people
50 40 30 20 10 0 0 5000 10000 15000 20000 25000 30000 GNI per capita Upper-middle Low er-middle

Cost to Start a Business vs. # of SMEs

# of SMEs per 1,000 people

High-income

50 40 30 20 10 0 0

High-income Upper-middle

Low er-middl

L

10

20

30

40

50

Cost to start a business (% of income per capita)

Priv. Bureau Coverage vs. # of SMEs

# of SMEs vs. Inform ality

# of SMEs per 1,000 people

50 40 30 20 Low -income 10 0 0 100 200 300 400 500 600 Private bureau coverage (borrow ers per 1,000 capita) Low er-middle Upper-middle High-income

# of SMEs per 1,000 people

50 40 30 20 10 0 0 10

Hign-income Upper-middle

Lo Low

20

30

40

Informal Sector as % of GNI

Cost to Enforce a Contract vs. # of SMEs

Private Credit vs. # of SMEs
50 40 30 20

# of SMEs per 1,000 people

High-income

# of SMEs per 1,000 people

50 40 30 20 10 0 0 10

Hig Upper-middle Lower-middle Low-income

Upper-middle Low er-middle Low -income

10 0 0 20 40 60 80 Private credit as % of GDP

20

30

40

50

10

Cost to enforce a contract (% of debt)

Investment Climate vs. # of SM Es
50

# of SMEs per 1,000 people

40 30 20

High-income Upper-middle Lower-middle Low-income

10 0

50

# of SMEs per 1,000 people

40 30 20

High-income Upper-middle Lower-middle Low-income

10 0 0 10 20 30 40 50 60 70

Investment Climate Index

o Start a Business vs. # of SMEs

income Upper-middle Low er-middle Low -income

20

30

40

50

60

start a business (% of income per capita)

# of SMEs vs. Inform ality

Hign-income Upper-middle Low er-middle Low -income

20

30

40

50

Informal Sector as % of GNI

Private Credit vs. # of SMEs

High-income Upper-middle Lower-middle

me

40

60

80

100

120

Private credit as % of GDP

SM Es

High-income Upper-middle

-middle

High-income Upper-middle

-middle

50

60

70

ex

Time to start a business vs. # of SMEs
90

# of SMEs per 1.000 people

80 70 60 50 40 30 20 10 0 0 20 40 60 80 100 120 140 160 Time to start a business (days)

Cost to start a business vs. # of SMEs
90

# of SMEs per 1.000 people

80 70 60 50 40 30 20 10 0 0 10 20 30 40 50 60 70 Cost to start a business (% of income per capita)

Private Credit vs. # of SMEs
90

# of SMEs per 1.000 people

80 70 60 50 40 30 20 10 0 0 50 100 Private credit as % of GDP 150 200

Investment Climate vs. # of SMEs
80

00 people

70 60 50

0 0 50 100 Private credit as % of GDP 150 200

Investment Climate vs. # of SMEs
80

# of SMEs per 1.000 people

70 60 50 40 30 20 10 0 15 25 35 45 55 65 75 85

Investment Climate Index


								
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