Description
One of the shortcomings of the MPI presented at the website of MSU-CIBER is that it is not product specific. A company might for instance want to identify the potential of markets across the world in regards to their product. Your textbook gives an example of such a case and how the MPI can be constructed. In the following example, a more general example is given with explicit steps on how to construct such an index and its advantages/disadvantages in assessing markets for firm entry. Your assignment is to replicate the MPI 2009 worksheet for any other year in the period 2004-2008. For this particular research task, your report should be a Word or PDF document that has the final MPI table (e.g., Step 4 table in the excel file below). Make sure that you sort the final MPI table by Overall Ranking. You may find it easier to report the top 10 countries in your first page along with a short paragraph describing your findings and copy/paste the full table in the following pages of your document.
Step 1:
The first step in constructing such an index is to select the variables that measure the various markets' potential and the sample of countries that you want to include.
In regards to the sample of countries, the more countries we include in the analysis the more representative the sample is and the more options to choose from. Therefore, a sample with more countries is preferred even if we want to focus on emerging markets since we can always isolate the emerging markets after the analysis is performed.
In regards to variables that measure the various markets' potential, it sometimes is product-specific (e.g., a pharmaceutical company might want to include some different measures in the calculation of MPI than a retail company) but most of the measures will be the same, especially the institutional measures (economic and political freedom, country risk rating). In this example, we have selected the following variables for the year 2009:
Dimension | Weight | Measures Used |
Market Size | 6/25 |
|
Market Growth Rate | 4/25 |
|
Market Intensity | 3/25 |
|
Commercial Infrastructure / Access to Consumer | 3/25 |
|
Market Receptivity | 3/25 |
|
Free Market Structure | 3/25 |
|
Country Risk | 3/25 |
|
1 Source: World Bank, World Development Indicators
2 Source: U.S. Census Bureau Foreign Trade Division, Country Trade Data - 2009
3 Source: Heritage Foundation, The Index of Economic Freedom - 2009
4 Source: Freedom House, Survey of Freedom in the World - 2009
5 Source: Euromoney, Country Risk Survey - March 2011 (earlier data were not freely available)
Step 2:
After the collection of the data, each measure needs to be standardized in order to be comparable with the rest of the measures. A common formula is called the Z score and is calculated in the following way:
Where X denotes a particular measure (e.g., urban population) and its values represent the value for each country in the sample.
Step 3:
After each measure has been standardized, we find the average of all standardized measures within each dimension for each country. That is, for dimension Market Size, its first value will be the average of the standardized urban population and standardized electricity production for country A. Therefore, after this step we have a column of data for each of the seven dimensions of the MPI index.
Step 4:
The resulting scores need to be converted to a scale of 1-100 and for this we use the following formula:
Where Yijs is the scaled final value of country j for the dimension i (i=1,.., 7 ); Yij is the average score of country j on dimension i; mini and maxi are the minimum and maximum values for dimension i, respectively. Finally, we find the weighted average of all dimensions using the weights presented in the previous table (based on input from managers).
Now if all the above sounds really confusing, the following Excel file demonstrates the steps in the construction of the Market Potential Index. In the worksheet "Raw Data" you will find the data that are used in the construction of the MPI for the years 2004 to 2009. In the worksheet "MPI 2009" the steps required for the construction of the MPI are demonstrated (see formulas in the first row cells of each table).
What are some potential advantages and disadvantages of the index?
Advantages
- It's construction is straightforward and it requires only freely available data.
- It provides an initial screening for attractiveness of the foreign market and can be easily modified to account for product-specific factors using different variables from the World Development Indicators or other sources.
Disadvantages
- Looking at the 2009 MPI, Luxembourg is in the third position owing to ratings in all dimensions of the index apart from Market Size. However, market size is an important determinant in assessing entry. Therefore, while the overall index helps us to split good vs. bad choices, we also need to look at the individual components of the index.
- It cannot predict potential future economic or financial distress of the foreign market, especially if it is calculated for a particular year. For instance, Ireland is in the 21st place but it recently received a bailout from IMF. Therefore, for more complete picture several years of observation are needed but more importantly measures that more accurately capture deterioration of the economy and financial situation of each country are needed. We will cover these in more detail in later chapters.
What if we don't have any input from managers to calculate Weights?
If we don't have any information about appropriate weights to use in the calculation of MPI, then we can follow the textbook's paradigm and find the average MPI. In other words, in step 4 of the above example, instead of weighted average we calculate the ordinary average.
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Explanation & Answer
Attached.
Calculating the Market Potential index (MPI)
Data
Market Size
China
100.00
Hong Kong
2.04
Luxembourg
1.00
Singapore
1.89
Canada
10.75
Australia
5.89
Switzerland
2.26
Netherlands
3.56
Iceland
1.16
Norway
2.87
New Zealand
1.80
Denmark
1.81
Germany
13.63
United Kingdom
10.59
Belgium
2.99
Sweden
3.31
Korea South
10.09
Ireland
1.52
Austria
2.24
France
12.08
Finland
2.11
Qatar
1.37
Japan
21.42
Kuwait
1.81
India
45.20
Uruguay
1.32
Panama
1.25
Israel
2.23
Chile
3.05
Oman
1.32
Czech Republic
2.63
Cyprus
1.06
Brazil
21.99
Spain
7.74
Poland
4.92
Estonia
1.12
Bahrain
1.17
United Arab Emirates
2.52
Italy
8.22
Slovenia
1.21
Slovakia
1.52
Saudi Arabia
5.60
Trinidad and Tobago
1.03
Malaysia
4.04
Lebanon
1.43
Mexico
12.13
Costa Rica
1.31
Peru
3.26
Colombia
4.78
Russia
22.49
Hungary
1.99
South Africa
6.71
Portugal
2.12
Turkey
7.89
Indonesia
14.38
Lithuania
1.31
Argentina
5.82
Kazakhstan
2.75
Bulgaria
1.94
El Salvador
1.34
Botswana
1.04
Croatia
1.31
Mongolia
1.12
Greece
2.30
Jordan
1.53
Thailand
4.87
Morocco
2.84
Tunisia
1.76
Dominican Republic
1.74
Algeria
3.58
Vietnam
4.19
Philippines
7.25
Georgia
1.24
Paraguay
1.95
Ghana
2.15
Bolivia
1.60
Romania
2.71
Market
Receptivity (No.
of customers
expected)
8.87
87.22
69.46
100.00
67.40
16.18
36.33
39.20
25.99
16.63
13.92
18.30
17.89
16.82
41.37
19.22
20.99
41.93
18.35
12.18
14.94
28.83
8.54
20.70
7.87
11.36
33.58
23.17
16.79
19.12
21.88
15.48
5.62
10.15
13.45
20.91
32.22
39.37
10.12
19.52
22.83
19.47
30.61
30.35
15.45
20.43
23.41
9.29
8.11
8.66
24.83
10.24
11.52
9.11
8.05
18.81
7.93
12.78
16.93
13.42
13.39
12.69
17.39
10.57
19.25
20.97
11.78
15.47
13.99
9.44
23.50
11.47
13.63
17.81
12.06
11.75
12.37
MONITORING HUMAN DEVELOPMENT: ENLARGING PEOPLE'S CHOICES...
Market Growth
Rate
93.10
54.56
22.60
32.52
32.26
51.95
43.25
38.04
68.00
44.72
46.92
32.10
31.88
26.07
36.64
23.77
54.71
26.17
32.06
34.94
25.55
41.60
26.06
54.60
82.71
85.94
64.55
47.68
43.66
70.46
30.95
49.78
52.30
25.80
52.25
11.34
41.62
27.21
25.48
24.96
26.75
45.26
56.44
43.66
89.45
32.02
55.95
58.79
57.09
30.99
24.88
48.77
32.75
45.66
62.73
15.91
55.24
69.12
26.74
50.07
37.40
32.95
61.02
36.78
54.14
46.28
66.81
60.27
51.99
66.29
76.31
43.18
48.91
45.78
54.47
64.55
21.23
Page 1
Market
Penetration Rate
(Markert
Size/Growth
1.07
0.04
0.04
0.06
0.33
0.11
0.05
0.09
0.02
0.06
0.04
0.06
0.43
0.41
0.08
0.14
0.18
0.06
0.07
0.35
0.08
0.03
0.82
0.03
0.55
0.02
0.02
0.05
0.07
0.02
0.08
0.02
0.42
0.30
0.09
0.10
0.03
0.09
0.32
0.05
0.06
0.12
0.02
0.09
0.02
0.38
0.02
0.06
0.08
0.73
0.08
0.14
0.06
0.17
0.23
0.08
0.11
0.04
0.07
0.03
0.03
0.04
0.02
0.06
0.03
0.11
0.04
0.03
0.03
0.05
0.05
0.17
0.03
0.04
0.04
0.02
0.13
Market
Intensity
20.24
77.05
93.68
82.20
62.08
67.96
63.03
65.33
68.09
71.82
59.82
66.06
56.98
65.22
70.92
63.99
55.51
52.66
55.26
57.60
50.98
100.00
50.24
82.33
9.64
51.98
41.57
61.46
50.80
49.54
49.27
51.71
46.65
56.50
38.26
43.56
58.51
68.86
51.39
36.47
38.16
52.49
15.58
40.54
49.07
44.10
34.45
37.23
39.36
44.84
42.89
32.41
41.67
39.73
23.25
40.22
53.04
31.44
40.52
29.73
33.74
36.75
25.79
45.33
39.08
15.05
25.72
34.91
36.20
33.63
8.68
30.46
23.85
28.31
20.49
31.34
31.27
Market Potential
index (MPI)
value
1,794,175.17
28,030.05
6,507.24
29,441.93
483,322.09
38,202.56
11,691.98
32,471.30
2,361.01
9,833.43
2,689.40
3,958.14
189,266.35
123,014.49
26,164.57
13,456.98
118,539.22
5,076.48
5,093.98
102,321.99
3,395.24
5,380.10
196,764.21
5,581.96
155,059.58
1,024.83
2,165.19
7,057.21
7,954.05
1,649.77
7,447.01
896.36
126,657.40
34,341.61
12,460.78
1,135.66
2,562.22
17,250.81
35,172.77
1,048.76
2,019.25
32,034.35
510.31
20,116.49
1,549.06
132,653.84
1,379.17
3,672.90
7,303.72
196,559.18
4,215.86
14,952.12
2,148.29
22,529.99
38,680.52
1,296.24
14,260.53
3,028.80
2,579.73
718.59
488.63
805.21
561.08
2,542.99
1,754.13
7,472.85
2,437.58
1,674.93
1,531.28
4,058.37
3,579.42
18,388.56
502.70
1,912.48
1,146.08
938.20
2,835.16
28 March: 5:45pm
Data
Market Size
Latvia
1.13
Egypt
5.77
Libya
1.74
Azerbaijan
1.58
Ecuador
2.01
Albania
1.13
Jamaica
1.12
Nigeria
8.19
Iran
8.06
Bosnia and Herzegovina 1.28
Belarus
1.94
Ethiopia
2.28
Bangladesh
5.15
Venezuela
4.88
Sri Lanka
1.33
Zambia
1.47
Pakistan
7.86
Armenia
1.17
Kenya
1.81
Senegal
1.44
Ukraine
5.93
Nicaragua
1.27
Cote d'Ivoire
1.88
Syria
2.46
Uzbekistan
2.48
Cameroon
2.02
Cambodia
1.23
Moldova
1.10
Myanmar
2.46
Market
Receptivity (No.
of customers
expected)
15.66
10.13
16.30
12.32
12.87
13.62
18.79
11.10
9.12
14.04
18.06
6.96
7.94
9.93
8.50
11.24
6.08
10.04
10.30
11.29
15.41
16.53
12.60
10.21
12.00
9.80
16.93
17.70
1.00
MONITORING HUMAN DEVELOPMENT: ENLARGING PEOPLE'S CHOICES...
Market Growth
Rate
7.24
66.06
57.90
50.28
47.30
31.83
27.74
56.86
65.83
57.18
49.74
100.00
75.56
35.47
53.89
59.30
58.78
20.27
55.84
46.98
1.00
30.28
55.28
57.37
62.61
43.27
51.08
8.39
62.46
Page 2
Market
Penetration Rate
(Markert
Size/Growth
0.16
0.09
0.03
0.03
0.04
0.04
0.04
0.14
0.12
0.02
0.04
0.02
0.07
0.14
0.02
0.02
0.13
0.06
0.03
0.03
5.93
0.04
0.03
0.04
0.04
0.05
0.02
0.13
0.04
Market
Intensity
40.21
18.90
46.34
26.62
33.56
23.32
26.21
20.00
37.68
23.70
41.32
1.00
7.30
52.40
2.29
11.76
13.12
30.48
4.06
16.09
33.62
24.86
19.95
25.12
13.47
24.86
4.54
16.10
10.64
Market Potential
index (MPI)
value
809.38
6,370.05
2,296.10
823.12
1,742.38
403.89
622.83
14,900.66
22,326.64
546.48
2,817.52
36.05
1,535.75
12,405.27
34.53
285.00
4,928.22
422.21
136.57
375.18
18,216.69
660.04
890.02
1,554.06
991.36
990.86
115.58
347.71
64.46
28 March: 5:45pm
Attached.
World Development Indicators (WDI from World Bank)
Year
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
Row Labels
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bahrain
Bangladesh
Belarus
Belgium
Bolivia
Bosnia and Herzegovina
Botswana
Brazil
Bulgaria
Cambodia
Cameroon
Canada
Chile
China
Colombia
Costa Rica
Cote d'Ivoire
Croatia
Cyprus
Czech Republic
Denmark
Dominican Republic
Ecuador
Egypt
El Salvador
Estonia
Ethiopia
Finland
France
Georgia
Germany
Ghana
Greece
Hong Kong
Electricity production (kWh)
5443000000
33915000000
1,05505E+11
6317000000
2,45216E+11
63613000000
21218000000
8867000000
26506000000
30961000000
85709000000
4896000000
12602000000
867000000
4,03423E+11
43972000000
880000000
4004000000
6,26033E+11
52484000000
2,49966E+12
50411000000
8252000000
5684000000
12354000000
4377000000
81931000000
36246000000
12623000000
12164000000
1,0869E+11
4770000000
10205000000
2845000000
70550000000
5,71497E+11
7267000000
6,13438E+11
6788000000
59427000000
38451000000
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
Hungary
Iceland
India
Indonesia
Iran
Ireland
Israel
Italy
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Korea South
Kuwait
Latvia
Lebanon
Libya
Lithuania
Luxembourg
Malaysia
Mexico
Moldova
Mongolia
Morocco
Myanmar
Netherlands
New Zealand
Nicaragua
Nigeria
Norway
Oman
Pakistan
Panama
Paraguay
Peru
Philippines
Poland
Portugal
Qatar
Romania
Russia
Saudi Arabia
Senegal
Singapore
Slovakia
Slovenia
35756000000
8686000000
6,98242E+11
1,27751E+11
1,75698E+11
25626000000
48602000000
2,96839E+11
7422000000
1,08991E+12
9654000000
67847000000
5995000000
3,87874E+11
43734000000
4906000000
12419000000
22317000000
14415000000
3346000000
84826000000
2,43823E+11
3864000000
3512000000
19911000000
6015000000
1,00219E+11
42969000000
3051000000
23539000000
1,37229E+11
12648000000
93832000000
5827000000
51166000000
25499000000
56567000000
1,55359E+11
46188000000
14396000000
59413000000
9,51159E+11
1,76124E+11
2544000000
38213000000
31352000000
15117000000
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
South Africa
Spain
Sri Lanka
Sweden
Switzerland
Syria
Thailand
Trinidad and Tobago
Tunisia
Turkey
Ukraine
United Arab Emirates
United Kingdom
Uruguay
Uzbekistan
Venezuela
Vietnam
Zambia
2,42053E+11
2,88924E+11
9324000000
1,58365E+11
57789000000
34935000000
1,32198E+11
7058000000
13793000000
1,61956E+11
1,85913E+11
60698000000
3,95425E+11
7682000000
49200000000
1,05492E+11
53462000000
8936000000
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
4,02589E+12
3,83883E+12
4,0264E+12
4,05465E+12
4,14808E+12
4,26889E+12
4,27501E+12
4,32391E+12
4,34298E+12
4,16539E+12
Indicators (WDI from World Bank)
Energy use (kg of oil equivalent per capita)
724,181361
980,8751395
1731,386204
817,0536805
5863,865691
4126,327492
1652,886193
10348,06369
169,8442132
2749,003988
5600,4279
571,0302837
1334,888036
1027,91638
1158,386111
2569,26304
356,0735655
398,4864292
8424,31202
1699,574266
1301,191587
650,2511422
943,9958528
534,6092819
2004,788158
2150,063628
4386,925904
3485,343298
851,5017972
803,0777717
819,9623156
747,886171
3836,514753
289,1792012
6523,702006
4295,595708
651,5215996
4107,001671
393,5033429
2724,028849
1858,726149
GDP growth (annual %)
5,5
5,099999286
9,178950217
13,86571125
2,959140943
2,400671933
26,4
7,8
5,955478473
9,440903631
1,731614415
4,4214331
5
1,642293696
3,159673613
6,35830682
13,25008556
2,296654441
3,019057345
5,559452531
11,3
4,706555934
5,886377766
1,255967959
4,279805801
3,909963232
6,316354932
2,445147924
9,262750072
5,743750704
4,471744472
3,562814501
9,434108527
11,81884442
2,916059866
1,826524011
9,599640575
0,684655658
5,900003848
2,280343689
7,082103152
2734,495515
11729,26931
471,831885
797,969936
2524,818452
3470,473909
2919,925109
3137,385229
1422,833157
4073,745697
1232,396009
3349,790048
458,8983174
4364,577797
11660,15802
1920,583331
1236,598131
3042,884312
2521,213108
9393,657639
2396,604844
1597,933401
983,6116781
1005,00326
430,0820141
344,7138481
4829,935573
4004,607513
611,8806062
745,2199254
5787,639151
4482,946767
480,1552881
785,6324311
696,7804692
495,1523415
457,9776313
2420,428846
2508,874703
20550,78893
1767,370126
4552,64846
6053,805323
256,7071024
4363,163299
3495,53657
3645,458526
3,964434001
7,22998096
9,318924227
5,692571304
4,623405402
5,339613725
5,098819056
0,931267136
1,029633059
1,934092538
8,121307574
9,7
5,906666078
3,957153703
10,6
10,60091218
1
9,9
7,802232865
5,429813842
5,332139139
3,205432102
7,501389578
7,253665443
2,97851241
13,49177739
2,046466883
3,302650115
4,282553784
5,4
2,58893558
3,994
7,667304273
7,191278857
2,876177892
6,826688658
4,777663461
3,617049813
0,77520316
7,6
4,17229732
6,376187027
5,553678497
5,627088763
7,382768859
6,655217262
4,007255923
2761,959546
3268,1288
453,6122298
5711,127283
3484,700855
1157,224996
1439,566804
12744,20512
820,6526074
1238,261636
3033,34474
10623,75653
3692,259605
891,7704236
1794,277334
2503,197313
618,4086002
628,2782829
5,277116992
3,614326038
6,241748044
3,160784989
2,640644969
6,2
4,604698946
5,8
4,000154486
8,401617472
2,7
4,855141195
2,085765842
7,460132065
7
10,3179138
8,441789562
5,341379152
8056,819755
7828,280431
7843,392547
7794,172574
7881,753533
7846,804917
7697,187705
7758,205892
7487,930303
7050,573288
4,17339067
1,093331662
1,82731315
2,502587834
3,585430846
3,059076051
2,674149622
1,941762606
-0,020505966
-3,5
GDP per capita, PPP (current international $)
6101,647077
7168,564544
10833,40561
4096,440119
32719,02501
33626,38683
4496,143936
28068,47168
1164,596077
8540,815921
32181,07154
3772,038631
6234,0612
11542,21597
8509,426303
9809,434513
1508,008397
1985,738586
35033,42293
12168,37625
4114,572834
7304,555744
9041,537249
1666,009606
15331,95179
24408,1916
20362,30307
33193,23729
6380,369074
6510,394446
4490,619597
5702,187624
16547,96059
636,0687043
30707,94588
29534,32827
3610,648433
31114,53059
1208,014388
24348,40224
35677,91851
Internet users (per 100 people)
6,043890864
5,843942092
17,72058337
5,252983352
63,02693628
58,03078406
8,217982517
21,30373351
0,241637326
14,45172945
59,4423711
5,227583957
21,326701
3,262554036
21,02274725
19,96797459
0,317321781
1,402654226
71,59660113
31,17534703
8,548580494
11,00726389
22,07
1,039238205
33,13989555
32,81
35,21765921
82,74018321
11,48319778
5,994255161
11,69839821
4,2
61,43904388
0,219659819
74,45509807
41,50584453
6,240889728
68,76941828
1,831197461
24,17107186
56,87209785
16974,55981
34889,18754
2208,058729
3102,28377
9228,236095
38896,38661
23390,11179
28279,87053
7027,444445
30310,34056
4334,477445
8699,098081
1346,397519
22783,27005
48782,64549
13040,5161
9595,290945
14015,36563
14197,38197
68319,63721
11544,27732
12191,06382
2361,950703
2861,679068
3508,299806
1062,307745
35104,48753
25304,94062
2335,563655
1749,651332
47626,27982
21047,46362
2144,795404
9166,563557
3900,787361
6386,955259
3050,826694
13784,16006
21368,95879
69512,33141
9361,408043
11852,80594
20405,80675
1674,808252
45374,23755
16174,8268
23475,57268
38,96950163
87,00263873
2,388075
3,602024763
8,1
41,59127511
24,01060117
35,03831801
12,9509351
66,19826223
12,76675995
2,966551957
3,101897702
71,82980724
25,92610837
46,10029767
10,14
3,917787977
36,2353184
68,80197696
48,62917025
17,21
15,32896378
7,264786302
15,08444452
0,065238856
80,92847424
62,72350473
2,566351177
3,549155718
81,99012414
6,68358142
6,332329098
11,48400928
7,907007861
17,1
5,397636329
38,80958816
34,9708921
24,73349378
21,63652475
15,30040359
12,70503599
4,786684083
61,00284566
55,4819322
46,84767312
8596,830871
27376,80046
3514,691409
32702,98278
35784,01319
4133,448396
6674,740219
20058,23691
7182,365625
11464,73258
5583,399175
66854,72186
32737,9538
9682,791069
2000,965505
9924,462109
2161,272404
1157,593472
7,582837445
47,87701896
1,792046794
84,82786741
69,89161667
5,648106049
15,02600436
28,97671243
9,542558429
15,46
3,735338316
40
69,9749171
20,19031612
3,315452107
12,59414786
12,85862486
2,851752261
35081,92308
35912,33298
36819,44509
38224,39423
40341,82469
42568,5056
44695,3681
46459,32983
47014,74412
45793,2218
43,13014069
49,18000685
58,95751701
61,94868178
65,03644256
68,26789985
69,20484774
75,26226292
74,21781837
71,21181627
Mobile cellular subscriptions (per 100 people)
48,70596473
41,53845929
57,27961101
10,37341069
90,31713966
105,3133214
26,71639746
105,8354845
6,401687906
41,93608134
91,65994902
26,4730877
42,16785449
30,05758466
46,3528917
80,68478921
7,950545511
12,83217922
52,66340678
64,83713442
30,17565121
50,76605419
25,55580076
13,03726785
82,16343989
75,78266487
115,0456807
100,5493934
39,1103689
46,5227542
18,36793999
39,86030606
107,3696769
0,552933815
100,4556531
76,32864064
26,92625883
96,12168738
13,28366807
92,40299298
125,407371
Population, total
3141800
32888449
38681174
3065954
20394800
8227829
8391850
724807
140587922
9775591,494
10478617
9146655
3781001
1875673
185986964
7739900
13357574
17553589
32312000
16301726
1303720000
43040558
4309413
18020946
4442000
1032562
10235828
5419432
9264267
13426402
74203215
6050513
1346097
74263861
5246096
63001253
4361200
82469422
21639806
11103965
6813200
Roads, paved (% of total roads)
39
70,19999695
30
89,97000122
41,57
100
49,38999939
80,31283711
9,5
88,63999939
78,21199799
6,913
52,29999924
32,59999847
5,5
98,40000153
6,289999962
12,86499994
39,86999893
21,038
40,79999924
14,39999962
24,39999962
8,119999886
84,92774536
64,58999634
100
100
49,40000153
14,97000027
81
19,79999924
22,67000008
11,04791126
65,04000092
100
94,06758817
100
14,93029308
91,80000305
100
92,39555807
95,40800852
7,906720258
20,63762286
12,20460068
102,6463528
111,9320068
121,9989891
74,76094174
75,51204089
57,98207521
35,63735172
12,94966982
79,65084341
100,573583
81,35588947
24,51762157
34,66379327
127,506133
109,6401653
74,88436601
44,2590939
30,31279084
21,87408115
40,77590198
0,277842771
97,02284357
85,3915189
20,63624009
13,29320269
102,8369834
54,87629193
8,050153316
54,00144087
31,99489438
20,25981639
40,65511117
76,42093784
108,5112609
87,30514284
61,72649068
83,82815229
58,91649955
15,91354526
102,7849407
84,28389005
87,94075804
10087065
296734
1140042863
227303175
69732007
4159914
6930100
58607043
2650400
127773000
5411500
15147029
35614576
48138000
2264014
2300512
4052420
5769709
3414304
465158
26100241
106483757
3595182
2547339
30392473
46321162
16319868
4133900
5424336
139823340
4623291
2429510
158645463
3238321
5897816
27558769
85546427
38165445
10549424
820986
21634371
143150000
24041116
10871908
4265800
5387001
2000474
43,90000153
35,38999939
46,99
55,4242997
71,02431595
100
100
100
73,27999878
79
100
91,16000366
14,11999989
76,81999969
85
20,42
84,90000153
57,20000076
28,29999924
100
81,31999969
36,97999954
86,25
3,5
61,88999939
11,85000038
90
64,88999939
11,35999966
15
77,5
39,65624456
64,69999695
34,12263447
50,79999924
14,39999962
9,899999619
66,52847932
86
90
30,20000076
84,40000153
21,46999931
29,26000023
100
87,01999664
100
71,95139741
98,37774626
16,94226484
100,8242694
91,8936039
15,95964363
46,68253249
70,25314242
56,64299531
63,99607585
63,71596312
111,4218269
108,7130235
34,93707731
2,751557305
47,01704858
11,64315146
8,284145549
47198469
43398143
19842536
9029572
7437115
18484122
66698483
1315386
10029000
68143186
47105150
4069349
60224307
3305723
26167000
26577000
82393500
11462365
17,29999924
99
81
31,47999954
100
95,15
98,5
51,09999847
65,80000305
61,225
97,41999817
100
100
9,960000038
87,30000305
33,59999847
43,89301029
22
38,7996511
45,09263123
49,30027113
55,37146066
63,12010106
68,93013817
76,94887986
82,76034959
85,92738733
89,41507737
282162411
284968955
287625193
290107933
292805298
295516599
298379912
301231207
304093966
306771529
66,19999695
64,5
65,33999634
65,33999634
65,12
67,37
67,37
Roads, total network (km)
18000
108302
231374
7515
810641
105660
59141
3708
239226
94797
151372
67076
21846
25798
1751868
40231
38257
40023,8
1408900
80651,11
3345187
164257
35330
80000
28472
12146
128437
72257
12600
43197
98875
10029
57016
42370
78821
950985
20247
644480
57614
117533
1955
Secure Internet servers (per 1 million people)
0,318288879
0,091217436
10,80629042
1,304651016
498,068135
231,6528455
0,476652943
48,28871686
0,02133896
0,511478001
117,8590648
2,405250881
3,438242941
0,796008199
14,17841306
8,65644259
0,074863894
0,113936814
569,1074523
21,04071679
0,326757279
4,437674809
61,9573942
0,277454913
39,62179199
175,2921374
41,52082274
411,2977153
5,612964307
4,021926351
0,525583696
6,115183952
101,7757264
0,013473539
308,2292051
76,28419708
4,585893791
274,1622222
0,138633405
31,43021434
162,3319439
Telephone lines
278973
2572000
9441673
594404
10120000
3739000
1094200
193520
1070000
3284272
4794583
646291
968857
136463
39852600
2490022
32971
100331
18148000
3435888
350445000
7678804
1388503
258515
1882500
420030
3217340
3348177
896252
1679568
10474273
971455
442045
610347
2120000
33707000
570200
54791000
321526
6311656
3792912
159600
13029
3929439
391009
172027
96418
17589
487700
20996
1192400
7601
90845
63265
102293
5794
69829
6970
83200
79987
5227
98722
355796
12737
49250
57626
27000
134218
93460
19501
193200
92864
40203
258214
11983,92
28835
78506
202123
381462,8
82900
7790
198817
858000
221372
14805
3234
43744,64844
38484,89844
30,03847006
1004,266447
0,577171281
0,453139293
0,286812339
353,8534691
162,768214
44,2097036
14,3374585
257,6992009
3,695832948
0,858254117
0,252705521
20,02575928
35,33547054
37,81766841
8,390048416
0...