 Chapter 2
The Middle-Income Trap Verified by Data
—The Exit Key is Developing Institutions
Nariyasu Yamazawa
Professor, Atomi University
Key Points


Data were confirmed focused on the conditions in each ASEAN country regarding
the reality of the middle-income trap. Surprisingly few economies, just South Korea
and Taiwan, made the transition to being high-income countries/regions within 30
years after the per-capita GDP reached $2000 (on a 2005 PPP basis). Of the major
five ASEAN countries excepting Singapore, only Malaysia has reached $10,000.

Examining the middle-income trap from the perspective of a stagnating growth rate,
there are many countries which reached this stagnation around a per-capita GDP (ona 2005 PPP basis) of around $10,000. However, many Asian countries stagnated in
the 1990s, and there is the possibility of an influence from other regions such as
Japan’s economic slump.

In order to escape from the middle-income trap, it is necessary to develop theinstitutions of each country. In an investigation of the institutional factors in eachcountry, areas to improve are seen in the political institutions in Thailand, theinstitutions pertaining to entrepreneurship in Indonesia and the Philippines, and thelike.


The levels of each ASEAN country having many areas of improvement(comparison of “institutional quality)
Institution evaluation index (deviation values)
Overall

Politics

Openness

GenderEntrepreneurship

Labor

Japan

54

60

49

41

49

62

S. Korea

52

53

53

40

49

40

China

38

43

35

50

38

44

Malaysia

45

48

42

40

45

55

Thailand

44

38

48

48

48

57

Indonesia

40

43

41

44

34

43

Philippines

42

42

44

61

36

43

Vietnam

39

46

34

50

40

53

Note: The light shading indicates a deviation value of at least 40 and less than 50.
The dark shading indicates a deviation value of less than 40.
Source: JCER “Global Long-Term Forecast and Three Futures.”

Chapter 1 Research,| The Middle-Income
Verified Reportby Data
Japan Center for Economic
2013 “AsiaTrap
Research”

1. Defining “middle-income”
In order to analyze the “middle-income trap,” it is first necessary to define“middle-income.” The World Bank classifies countries into income levels on the basis of percapita gross national income (GNI).
The classification baseline is altered one time per year. It is made public on July 1 ofevery year based on the per capita GNI from the previous year, and is not changed for theduration of the year. It is based on the nominal exchange rate, and so is revised annually so thatthe real value does not change.
Data from 2011 were used until June 30, 2013, and “middle-income” was defined asa per capita GNI of at least $1025 and less than $12,475. The 2012 data have been the baseline
since July 1, 2013, and “middle-income” is defined as a per capita GNI of at least $1035 andless than $12,615.
Analyses of the middle-income trap also, at times, use per capita gross domestic
product (GDP) depending on the person performing the analysis. GNI includes the net receipts
of income from abroad by the general concept of the “populace,” but GDP does not include
those net receipts as part of the general concept of “domestic.” Although GNI, based on thegeneral concept of income, is preferable for classifying income compared to GDP, based on thegeneral concept of product, GDP is often used as data are more easily obtained compared to
GNI.
When comparing GNI or GDP among countries, it is not possible to make acomparison based on the currency of each country, and so it is necessary to adjust to a common
unit. It is common for US dollars to be the baseline, but there are a number of methods forconverting to US dollars represented primarily by two types: nominal exchange rate, andpurchasing power parity (PPP).
The nominal exchange rate applies market exchange rates as-is, and sostraightforwardly represents the value on a dollar basis at a particular point in time. However, itchanges greatly when exchange rates fluctuate, even if the real state of the economy in the
country in question remains the same. It is not suitable for continuous comparisons between
countries, and so purchasing power parity is more often used for the exchange rate.
Purchasing power parity does not indicate the market exchange rate, but rather a ratioof common commodity prices between a particular country and the US. Annual fluctuations incommodity prices are reflected in it, but these are not large fluctuations, and so it is used as anindex better representing the purchasing power in each country.

Japan Center for Economic Research “Asia Research” ReportMiddle-income has been defined using a variety of units and baselines, but to what
degree are each of these consistent? What will be compared here are per capita GDP (on a2005 PPP basis) and per capita GNI (in nominal dollars).
Figure 1 plots the values for each country/region in 2011 with per capita GNI (innominal dollars) on the horizontal axis and per capita GDP (on a 2005 PPP basis) on thevertical axis.
Here, let us consider the relationship between nominal exchange rates and purchasing
power parity. Purchasing power parity on a dollar basis is a ratio between commodity prices in
the US and commodity prices in a given country, and is represented by the following formula:
Purchasing power parity domestic currency / dollars
domestic commodity prices domestic currency / US commodity prices dollars

1

The ratio between domestic commodity prices and US commodity prices in terms ofthe domestic currency is the domestic/foreign price difference. The cheaper commodity prices
in a country are compared to those in the US, the lower the domestic/foreign price difference.
Domestic/foreign price difference
domestic commodity prices domestic currency / US commodity prices dollars
nominal exchange rate domestic currency / dollars

2

Substituting formula (1) into formula (2) results in the following:
Purchasing power parity domestic currency / dollars
multiplicative factor

domestic/foreign price difference

nominal exchange rate domestic currency / dollars

If there is no domestic/foreign price difference, the two match, but if there is such a
difference and domestic commodity prices are cheaper than those overseas, purchasing power
parity moves in the direction of appreciation of the domestic currency.

In general, domestic

commodity prices compared to those abroad tend to be lower in low-income countries andhigher in high-income countries. As a result, purchasing power parity and nominal exchange
rates do not have a linear relationship when incomes increase (Figure 1).

Chapter 1 | The Middle-Income Trap Verified by Data

Figure 1: The relationship between GDP and GNI (1 of 2)
($)
（ド
90000
１人当たりＧＤＰ（２００５年購
Per capita GDP (2005 PPP basis)

80000
70000
60000
50000
40000
30000
20000
10000
0
0

20000

40000

60000

80000

Per
capita GNI (nominal dollars)
１人当たりＧＮＩ（名目ドル）($)（ド

Figure 2: The relationship between GDP and GNI (2 of 2)
($)

25000

Per capita GDP (2005 PPP basis)y = 1.2523x + 848.47
R² = 0.9264
20000
15000
10000
5000
0
0

5000

10000

15000

Per capita GNI (nominal dollars)

Japan Center for Economic Research “Asia Research” Report

20000

($)

However, for countries with a per capita income up to approximately $20,000 which
are the topics here, this seems to approach a linear relationship (Figure 2).

Examining thedata from 2011, the following formula can be inferred:

Per capita GDP = 1.3 × per capita GNI + 850

The standard for middle-income countries in Alyar at al. (2013) is similar to theresult of substituting the World Bank standard in the inferred formula above. If the World Bank
per capita GNI (on a nominal dollar basis) is estimated as per capita GDP (on a 2005 PPP
basis), the upper limit for low-income countries becomes $2132, which is a value
approximately double the $1000 per capita GNI (on a nominal dollar basis). The upper limit
for lower-middle-income countries becomes $5902 and the upper limit forupper-middle-income countries becomes $16,471. The standard in Alyar et al. (2013) has an
upper limit for low-income countries of $2000 and an upper limit for upper-middle-income
countries of $15,000, which is broadly speaking similar to the World Bank standard.
In Felipe (2012), the PPP baseline differs by being from 1990, but the upper limit for
low-income is similar to that of the World Bank. Nevertheless, the upper limit forlower-middle-income countries is higher than that of the World Bank, and the upper limit forupper-middle income countries is lower than that of the World Bank.

Figure 3: Definitions of middle-income countries
SourceIndex

World Bank
(FY2012)
Felipe (2012)

Per capita GNI(nominal dollars)
Per capita GDP(1990 PPP)Per capita GDP(2005 PPP)

Aiyar et al.
(2013)

Upper limit for
low-income
countries
1025 (2132)

Upper limit forlower-middle-income
countries
4035 (5902)

Upper limit forupper-middle-income
countries
12475 (16471)

2000

7250

11750

2000

-

15000

Note: The values in parentheses are estimated conversions to per capita GDP.

2. The reality of the middle-income trap

2.1 The middle-income trap depending on differences of definition

Chapter 1 | The Middle-Income Trap Verified by DataAs seen in chapter 1, there are many definitions for “the middle-income trap.” Here,the reality of the middle-income trap as seen from income levels and as apprehended as thestagnation of growth is examined focusing on the ASEAN countries.

2.2 The middle-income trap as seen from income levels
IMF (2013), Chapter 3, “Is Middle-Income Asia at Risk of a Sustained Growth
Slowdown?” makes the analysis that after reaching a per capita GDP on a PPP basis of $3000,
there are countries that grow and countries that stagnate. This way of thinking uses the point intime that a particular income is reached as a baseline, investigates how much income increased
thereafter, and determines whether or not the country was caught in the trap. For example, after
reaching a per capita GDP of $3000, failing to reach $10,000 after 30 years would beconsidered being caught in the trap. The analysis results notes Taiwan and South Korea as
countries/regions that succeeded, and Brazil, Mexico, and Peru as countries that stagnated.
In IMF (2013), the boundary between low-income countries and middle-income
countries is considered to be $3000, but as seen in the previous section, the boundary between
low-income and middle-income is often taken to be $2000 on a PPP basis. Therefore, theincome movements of countries/regions after reaching $2000 was examined (Figure 4). The
per capita GDP (on a 2005 PPP basis) data from the Penn World Table (PWT 7.1) were used.
The data start in 1950, and so many of the Western countries that had reached $2000
by that time are not included in the table. Japan’s per capita GDP in 1950 was $2787, and soJapan is also not included. Also, for countries for which data started to be collected later on,
those which started above $2000 are not included.
Although the lowest standard for a middle-income country to become a high-income
country, which is in Felipe (2012), is $11,750, a classification was performed with an evenlower standard of having reached $10,000. This is because looking at the movements of eachcountry after reaching $2000, there are not that many countries that even reached $10,000.
After reaching $2000, the only two countries/regions that reached $10,000 within 30
years were South Korea and Taiwan. Countries which reached $10,000 later, and grew steadily
thereafter were St. Christopher and Nevis, Malaysia, and Panama. In 2012, the population of St.
Christopher and Nevis was 54,000, and that of Panama was 3.4 million, and so both are small
countries. After reaching $2000, Malaysia exceeded $10,000 after 35 years, standing at$11,956 after 41 years in 2010, but has not reached the $15,000 standard for being ahigh-income country according to Aiyar et al.

Japan Center for Economic Research “Asia Research” Report

There are also many countries which have not reached $10,000 for a long period oftime. The countries which reached $2000 but have not reached $10,000 in the subsequent 60
years are South Africa and Bolivia. The Latin American countries of Chile, El Salvador, andPeru can be cited as countries which have taken over 50 years.

Figure 4: Income level trends in various countries after reaching $2000
Classification
Reached $10,000 by 30th year
Other countries that reached $10,000

Did not reach $10,000 after at least 60 years
Did not reach $10,000 after at least 50 years but less than
60 years
Did not reach $10,000 after at least 40 years but less than
50 years
Did not reach $10,000 after at least 30 years but less than
40 years
Did not reach $10,000 after at least 20 years but less than
30 years
Did not reach $10,000 after at least 10 years but less than
20 years
Less than 10 years after reaching $2000

Countries
Taiwan (25 years), South Korea (24 years)
St. Christopher and Nevis (34 years), Malaysia (35years), Botswana (36 years, declined thereafter, Romania(44 years, declined thereafter), Panama (49 years)
NicaraguaBrazil, Dominica
Syria, Tunisia, Fiji
Swaziland, the Philippines, Thailand, Mongolia,
Morocco, the Congo
Egypt, Indonesia, Maldives
Sri Lanka, Bosnia and Herzegovina, Armenia, China,
Bhutan, Cape Verde
India, Vietnam, Pakistan, Uzbekistan, Laos, Sudan,
Kyrgyzstan, Ghana

Source: classified using the PENN World Table

Figure 5 indicates the movements of per capita GDP after reaching $2000. Thailand
and the Philippines have not reached $10,000 after over 30 years. Indonesia was at $3966 on
the 22nd year, China was at $7130 on the 15 year, and Vietnam was at $2780 on the secondyear.
The vertical axis is on a logarithmic scale, so the slope of the graph represents thegrowth rate. China had a growth rate exceeding that of South Korea and Taiwan, which wereable to become high-income countries/regions. There is a high likelihood that China will reach$10,000 soon. However, it is unknown whether the steady high growth rate will continue
thereafter.
Malaysia continued with high growth until the fifth year, but its growth rate thereafter
has not been as high as that of South Korea and Taiwan. Thailand, the Philippines, andIndonesia have even lower growth rates.
It is true that there are many countries that have not become advanced nations after
becoming middle-income countries, and countries where incomes have steadily increased are
the exception.

Chapter 1 | The Middle-Income Trap Verified by Data

Figure 5: Per capita GDP in Asian countries/regions
($)

20000

TaiwanS. Korea
Malaysia
Philippines
ThailandIndonesia
China

2000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49(Years)Note: The per capita GDPs (PPP 2005 basis) are plotted from when $2000 level was reached.

2.3 The middle income trap as the stagnation of growth
Meanwhile, Eichengreen et al. (2013) considers the situation of growth stagnation to
be the middle-income trap. The conditions for stagnation are as follows: from a point in time t,
the average growth rate in per capita GDP is calculated for a seven-year period before and after,and stagnation is diagnosed when 1) the average growth rate in the first half of the period is atleast 3.5%, 2) the average growth rate in the second half of the period is at least two percentage
points lower than that in the first half, and 3) the per capita GDP at time period t is at least$10,000 (2005 PPP basis; below referred to as the “$10,000 baseline”).
On this basis, the conclusion was that stagnation occurs when the per capita GDP
reaches around $10,000-$11,000, and around $15,000-$60,000.
However, when considering the ASEAN countries, Malaysia is the only country thatrecently met these conditions. This is because the others do not fulfill the $10,000 baseline
criteria in 3).
Therefore, whether or not there was a stagnation in growth rates was examined
excluding the condition in 3), and the years in which Japan, South Korea, Taiwan, Hong Kong,and the ASEAN countries met the conditions were listed.

Japan Center for Economic Research “Asia Research” ReportFigure 6 has shading during the periods in which stagnation occurred for eachcountry/region. The crosshatching is applied to stagnating growth including the $10,000
baseline. The circles indicate the years in which per capita GDP reached $10,000.
Looking at the table, it can be understood that the $10,000 demarcation asserted by
Eichengreen et al. (2013) is appropriate even when considering only Asia.
The per capita GDP in Singapore exceeded $10,000 in 1974, and in Hong Kong in
1977. It can be understood that stagnation occurred around when $10,000 mark was exceeded.
A similar tendency can be noted for South Korea and Taiwan. There was a period of stagnationin the 1970s, but not in the 1980s. Taiwan exceeded $10,000 in 1987 and South Korea did in
1989. Both countries/regions stagnated in the 1990s, at which point they had exceeded$10,000.
Looking at the ASEAN countries, Malaysia, the Philippines, and Indonesia stagnatedin the 1970s. In the 1990s, Malaysia, Thailand, and Indonesia stagnated. The reason there is nosign of the Philippine stagnation in the 1990s is that the growth rate was less than 3.5%, and sohigh growth has not been continuing.
Meanwhile, data are available from 1977 onwards for Vietnam, but the country has
continued high growth, and has not experienced stagnation. Malaysia reached $10,000 in 2004,
and based on past experience, there is a possibility that it will stagnate in the future.
From the start of the 1990s, Japan, Hong Kong, Singapore, South Korea, Taiwan, and
the ASEAN countries experienced stagnating growth. In Japan, the bubble burst and there was
the Asian currency crisis in 1997. Looking at Figure 6, it would appear that Japan escaped
stagnation the fastest in the 1990s, but this is due to ceasing to fulfill the requirement of an
average growth rate of at least 3.5% in 1), and the growth rate actually dropped. It also seems
that Japan’s stagnation and the like depressed business in the Asian countries.

Chapter 1 | The Middle-Income Trap Verified by Data

Figure 6: Stagnating growth
1960s
1970s
1980s
1990s
Japan
Hong Kong○
Singapore○
S. Korea○
Taiwan○
Malaysia
Philippines
ThailandIndonesia
Vietnam
Note: The shading and crosshatching indicate satisfying the conditions for stagnation. The shading indicate
satisfying the conditions excepting the $10,000 baseline. The circles indicate the years in which per capita GDP
reached $10,000.

3. The relationship between institutions and growth

3.1 Forming an institution evaluation index
Institutional factors have recently been garnering attention as elements of economic
growth. In addition to the production factors of labor and capital, institutions affect total factor
production, and have the possibility of creating a difference in growth rate.
In JCER’s “Global Long-Term Forecast and Three Futures,” an “institution
evaluation index” was formed by combining variety of institutional factors. Based on the
results thereof, tactics for ASEAN to escape from the middle-income trap in the future areconsidered below.
“Global Long-Term Forecast and Three Futures” is an analysis using growth statistics.
A Cobb-Douglas-type production function is envisioned for GDP. With Y being GDP, K
being capital stocks, A being total factor productivity and H being the amount of labor input
taking into consideration human capital, there is the following relationship:

Kα AH 1‐αY

For human capital efficiency, the years of education E function (from Barro and Lee(2013)) is used.
HeΦ E L

Japan Center for Economic Research “Asia Research” ReportFor total factor productivity, the institution evaluation index function is used.
Log At8.44 1.21 0.4Z1t 035Z2t 0.05Z3t 0.15Z4t 0.05Z5t

et

The institution evaluation index is a newly introduced index, and combines fiveindices pertaining to institutions from Z1t to Z5t. The coefficient applied before each index is
the weighting. Z1t to Z5t are indices selected by investigating the correlation with per capita
GDP (Figure 7).
Z1t (“politics”) is political risk, and the basis of the evaluation is the strength of
bureaucratic institutions, the presence/absence of conflicts, and the like. Z2t (“openness”) is
economic openness, and represents to what degree trade, investment, and financial activities
can be freely carried out with other countries. Z3t (“gender”) is the gender gap, indicating thedegree of equalization between men and women in the economy and politics, with the value
rising the more equality there is. Z4t (“entrepreneurship”) is the ease of starting a business, andis evaluated on the basis of the procedures, time, capitalization, and the like required to start abusiness. Z5t (“labor”) is the degree of labor freedom, and evaluates ease of hiring and firingfrom the point of view of businesses.
The institution evaluation index influences total factor productivity, and total factor
productivity influences economic growth. In this relationship, an improvement in institutions
leads to an increase in growth rate.

Chapter 1 | The Middle-Income Trap Verified by Data

Figure 7: The wellspring of growth; a summary of the institution evaluation index.
Physical capitalAge structure

Years of education
Quality of
institutions

Politics

Index

Summary

Capitalstock as apercentage
of GDP
Aging rate

Capital stock is the cumulative value ofinvestment minus depletion

Years ofeducation
Aggregateof theindicesbelow
Political risk

Average number of years in educational
institutes
Weighted calculation from the relationshipbetween each item and per capita GDP

The elderly as a percentage of population

OpennessOpenmarkets

Government stability (government unity,
strength of the judiciary, national support),socioeconomic conditions (unemployment rate,
consumer confidence, poverty), investment
environment (contract executability, payment
delays, repatriation of profits), internal conflict(civil war, terrorism/political violence, civil
disorder), external conflict (war, border issues,
external pressure), corruption, politics and themilitary, religious tensions, law and order,
national tensions, accountability, quality ofadministration
Trade freedom, investment freedom, financial
freedom

GenderGender gap
index

Political authority, economic participation,
opportunities

Entrepreneurship

Starting
businessLabor
freedomStart-up period, minimum capital, costs, etc.

Labor

Ratio of minimum wage to average added value
per worker, barriers to employing new workers,
strictness of working hours, difficulty ineliminating surplus labor, legal notice period,
retirement benefits

Presenting
Institution
OECD, etc.

Document
Name

World BankWorld
Development
Indicators
Barro and Lee(2013)
GlobalLong-Term
Forecast andThree Futures
International
Country Risk
Guide

JCER

Political
Risk
Services

The
HeritageFoundation
World
Economic
Forum
World Bank

Index of
Economic
Freedom
Global Gender
Gap Index

The
HeritageFoundation

Index of
Economic
Freedom

Doing Business

3.2 The correlation between institutional factors and per capita GDP
Whether is possible to escape the middle-income trap is the same question as whether
per capita GDP will continue to rise.

First, in order to increase GDP, the state of production

factors such as labor and capital is important. Institutional factors have a concomitant effect on
growth. It is difficult to change the preconditions of labor and capital stocks, and so in many
ways these must be taken as a given. However, there is room for improvements in institutions,
including the number of years of education, which has an effect on human capital. Looking at
the relationship between per capita GDP and the institution evaluation index for 2010, there are

Japan Center for Economic Research “Asia Research” Reportmany countries where the per capita GDP exceeds $10,000 when the index exceeds 50. There
are also countries such as Egypt where the per capita GDP is extremely low at $1492 even withan index of 49.1, but it can be said that once the index exceeds 50, the path towards becoming
a high-income country opens up.

3.3 An evaluation of growth factors in each country
What are the weak points of the ASEAN countries etc. from the perspective of
economic growth factors, institutions, and the like? An index was compiled with two
evaluation axes in order to observe the characteristics of each country (Figure 8).
The subjects were Japan, the US, China, South Korea, and the nine ASEAN countries
excluding Brunei. Each index is represented as a “deviation” with a standard deviation of 10
from a global average of 50.
The first evaluation axis is the wellspring of growth. A variety of factors that form the
GNI are used. As production factors, there are labor and capital. Age structure (the population
over age 65 as a percentage of total population) and the number of years of education are used
as having an effect on the quality of the labor force. Physical capital refers to capital such as
stores and factories, and its degree of fullness is represented by a capital coefficient (capitalstock/GDP). Furthermore, total factor productivity is considered to be influenced by the qualityof institutions, and so the quality of institutions is also an important factor. The second
evaluation axis is a breakdown of the quality of institutions. As explained above, these arepolitics, openness, gender, entrepreneurship, and labor.

Chapter 1 | The Middle-Income Trap Verified by Data

Figure 8: The wellspring of growth and institution evaluation index for the ASEAN countries
The wellspring of growth (deviation values)
Quality of PhysicalAge
Years ofGNI
institutions
capitalstructure education
63
61
49
46
66

US

Institution evaluation index (deviation values)
EntreprePolitics Openness Gender
Labor-neurship
60
57
57
61
70

Japan

60

54

78

27

61

60

49

41

49

62

S. Korea

50

52

46

51

59

53

53

40

49

40

Malaysia

44

45

46

61

51

48

42

40

45

55

Thailand

42

44

51

55

42

38

48

48

48

57

Indonesia

41

40

48

60

39

43

41

44

34

43

Philippines

41

42

44

62

49

42

44

61

36

43

Vietnam

40

39

48

59

38

46

34

50

40

53

China

42

38

49

56

46

43

35

50

38

44

India

41

31

46

60

34

25

39

43

32

47

Laos

40

33

41

62

33

33

44

48

Cambodia

40

40

34

62

39

47

46

31

38

Bangladesh
40
32
41
61
36
27
35
49
Note: The light shading indicates a deviation of at least 40 and less than 50, and the dark shading indicates a
deviation of less than 40.
Source: JCER “Global Long-Term Forecast and Three Futures”

42

44

Malaysia
Although Malaysia ranks slightly above South Korea in terms of physical capital(capital coefficient), with a deviation value of 46, it is below average from a global perspective.
Like the other ASEAN countries as well, the age structure is younger than that of South Korea,
with a deviation of 61. The number of years of education is the highest after the US, Japan, andSouth Korea among the countries listed.
Malaysia has an institution evaluation index for 2010 of 45. This is the highest value
within ASEAN. Although ranking higher than South Korea for labor, the deviation for genderis 40, the lowest alongside South Korea. The other values are inferior to those of South Korea.
Its openness value of 42 is lower than that of the other ASEAN countries.
ThailandThailand has a high value for physical capital (capital coefficient) indicating
advancements in capital accumulation. Despite an age structure deviation of 55, it ranks lowest
within ASEAN, and so the aging of the population has progressed, relatively speaking. The
number of years of education is lower than that in Malaysia, the Philippines, and China, and isrelatively short compared to the size of the GNI.

Japan Center for Economic Research “Asia Research” ReportThailand’s institution evaluation index for 2010 is 44, the next highest in ASEAN
after Malaysia. The labor value of 57 is the highest after the US and Japan. The values for
openness and gender also exceed those in Malaysia. The fact that the value of the institution
evaluation index, which is a comprehensive index, is lower than that for Malaysia is solely
caused by the low value for politics.
The Philippines
The Philippines has a deviation value for physical capital (capital coefficient) of 44,
which is low among the ASEAN countries. The value for age structure is the highest after
Cambodia at 62, and the number of years of education is average, with a deviation value of 49.
The institution evaluation index is 42, ranking third after Malaysia and Thailand among theASEAN countries. Due to a low gender gap, the gender value ranks highest among thecountries listed at 61. The value for the ease of starting business is extremely low, at 36.
Indonesia
Indonesia has a value for physical capital (capital coefficient) of 48, which is average,
and with an age structure value of 60, an aging problem has not arisen. Meanwhile, thedeviation value for number of years of education is 39, which is low among the ASEAN
countries.
The institution evaluation index is 40. The deviation for entrepreneurship is in therange of 30.

An overall improvement in institutions is necessary.

VietnamVietnam has similar tendencies to Indonesia. The physical capital (capitalcoefficient) value is average at 48. The age structure value is high at 59. The number ofyears of education has a deviation value of 38.
The institution evaluation index is one lower than Indonesia, at 39.

In particular,

efforts are needed to raise openness (deviation of 34) and entrepreneurship (deviation of 40).
References
Aiyar, Shekhar; Duval, Romain; Puy, Damien; Wu, Yiqun; Zhang, Longmei (2013) “Growth
Slowdowns and the Middle-Income Trap” IMF working paper No.13/71(IMF).
Barro and Lee (2013) “Barro-Lee Educational Attainment Dataset.”

Chapter 1 | The Middle-Income Trap Verified by Data

Eichengreen, Barry; Park, Donghyun; Shin, Kwanho (2013) ”Growth Slowdowns Redux: New
Evidence on the Middle-Income Trap,” National Bureau of Economic ResearchWorking Paper Series No. 18673.
IMF (2013) “World Economic and Financial Surveys Regional Economic Outlook: Asia andPacific Shifting Risks, New Foundations for Growth.”
JCER (2013) “Global Long-Term Forecast and Three Futures.”Jesus Felipe (2012) “Tracking the Middle-Income Trap: What is It, Who is in It, and Why?
(Part 1)” ADB Economics Working Paper Series.
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Japan Center for Economic Research “Asia Research” Report