Thesis in economics
Supervisor : Associate Professor Bertil Tungodden
This thesis was written as a part of the Siviløkonom-degree program. Neither the institution, the advisor, nor the
sensors are- through the approval of this thesis- responsible for neither the theories and the methods used, nor
results and conclusions drawn in this work.
1.1 Outline of the essay
2.1 Economic growth theory
2.1.1 The Solow decomposition
2.2 Institutionalistic approach
220.127.116.11 The access to productive knowledge
18.104.22.168 Overpopulation and diminishing returns to labour and surprising results of large migrations
22.214.171.124 Surprising evidence on density of population
126.96.36.199 Diminishing returns to capital
2.2.2 The neo-classics and the institutionalists- discussion on the High Performing Asian Economies.
2.3 Some wider theories on the development in Asia
2.4 Economic history of Malaysia and Thailand
188.8.131.52 Sectoral composition
184.108.40.206 Sectoral composition
3.1 Regression analysis
3.1.1 Convergence effect
220.127.116.11 Initial per capita GDP – interaction?
18.104.22.168 Educational attainment
22.214.171.124 Life expectancy
126.96.36.199 The interaction between GDP and human capital
3.1.2 Investment ratio
3.1.3 Government consumption
3.1.4 Black market premium on foreign exchange
3.1.5 Political instability
3.1.6 Public spending on education
3.1.7 The terms of trade
4.1 The convergence effect.
188.8.131.52 Government expenditure on education
184.108.40.206 Years and level of schooling
220.127.116.11 Returns to education
4.1.2 Increased education- but the right one?
4.1.3 Life expectancy
4.2 Public spending on education
4.3 Investment ratio
4.3.1 World Bank regression
4.3.2 The importance of foreign investment
4.3.3 The role of the overseas Chinese
4.4 Government consumption
4.4.1 The quality of the Asian bureaucracy
4.4.2 Private-Public relations.
4.5 Black market premium
4.6 Political instability
4.7 Terms of trade shocks
4.8 Actual and fitted values for GDP growth
5. THE ASIAN CRISIS AND AFTER.
5.1 Outline of the Asian crisis
5.1.1 Someone to blame?
5.1.2 The governmental responses
5.2 Can the regression analysis be helpful in predicting the future economic growth?
5.2.1 Convergence effect
5.2.3 Government consumption.
5.2.4 Governmental spending on education
5.2.5 Political instability
5.2.6 Terms of trade shocks
5.2.7 Black market premium
Some tables have been omitted because of difficulty in converting from Word to html
Then last year’s crisis came and interrupted what seemed to be so idyllic and put a question mark to the sustainability of the growth. The currencies fell, the foreign capital was withdrawn, and some of the countries affected needed help from the International Monetary Fund and Asian Development Bank in the form of huge financial packages. How could this happen?
When talking about the East Asian countries, I have in mind the ones
having experienced high growth rates the last decades, Japan, South Korea
(hereby Korea), Taiwan, Singapore, Hong Kong, China, Malaysia, Thailand
and Indonesia. Korea, Taiwan, Hong Kong and Singapore are often referred
to as the Asian tigers or the first tier economies, and Malaysia, Thailand
and Indonesia are referred to as the second tier countries or the small
tigers. The tier nomination is due to development models where development
is seen as a ladder, going from developing country status and reaching
a more advanced level of development. The steps at the top of the ladder
are the status of a developed nation. The period of development and growth
has differed between the East Asian countries, with Japan in the lead,
starting the industrialisation right after World War II. The tigers, Korea,
Taiwan, Hong Kong and Singapore, followed. The last decades, Indonesia,
Thailand, Malaysia and China, have experienced high growth rates. So in
the ladder metaphor Japan and Korea are on the top steps, with Indonesia
and Thailand on the lowest steps of the East Asian development ladder.
Outline of the essay
I will in this essay have a fairly universalistic perspective and try to see what factors that have driven the development in a couple of the East Asian countries. My point of departure is the regression by Barro and Lee (1994) and Barro and Xala-I-Martin (1995). The regression is computed on the basis of a sample of 118 developing countries in the world, and out of that they try to find what variables that have been important for economic growth an different countries.
In order to be able to meet/handle the criticism/shortcomings of the generalisation in the universalistic approach, I have chosen to put the focus on two countries. That gives me the opportunity to study each country quite detailed, and at the same time have the other country to control differences and similarities for. I have chosen Malaysia and Thailand because among the East Asian fast growers they share some similar features. Simone and Thomson Feraru (1995:198) provide us with differences between the first tier economies and the second tier economies. They differ in the sense that the second tier economies are well endowed with a wide variety of natural resources, they are ethnically pluralistic, especially with Chinese, and last they are heavily and enduring dependent on international, increasingly Japanese investment capital, technology and organisational skills. This applies well for Malaysia and Thailand.
Income from these two countries are derived to a large extent from natural resources, and they are in a transition process leaving the agricultural sector and striving towards a greater share of the economy in the manufacturing and more value added sector.
Since this essay is in the field of economics I will mainly base my analysis on the economic discipline. But I am not ignorant of the importance of cross disciplinary research, and personally I am of the opinion that economics alone can not explain the complexity that is involved in the development of a nation. Development contains both economic, political, social and cultural aspects, at micro and macro level, that can not be considered separately.
My point of departure is the economic growth theory. But I will also present some wider theories on growth and development.
In chapter two I will present the economic approach. First I give a presentation of economic growth theory. I will present it in a historically chronological order to show the development in the research discipline. Then the institutionalistic criticism of the economic growth approach will be presented, including a presentation of the discussion between the neo-classics and the institutionalists about the Asian case. Following that I will give some examples of how the development question can be approached in a wider manners, outlining a cultural approach most detailed. In order to give the reader an overview of what the growth consist of and in what sectors it has been in, I also find it appropriate to outline the most important events in the economic history of Malaysia and Thailand.
In the third chapter I will present the method which is the regression analysis.
The fourth chapter is the analysis. I will present the regression results for East Asia and I discuss how well the results fit with the development patterns for Malaysia and Thailand.
Because of the Asian crisis that started in July 1997 the development patterns for Malaysia and Thailand might have been affected from that. I will outline the background for the crisis and ask to what extent the crisis has affected the growth process in Malaysia and Thailand.
I hope this essay will enable the reader to get an overview of what lies behind the "miracle" of the growth in the Malaysia and Thailand, and also see what critical factors that are important to the social and economic development in these countries
In the analysis I will use the results from a regression. The regression is empirically constructed. When the researchers are to explain what theoretical mechanisms that are behind empirical evidence, their point of departure is the neo-classical theories. But there is not a perfect (100%, 1:1) fit between neo-classical theory and empirical results. In the Asian case the critisism from the institutionalists has been strong. That is why I choose to leave that much room to the institutionalistic explanation as well. Also a distinct Asian culture has been mentioned to have been influential in the Asian growth miracle, so I pay some attention to that explanation as well.
When measuring growth we use the growth in Gross Domestic Product (GDP) per capita. It is reasonable to question whether this is a good measure or not. Even if it is a narrow definition I have chosen to consider it, because I believe that it is difficult to develop a society without also experiencing a GDP per capita growth. That is because development is e.g. more and better schooling, health services and nutrition. These goods need to be paid for, and therefore GDP growth is required. In addition the measure is easy to use due to its possibility to get fairly exact figures. Still it is important to be aware that this measure does not necessarily say anything about the social development in a country. If a society experiences GDP growth that may leave only the already wealthy population better off. Can that be called development? Since this is a descriptive, not a positive/normative essay, I will leave out that discussion in my essay. But I think it is almost impossible to deal with the growth issue without getting involved in the normative question as well.
I will start out with giving an overview of the basic framework in the neo-classical growth theory and in a chronological order introduce more aspects to the model, making it more complex.
The neo-classical theory assumes the existence of competitive markets. In the markets goods and services are traded and the prices reflect demand and supply of the goods. The markets work so that the volume of traded goods will end up in a market equilibrium.
The point of departure for the economic approach to Gross Domestic Product(GDP) growth in a more formal way, is the aggregate product function with the aggregate input of capital (K) and labour (L), as shown below.
Increasing one of the inputs while holding the other input constant, makes the output grow. But the more input of one factor the lower the marginal productivity of that factor is. That means as more input is added, output grows, but not as much as the previous amount of output with the output same amount of inputs. That is called diminishing marginal productivity.
We assume constant returns to scale. That means that when increasing both input factors by the same proportion, say twice as much, the output doubles. If output more than doubles we have increasing returns to scale, and with less than doubled output we have decreasing returns to scale.
What is interesting to see is what changes output. In order to that we need to see what the marginal changes are; that is if we change one of the units, what happens to output, y, then. Therefore we find production per worker (y).
Production per worker (y) can be written as the function of the amount of real capital per worker (Y/L). Then y and k give the production and capital per person (y=Y/L and k=K/L) and that leads us to
This is the production function per worker. The ouput is a function of capital.
To find out what happens when changes in the input factors occur, we need to find the derived production function, [f’(k)].
f’(k) is the marginal product of capital which is positive, but diminishing. So when increasing one unit of capital (labour), the output will increase, but less than the previous unit of input of capital (labour).
Part of the neo-classical theory is the assumption of a general equilibrium
where the inputs are optimally employed. Then we will be on the frontiers
of the production function. In cases of changes in the amount of one of
the inputs, shifts in the marginal productivity of capital (MPK) and labour
(MPL) will occur.
Here is a secction which has not been converted
from Word to html. Is available in Word
For labour the MPL shifts downward if more labour is supplied to the economy, but the MPK shifts upward. The opposite shifts occur if more capital is supplied; MPL shifts upward while MPK shift downward.
Supply of labour.
Figure 2 After an exogenous increase in labour supply from ` L to ` L¢ shown in the right panel, a partial equilibrium occurs at point B and real wages decline.However the MPK schedule in the left panel shifts upward as a consequence. As more capital is accumulated, there is a further shift to MPL¢ in the right panel. In the new equilibrium income and capital have increased. Under constant returns, real wages return to their original level.
In equilibrium the marginal productivity of labour (MPL) equals the real wage, w. The wages will fall when more labour is supplied in the economy. In addition the MPK shifts upward. That will lead to inflow of more capital and after a while wages will rise to the same level as before. Because both labour and capital has increased output has also increased and thereby growth in the economy. See figure 2.
Supply of capital.
Supply of capital is given by its past accumulation (investment). In equilibrium the marginal productivity of capital (MPK) equals the world interest rate, which is the real cost of capital. A reduction in the world interest rate leads to a higher capital accumulation because the opportunity cost of investing has become lower. With a higher capital stock the MPL shifts upward and real wages rise. See figure 3.
Capital stock Labour
Figure 3 Given the world real interest rate, capial is accumulated to point A. This implies the MPL schedule in the right panel and real wages ` w. The effect of a lower world real rate of interest is represented by point A¢ in the left panel. The higher capital stock shifts the MPL schedule to MPL¢ , raising real wages in the process.
The increase of capital or labour will therefore lead to increased GDP and therefore also increased economic growth.
where the different parts can be divided as in the equation under.
g = dY/Y= dA/A+a (dK/K)+(1-a )(dL/L)
where g is the growth rate in a period in a country/geographical region
dY/Y is the GDP growth rate (changes from one period to the next)
dA/A is total factor productivity or technological change (the Solow’s residual)
a (dK/K) is capital accumulation to growth in proportion to its income share in GDP
(1-a )(dL/L) labour contribution in proportion to its income share in GDP.
How the total factor productivity leads to GDP- growth is shown in figure 4. If labour and capital is unchanged, the increased TFP will lead to increased quantities of output. As we can see from figure 4 both MPL and MPK shifts upwards. That is because more capital is accumulated because it is more productive (point A¢ in left panel), growth rises and wages are higher (point A¢ in right panel). The increase in the stock of capital further pushes the MPL schedule upward, with still higher wages at point A¢¢ . Equilibrium output increases for two reasons: 1) both factors are more productive, 2) more capital has been installed in the mean time.
Capital stock Labour
Figure 4 An increase in total factor productivity (Solow’s residual) makes production grow. The increase shifts both the marginal productivity schedules to MPK¢ (left panel) and MPL¢ (right panel). At unchanged world interest rates, capital rises as shown in the left panel by the move from A to A¢ . This higher capital stock further shifts the MPL schedule to MPL¢¢ in the right panel. Overall, capital, output and real wages rise.
Norman (SNF-report) points to two types of explanations that try to explain what is behind the Solow-residual.
The second result from this theory is that per capita GDP-growth will stop. In this case no continuing improvements in technology is assumed. This is due to diminishing returns to capital, like the assumption mentioned above.
What was done to make the theory work was to assume that growth was due to technological progress and that the technology variable was exogenously given in the model. But since it was economic growth they wanted to try to explain, it was, mildly speaking, unsatisfactorily to consider the most important variable as explained outside the model.
What happened was that the per capita GDP growth rates kept on growing, going against the second result from the theory. Like Victor Norman puts it: "Western countries have experienced economic growth for 200 years, and there are no signals that it will stop." And that puzzled the scholars. How could they explain the continuous growth? This question was addressed by Lucas (1988) and Romer (1986) and Rebelo (1991) in the mid-80s. The researchers had found out that taking too many important variables as exogenously given, did not bring the explanation of growth any further. That acknowledgement paved the way for endogenous growth theory.
The endogenous growth theory keeps the framework of the neo-classical growth models, but loosens up some of the assumptions. The assumption that growth is ceasive was one of the most important assumptions that was left. Under the new assumptions returns to investment do not necessarily diminish with economic growth in a country. The important difference between the the exogenous and endogenous growth theories was the role of knowledge. In contrast to capital and labour, knowledge is assumed to be cumulative, and can therefore explain the long term continuous growth. The reason why knowledge is considered cumulative is that copying knowledge is most often cheaper to than creating/innovating it. And the more knowledge you have, the cheaper it is to create new knowledge. Following economies will copy technology and reap the same benefits from the product as the leading-edge economies, but at a lower cost. Also spillovers and spread of knowledge across producers, and external benefits from human capital, are parts of this process: that is because they help avoid the tendency for diminishing returns to the accumulation of capital. So the assumption of diminishing returns to inputs do not hold for production of knowledge or use of knowledge and therefore there are no mechanisms that lead to a flattening of long term growth based on knowledge.
The most recent research try to build a bridge over theory and empiri, trying to link the two parts together into something that can stand the test of time. That is were Barro and Lee (1994) and Barro and Xala-I-Martins’s (1995) contribution come in with their regressions. The regressions lay the foundation for my analysis of Malaysia and Thailand. These researchers have found out what factors that are important determinants for economic growth in a country and made an econometric regression analysis in order to see what driving forces for economic growth there are around the world.
Most resent research is also characterised as more cross disciplinary. Econometric models try to quantify non-economic variables, or in the cases where a quantification is difficult, take non-economic considerations into their analysis. As a professor in development sociology put it, "Before we didn’t care to read the reports from the World Bank and other economy dominated institutions. Now the reports actually are interesting reading for sociologists too."
Even if the economic growth theory seems to have improved, as shown above, it has been widely criticised, for instance by the institutionalists. I will present one institutionalistic point of view, being a critique of the general neo-classical theory. This perspective is provided for by Olson (1996). He points to the lack of good institutions to explain the lack of optimal employment of resources in several countries. After Olson’s criticism of the economic approach, I will present the discussion between the institutionalists and the neo-classics on the particular case of the High Performing Asian Economies (HPAEs).
Olson is also concerned about what makes some countries experience high growth rates while others do not. He goes through some of the input factors that are presented in the theory. These factors are assumed to be employed optimally. The neo-classical theory also assumes that production knowledge is accessible to all countries, so what is of importance for growth are input factors- labour and capital. If factors were not optimally employed growth would be possible with only a change of organising them. For instance the growth rates in China are largely due to transferring labour from agricultural sector to the manufacturing sector. In the manufacturing sector the returns were much higher than in the agricultural sector. So the Chinese economic growth was to agreat extent due to that.
Olson argues that the neo-classical theories are based on some assumptions
that he falsifies. The neo-classical theory assume that markets work perfectly
so that resources are employed in the most efficient way and are in a general
equilibrium. Put in another way; the societies are assumed to be on the
frontiers of their aggregate production functions.
Olson asks if modern technology, developed in the developed countries, is accessible to third world countries. If that is not the case that might be part of explaining the differences in per capita incomes across countries, because the cost of obtaining the technology is too high for developing countries. A study from Korea from 1973 to 1979 (Koo, 1982) shows that less than 1.5% of the increase in Korea’s GDP over the period is due to access of foreign technology. Foreign owners of productive knowledge obtained less than a fiftieth of the gains from Korea’s rapid economic growth. He therefore rejects the hypothesis, arguing that it is not the lack of access to technology that prevents developing nations from developing.
Another hypothesis is that a big population leads to a lower per capita income due to a low ratio of land and other natural resources to population. From the presentation of the neo-classical groth theory we recall that marginal productivity of labour (MPL) is equal to the wage level (w) when the resources were optimally employed. Then on a short term basis more labour would lead to lower wage level and MPL would also detoriate. He therefore asks if we can observe a change in the relative wages and the marginal productivity of labour (MPL) when a country experiences strong immigration/migration. He uses the "bathtub"-model with MPL for northern countries (developed countries with higher wages) and southern countries (developing countries with lower wages than North) on the two axes. According to the neo-classical theory he would have expected that wages in the North would decline due to more labour. See figure 1. But his studies and other studies conclude that wages are not depressed in countries experiencing large waves of immigration. So we can not say that high populations are the reason for a low per capita income.
Figure 5 Population distribution
and relative wages in a "bathtub"-model. Moving from left to right moves
the workforce from South to North, and also the wages (MPLN) moves downwards
in North. But Olson points out that this fact does not happen, and therefore
one of the assumption the neo-classical theory relies on, is not reliable.
Olson’s third hypothesis is that a population density (land/labour relations) influence on a country’s income per capita. In the hypothesis he assumes that a country well endowed with labour have a lower per capita income because it is shared between more people. However the hypothesis is rejected. The result is significantly in favour of the greater the number of people in an area the greater the income per capita. Japan is an excellent example because the population density is high, the natural resources are relatively limited, but in spite of that the income per capita is one of the highest in the world. Olson emphasises better economic policies and institutions in the countries with higher per capita income arguing that ".. these higher incomes bring about a higher population growth through more immigration and lower death rates. In this way, the effect of better institutions and policies in raising per capita income swamps the tendency of diminishing returns to labour to reduce it."
Olson continues to argue about differences in human capital in a cultural perspective. One aspect is whether the productivity of some ethnic groups are higher than other groups. In order to measure differences in productivity the context surrounding the different ethnic groups needs to be similar. Productivity is measured as how much different ethnic groups are paid when they migrate to a new country. Olson is aware that also the context, that is the institutions and public policies, can explain why the income in different countries varies. Then he hypothetically has one ethnic group migrate into another country, with the institutions and economic policies that the other country holds. He finds that there are differences in productivity between the ethnic groups. Ethnic groups that earn the least would still achieve only a fraction of the per capita income if they lived in another context. He concludes that differences in human capital is of importance in explaining the differences in income per capita between countries. But this explanation is not enough. Olson is clear in his argumentation: "The only remaining plausible explanation is that the great differences in the wealth of nations are mainly due to differences in the quality of their institutions and the economic policies." The way a country organises and exploit its resources is of importance, and that puts Olson in the category of institutionalists.
The World Bank has their way of explaining the economic growth process. Traditionally the main task for a country’s authorities is to make sure that the macroeconomic foundations are working, such as the interest rate- and exchange rate systems. In addition the legal framework needs to be reliable. The governmental influence should be as little as possible and the markets should be lead by consumer’s preferences, or by "the invisible hand" as Adam Smith formulated it in 1789. Joseph E. Stiglitz, Senior Vice President and Chief Economist in the World Bank, has formulated the policy of the World Bank and other international economic institutions in more recent times, called the "Washington Consensus": " "The Washington Consensus" on economic policy was formed in the 1980s by US economic officials, the International Monetary Fund, and the World Bank. It emphasized liberalized trade, macro-economic stability, and getting prices right. Once the government got out of the way, private markets would produce growth." (Wider Angle, 1997/98: 1)
The sustained growth of first Japan, then the four tigers, and at last the three small tigers put a question mark to the World Bank’s perception of what factors that were needed to develop a country. The role of the government in the Asian countries for promoting certain industries puzzled the analysts of the World Bank and other institutions that are pro the neo-classic point of view. As Stiglitz puts it in the same lecture: "East Asia’s phenomenal success over the last three decades was one of the original motivations for rethinking the Washington Consensus, these countries have managed the most successful development in history while not closely following all the prescriptions of the Washington consensus. .....In most cases, the current problems are due to the governments doing too little, not too much." (Wider Angle, 1997/98:2).
In 1993 the World Bank published a report on the High Performing Asian Economies (HPAEs) which was called "The East Asian Miracle". The factors below are the building blocs for the economic growth in East Asia, according the World Bank report (1993:12-18).
Alice Amsden (1994) is fundamentally disagreeing with the World Bank (1993:5) in their conclusions when they claim that "In large measures the HPAEs achieved high growth by getting the basics right. Private domestic investments and rapidly growing human capital, were the principal engines of growth [along with an export orientation, essentially in Japan, Korea, Hong Kong, and Singapore, whose supply of natural resources, including land, was minimal.] In this sense it is little "miraculous" about the HPAEs record of growth; it is largely due to superior accumulation of physical and human capital."
Even if the World Bank do admit that "the governments intervened-systematically and through multiple channels", Amsden (1994:627) is not satisfied with the emphasis the World Bank puts on the role of the governments. She says that "Thus the basics cannot tell the entire story. But since they allegedly tell most of the story, and the effect of government intervention on the "supernumerary" growth rate cannot be determined (the effect might conceivably be nil or even negative) other developing countries are advised to forget intervention and focus on the fundamentals." She points to the fact that the authorities have laid the ground for carrying out a lot of the fundamentals and actively promoting certain policies, and she makes a point out of it showing that the industrial policies are more conscious and deliberate than the World Bank admits. She says "If East Asia has had high rates of saving and investment,(...), then these rose in conjunction with, say, a particular structure of business enterprise and financial system. (...) If the high-performing East Asian countries have exported a lot and have been aided in doing so by reasonable exchange rates, then their exchange rate regimes have operated only in conjunction with extensive import substitution policies (...) and elaborate export incentive systems." (Amsden, 1994:628) She criticises the World Bank for not having used more room and efforts in systematically analysing "...which of East Asia’s supporting institutions has served investment, education and exports especially well with an eye toward what must be done to modify these institutions to make them work elsewhere". (Amsden, 1994:628)
Further on Amsden (1989) argues that the governments "led the market" in critical ways. She contend that markets consistently fail to guide investment to industries that would generate the highest growth for the overall economy. In East Asia governments remedied this by deliberately "getting the prices wrong"- altering the incentives structure- to boost industries that would otherwise not have thrived.
One often talks about the same kind of development pattern for all the High Performing Asian Economies (HPAEs), but that is a too simple generalisation. The countries differ when it comes to resource endowments, institutions, history and culture, among other things. Different categories have however been made for the development pattern of the Asian economies, and Perkins (1994) provides us with 1. the state-led growth, 2. the trade based growth and 3. the resource based growth, as point of departures for the growth models. Japan is a representative of the first one, Singapore and Taiwan for the second one and the small tigers are the representatives of the last category. The categories are not exhausting, and the economies might have elements from the different categories, but for growth they emphasise the importance of the different departures. The two countries in focus of this essay are in the resource based category.
Another development approach on Asia is characterised as a "flying geese"; where Japan is the leading geese, followed by Korea, Taiwan, Hong Kong and Singapore. The latter cackle of geese are the small tigers, Indonesia, Malaysia and Thailand. What characterises this kind of formation is first, the time of development, second, the role model the geese in the head makes, and third, the dependency of each other. Japan needed cheaper locations for their production. At the same time the other geese (Korea, Singapore, Hong Kong and Taiwan) wanted to develop. But the tigers needed capital, technology and knowledge, and that was supplied for by Japan. Some decades later the second tier economies were provided for with capital, technology and knowledge by the first tier economies and Japan.
But later, as Japan and the other newly industrialised countries (NIC) experienced remarkable economic growth rates, other researchers turned Weber’s arguments up side down, arguing that Confucianism was favourable to economic growth. The hard work ethic, high savings for the security of the family in the future, emphasis on education were traits that were pointed out as favourable to development in the Confucianistic states. Other researchers argue that Confucianism has been seen as a factor both hindering and promoting economic growth and suggest that any interpretation of the role of Confucianism in economic development is arbitrary.
Another pragmatic approach, but not rejecting the cultural aspect is the approach by D. Peng .
"My argument is that Confucianism, as a social and cultural ethic, always works with other more fundamental factors such as the political or economic systems. It acts as a norm for people’s behaviour. It emphasises authority, hierarchical order, and discipline and thus often serves as a tool for the ruling class. It enhances the ability of the government to control and mobilise the society. By itself, Confucianism does not have a strong influence on economic development. Only when combined with other factors does Confucianism have an important impact. For example when the government is seriously committed to economic development, Confucianism can facilitate this. In contrast, when the government carries out policies unfavourable to development, Confucianism can also make things worse because it increases the ability of the government to implement such policies. Therefore Confucianism is a double-edged sword that can cut both ways."
Malaysia was decolonised in 1957 and has had four different prime ministers, each pursuing distinct and influential economic and development policies. Jomo (1994) divides the economic growth period into five. The first period is the British colonial period up till 1957 with Malaysia producing and exporting tin and rubber. The second period, called the post-colonial conservatism, lasted from 1957 till 1969 and was led by Prime Minister Tunku Abdul Rahman. They pursued laissez-faire policies and policies on industrial estates that were in favour of import-substituting industrialisation and protection by tariffs. Some agricultural diversification, greater rural development efforts and modest but increasing ethnic affirmative action policies was also pursued.
The third period was led by Hussein from 1969 till 1976 and Onn from 1976-81. In this period the New Economic Policy (NEP) was introduced which legitimised increased state intervention and expansion of the public sector for interethnic redistribution. At this time oil was found. Import substitution was left in favour of export orientation. Industrialisation in electronic components and other manufactured exports accelerated, even if the exports from the manufacturing sector until 1990 was less than exports from the primary sector (FEAE 1998). In this period unemployment declined, productivity rose and wages increased.
In 1981 the present Prime Minister, Mahathir Mohamad, came into office and Jomo characterises the fourth period from 1981 till 85 as heavy industrialisation. During these years the government kept on subsidising heavy industries, such as steel and car industry. It was also a countercyclical period and the global crisis struck Malaysia fairly severely. New private investments in manufacturing fell, problems arose relating to fiscal and debt crisis, growth was slow and unemployment rose. These problems culminated in the mid-80s.
The fifth and last period is called the economic liberalisation period and stretches from 1986 to present. The Malaysian exchange rate, the ringgit, depreciated and privatisation was encouraged. Official support for private sector improved, investment incentives increased, production costs lowered and regressive "supply-side-oriented" tax reforms were implemented. Since 1986 the manufacturing sector has been growing sustainably. This period has been characterised by a dual structure. One sub-sector was producing mostly for a domestic market, shielded by tariff and non-tariff protection. The other sector was export-orientated and was producing for the global market with relatively few linkages into the domestic market.
The Malaysian economy can be characterised as a planned one. It is now in the middle of the seventh plan, and the outspoken Prime Minister, Mahathir Mohamad, has clearly expressed the development aspirations on behalf of the country; to become a developed nation within year 2020. Among the aims of the plan are a per capita of $13.000, a fairly equal income structure between the different ethnic groups and equal access for the Bumiputras (Malays) to educational system, and so on.
There are three ethnic groups, Malays or Bumiputras (58% of population), Chinese (31%) and Indians (11%), and the groups are engaged in different activities in the social and economic life.
In the 25 years-period following the implementation of the New Economic
Policy in 1971 the GDP grew at an annual rate of 7%. Between 1985 and 1995
the GDP grew at an annual rate above 8%. Regulating for population expansion
leaves Malaysia with a growth in capita output of 5.7% per annum.
Industry, especially manufacturing, has grown in importance. The state has led the development of a car industry (PROTON in co-operation with the Japanese company Mitsubishi) and a high-technology project. The government’s anticipatest hat these projects among other projects will contribute to the advancement up to more advanced forms of production and thereafter production that has a higher value added element. In 1975 the sectoral composition of GDP showed that industry contributed with 31.2% and this had risen till 44.9% in 1995. Manufacturing increased its share of industrial output in GDP from 54% in 1975 till 74% in 1995.
The service sector has been fairly stable from 1975 to 1995, contributing with 40.7% to GDP in 1975 and increasing only slightly to 41.5% in 1995.
Figur 6. Sectoral composition in Malaysia.
Source: Far Eastern and Australasian Encyclopaedia 1998.
Thailand does not have a colonial past and is a formally a constitutional monarchy. The military plays a significant role in Thai politics, but with the economic boom period the last decades an urban, educated middle class has appeared and they demand democratic reforms and reduced military control, both in politics and in economic affairs. The World Bank report (1993) makes a three- parted distinction dependent on what industrial policies that were pursued. From 1955 to 70 natural-resource-based and agricultural exports were encouraged. From 1971 to 80 Thailand followed an import-substitution strategy. From 1980 and forth reforms for the economy that suffered from oil crisis was required and an export-promoting strategy was followed.
Different factors like oil crisis, prices of important exports, have contributed to a volatile growth in GDP for Thailand. Nevertheless Thailand has been one of the fastest-growing economies in the world. Between 1961 and 1972 the growth in GDP per year was 11.3%, between 1973 and 79 it was 7.7% and between 80 and 85 5.5% and between 1986 and 89 the economy grew with 10% per year. Between 1992 and 1996 the annual growth was 8.2%. See figure 2.
Figure 7 Annual growth rates in Thailand from 1961 to 1996.
Source: Warr (1993) and Far Eastern and Australasian Encyclopaedia (1998).
Manufacturing has increased its share of GDP from 11% in 1960, being 18% in 1980 and by 1990 it has increased to 28%. (Warr, 1993). Articles that are exported that gave the highest contributions to national income in 1995, are miscellaneous manufactured articles (e.g. clothing, footwear) (24%), food and live animals (19%) and basic manufactures (11%). Most important imports are machinery and transport equipment (47%), basic manufactures (19.5%) and chemicals and related products (10%). (Far East and Australasian Encyclopaedia 1998)
Figure 8. Sectoral composition in Thailand
Source: Warr (1993)
Thailand’s growth was not driven by manufacturing, the driving force
was to a large extent from production of a comparatively limited range
of primary products. It was not until the mid-80s when manufacturing increased
its share of export earnings, that manufacturing became important for the
It is not necessarily that the different disciplines are fighting for their versions to be considered as the most truthful in growth theory. Neo-classical theories have been the winners in that sense until only recently. But with development in the theoretical approach and empirically observing the growth in East Asia the last decades made the institutions following the neo-classical paradigm rethink its fundaments for policies. These institutions have not left their basic policies for growth, but they have opened up for additional variables that might contribute to the economic growth, like political and cultural variables. The different fields of research might have turned more humble that their field of research is incomplete in being able to explain such a complex question as economic growth is. A regression analysis tries to compute a quantitative function/equation about a societal phenomenon, in this essay an economic phenomenon. The purpose of a regression analysis is to investigate if and to what extent one or a set of variables (independent variables) influences another variable (dependent variable). When talking about economic growth the dependent variable is the growth rates of real GDP per capita in a state, usually over a period of time, such as five years average annual growth of GDP. A regression analysis can also try to estimate a set of equations. The regression will outline the independent variables below.
Computing a regression is done through an econometrical method that is quite technical. I have wanted to write a non-technical essay, because a proper discussion on technical issues would require almost the whole essay. Instead I have wanted to consentrate on the variables that are found in the regression and discuss the content of them; that is how well these variables explain the economic growth in Malaysia and Thailand. I leave to the reader to check out the considerations Barro and his co-researchers have done, and refer discussion of the technical execution and reliability of the method to Barro and Xala-I-Martin and other relevant statistical literature.
The regression model was later developed into a more complex regression, and was a result of a co-operation between Barro and Xavier Sala-I-Martin. These results are published in "Economic growth" (1995). Data the regression equation is based on come from between 87 and 97 economies in the different decades.
Barro and Lee’s (1994) regression analysis found the following five variables:
This variable has enjoyed an enormous attention due to its central role in the neo-classical theory. In this essay it is also important because the neo-classical theory is the point of departure for the regressions Barro has computed with Lee and Xala-I-Martin. But attention has also been drawn to this variable because of its lack of ability in explaining the situation we actually have observed. As part 2.1 showed the convergence effect alone could not explain the differences in income between countries. Therefore the convergence effect is computed in interaction with some other factors. The convergence effect interacts with accumulation of physical and human capital, that is secondary and higher education, initial level of GDP, life expectancy and interaction between human capital and GDP growth rate.
The variable is entered in the form log(GDP), and the logarithm has been taken to this variable in order to have it on a linear form. This variable shows whether a country grows faster or not if it starts out with a low GDP per capita. The estimated coefficient is – 0.026 which means that there is a significant correlation between initial GDP level and growth. When a country starts out with a low GDP per capita the GDP in the country will grow faster than if it started out with a higher GDP per capita. From the coefficient we can see that the convergence occurs at a rate of 3.0 percent per year.
This variable is separated into male and female schooling and secondary and higher education.
For men the increase in schooling, both at secondary and higher level leads to a significantly positive effect on GDP. The coefficients 0.016 for higher education and 0.050 for secondary shows this. A one-standard-deviation increase in male secondary schooling raises the growth rate with 1.1 percentage points per year. A one-standard deviation in male higher shcooling raises the growth rate with 0.5 percentage points per year.
However for women the trend is somewhat different because an increase in education is negatively correlated with GDP-growth. The estimated coefficients for this group is – 0.009 and – 0.079 for secondary and higher education respectively. A plausible explanation on the negative correlation for women is that "a large spread between male and female attainment is a good measure of backwardness; hence, less female attainment- especially at higher level-signifies more backwardness and accordingly higher growth potential through the convergence mechanism."
This variable measure the quantity of education, not the quality of
A population with longer lives leads to a higher growth rate. This might be explained not only with the fact that good health reflects desirable performance of a society, but also a connection to better work habits and a higher level of skills.
The estimated coefficient is 0.064 which is highly significant. A one-standard-deviation
increase in life expectancy is estimated to raise the growth rate by 1.4
percentage points per year.
The regression shows a positive, but low and hence an insignificant correlation between GDP growth and the investment ratio (I/Y= real gross domestic investment/ real GDP). But if we apply another technique, called SUR(seemingly unrelated technique), the estimated coefficient is significantly positive, 0.074. Other studies have also shown a strong correlation between these two factors (Levine and Renelt (1992), Mankiw, Romer and Weil (1992)).The deviations between the regression results is discussed more in detail in the analysis.
This variable (G/Y) does not contain expenditures on defence and education. It is assumed that a high share of governmental spending will lead to unproductive use of resources as well as a signal of money spent on corruption, and therefore this variable is negative. The coefficient shows a significantly negative correlation between government consumption and per capita GDP growth. A one standard deviation increase in this variable leads to a fall in the growth rate of 0.7 percentage points per year in the 1965-1975 period.
The black market premium (BMP) is computed as shown under:
(black market exchange rate/ official rate) - 1
The measure used in the regression is log(1+BMP). That has been done to make it linear.
The reasoning behind this variable is that a black market premium is partly the same as a government distortion of the markets and thereby lowers the effectively of the market mechanism. Therefore a negative effect is expected here. The regression estimates a significantly negative coefficient, - 0.030. A one standard deviation increase in the variable in the 1965- 1975 period will reduce the growth rate by 0.6 percentage points per year.
Political instability is measured by the number of revolutions and political assassinations. A high score on this variable will be reflected in lower investment activity due to higher probability of loosing the properties than in a stable political environment. The coefficient is significantly negative, - 0.033. A one standard deviation increase in political instability (1965-75) lowers the growth rate by 0.4 percentage points per year.
This effect is positive which means that investment on education leads to higher economic growth. The coefficient is 0.23 which is highly significant. A one-standard deviation increase in this variable leads to a raise in the growth rate of 0.3 percentage points per year. This is a measure of the quality of education.
The purpose of this essay is to see to what extent Barro and Xala-I-Martin’s regression is able to explain the economic growth in Malaysia and Thailand. To do that I will in the analysis compare the figures for Malaysia and Thailand from Barro and Lee’s dataset and see how well they fit with the general regression. The general regression was mentioned in chapter 3 and is based on a sample of 116 economies throughout the world. I will also compare the figures from the data set for Malaysia and Thailand with the average the regression have found for the 9 fast growing economies in East Asia. I will refer to the results for the East Asian fast growers as the East Asia regression.
In the period 1965-1975 the predicted GDP growth rate is 2.8 % for East Asia, and out of that figure the convergence effect contributed with 2.1 (or ¾ of the growth was due to the convergence effect.). See table 2. The next two decades the influence of this effect declined to 48,1% in 1975-85 and 20% in the 1985-95 period.
Table 1 The table shows the importance of the convergence effect to growth in East Asia, the relation between predicted and actual growth rates, and the convergence effect’s contribution to predicted growth.
Source: Barro and Xala-I-Martin (1995).
The quantity of education has increased very much in Malaysia and Thailand, both as governmental spending on education to GDP and average years of schooling in the population. And for both men and women the level of education has increased.
From 1960 to 1964 the total government expenditure on education to nominal GDP was 0.033 in Malaysia. See figure 9. In the following periods it increases and in the 1980-84 period it is 0.063. From the first period to the last the increase in this public expenditure rose by an annual rate of 2.7%.
Figure 9 Ratio of total government expenditure on education to nominal GDP for Malaysia and Thailand.
Source: Barro and Lee dataset (1994).
Concerning Thailand, the same phenomenon occurs, though the increase
was a bit lower. See figure 3. The first period starts with a ratio of
0.0209 on education as share of nominal GDP and grows during the whole
period and finally between 1980 and 1984 it has increased to 0.037. That
leads us to an annual increase of 2.4% from 1960 to 1984.
Figure 10 Education, years of schooling in total population for Malaysia and Thailand
Source: Barro and Lee dataset (1994).
Malaysia has a slightly higher average schooling years in the total population over age 25 than Thailand. Thailand started out in 1960, with more years than Malaysia with 3.451 years to Malaysia’s 2.336 years. Between 1970 and 1975 Malaysia overtook Thailand and has kept that position in 1985 with 5.361 years to Thailand’s 5.081 years. Annual average increase is for Malaysia 3.4% and for Thailand it is 1.6%. From the figure we also see that Thailand increased the years considerably from 1980 to 1985. That might have been due to changes in industrial policy and more emphasis on getting a labour force that was better qualified for the new needs in the industry (Duggan 1991).
Barro and Xala-I-Martin only use secondary and higher schooling in their regression. That is questionable, taken into consideration that the returns for a society is normally higher from investing in primary schooling than the two higher levels of schooling (Psacharopoulos, 1994 and see discussion later). Therefore I find it reasonable to mention the development in this factor as well, and data for higher, secondary and primary education will be presented below. Barro and Xala-I-Martin do check for primary education but they do not find a significant effect
Divided into primary, secondary and higher schooling we find that Thailand
has a higher ratio of people in higher and primary education than Malaysia,
while Malaysia has a far higher ratio of people in secondary education.
Figure 5 Higher education, average years in total population over 25 years.
Source: Barro and Lee dataset (1994).
What is quite noticable is the increase in Thailand’s capacity in higher
education from 1970. From 1970, where 0.044 was the average years of
higher schooling in the total population over 25, the figure increases
to 0.116 in 1980 and 0.201 in 1985. Comparing with Malaysia we see that
the figure shows 0.057 in 1970 and 0.074 in 1985 for this country. The
average annual increase is 1.2% for Malaysia from 1960 till 1985 and as
much as 10.7% for Thailand in the same period of time. The rapid expansion
of higher education was a response to social demand and political pressure
caused by the rapid rate of economic growth. Universities in the different
regions were opened which gave the rural population easier access to higher
education. Still it might be reasonable to question if the definition of
higher education is the same across national borders.
Figur 6 Secondary education, average years in total population
Source: Barro and Lee dataset (1994).
For secondary education Malaysia has a population with more years
of schooling than Thailand. In 1960 average years of secondary schooling
for the total population in Malaysia was 0.441 years. In 1985 it had increased
to 1.138 years. For Thailand’s part it was 0.232 in 1960 and 0.642 in 1985.
That leads us to an average annual increase of 3.9% for Malaysia and 4.2%
Figure 7 Primary education, average years in total population over 25 years.
Source: Barro and Lee dataset (1994).
Primary education shows that average years of schooling in the
total population over age 25 in Malaysia increases from 1.840 in 1960 to
3.902 in 1985. In Thailand average years of primary schooling increases
from 3.196 in 1960 to 4.238 in 1985. From these figures we see that Malaysia
increases average years much more than Thailand does over the 25 years
we consider, but Thailand starts out with a higher year average and they
keep the lead to Malaysia all the time. Average annual growth rate is 3.1%
for Malaysia and 1.1% for Thailand.
Several other studies show strong positive connections between a higher
educated female labour force and economic growth. (Psacharopoulos 1994:1327).
These studies are estimations of returns to investment in education, e.g.
Hicks(1980), Wheeler (1980) and Psacharopoulos (1994). The returns I will
refer to are estimations from Psacharopoulos (1994). He divides the results
into private and social returns. This is how he defines private and social
rates of return to education. "The stream of costs consist of the foregone
earnings of the individual while in school (measured by the mean earnings
of graduates of the educational level that serves as a control group) in
a private rate of return calculation, augmented by the true resource costs
of schooling in a social rate of return calculation. Private rates of return
are used to explain people’s behaviour in seeking education of different
levels and types, and as distributive measures of the use of public resources.
Social rates of return can be used to set priorities for future educational
The tendency is that the private rates of return are higher than social returns. In a world sample social returns are higher for primary than secondary education and the returns are lowest for higher education. See figure 8.
Figure 8 Social returns to investment in education by level (percentage), regional averages.
Source: Psacharopoulos (1994, table 1)
The picture is not as linear for private returns, where investment in primary sector is most profitable, returns in higher education range second and investment in secondary education pays least off. See figure 9. But all returns are positive and compared with an international interest rate it throws more off to invest in education than to invest the money in other projects.
Figure 9 Private returns to investment in education by level (percentage), regional averages.
Source: Psacharopoulos (1994, table 1)
Figure 8 and 9 also show the different rates of return between regions and we see that the returns are highest in Sub-Saharan Africa. Asia’s rates of return are fairly close to the world average, and enjoys higher rates than the OECD countries. We should keep in mind that all the Asian countries are included in the Asia category, not only the fast growing East Asian economies.
Studies have been made specifically for Malaysia and Thailand, and the results are presented in table 3.
Table 2 Private and social return to education for Malaysia and Thailand
As we can see for Malaysia’s part only private returns have been estimated, and only secondary and higher education. We see that the returns are very high, 32.6% for secondary and 34.5% for higher education. The estimates for Thailand are also strongly positive. Social returns for primary, secondary and higher education returns are 30.5%, 13.0% and 11.0% respectively. Private returns reveal the same pattern as for most countries, higher returns than for social return. The figures for private returns for primary, secondary and higher education are 56%, 14.5% and 14.0% respectively. Compared with Norway the returns are very high where Norway has a return in all categories on around 7%. Norway might not be the proper comparative unit with Malaysia and Thailand because of different emphasis on access to educational system and wage formation, but still it is interesting for the sake of pure comparison. The specific results for Malaysia and Thailand coinsides to a great extent with the general results that Psacharopoulos found. When Barro and Xala-I-Martin found the negative connection for women, it is resonable to question that result. The importance of this variable is declining for East Asia in the East Asia regression, and that is also reason for question, especially when the East Asia regression in the last period is estimated to be able to explain only 42.1%.
According to the social rates of return, which is put on the ground by the decision makers, has the development of the educational system been wise? Based on the social rates of return it is profitable for the countries to encourage education on all levels, but the social returns are definitely highest for primary education. We have seen that Malaysia and Thailand have given priority to increased education, which most likely have contributed to the economic growth in the two countries. But when comparing the social rates of returns with the average annual growth of years of education on the three levels, we see that Malaysia has made priorities in line with the rates of return, but that is not the case for Thailand. They have made priorities on the contrary to the rates of return with extreme priority to higher education, 8.9%, and very low priority to primary education, only 1.2% annual growth. See table 4.
Table 3 Average annual growth rates of primary, secondary and higher education in Malaysia and Thailand from 1960 to 1985.
Required labour at different periods of time is dependent on what step the economies are on the development ladder, and that makes the picture with the rates of return more complicated. When a country wants to achieve a more advanced line of production they need people being educated into different disciplines in order to handle the increased level of competence; engineering as well as finance, administration, science, teaching and other disciplines will be required.
Malaysia and Thailand are on different steps of the development ladder. Malaysia has a higher per capita income, and started the economic growth about ten years before Thailand. Malaysia also seem to have worked out more and better plans for development, so when it comes to education the countries have somewhat different needs today and in the nearest future.
We have seen that Malaysia and Thailand have increased their shares of the budgets to education. But it is right to ask if the money have been spent on the right kind of education. Malaysia has increased secondary education, and according to their step on the development ladder that has been wise. In order to develop they need more people from this level of education, but as they reach higher steps on the development ladder, they need to increase their capacity in higher education.
On the other side Malaysia and the World Bank have been arguing about a loan Malaysia was to receive from the World Bank. Malaysia wanted to finance an expansion in higher education, while the World Bank thought it better to expand the primary education. It might be a discussion on how far up on the development ladder they have reached and if the necessary basic requirements, like primary education, already are taken well enough care of.
Thailand increases more than Malaysia in primary and higher education. But Thailand has also been criticised for paying too little attention to primary education. (World Bank press release). Their high level of higher education might not be exploited because the lack of industries and other work-places for using their high competence. Thailand has managed to achieve high growth rates, as in most cases for countries in their position they have a comparative advantage due to their low wages. But as the growth rates keep on being high, the wages are pushed up, and the country loses its comparative advantage. Therefore it is of importance to encourage the population to educate themselves. In order to climb the development ladder, Thailand needs to put more emphasis on secondary education.
Looking into the numbers there might be an explanation found in the composition of skills when talking about Thailand. On a conference held in 1988 associate professor Apichai Puntasen from Tahmmasat University emphasised that the skills composition in Thailand was wrong when it came to what skills that were required in the Thai economy. " It is also accurate to conclude that higher education was made subservient to the immediate economic development objective without a much longer range vision. The higher educational system in Thailand, ...., was guided by development policy forcefully recommended by the United States and the World Bank. Since the Thai economy was mainly agro-base with a predominantly rural sector, it is conceivable that higher education could be inconsistent with the desirable development pattern of the Thai society."
He pointed to the unemployment rate in Thailand which was far much higher for graduates than for the labour force in general. Up till the 80s the public hired almost all the graduates so that hardly anyone with a university degree would be unemployed. That was defendable as long as the country experienced high economic growth rates. But in the 80s the country experienced an economic recession and could not afford to hire that many persons in the public administration. With the increased capacity to the universities the number of students supplying labour was higher than the demand for graduates.
We have seen here that there might have been a mismatch between the required qualifications in the industry and the actually educated labour force. So when planning what is needed of education in an economy the planners need to look several years ahead and project how the composition of the industry will look like. It is important to know that new needs and requirements will show up tomorrow and be able to supply the needed education, and hope that the past has provided for necessary education to supply the labour force of today with. If not there is a bottleneck that needs to be straightened out.
Figur 10 Life expectancy in Malaysia and Thailand
Source: Barro and Lee dataset (1994) for 1960-84 and Far Eastern Economic Review (1997) for 1994.
For Malaysia and Thailand it is most likely that the expansion of years of living has contributed to the economic growth in those two countries (Fernia 1990, World Bank 1993), and I will not discuss that any further.
The general regression showed that the public spending on education as a proportion of GDP contributed positively to economic growth. In the East Asian regression however this variable is reckoned to have a negative effect on the growth rates. It is very low but not unimportant. For East Asia governmental spending on education between 1965 and 1975 contributed with - 0.001 to the GDP growth rate, see table 5. In the following decades, 75-85 and 85-95, the contributions were - 0.002 and - 0.001 respectively. This measure is a proxy to the quality of the public money spent on education, not a direct measure of the quantity of education.
Table 4 The table shows the importance of quality of public money spent on education to growth in East Asia, the relation between predicted and actual growth rates, and education’s contribution to predicted growth.
The quality of education is measured as the student/teacher ratio, and figure 5 and 6 show the ratios for primary and secondary schooling in Malaysia and Thailand.
Figure 11 Student/teacher ratio in primary school for Malaysia and Thailand.
Figure 12 Student/teacher ratio in secondary school for Malaysia and Thailand.
Source: Barro and Lee dataset (1994) from 1950-1980 and Far Eastern and Australasian encyclopaedia 1997 from 1990-1995.
As we can see from the figure 5 and 6 the student/teacher ratio for both primary and secondary school in both Malaysia and Thailand are improving. Primary school experienced a fairly stable improvement. In Malaysia the ratio was 27.4 in 1960 and in 1995 it was 20.1, which leads to an average annual decrease of 0.9%. In Thailand the improvment has been slightly better. In 1960 the ratio was 36.2 and it had decreased to 20.2 in 1993. That is an average annual decrease of 1.75%.
The figures for secondary education are a bit more volatile, especially if we start at the figures form 1950. From 1960 Malaysia keep the level fairly constant around 25, but from 1975 the ratio start decreasing and by 1995 it has fallen to 18.7. From 1960 to 1995 the average annual decrease is 0.8 %. Thailand’s figures is falling to 1970, but raises markedly in 1975. The same pattern as for Malaysia appears; the ratio is decreasing to 18 in 1993, which is an average annual decrease of 1.6 %.
Some studies have been made when it comes to quality of education often in the context of rate of returns. Card and Krueger (1992a) examined the effect of school quality on the returns to education using 1980 US census data. Quality was in this study measured by the student/teacher ratio, average term length and the relative pay of the teacher. Their findings showed that people educated in states with high quality schools exhibit higher returns to additional years of schooling.
Assuming that this fact holds for the Asian countries, which might be a likely assumption, Malaysia and Thailand could have experienced higher GDP growth rates if they improved the quality of schooling. Even if they have improved the quality of their school system, they could have experienced higher economic growth if the quality was further improved. What this analysis does not have is the ability and scope to cope with the contribution from the other East Asian countries. There is a big variety within these 9 fast growers. Korea, Taiwan, Hong Kong and Singapore differ to a great extent from the small tigers, and their development came much earlier in time. Without going into the other countries’ quality of schooling all I can say is that on the average this variable could be improved in the other /some of the other countries as well since this variable contributes negatively to the growth in the whole of the HPAEs.
But we could also question if the student/teacher ratio is a good measure for capturing the educational quality aspect. Other measures could have been applied here, like scores on cross-national ability tests, volume of equipment in schools etc. These measures might give another picture of the quality of education.
Stephan Duggan makes a point out of the quality/quantity question. He
points to Thailand and argues that they have emphasised quality of the
educational system instead of quantity. But he says that there has been
a change in this approach due to the National Educational Plan from 1982.
The aim was " speeding up the quantitative and qualitative development
in line with the economic and social needs of the country." (Faraj,
1988:23). Duggan continues, " ... the Thai approach to education and
development which has stressed quality above quantity- a fundamental difference
between the Thai educational system and that of its neighbouring countries.
(...) countries such as the Philippines and Malaysia have concentrated
on a quantitative expansion of education to expand and meet human capital
requirements..." (Duggan 1991:145). Duggan underlines his quality arguments
with the difficulties in getting into the universities and almost elitistic
approach to higher education. And most of the universities were situated
around Bangkok which leads to a lack of access to universities for rural
students. When new universities and colleges are opened and more students
are enrolled he sees that as an approach to leaving the quality aspect
and heading for the quantity aspect. He gives the impression of looking
upon the two concepts as being complementary. It can be questioned if the
quality of the schooling is as good as Duggan presents it. In several of
the reports and recommendations where development institutions is occupied
with the development of Thailand, they emphasis a better human capital
formation, both the qualitative aspect and the quantitative one.(World
Bank 1997, Lim 1997, Rodenberger 1997).
One factor that has often been mentioned as important for the high growth rates in Asia is investment to GDP (I/Y). The general regression showed a positive, but small effect. For the 9 East Asian fast growers the contribution of the I/Y ratio is in line with the general regression; positive, but small. Out of the actual growth in the three decades, 1965-75, 1975-85 and 1985-95 the contributions are 3,6%, 7,4% and 10% respectively, see table 5. That means that they are not that important as one would think after reading various reports on this issue.
Table 5 The table shows investments contribution to growth(Inv/Y),
the relation between predicted and actual growth
rates (PG/AG) and investment’s contribution to the prediction of growth (Inv/Y/pred.growth) in three periods.
Source Barro and Xala-I-Martin (1995)
Gross domestic investment (GDI)
This factor started in 1960 out with 13%, increasing to 21% in 1970, in 1981 it is 32% and in 1993 it has increased to 33 %.
Another measure that is interesting to study is the ratio of real domestic
investment (private and public) to real GDP. That is Gross domestic
investment minus deteroriation. For both countries` part the ratio has increased from the first to the last period.
Real domestic investment
Malaysia started out in the 1960-64 period with 17.6% invested to real GDP, then increasing steadily till the 1980-84 period with a ratio of 32.9%, but experiencing a decline to 27.9% in the 1985-90 period. For Malaysia real domestic investment has on an annual average risen with 1.5%.
Figur 13 Real domestic investment in Mlaysia and Thailand.
Source: Tenold (1997)
Figure 14 Ratio of real domestic investment (public and private) to real GDP in Malaysia and Thailand.
Source: Barro and Xala-I-Martin’s dataset (1994)
Gross domestic investment
This factor started in 1960 out with 15%, increasing to 25% in 1970, in 1981 it is 27% and in 1993 it has increased to 37%. See figure
Real domestic investment
Thailand started out with 14.5% investment to GDP in the 60-64 period, and moving up to a level around 20% in the following periods. Their growth was mainly due to the growth between the first (60-64) and second (65-69) period and the peak ratio appears in the second period. The real domestic investment ratio has risen annualy with an average of 1%. This deviation in the might appear strange, but since they started with a fairly high investment rate, and since the increase from the first to the second period happened rapidly, that might have been enough to supply the economy with capital to invest.
As outlined in the theory part capital is of extreme importance for economic growth. Solow’s decomposition showed that it was one of the three main factors for explaining economic growth. It has been important for Malaysia and Thailand as well as for the other HPAEs. There are two ways of getting capital: domestic savings and foreign investments. What characterises the HPAEs is their high savings rates. In the expanding periods both Malaysia and Thailand managed to hold a high level of savings.As we can see from the figure Malaysia’s saving rate was around 26% in 1960, 1970 and 1981, but increased in 1993 to 37%. In Thailand the saving rate as a proportion of GDP increased every year from 13% in 1960 and jumped to 37% in 1993.
The high saving rates were not random, they were encouraged, and partly forced by the government. The higher rate of production made saving and investment possible without having to reduce consumption.
Research done by Young (1994) (in Barro and Sala-I-Martin, 1995:381) with the Solow’s decomposition method, shows that capital was most important and then labour and the least important was technological progress for the East Asian tigers. This does not coincide with the picture given in the regression analysis about the importance of the investment. Of course one cannot directly compare theses two measures but it is still interesting to observe the different pictures they give.
In contrast to Barro and Xala-I-Martin’s regression, another regression, computed by the World Bank, finds that investment explains more of the economic growth, and that is in line with Young (1994). The World Bank estimates(1993, tab.1.9) show that the investment factor is important in the explanation of growth for Malaysia. See table 10. Out of a growth rate explanation of 3.46 it contributes with 47%. The investment factor is the second most important factor for explaining growth, only primary enrolment is of more importance, accounting for 73% of the explaining effect. Checking for the reliability of prediction the whole World Bank regression is high, 87% (3.46/4.00).
The World Bank estimate shows that investment to GDP has not been as important to Thailand as for Malaysia. It has contributed to the explanation of growth with 35%. Still it is the second most important factor in the WB estimates, ranging only after primary enrolment in importance for explaining growth. The explanation reliability effect for the whole regression is 66% (2.51/3.82) for Thailand.
Figure 11 The table shows the predicted contribution to growth
of investment, human capital, population growth, and
relative income for Malaysia and Thailand. It also shows the share of actual growth predicted by these variables.
Source: World Bank (1993:53, tab.1.9)
Without the foreign investment in the region we would most probably not have experienced the high growth rates. As Graham Field puts it: "Asian countries striving to make optimal use of their natural resources and labour endowments cannot hope to do so without capital investment. Foreign capital is particularily prized, ..."
In 1995 of total FDI 60% went to East Asia, where China received the largest proportion, and Malaysia received 6.7% of world total FDI.
It is no surprise that developed countries contribute with the largest shares of FDI to both Malaysia and Thailand. In 1981 developed countries contributed with 58.6% of the FDI to Malaysia and increased a little bit to 59.2% in 1987. The equivalent proportions for Thailand show that Thailand received 80.2% in 1980 and 77.3% in 1988.
To sum up the investment variable we have seen that there is a divergence
between Barro and Xala-I-Martin’s regression and the results of other researchers.
Barro and Xala-I-Martin also question the low explanatory power of the
investment variable. One possible reason they suggest " ... the measure
of investment in the data is inappropriate. In particular, the concept
includes public and private spending..." (1995:433). But when they
later separate into public and private components, they "...find that
the conclusions do not change very much." (1995:434) The data that
have been used in the regression is also the same as other researchers
use, so differences cannot be explained with a weak data base. If we can
not find the proper explanation for deviations between Barro and Xala-I-Martin’s
regression results and results from researchers at the World Bank and Young,
we still need to be aware of the weakness in the regression analysis.
The general regression showed a negative correlation between large governmental consumption to GDP and economic growth. According to Barro and Xala-I-Martin’s East Asia regression this is an important variable in explaining the growth in East Asia. Between 1965 and 1975 it contributed with 14%. In the next period, 1975-1985 it increased its share to 22%. The last period it increased its share even more to 30%, see table 7. That means that this variable has an increasing share of explaining the economic growth in the 9 East Asian countries. These figures are net of spending on education and defence.
Table 6 The table shows governmental consumption’s contribution
to growth(G-cons/Y), the relation between predicted and actual
growth rates (PG/AG) and government’s consumption’s contribution to the prediction of growth (G-cons/Y/pred.growth) in three periods.
Source: Barro and Xala-I-Martin (1995)
Below I will see how this is applied to Malaysia and Thailand.
Figure 15 Ratio of real government consumption expenditure net of spending on defence and education to real GDP.
Source: Barro and Lee dataset (1994)
Malaysia has a clear decline in the ratio of real government consumption expenditure to real GDP. In 60-64 they spend 9.3% , and decrease it gradually to 4.97% in 80-84.
The ratio of real government consumption to real GDP is quite stable in Thailand during all the decades. They start with 5.86% in 60-64 and increases it to between 6.1% and 6.3% in the following years.
With the general regression showing negative correlation and the East
Asia regression figures being positive, one explanation is that the East
Asian countries have reduced their governmental spending. For the two countries
in focus in this essay we see that Malaysia fits into that picure, but
Thailand contradicts it. Figure 15 visualises that. We could also say,
according to the general regression, that if Thailand reduced its governmental
consumption they could experience higher economic growth rates. This might
be a too simple conclusion and might show the authors point of departure
when it comes to how big the public sector ought to be. It could be argued
that under some circumstances it is reasonable to increase the governmental
consumption. The size and the role of the public sector is widely discussed
in the political economy literature about Asia, as mentioned in part 2.2.2.The
neo-classics and the institutionalists- discussion on the High Performing
Asian Economies. Put into a philosophy of science perspective we know
that all research is based upon a certain set of data. These data are worked
with and interpreted. Parts of the research are later used in some kind
of relation, often used as recommandation for policies. When this is done
research gets a positivistic/normative role, not only a descreptive role.
It is possible to draw a line from the left hand side politics to the right
hand side of politics, where we roughly can divide the two groups into
point of view on the size of the public sector. The former are in favour
of a big public sector whereas the latter want the public sector to be
as small as possible. The authors are somewhere on the political right
hand side meaning that they would use arguments in favour of a small public
sector. I am not going to go any further into that question, but I am of
the opinion that we need to be critical to the researchers conclusions
about the size of public spending.
When measuring the quality of the bureaucracy the World Bank (1993:175) points at three factors that is, to more or lesser extent, characteristic for the Asian bureaucracy which they reckon to have contributed to what the World Bankk call "the East Asian Miracle".
The governmental spending factor is important, according to Barro, but
I find it strange that it is so important since the discussion on the size
of the governmental spending is beneficial or not. But with the last years’
revelations of corruption in several of the Asian countries, Malaysia and
Thailand included, it might be appropriate to attach that much explanatory
power to this factor.
The general regression showed a negative correlation for this variable and economic growth. The results from the East Asian regression in respect to black market premium (BMP) show that it has played an important role for the economic growth in all the three decades. In the 65-75 period it contributed with 0.003 out of 0.028 of the growth rate, or 11%. The importance grew to 0.006 out of 0.040 (22%) in the 75-85 decade. The last five years it contributed strongly to the explanation of the growth rate with a share of 0.007 to 0.020 or 35% of the growth, see table 8.
Table 7 The table shows Black Market Premium’s (BMP) contribution
to growth, the relation between predicted and actual
growth rates (PG/AG) and BMP’s contribution to the prediction of growth (BMP/pred.growth) in three periods.
Source: Barro and Xala-I-Martin (1995)
Figure 16 Black Market Premium
Source: Barro and Lee dataset (1994)
Starting in 60-64 with 0.018 in Malaysia, the following years show a clear tendency for declining with the lowest figure in 80-84 being 0.003. A rather unexpected phenomenon appears in the 85-90 period, the black market premium (BMP) has risen to 0.0187, which is actually higher than the first period. Either there is a plausible reason or the data are weak.
After having read through literature for trying to find plausible explanations for the rise in BMP, I do not find any good explanations. In addition the trend is so steady so most likely the data are weak or something unusual happened in that period of time, and will not happen again. I therefore do not seek to explain the deviation any further, and believe that the figures are random deviations.
For Thailand’s part the same declining tendency occur, even at a much higher speed of decline than in Malaysia. Starting in 1960-64 with 0.027, in the 70-74 period the BMP is removed. It does reappear in 75-80 with 0.004, but vanishes in the last periods. It is therefore likely that Thailand have got rid of the discrepancy between actual and official exchange rates.
Comparing the diminishing trend of the BMP in Malaysia and Thailand with the regression of Barro and Sala-I-Martin I find a fairly good correspondence. The correlation for the world sample showed a significantly strong connection between a low BMP and economic growth. Since we find a positive economic growth in East Asia combined with a diminishing BMP this could likely mean that the diminishing BMP has contributed strongly to the high growth rates in East Asia the last decades. And since Malaysia and Thailand have contributed to lowering the BMP, that might as well have contributed to the high economic growth rates in their respective countries.
One critical remark is the importance this variable comes out with in
the regression. In the last decade it contributes with 35% in explaining
the economic growth in East Asia. I do agree that it is important to have
a well functioning market, which the BMP is an indicator for. But one could
question the importance of BMP when compared with the other variables.
Could it be an artefact of another significant latent variable?
The general regression shows a negative correlation between political instability and economic growth. The East Asia regression results show that this variable has had little influence on the economic growth rates in the three decades. 0.001, 0.001 and 0.002 out of 0.028, 0.027 and 0.020 respectively shows that they have had a positive, but little contributing effect on the growth rates. See table 9.
Table 8 The table shows political instability’s contribution to growth, the relation between predicted and actual growth rates (PG/AG) and political instability’s contribution to the prediction of growth (Pol.instab/pred.growth) in three periods.
Source: Barro and Lee’s dataset (1994)
For Malaysia’s part the measure of political stability is zero all the periods except one. In the period between 1975 and 1979 the measure shows 0.10815, see figure 17.
Figure 17 Measure of political instability in Malaysia and Thailand from 1960 to 1984.
Source: Barro and Lee dataset (1994)
The index of political rights ranges from 1 to 7 where 1 shows most freedom and 7 least freedom. Malaysia starts out in the 72-74 period with 2.67 and actually increases as time passes like shown in the figure below, finishing in 85 to 1990 with 3.6. The average in the 1972 to 1989 period is 3.11, see figure 18.
Malaysia has had a fairly strong political governing but not as authoritarian as some of the other Asian countries, like Singapore and Indonesia. The freedom of speech has been exercised. The Prime Minister from 1980, Mahathir Mohammed, has been a strong and outspoken Prime Minister. But he and his government have allowed critics. The freedom of speech and democracy and other factors are some of the characteristics for a modern society, a society that is the goal for the Malaysian politicians in Vision 2020. Ahmad Sarji Abdul Hamid have formulated what kind of political society Malaysia is to become within year 2020: "These challenges range from the need to establish an economy that is competitive, dynamic, robust and resilient to the evolution of a united Malaysian society that is democratic, just, moral, liberal, peaceful and progressive."
The authors do not describe what variables that the civil liberties and political rights are based upon. But one feature might be the availability for all ethnic groups, all social groups as well, to participate in the processes where the decisions are taken. Education is one entrance to where everyone can qualify for participation in the bureaucracy and politics. But Malaysia exercises a positive discrimination in favour of the Bumiputras, both in the educational system and in employments in the bureaucracy. That might be one of the reasons why Malaysia increases its score on the political rights index.
Figure 18 Index of political rights where 1 is most freedom, 7 least freedom
Source: Barro and Lee dataset (1994)
Thailand starts out with zero on the political stability measure in the two first periods, 60-64 and 65-69. However in 70-74 it is 0.200, in 75-79 it increases to 0.302 and in 80-84 it is reduced to 0.200, see figure 17.
The political rights index shows that Thailand started out with a bad degree of political rights, scoring 6 in the 1972-74 period, but decreasing as time passes on, ending with 2.800 in 85-90, see figure 18. The average from 1972 to 1989 is 3.944.
Thailand is a quite homogeneous society and do not have the same potential for ethnic tensions as Malaysia has. But the country has experienced several coups after the second world war and all the way up till today. The last coup was in 1992. None coups are exactely similar, because different motives lie behind coups at different times in history. But compared to coups in other countries the coups in Thailand seldom shed much blood, and not many people are involved. It is mainly a struggle for power among some few military generals. Thailand has been strongly influenced by the military and they have held political power. The number of seats in the parliament has been lowered in the last decade(s), but still the military is an important part of the political system in Thailand. In a personal conversation in June 1998 with Viggo Brun, a senior Thailand researcher at Copenhagen University, he expressed that even if the military formally speaking had lost part of their political power, they still were very much present in the economy. They had only different ways of exercising the power. Now their ways of exercising power was more hidden, more subtle and more difficult to look through. Even if the power of the military seem to have diminished, they do hold an important position in their potential to exercise pure military power and let the population and investors suffer from it.
The King of Thailand, Bhumipol Adulyady (King Rama IX), has also played a political part. He has kept the Thai people gathered in a post-war period where Thailand through coups tried to find out what its fundaments should be. The King and his family is respected and symbolises a united Thailand. Since the coups do not seem not to affect the daily running of the country the foreign investors seem not to have been scared away from investing in Thailand.
When discussing the high growth rates in Asia one argument has been that it actually might be beneficial to pursue a bit more authoritarian rule in order to follow a industrial strategy. With democratic regimes so many involved parties need to decide. That lead to a "waste" of time as well as the existence of horsetrade and therefore problems with following one path of development. On the other we have enough examples of countries that have succeeded in achieving economic growth following a democratic regime. West-Europe is a good example of that phenomenon. But it does not actually say anything pro or against the type of regimes that in the best way provide room for economic growth. Several other factors is needed to complete the picture.
Knowing how many political assassinations that are present in a country have high dark figures. That might be due to lack of statistic on the issue because it will hurt the reputation of the authorities. Human rights organisations will have to make estimates based on eye witness testimonies and more uncertain estimates. So in that sense the data used are not very reliable. Of course the data might give a picture of how advanced the country is as an advanced democratic and civil society. We need to be critical when using the data in research.
The other critical remark has a political bias. Why have the researchers not taken into account the number of coups, but instead incorporated the number of revolutions? Usually revolutions are executed by groups sympathising with communists, coups are executed by the military. When discussing one may ask why nobody brings coups into the discussion. It could lead to a discussion against revolutions, with not putting the problems with coups on the agenda. Often the US has supported coups by the military, e.g. Indonesia (1965), South Korea (1950), Chile (1977) and Nicaragua (1980s). The USSR used to support other parts, e.g. North Korea (1950), North Vietnam (1960s).
I think it is valuable to include the political dimension in this quantitative regression analysis. It is undoubtedly a significant factor. But the political dimension is a discipline of its own (political science), and I think the lack of ability to cover a greater aspect of the political discipline is mirrored in the regression. Too few aspects are covered when only including political assassinations and revolutions in the quantification. When this factor plays such a small role in the regression that reflects that only a fraction of the factor has been included. For Malaysia and Thailand’s parts the increased stability has improved the investors risk premium and has contributed to the increased investments done there the last years.
In this regression we look at terms of trade shock (growth rate of export prices minus growth rate of import prices). Improvements in the terms of trade raises a country’s income and thereby increases its consumption. Therefore a positive effect is expected and in the general regression it is found to be positive.
If a country has succeeding negative terms of trade shocks it shows
that a country needs to produce more of the same products in order to be
able to import the same amount of goods as before. Therefore it is desirable
to increase the terms of trade variable so that one can buy more for the
same amount of domestically produced goods.
Table 9 The table shows terms of trade’s contribution to growth,
the relation between predicted and actual growth rates
(PG/AG) and terms of trade’s contribution to the prediction of growth (terms of trade/pred.growth) in three periods.
Source: Barro and Lee’s dataset (1994)
The terms of trade shocks variable shows no explanatory power in the
East Asia regression. In all three decades this variable does not contribute
at all to the economic growth in East Asia, showing 0.000 in three decades,
see table 10. That might mean that either the terms of trade has not played
any role at all/any significant role in explaining the growth in
East Asia, or that the data are weak and would need some more emphasis.
Figure 19 Terms of trade shocks in Malaysia and Thailand from 1960 to 1984.
Source: Barro and Lee dataset (1994)
Malaysia experiences negative terms of trade shocks in the 1960-64 period and in the 1965-69 period. The figures ranges from -0,035 to -0,077. In the 1970-74 period and the 1975-79 period it is positive. The figures are between 0,030 and 0,069. The last decade it turns negative again, being -0,040.
Most of the time the dataset shows negative terms of trade shocks for Thailand. The exception is the 1970-74 period. In that year it is 0.018. The negative terms of trade shocks are volatile, ranging from - 0.041 in the 1965-69 period to - 0.018 in the 1970-74 period.
When countries are exporters of natural resources or goods consisting of a high degree of natural resources, the GDP of the country is also more vulnerable because the prices of natural resources tend to be more volatile than prices on goods that are produced with more advanced technology. In East Asia’s 9 fast growing economies the small tigers are the economies with highest share of income from natural resources. If the reasoning above is correct these economies are also most prone to be affected by terms of trade shocks.
In the case of all the 9 East Asian countries, as well as Malaysia and Thailand, there has been a positive economic growth and therefore I only consider a positive terms of trade shock. It could be that these countries have experienced a negative shock but it has in that case only been minor since they have managed to turn the growth ratios to positive ones rapidly. If there had been a positive terms of trade shock that would mean that it pushed the trend of growth to a constant higher economic growth trend.
In the discussion on share of GDP coming from different sectors, it
is also important to consider other factors. If a country is diversified
when it comes to production and export of natural resources the country
is not as vulnerable to changes in prices as is the case if national income
is based on few resources. With fluctuations of prices on the natural resources
the country’s income can decline so much it can have a significant economic
effect on the country.
For Malaysia the most important export goods are palm oil and rubber. The prices have rather declined than increased. That leads us to a conclusion it might partly explain the negative terms of trade shocks (1960s and 1980) and that it has not contributed to the economic growth of Malaysia the last decades.
However Malaysia started fairly early with development of industries and therefore more advanced production has increased its share of the contribution to GDP. To check for terms of trade shocks we can see which are the most important export goods among this group of goods. Those are first machinery and second transport equipment and basic manufactures and third is miscellaneous manufactured articles. If there had been a marked change of export prices it would have been a negative one. Especially the demand for electronics and semi-conductors declined severely in the 80s, leaving Malaysia in an economic downturn.
Import prices are important as well. The most important import goods in Malaysia in 1995 are machinery and transport equipment far ahead of the second, basic manufactures. Chemicals ranges third.
The most important import articles in Thailand were in 1995 machinery and transport equipment (e.g. power generating machinery and equipment, general industrial machinery, office machines and automatic data processing equipment) then basic manufactures (textile yearns, fabrics, iron and steel) and third chemical products (e.g. organic chemicals and artificial resins and plastic materials).
Exported goods are first and foremost miscellaneous manufactured articles (e.g. clothing and accessories, footwear), then food and live animals (e.g. fish, rice, fruits, sugar) and third basic manufactures (e.g. textile yearns, fabrics).
Thailand’s economy is more dependent on agricultural products than Malaysia. If the term that goods made from natural resources are more exposed to price shocks hold, that could partly explain why Thailand has had negative terms of trade shocks in all periods but one. Also Thailand has gone through a remarkable structural change the last decades, and increased the importance of the manufacturing sector in the economy.
Without being able to say exactly what redeemed the shocks, it is likely to believe that the shocks have in one way or another have influenced the economic growth processes in the two countries. Since Thailand has mostly experienced negative terms of trade shocks we might say that the economic growth could have been even higher than it was if the growth rates of export prices had been higher than the growth rates of the import prices. Since Malaysia has experienced both negative and positive shocks their economic growth has not been that much influenced. But also in Malaysia the economic growth might have been bigger if the terms of trade shocks had been positive in all periods. So when the regression figures show that this variable is of insignificant importance for East Asia, the non-importance might apply for Malaysia and Thailand as well.
It is interesting to see how well the regression have managed to explain the economic growth for Malaysia and Thailand. Table 10 shows the regression function results (predicted values) for Malaysia and Thailand. The predicted values are compared with the actual growth rates for the decades between 1965 and 1975 and between 1975 and 1985. The last years are from 1985 to 1990.
|Fitted growth value 85-90||
Table 10 Predicted values (PV) show how well the regression has been to explain the actual growth rates (GR) for Malaysia and Thailand between 1965 and 1990.
Source: Barro and Xala-I-Martin (1995:418-419, fig.12.2)
The first decade in Malaysia the relation between actual growth rate and predicted value is higher than the proceeding decades, with 0.90 (0.047/0.052). The last five years have the lowest relation, with 0.67 (0.037/0.055). The overall relation in the 1965 to 1985 period is high with 0.92 (0.046/0.050). It might appear strange that the 25 years average relation is so strong and even a closer relation than all the other years.
We see that for Malaysia’s part the predicted value is in all three cases higher than the actual growth rates.
The last five years the relation is very weak (0.32), and we might ask if it is significant at all. The overall relation is 0.87 and also here like with Malaysia we might ask what causes this strong relation when the separated years are not that well explained by the regression function. It may partly be explained by a higher Standard Deviation(SD) in the sample for the whole time period compared with the shorter period. With higher SD in a sample it is easier to get high correlations. Further, what may be a good set of predictors at one time may not be so in the future because of different conditions.
The findings show that the function’s variables explain well the economic growth. But the fit for Thailand the last period is questionable.
I have used the general regression and the East Asia regression to try to answer that. The East Asia regression is referred to in table 11.
Table 11 The table shows the gathered results from tbls 2,5,6,7,8,9,10, which show the importance of the different variables for the economic growth in East Asia.
Source: Barro and Xala-I-Martin(1995:448, tbl 12.4)
The general regression showed that the convergence effect in interaction with human capital factors was strong. But the negative correlation for women and economic growth is questionable. The East Asia regression showed that this variable was strong in the first decade, but declining in the following decades. It could very well be argued that this variable has been important in explaining the economic growth in Malaysia and Thailand due to their priorities to education.
Improvements in the quality of education showed a positive correlation with economic growth according to the general regression. The East Asian correlation showed that this variable contributed negatively to the growth in East Asia. Malaysia and Thailand have improved their educational quality, and therefore it is not likely that they have contributed to the negative figures for explaining the growth in East Asia.
The general regression showed a positive, but low correlation for investment and growth. The East Asia regression showed a positive, but low effect from this variable. I have questioned the low correlation. For Malaysia and Thailand’s part it is arguable that this factor has played a more important role than the regression figures shows.
A high degree of governmental consumption the general regression showed a negative correlation to economic growth. This variable is growing in importance in East Asia, contributing more and more to the explanation of the East Asian economic growth. Malaysia has decreased their governmental consumption, and fits well with the two regressions, but with Thailand’s governmental consumption being status quo, their growth is not well explained with this variable.
A high Black Market Premium (BMP) has a negative effect on economic growth was shown by the general regression. The East Asian regression shows that this variable contributed to explaining the growth, and the importance is increasing. Both Malaysia and Thailand have decreased their BMP so most likely this variable has contributed to explaining the economic growth. It is questionable that this variable is as important as the estimates show.
The general regression showed that a high degree of political instability correlated negatively with growth. The East Asian regression showed that this variable has little contributing effect on the explanation of economic growth. Malaysia and Thailand have decreasing political instability, and this increasingly sound political climate might probably have participated in explaining the high growth rates.
Finally the terms of trade shocks variable showed a negative correlation with economic growth in the general regression. For the East Asian regression it had no contributing effect on growth. I have questioned the lack of explanatory power due to the high ratio of traded goods to GDP in most of the East Asian countries. That applies for Malaysia and Thailand as well.
In the aftermath of the analysis there are four comments I would like to make.
First the degree of explanatory power seem to have been reduced as the decades pass on. See table 11. From having a perfect fit, where the 2.8% actual economic growth in East Asia is explained, the explanatory power is reduced to 68% in the 1975-85 period and to as low as 42% in the 1985-95 decade. Observing that we might rely more on the explanatory effect of the variables in the first decade than the latter ones. In the analysis I have made a point out of changes in importance of different variables. But with the declining accuracy of the predicted values, it is reasonable to ask if the changes are interesting to comment upon.
But if we use the fit for Malaysia and Thailand specifically we find the fit to be much higher than for the general East Asia regression. And the fit is high for the other fast growing Asian economies as well. See figure 12.
Figure 12 The figure shows the ratio between actual growth rates (GR) and predicted growth rates(PV) for 8 East Asian economies in three decades. China is also part of the HPAEs, but the predicted values have not been estimated and therefore is left out in this figure. We see that Korea and Japan have high degree of fit between actual and predicted values. We also see that the ability to explain is somewhat better the first decades than the last decade. The latter fact applies especially to Thailand, Hong Kong, Taiwan and Singapore.
Source: Barro and Xala-I-Martin (1995: 418-419, tbl 12.2.)
We see that the results from the two ways of measuring fit spread out which makes it hard to draw any clear conclusion about the regression’s ability to explain growth in East Asia, and specifically in Malaysia and Thailand.
Second what I find questionable with the East Asian regression is the weights that have been estimated for the different variables. That is because other studies have shown that the variables might be of different importance than the East Asia regression has estimated. The World Bank regression showed that investment played a much more important role for the East Asian growth than Barro and Xala-I-Martins regression did. In addition the discussion on returns to education showed that education might be more important than Barro and Xala-I-Martin’s regression results showed. That would especially apply for women, where the regression showed a negative relation, while Psachoropoulos estimates showed positive relations for both men and women. The quality of education has improved in East Asia, and that was shown also for Malaysia and Thailand. But still the regression estimates this variable to have a negative impact on economic growth. I have also questioned the ability to capture factors that are more difficult to quantify, like political factors. In the regression I do not think the political instability variable captures all aspects in the importance of the role of politics in economic growth.
Therefore I would think that the convergence effect, investment, educational spending and political stability was more of importance than their weights show. And that governmental spending and BMP was less important. I would also think that the terms of trade was given somewhat more importance because the East Asian economies are so dependent on export and import prices since their economies have a high share of GDP from trade.
A third point is does the regression explain the economic growth better in some periods? When using the results from Barro and Xala-I-Martin we find that there is a difference, but it is not very significant. See figure 13.
Figure 13 The figure shows the fit between actual and estimated growth values for 40 economies in three decades. We see that the fit is better in the first decade, but it does not differ significantly from the other decades.
Source: Barro and Xala-I-Martin (1995:448, tbl.12.4)
In the 1965-75 period the growth fit was 76.6%, in 1975-85 it declined to 57.2%, and in 1985-95 it increased to 63%. So there is not a clear tendency in favour of better fit in some periods than others.
A fourth point is, do the variables fit better for some regions than others. The power of explanation differs between the regions, but it differs between a not too wide range, from 45% (Sub-Saharan African slow growers) to 78% (Latin American slow growers). East Asia has a 60% fit. See figure 14.
Figure 14 The figure shows the ratio between the actual and predicted values for 5 regions over the 1965-95 period. The three sub-periods, 65-75, 75-85 and 85-95 have been added for each region and then divided by 3. We see that there is not a big difference between the regions when it comes to ability to estimate the economic growth when using Barro and Xala-I-Martin’s regression.
Source: Barro and Xala-I-Martin (1995: 448, tbl 12.4)
The economic collapse in Asia was not expected. The economic growth was seemingly everlasting. And even those actively involved in market transactions believed that. In a survey made by John Frankenstein in the spring of 1997, business leaders were asked about their expectations of the future in doing business in Asia. The majority of the answers was positive, the question was whether the growth was going to be one-digit or two-digits. Only a few foresaw an economic downturn that later actually did happen. The question is how deep the crisis will be and what implications it will have on the economic growth in the years to come. Has it left the countries affected with a constant slowdown of growth or is it only a cry for some adjustments in different economic structures, like the financial sector and political-business relations? Is the regression suitable for saying something about the next years` growth rates. Are there other factors that need to be used to be able to analyse the future economic growth? If so, what are they?
First the financial sector was in trouble. A great share of the loans went to the property market. Paisley’s (1996:61) estimates show that almost 50% of the investments in Thailand were in relation to the property market. The extensive lending to the property market resulted in a strong increase in the volume of constuctions. The property market contained a large "bubble" element. The "bubble" burst when it was known about the overcapasity in the property market in Bangkok. Much of the collateral that the banking sector accepted for loans was real estate and equities, assets whose prices contained this "bubble" element. With the bursting of the "bubble" it was revealed that two of the largest banks in Thailand were not able to pay their loans. Later 58 finance companies were closed by the authorities due to the same lack of ability to pay.
The financial sector had been borrowing short, lending long. That meant that the loans should be paid back within a year, but the borrowers had conditions allowing them to pay back in a long term perspective. A large share of the foreign loans was unhedged and denominated in dollar. That also lead to different interest rates on the loans. The short term rates that applied to loans borrowed at internationally were lower than the ones they were lent at domestically. In an interview in Asiaweek magazine with Chumpol Nalamlieng, the chief executive of the blue-chip Siam Cement company in Thailand explain how the company ended up with a $4.3 billion foreign currency debt:
"We could have borrowed locally, something like 14 percent per annum, or borrowed overseas, where we could get (dollar) loans for 8 percent or 9 percent. If I had borrowed locally, the (securities) analysts would be saying that we were being foolish for not taking advantage of lower interest rates overseas.... We could have bought insurance, but that would only be adding to the cost. Our government, our bankers, economists, even foreigners were telling us that the baht was stable, that there was nothing wrong with its fundamentals. We never imagined that the baht would be devalued. And if there was even a small chance of that happening, nobody, not even the most pessimistic, was saying that there would be a 30 percent or 35 percent devaluation."
In addition the affected countries suffered from two critical frailties, moral hazards and lack of independence from supervisory and regulatory authorities. When the moral hazards exist, borrowers and lenders, and other information problems occur, then compounded with currency crisis they are often sufficient to bring about a sharp contraction of economic activity and precipitate a financial crisis.
The overcapacity was also shown in the stock market prices. Since relatively much, in some cases up to 40%, of the stocks at the stock exchanges in Asia were asset related, that contributed strongly to the fall. In Thailand the top value was in 1994, by the summer of 1997 it had fallen with 2/3 (Tenold:1997). From July 1997 to January 1998 the composite stock market price index had reduced its value with about 56%. (ADO:1998)
The Malaysian stock market was also struck hard, from July 1997 to January 1998 it had reduced the value of the composite stock market price index with about 65% (ADO:1998).
It might seem strange that these deficiencies were not revealed before, but there had been coverings of the real figures in the finance institutions, and even made deliberate mistakes in the reports to the authorities and investors. In addition the absence of authorities executing their supervisionary and regulatory task to ensure that prudential standards were met and in some countries the standards were inadequate and these factors led to a lack of transparency and lax regulations. (ADO, 1998:30).
Second, the real side of the economy was struck with stagnation of exports in the mid-90s. That was due to real economic factors. Both Malaysia and Thailand went through some heavy structural changes in the 70s and the 80s. Both economies went into more advanced production, with imports of components and machinery for the production of e.g. electronics and semi-conductors. Even if the export incomes were growing at enormous rates the imports where still larger, and created large deficits on the trade balances and current accounts. In addition the countries lost competitiveness due to higher wages in labour intensive industries such as garment and footwear and met more fierce competition from neighbouring countries with lower wages. That led the export earnings to lose the extremely high growth rates that the countries were spoiled with. And that affected the real side of the economy in Thailand and Malaysia.
Third the fixed exchange rates deviated from the real currency values. The exchange rates were pegged to a basket of currencies, in the case of Thailand the basket consisted of 80% US dollar. This was done very consciously because the countries were so dependent on exports and imports and with stable currencies it created predictability for the actors in trade. The stability, and implicitly the risk reduction, was crucial to the inflow of foreign capital. And the inflow of capital also led to a further deterioration of the current account deficit. Tenold (1998) makes a point out of the deficit on current account saying that it is not harmful per se, because if the investments are done in industries where anticipated profits would follow investments, it was defendable. This happened up till the beginning of the 90ies and investments were in export industries. But with the coming of the 90ies foreign investments were channelled to sectors that would not be traded internationally, e.g. assets, and then there was no legitimacy for a constant deficit on the current account. The appreciation also led to more expensive exports which gave the countries a reduced competitiveness.
With the economic expansion in the US in the mid-90s, the US dollar appreciated and the Asian currencies followed in the appreciation, but the real values did not follow as much as the currencies did. Due to the problems in the financial sector, the export stagnation and real side of the economy and the unbalanced exchange rate, the Thai economy turned very vulnerable and the confidence to it was declining. That led to a massive sale of baht. The central bank tried to compensate by buying baht. But on the 2nd of July the authorities had to give in and let the baht float. The international and domestic actors reacted with selling off baht when the baht was released from the peg to US dollar. Within the first month the baht depreciated with more than 30% compared to US dollar.
Like Frankenstein’s survey showed investors had faith in the Asian investments all the way to the floating of the baht. That led to a huge inflow of capital to the Asian countries. On a cumulative basis from 1987 through to the end of 1996 Thailand received $75 billion and Malaysia $68 billion. For Thailand that was 7.4% and for Malaysia it was as much as 12% of GDP on an average. Only a small fraction came from foreign direct investment (FDI), most came either through portfolio investment or through the banking sector. The investors expected high returns in the Asian countries, and by spreading the investments to Asia as well as to Western developed countries the diversification made the risk lower. In addition high interest rates together with pegged exchange rates, created a false sense of security among many investors. But when the revelations about the unfavourable condition Thailand was in, the capital was drawn out from Thailand
The panic of holding Asian currencies spread, including Malaysia. The spread was due to
1. Competition and intra-trade, where the East Asian countries competed in the same markets and changes in competitiveness such as a depreciation/appreciation for one of the countries affected the competitiveness for the other countries.
Thailand had to ask the International Monetary Foundation (IMF) for technical and financial assistance. Malaysia managed without this assistance.
There is a discussion on who were to blame for starting the sale of the local currencies. The Malaysian prime minister, Dr. Mahathir Mohamad, put the blame on international speculators, naming especially the American finance man George Soros. "We have worked 30 to 40 years to develop our countries to this level but along comes a man with a few billion dollars, and in a period of two weeks has undone most of the work we have done." In his speech he concluded that speculators should be treated like common criminals. Mahathir Mohamad’s reasons for the problems are too simple and after he had proclaimed his point of view, a further depreciation of the ringgit occurred. It was not only foreigners that withdrew money from the Asian countries, also domestic actors sold local currencies to prevent a further loss when the currencies kept on depreciating.
The IMF recommended Malaysia to reduce growth for some time to get out of the economic crisis. But Malaysia hoped to sustain rather than reduce growth. They cut some major infrastructure projects which at the time being are too expensive to fund through external borrowing, and halted its privatisation program because of depressed stock market values. Its 1997 budget actually proposes a small increase in government spending and a cut in corporate taxes (the opposite of the IMF prescription), but projects a budget surplus of 3% of GDP on the assumption that growth will continue at an only slighter lower than 7% rate. Interest rates have not been raised because that would bee "too contractionary", but the central bank has imposed restrictions on property sector lending. The government seem to mainly be relying on the ringgit depreciation and the depressed stock markets to curb investment, consumption and the current account deficit. Given Malaysia’s stronger fundamentals- high savings, low external debt, low inflation, somewhat healthier banking and property sectors than its neighbours, and heavy dependence on exports- this "non-IMF" policy arguably has a chance to succeed and provides a useful "real-time" policy experiment in contrast to the standard liquidity-crunch IMF prescription followed by its neighbours. But confidence has been severely damaged, and the value of the currency and stock markets are not on the level they used to be. So the circumstances are not the best for trying out the "non-IMF" policy. (Lim 1997)
What happened in 1997 showed how vulnerable the development in these
countries are. It has led to a loss of confidence to the functioning of
these markets, and these markets ability to rebuild the confidence is essential
for the further economic and social development in these countries. The
governments will solve that in different ways.
We have seen that the economic crisis in Asia has also hit Malaysia and Thailand. And the crisis does not seem to recover within a short term neither. Therefore I need to ask if the crisis will affect the growth in Malaysia and Thailand. Since the regression is the central in this essay I will use that as a point of departure for a brief discussion on this issue. In addition to the seven variables I will add a final comment on the prospects of the future growth in Malaysia and Thailand.
We have in the regression seen that Malaysia and Thailand started out with fairly low initial GDP levels, and the potential to grow was present. Both countries managed to exploit this advantage. The convergence effect has been important for them. They raised the level of education and life expectancy increased as well. These factors contributed to growth. The question is whether the investment in education is enough. The general regression showed that there was a negative effect of educating women. I have been very critical to this fact, because other studies show a strong correlation between education and growth, and particularly for women. Both Malaysia and Thailand have spent more of the public budgets on education, but we have seen that it might not be enough or good enough. For Thailand especially secondary education is not satisfying as skills for advancing to a higher step on the development ladder requires more vocational skills. In addition the docile and learning principles of the Thai education system needs to be transformed to a more creative educational system (Rosenberger, 1997, Dixon 1995).
Malaysia has been more conscious about educating persons, but still they have some problems in this field. They have. One could argue that the affirmative actions in favour of the Bumiputras as well as the redistribution of wealth, is defensible if the Bumiputras had been systematically held outside the educational system. But that is not the case. It is more reasonable to believe that there has not been a culture for educating their children within the Malay culture. For a society as a whole it is preferable to let all minority groups to participate in arenas where important premises for the running of the society is laid. That will prevent the inhabitants from having the opportunity to claim discrimination. It is important to give access to education to all ethnic groups because it most often leads to positions in bureaucracy and political life. So when a group is quoted that much into the educational system it could lead other and better students to lose an opportunity to study. So far the Chinese have not argued, but the indirect discrimination against non-Bumiputras could lead to an upraising in the future. In most other societies the equivalents to the non-Bumiputras would have voiced their dissatisfaction about the redistribution and affirmative actions.
The strong reliance on foreign capital before the crisis was characteristic for both the Thai and Malaysian economy. That makes the investment variable is interesting to study. They are still dependent of it, but the question is if and when they will receive the same amount of capital as they were used to. It is also of importance what the capital is spent on. One could think that since the placement of capital were done in non-performing projects, the coming investors would be more critical to what the capital is invested in in the future. It would be reasonable to believe that the projects that will be invested in would pay better off than several of the investments before the crisis. If the economies are to recover hopefully some of the worst examples of investments have to be deleted. That is essential for the economies to revive its confidence, and that is one of the most important factors for getting the economies going again.
The general regression found a negative correlation with growth for governmental consumption. That could be right. But it depends what it is spent on. Barro assumes a negative relation because he thinks that it will only lead to more bureaucracy and corruption. That might be the case for many countries, and could be for Malaysia and Thailand as well. Especially corruption has been documented in Thailand (Rosenberger 1997) and also to some extent in Malaysia. But if the governmental consumption is spent on necessary infrastructure projects it could very well pay off, but what is a necessary project? In Malaysia they have some huge infrastructure projects going on, some they have put on ice for a while due to the crisis. Examples are the longest bridge in the world stretching from Malaysia to Sumatra in Indonesia, a project to reclaim six islands off the sparsely populated Northwest coast and they have projected building an international airport on one of them. But as long as the projects in a cost-benefit analysis of the project will contribute positively, one can defend spending governmental resources on the projects.
Where capital comes from is another issue. Malaysia have managed to have higher domestic saving rates than Thailand, and the Malaysian economy is therefore not that vulnerable as the Thai economy. (Lim, 1997). But both countries have been heavily dependent on FDI so the further growth is to a great extent dependent on how much capital foreigners send into the countries.
The quality of education is of importance, even if it did not contribute that much to the East Asian economies, actually it was negative for these economies. Even if we saw that the pupil/teacher ratio was improving for Malaysia and Thailand, several commentators have given the advise that the educational system needs to be improved if these countries are to climb on the development ladder (see ADO 1998, Rosenberger 1997, Lim 1997). And with the increased wages they need to distinguish themselves from other countries in the region, such as China, Vietnam, Laos, because they offer lower labour costs. The improvement of education is especially important for Thailand, since Malaysia is somewhat better off than Thailand.
As I mentioned in the analysis I do not see how likely it is that any of the two countries will score high on this variable. But if the revolution had been swapped with coups then Thailand might have scored higher. Since there is instability in the economy and it is not that easy to predict which way the economic pendulum/cycles will take, it might lead the military to exploit their military power to do a coup d’êtat if they feel that their position is about to be weakened. We have experienced several coups in Thailand during the decades of growth. But seldom has there been much bloodshed, and seldom anyone have noticed that a coup has been going on. So these coups are fairly peaceful. That is why this has not scared investors from investing in Thailand. And that might be the case later as well, so the investors might not fear the political instability variable.
Having three distinct ethnic groups in the country have not prevented Malaysia from having had a peaceful co-existence for most of the period after independence. But in 1969 there was a riot and the reduction of income inequality was made part of the economic policy, NEP, to prevent new riots for breaking out. ADO(1998:97) points out that the NEP for some time "seemed to succeed in reducing income equality; however, income distribution appears to have worsened since the mid-80s, both between and within ethnic groups, and especially within the Malay group. At the same time regional inequalities seem to be on the rise." When the income differences between the population rise there is a higher risk of people’s unrest. Indonesia is the Asian country experiencing that. When the growth rates were turning up and a majority of the population could reap the profits- of course to a larger or smaller extent- few complained. But when the growth rates turned down, when food became several times more expensive than before, and people were hungry, then the protests from the people appeared. And the pressure must have felt strong for president Suharto since he resigned after being a feared dictator for more than 30 years. In a hypothetical case if Malaysia does not manage to get the economy on the feet again, and confidence in the economy will not increase, the government can face the same kind of protests. And when the inequalities are huge, and some groups have been given more favourable situation, that could make the way for a dangerous uproar. Fong Chan Onn asks rhetorically about this question, "What other country could have three distinct ethnic groups, treat them differently, but still live peacefully side by side?"
What might be more relevant to consider when considering the political situation of these two countries is the credibility the authorities give to the outside world about pursuing a consequent economic policy. Thailand has changed prime ministers several times the last years. In addition the finance minister has been changed 6 times the last year. That has lead to a lack of consequent economic policy. They do make plans, but they do not seem to be followed up seriously.
Malaysia on the other hand have had few changes of important politicians, with only six prime ministers since independence in 1957. During those years they have had seven strategic plans for development of the economy. The two most important being the New Economic Policy (NEP) in 1971 and the Vision 2020 from 1991.
With the strong depreciation of the baht and ringgit, this has lead to deviations of the prices in exports in relation to imports, and we could expect a terms of trade shock. In January 1998 the value of the baht against dollar had fallen with about 54%, and the ringgit’s value had fallen with 40%. Following the reasoning of Barro and Sala-I-Martin we would think that this will lead to less spending in Thailand and Malaysia, and with the reduction in demand that will affect the industry and economy.
The first aspect that I find meaningful to point at in the conclusion, is the role of the explanatory variables. Since such a variety of aspects has been covered through the seven variables, the variables explain the growth well. The question is to what extent the estimated weights can explain the importance of the particular variables specifically for Malaysia and Thailand. That has been discussed in the analysis, and we have seen that the estimated values only to a limited extent manage to explain Malaysia and Thailand’s growth.
The second point is to what extent the findings in the analysis support the economic growth theories. The researchers point of departure is the neo-classical theories, where the convergence effect is central. For East Asia’s part this effect starts out with contributing to explanation of the growth with 75%. But it is reduced to 48% in the second decade, and only 20% is explained with the conditional convergence effect in the 1985-95 period. Since this effect is so central in the theory, it is reasonable to question the power of this theory to explain the empirically-based regression estimates. We have also seen that the fit between actual and estimated growth rates has declined in the East Asia regression (figure 11). The figures are somewhat better in the fit made specifically for the East Asian fast growers (figure 12). These premisis leads me to pick up the thread from the introduction: Is it possible to develop theories that capture all aspect of development in all countries throughout the world? If the answer is yes, we have reached a universialistic theory. That was the aim of this regression. But we have seen that it has not succeeded in doing that well enough. So the neo-classical theory is not verified with these empirical evidence. In societal questions like this it is very difficult to find clear causal connections. We might never be able to do that. The way a society works is very complex. Causal connections do not always go in one direction, effects might work backwards as well. As we have seen it is difficult to estimate exact weights for all variables. There are too many conditions that need to be taken care of. So making the society into a model or a theory is a difficult process. Perhaps is it not possible to capture the whole societal picture.
In this essay I have not tried to discuss how well the empirical findings coinside with the institutionalistic theories. Therefore I do not intend to draw any conclusions that verifies or falsifies this theory. Neither have I explisitly discussed the cultural explanation, and therefore I can not draw any conclusions about its explanatory power.
The final comment is in a more wider development perspective. I have
discussed what determines growth in Gross Domestic Product. But I have
not discussed other measures of development, measures taken from other
disciplines than the economic sector. In the transition process from a
developing to a developed nation, many other contextual obstacles need
to be forced. I will have to leave those questions to other researchers.
But I hope this essay have managed to give a picture of the driving forces
of the economic growth in Malaysia and Thailand up till last year. I also
hope that the outline of the Asian crisis gave an insight into the problems
that might strike developing economies in the transition process. And I
hope the questions I have asked have made the reader want to make a further
inquiery to see if there actually has been a miracle in East Asia.
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