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Comparative Study of Malaysia Human Capital with Selected ASEAN and Developed Countries: a Fuzzy TOPSIS Method

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Comparative Study of Malaysia Human Capital with Selected ASEAN and Developed Countries: a Fuzzy TOPSIS Method View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by UKM Journal Article Repository GEOGRAFIA Online TM Malaysia Journal of Society and Space 11 issue 6 (11 - 22) 11 © 2015, ISSN 2180-2491 Comparative study of Malaysia human capital with selected ASEAN and Developed Countries: A fuzzy TOPSIS method Lai Wei Sieng 1, Ishak Yussof 1 1School of Economic, Faculty Economics and Management, Universiti Kebangsaan Malaysia Correspondence: Ishak Yussof (email: [email protected]) Abstract Comparative study on human capital performance between countries is important especially for developing countries to measure their gap with developed countries. This article uses the unconventional TOPSIS method to compare Malaysia and other selected countries in terms of human capital achievement with education being the main measure of human capital. Results indicate that Malaysia is doing great among her ASEAN peers but more need to be done in order to catch up with the developed nations. Keywords : developed countries, developing countries, economic growth, fuzzy TOPSIS, human capital, Human Development Index Introduction Human capital has become the main focus in explaining economic growth of a country since the emergence of the endogenous growth theory introduced by Uzawa (1965), Lucas (1988) and Romer (1990). As evidences confirmed the positive relationship between human capital development and economic growth, human capital development has become one of the key factors in deciding fund allocation in a country’s development plan. Malaysian government is committed in enhancing human capital with 20% to 25% of total government expenditures spent on education. In 1990, an economist from Pakistan, Mahbub ul Haq created Human Development Index (HDI), which is a composite statistic of life expectancy, education, and income indices to rank countries into four tiers of human development with an explicit purpose, "to shift the focus of development economics from national income accounting to people-centered policies". It was then followed by economist Amartya Sen in 1990, published by the United Nations Development Programme. HDI is now used as the indicator to a country’s human capital development achievement. Malaysia ranked 64 among 186 countries in 2013 HDI report with a score of 0.769 and was categorized in the group of countries with high human development. Compared to other ASEAN countries, Malaysia’s HDI rank is the third highest as shown in Table 1. Brunei and Singapore were categorized in the “very high human development” group whereas the rest were “medium human development” except for Myanmar, which was in the “low human development” group. GEOGRAFIA Online TM Malaysia Journal of Society and Space 11 issue 6 (11 - 22) 12 © 2015, ISSN 2180-2491 Table 1. HDI report for ASEAN countries, 2011 Country HDI Rank HDI value Singapore 18 0.895 Brunei 30 0.855 Malaysia 64 0.769 Thailand 103 0.690 Philippines 114 0.654 Indonesia 121 0.629 Vietnam 127 0.617 Cambodia 138 0.543 Laos 138 0.543 Myanmar 149 0.498 Source : UNDP Human Development Report 2013 Another similar official report, The Human Capital Report was published by World Economic Forum in 2013. The report ranked 122 countries according to Human Capital Index (HDI). The index contained 51 indicators in total, consisting of four pillars, with 12 indicators in the Education pillar, 14 in the Health and Wellness pillar, 16 in the Workforce and Employment pillar and 9 in the Enabling Environment pillar. Brunei and Myanmar were not included in the report and the ranking reported for ASEAN countries was almost identical to UNDP’s report, and Malaysia was still behind Singapore as shown in Table 2. Table 2. Human Capital Report for ASEAN countries, 2013 Country HCI Rank HCI value Singapore 3 1.232 Malaysia 22 0.644 Thailand 44 0.158 Indonesia 53 0.001 Philippines 66 -0.161 Vietnam 70 -0.202 Laos 80 -0.297 Cambodia 96 -0.505 Source : World Economic Forum, The Human Capital Report 2013 According to the two published reports, even though those indices were calculated using different formulae, the ranking of most of the ASEAN countries remained the same. However, the indices could not measure the relative performance for each country in human capital development, and thus could not be a suitable tool to measure the gap between countries. The objective of this article is to compare the performance of Malaysia in terms of human capital development with selected ASEAN countries of Singapore, Thailand, Philippines, Indonesia and Vietnam, and with selected developed countries:, namely, United States, Australia, Japan, United Kingdom, Italy, and France. The most important goal of this article is to measure the gap between Malaysia as a developing country and developed countries. An unconventional method is applied to realize the objective of this study. Literature review Since the emergence of endogenous growth theory, various studies had investigated the relationship between human capital and economic growth. Most of them had found positive relationship between human capital’s variables and economic growth. Middendolf (2006), Park (2006), Altar et al. (2008), Yueliang (2009), Soukiazis and Antunes (2012) and Roseline and Esman (2012) are among the GEOGRAFIA Online TM Malaysia Journal of Society and Space 11 issue 6 (11 - 22) 13 © 2015, ISSN 2180-2491 researchers who confirmed the impact of human capital on economic growth at various countries. Despite numerous evidences found, there are very few studies conducted to compare the performance of different countries in terms of human capital. Many of the studies on this topic utilized the econometric methods. Neycheva (2010) examines the impact of education on growth in the EU members and makes comparison with post-communist economies. Lee at al. (1994) compares the relationship between education, human capital enhancement and economic development in South Korea and Taiwan. Bhatta and Lobo (2000) analyze the extent to which human capital differences can explain the differences in gross state product per capita levels between the richer and poorer states of the US. Musai et al. (2011) study information relating to Iran and 78 other countries to determine the relationship between education and economic growth. Moses (2006) identifies the two-way links between human resource development produced by formal schooling and economic growth, and between investment in physical capital and growth of African countries. There had also been comparisons between countries in terms of the role of human capital on economic growth. For example, the comparison between China and India (Andreosso, 2003). Nadir and Hatidje (2007) constructed human capital index for 105 countries. They gathered international surveys analyzing children’s learning achievement on a common scale in order to allow an international comparison of children’s learning achievement across countries. The ranking of each country’s index calculated was almost the same as Human Development Index and Human Capital Index. All in all, there were very few studies that actually compared the human capital development among countries. As past studies on comparing human capital of Malaysia and other countries are hardly found, this article aims to fill the reference gap. Data and methodology Based on previous studies, the variables of human capital in growth used in this study are labor force, school enrolment rate and adult mean years of schooling. This study employs the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method which is developed by Hwang and Yoon (1981). TOPSIS is commonly applied in management science but scarcely being applied in the field of economics. One of the few studies which applied TOPSIS method in economics is the study done by Karimi et al. (2010). They applied TOPSIS to examine the location decision for foreign direct investment in ASEAN countries. Sait (2011) applied TOPSIS and WSA (Weighted Sum Approach) in analysis of economic activities of European Union Member States and candidate countries. In fact, this method is a suitable tool in comparing human capital factor among countries; and is, therefore applied in this study. The concept behind this method is that the selected best alternative should have the shortest distance from the ideal solution and the farthest distance from the negative-ideal solution in the geometrical (Euclidean) sense. In other words, the ideal alternative has the best level of all attributes considered, whereas the negative ideal is the one with the worst attribute value. A TOPSIS solution is defined as the alternative that is simultaneous, farthest from the negative-ideal and closest to the ideal alternative. There are two main advantages in this method: its mathematical simplicity and high flexibility in the definition of the choice set. Chia and Liang (2009) listed three advantages of TOPSIS: simple, rationally comprehensible concept, good computational efficiency, and ability to measure the relative performance for each alternative in simple mathematical form. GEOGRAFIA Online TM Malaysia Journal of Society and Space 11 issue 6 (11 - 22) 14 © 2015, ISSN 2180-2491 The TOPSIS method evaluates the following decision matrix (A) for this study: Where is the ith alternative (Malaysia, Indonesia, Thailand, Philippines, Vietnam, Australia, France, Italy, Japan, United Kingdom and United States), is the jth criterion (enrolment rate in primary, secondary and tertiary education, adult mean years of schooling, and labor participation rate), and is the performance measure of the ith alternative in terms of jth criterion. The TOPSIS method consists of the following steps (which are adaptions of the corresponding steps of the ELECTRE method). Step 1: Calculate the weights of the evaluation criteria. To find the relative normalized weight of each criterion, first of all, the geometric mean of ith row in the pair-wise comparison matrix is calculated by Then, geometric means of the rows in the comparison matrix are normalized as: Where is the weight or the importance of criterion , =1 and W = be the criteria weight vector.
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