The Effect of Economic Growth and Human Development Index on Poverty in Indonesia

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1. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. THE EFFECT OF ECONOMIC GROWTH AND HUMAN DEVELOPMENT INDEX ON POVERTY IN INDONESIA 1 Zulfikar Hasan 1 + Department Syariah and Economics Academy of Islamic Studies, University Malaya + Corresponding author: zulfikarhasan61@gmail.com Abstract Indonesia’s economic growth, which ranges from 5% - 6% per year, apparently has not been able to reduce the number of poor people. There has even been an increase in the total of poor people, which is currently around 37 million people. A World Bank study shows that almost 50% of Indonesia’s population is categorised as “poor” and “on the verge of poverty”. The problem of poverty deserves significant attention from all parties. Economic growth accompanied by an increase in the number of poor people is certainly inviting several questions, such as who is enjoying the economic growth and whether the economic growth is caused by increased productivity or the use of factors of production, etc. In Indonesia, economic growth seems to be concentrated in specific sectors, while some other areas have relatively slow growth that poverty reduction is difficult. Hence, research on economic growth, human development, and poverty levels in Indonesia is warranted. The results are expected to explain the phenomenon of increasing poverty in Indonesia. Keywords. Economic growth, Human development index, Poverty. JEL Codes. O40, O15, I30. Received 8 Jun 20. Revised 16 July 20. Accepted 27 July 20. Introduction Economic growth is one of the indicators of successful development. Economic growth and income redistribution presumably could reduce poverty levels (Kakwani & Son, 2003), according to the trickle-down effect theory, which was first developed by Lewis (1954) and extended by Ranis and Fei (1961). The goal of poverty reduction is one of the critical topics in the economic development of developing countries (Least Develop Countries / LDCs) in the 1950s and 1960s. The trickle-down effect theory proposes that the progress of a group of people will automatically trickle down to create jobs and various economic opportunities, which in turn will foster multiple conditions for the creation of equitable distribution as a result of economic growth. The theory implies that economic growth will be followed by a vertical flow from the rich to the poor, which naturally occurs. The benefits of economic growth will be felt by the rich first, and then in the next stage, the poor will begin to benefit when the rich begin to spend the results of the economic growth received. Thus, poverty reduction is an indirect effect of the vertical flow from the rich to the poor. This also means that poverty will decrease on a tiny scale if the sparse population receives only a little benefit from the total benefits arising from economic growth. This condition can open opportunities for increasing poverty as a result of the growing income inequality caused by economic growth. Poverty is a multi-dimensional and cross-sectoral problem influenced by many related factors, such as the income level, health, education, access to goods and services, location, geographical, gender, and environmental conditions. Poverty indicates the condition of individuals, groups, and the prevailing situation of the community. Severe mass poverty is 42
2. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. found in developing countries, but there is evidence that poverty also occurs in developed countries. In developing countries, poverty is structural. For example, it occurs because of an unfair economic system, the practice of KKN (Corruption, Collusion, and Nepotism), social discrimination, lack of social security, etc. The Indonesian government envisions just and prosperous society as an outcome of its national development agenda. Thus, initiatives have been directed towards regional development, especially regions that are relatively poor and where poverty rates continue to rise annually. Local development programs are carried out in an integrated and sustainable manner according to the priorities and needs of each region with roots and targets established through long-term and short-term development plans. Therefore, one of the leading indicators of the success of national development is the rate of decline in the number of poor people. The debate about the signs of socio-economic development is fierce. Economic and noneconomic circles argue that per capita income as an indicator of progress is not valid and suggest new indicators relevant to measure human development. Morris (1979) built the Physical Quality of Life Index (PQLI), while the United Nations Development Program (UNDP) built the Human Development Index (HDI) or Human Development Index (HDI) based on the foundation established by Haq (1996), which is now widely used. According to the Central Statistics Agency (BPS), inequality in human development in Indonesia is measured by the human development index (HDI). This index reflects the quality of human capital as measured by such indicators like the level of education, health, and people’s purchasing power. Based on the HDI, human development gaps between the western regions (IBB) and eastern regions (IBT) are evident. Ten provinces in the IBT regions score the lowest. These provinces are the Province Papua, West Nusa Tenggara, East Nusa Tenggara, West Papua, West Kalimantan, North Maluku, West Sulawesi, South Kalimantan, Southeast Sulawesi, and Gorontalo. The provinces from the IBB region occupy moderate to high positions, such as DKI Jakarta, Riau, Yogyakarta, and Riau Islands. Only a few provinces in the IBT are classified as provinces with high HDI, namely North Sulawesi, East Kalimantan and Central Kalimantan. In essence, those classified as HDI are dominated by provinces from the IBB region. Local governments in Indonesia as policymakers have an important role in allocating resources as regional development inputs, especially after the enactment of Law No. 22 of 1999, which was revised to Law No. 32 of 2004 concerning Regional Autonomy. In this law, regional development policies are submitted to each local government, and the central government acts as a supervisor or policy controller. Some regions aim for economic growth as their strategic goal. In contrast, other areas pay relatively more significant attention to policies relating to social facilities and improving the quality of human development. The diversity of resources, capabilities, needs, and potential in each region affects the development strategies undertaken by local governments. Inappropriate policy formulation can reduce the efficiency and effectiveness of the prepared policy program of the regional government. Literature Review Economic growth essentially is a process of increasing output per capita in the long run, and this understanding emphasises three things, namely process, production per capita, and long term. The method of describing economic development over time is more dynamic; per capita output links the aspects of total output (GDP) and elements of the population so that the long 43
3. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. term shows the tendency of changes in the economy in a certain period driven by the process internal economy (self-generating). Economic growth is also interpreted simply as an increase in total output (GDP) in the long run regardless of whether the rise is smaller or more significant than the rate of population growth, and whether it is followed by economic growth structure. High economic growth and sustainable processes are the main conditions for the continuity of economic development (Tambunan, 2001). Economic growth shows the extent to which economic activity will generate additional community income in a given period. In other words, the economy is said to experience growth if the real income of the people in a given year is higher than the real income of the community in the previous year. In macro-economic terms, economic growth is the addition of Gross Domestic Product (GDP), which means an increase in the National Income. Economic growth is the basis for sustainable development. Governments can improve the welfare of the community by increasing economic growth by improving infrastructure for, education and health services, building facilities to encourage foreign and local investment, providing low-cost housing, carrying out environmental restoration, and strengthening the agricultural sector (Saad, 2009). Regional economic growth theory is an integral part of the regional economic analysis because growth is one of the main elements in regional economic development and has broad policy implications. High human development affects the process of economic growth, and vice versa, high economic growth affects the quality of social development. However, high human development is not necessarily accompanied by high economic growth and vice versa. The Human Development Index is a measure to see the impact of regional development performance which has a dimension comprehensive because it shows the quality of the population of an area in terms of life expectancy, education, and a decent standard of living. The Human Development Index is a composite index calculated as an average of three indices that illustrate the essential ability of humans to expand choices, namely the life expectancy index, education index, and standard of living standards. There are various theories about poverty. The World Bank describes poverty by adopting standards ability/purchasing power, which is USD 1 or the USD 2 per capita per day. Meanwhile, BPS defines poverty based on the principles of poverty. The poverty policy value applied to determine debt refers to the minimum qualification needed by someone who needs 2100 calories per capita per day, coupled with the non-eating minimum requirement, which is a person’s basic needs that involve clothing, school, transportation, immunotoxins needs of households, and individuals underlying it. According to BPS, a person/individual whose expenditure is lower than the Poverty Line is said to be defeated. While poverty, according to National Human Development Report (2004), is a condition where a person or group of women and men are incapable of fulfilling their fundamental rights to support and improve a severe life. These fundamental human rights include: meeting the needs of food, clothing, health, education, workers, extinction, clean water, land, natural resources and the environment, and insight of security from the strategy of intimidation of violence and the right to strive in life social statesmanship. Education is one of the most important pillars that significantly influence the progress of a country. Imagine an advanced education country where intelligent people manage the country wisely. On the contrary, if education is not considered, the country will collapse. Because of 44
4. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. poverty, the country will experience a high dropout rate. Poverty becomes a national threat, whether physical or financial. Poor health and nutrition are elements of the human development index. Health is a fundamental necessity for the community to be capable and prosperous. The health aspect is crucial to determine the standard of living of the people. Accordingly, the health sector needs proper consideration to enhance the quality of human resources. Therefore, health development is an indispensable element of the national development process and human resources. To accomplish this, what must be done is the provision of adequate health facilities – for instance, the construction of hospitals extended to remote areas even in unreached terrain – because this will significantly affect the level of public health—construction of hospitals that extended to remote areas even on unreached terrain. Factors that cause poverty include a low level of education, a low level of health, limited job opportunities, and the conditions of isolation. The World Bank (2004) reported five factors that influence the occurrence of poverty, namely education, type of work, gender, access to essential health services and infrastructure, and geographical location. Poverty is always associated with disability in achieving higher education, and this is related to the high education costs, even though the Indonesian government has issued a policy to waive fees at the elementary school and junior high school level. Other components of education costs that must be incurred are still quite high, such as book fees and school uniforms. Prices that must be paid by poor people to send their children to school must also include the cost of loss of income (opportunity cost) if their child works. Poverty is also always associated with the type of work. In Indonesia, debt is always related to the employment sector in agriculture for rural areas and the informal sector in urban areas. In 2004, 68.7 per cent of the 36.10 million poor people lived in rural areas, and 60 per cent of them had significant activities in the agricultural sector. Chaudhuri, Jalan, and Suryahadi (2002) found that between 1984 and 2002, both in rural and urban areas, the agricultural sector is a significant cause of poverty. They also found that the farm sector accounted for more than 50 per cent of extreme poverty in Indonesia, which is in direct contrast to the service sector and industry. That is, poverty is high among household heads who work in the agricultural sector because of a high level of debt compared to a low level of debt of those who in other industries. The relationship between poverty and gender in Indonesia is clearly felt, namely from several indicators of poverty, such as illiteracy, unemployment, informal employment, and others. The female population has a more unfavourable position than the male population. The relationship between poverty and a lack of access to various essential infrastructure services and a sound infrastructure system will, directly and indirectly, increase the income of the poor through the provision of health services, education, transportation, telecommunications, better access to energy, water, and sanitation conditions. Geographical location is also related to poverty for two reasons: (a) the measured natural conditions in the potential for soil fertility and natural wealth, and (b) equitable development, between rural and urban or inter-provincial development in Indonesia. The geographical location also exacerbates the already low achievement in education and hinders access for essential services in various regions, especially in the eastern region of Indonesia. 45
5. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. The poverty level of a country is also closely related to the dynamics of its economy, both due to the changes in its economic structure and the differences in the level of economic growth at the sectoral and regional level. Ravallion and Datt (1999) conducted a study on the effect of the composition of sectoral economic growth and the initial conditions of a region on reducing poverty. Similarly, Bigsten and Levin (2004) assert the importance of paying attention to intersectoral dynamics in developing strategies to reduce poverty. Hoeven (2004) observed a link between changes in economic structure in a country and the inequality of income and poverty. Meanwhile, Huppi and Ravallion (1990), who examined the structure of sectoral poverty in the adjustment period in Indonesia in the mid-1980s, found that although overall poverty rates had decreased, the effect was not evenly distributed across regional and sectoral areas where significant poverty reduction mainly occurs in the rural farming sector. Datt and Ravallion (2002) found the differences in poverty levels among several regions in India. Areas, where agricultural development and human capital are low, are relatively unresponsive to economic growth and poverty reduction. Meanwhile, Friedman (2002), who conducted a study on the response of poverty to economic growth in Indonesia, found a long reply. However, regional differences in poverty levels persist despite measures to control income levels at the provincial level. It appears that local factors play an essential role in poverty levels in an area. In another research, Siregar and Wahyuniarti (2008) found that industrial and agricultural sector contributions could reduce the number of poor people in Indonesia. They further found that the impact of the gift of the industrial area on reducing poverty was 2.6 times greater than the effects of the contribution of the agricultural sector, which indicates that industrialisation carried out appropriately could be an effective alternative in poverty alleviation. Also, the education variable was found to have a negative and significant influence and relatively a substantial effect on reducing the number of poor people. Rose et al. (2013) found that poverty in Pakistan is more influenced by growth rates in the industrial sector than growth in the agricultural industry. This happens because of the ability of the industrial sector to absorb unskilled labour. The agricultural sector still provides benefits for poverty reduction, but the effect is no longer significant. Meanwhile, the growth of the service sector leads to an increase in poverty because this sector does not absorb unskilled labour. Berardi and Marzo (2015) showed that the sector that has more influence on poverty in Africa is a sector that is pro-poor potential. An example of the industry in question is the agricultural sector where the increase in the agricultural sector will increase the areas of goods and services, thereby increasing the demand for labour, which will ultimately improve the welfare of the community. If growth is concentrated in industries that do not favour the potentials of the poor, then it needs to be compensated with distributed policies. Hasan and Quibria (2002) found a strong relationship between growth and poverty in Western Asia. The growth of the industrial sector mainly drives this relationship. This contrasts with what happened in Latin America, Southern Asia, and Sub-Saharan Africa, where the agricultural sector is the most dominant. In poverty reduction, efforts to improve policies and institutions are urgently needed to take advantage of the comparative advantage in labour-intensive industries to reduce poverty. Economic growth does not automatically alleviate poverty, and there is often a trade-off between economic growth and scarcity. Ahluwalia (2013) states that economic growth is accompanied by increasing inequality. However, the income of the sparse population also increases, although at a slower rate than the average increase in revenue. Economic growth is needed to reduce poverty, so economic growth is the initial goal. If poverty alleviation is prioritised, that economic growth will be relatively low. In this case, policies need to be developed to achieve economic growth to reduce the number of poor people. Such a policy is 46
6. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. or often called pro-poor growth. Bigsten and Levin (2000) state that a pro-poor growth strategy does not only focus on economic growth but must also combine with income distribution policies. But there are trade-offs. If poverty reduction can be achieved through improved income distribution, then income distribution policies are prioritised. Conversely, if high economic growth to reduce poverty can be achieved through greater inequality in income distribution, then there is tolerance for income distribution. At present, various efforts are being made to overcome poverty in Indonesia. Economic growth is not qualified because it cannot reduce poverty. However, there is a lack of directional analysis in which economic growth is always decomposed in terms of expenditure, namely how much growth in consumption, investment, government spending, and export-import. Meanwhile, poverty still is seen in the regional context, at the provincial or district/city level. Some institutions also begin to build a macro model by including poverty as a variable without first decomposing the amount of poverty. By using the sectoral approach where economic growth and scarcity are decomposed based on the sector side, this study expects to get an answer on the phenomenon of the magnitude of Indonesia’s poverty level amid relatively high economic growth. Research Methodology This study uses quantitative methods. The data used in this research came for 34 provinces in Indonesia from 2010-2019. The data collected include data on economic growth, human development index, and poverty. The data were obtained from the Indonesian Central Bureau of Statistics. The data were analysed by descriptive analysis and multiple linear regression. In the descriptive study, inequality conditions can be described as real conditions. The analysis of multiple linear regression aims to determine the effect of economic growth and human development index on poverty in Indonesia by using the following formula: Y = a + b1.X1 + b2.X2 + e where : Y = Poverty X1 = Economic Growth X2 = Human Development Index (1) Limitations of Research This research is limited to the effect of economic growth and human development index on poverty in Indonesia from 2020-2018. Poverty alleviation is influenced by many factors. However, this research focuses on economic growth and human development index. The data were taken from the Central Statistics Agency (BPS). Results Poverty rates in Indonesia have tended to decline in the last 21 years. In 1998, the poverty rate reached 24.2%, which continued to fall to only one digit in 2019. The percentage of poor people in September 2019 was 9.22%. This figure decreased by 0.19% compared to March 2019 and 0.44% compared to September 2018. The percentage of poor people in rural areas is more significant than in urban areas with 12.6% and 6.56%, respectively (Read: March Poverty Rate 2019 The Lowest Since 1998), The number of poor people in September 2019 reached 24.79 million people. This figure decreased compared to the March 2019 figure, which amounted to 358.9 thousand and September 2018, which amounted to 888.7 thousand. The number of poor people in urban areas is 9.86 million, while in rural areas 14.93 million. 47
7. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. Poverty Level 25 20 19.1418.41 18.2 15 17.75 17.4216.66 16.58 15.97 15.42 14.1513.33 12.3611.6611.47 10.9611.13 10.7 10 10.12 9.66 9.22 5 0 20002001200220032004200520062007200820092010201120122013201420152016201720182019 Figure 1. Poverty rates in Indonesia 2000-2019 (Data from the Central Statistics Agency of the Republic of Indonesia) Economic Growth 7 6 5 4 4.92 4.5 5.69 5.5 5.03 4.78 6.35 6.01 6.226.176.03 5.56 5.02 5.025.075.065.02 4.79 4.63 3.64 3 Economic Growth 2 1 0 Figure 2. Indonesia’s Economic Growth 2000-2019 (Data from the Central Statistics Agency of the Republic of Indonesia) Figure 2 shows that Indonesia’s economic growth in the period 2000-2018 experienced changes from year to year due to domestic politics which had a significant impact on financial decision making. In 2009, the world monetary crisis had a massive impact on the world economic sector, which had a significant impact on Indonesia and other countries that were working hard to get out of the red zone of the global financial crisis. Indonesia developed several policies and stimulus to the economic sector, such as reducing conventional bank loan interest and using domestic products. In 2010, the economic growth in Indonesia was above the world industrial average, which was 6.22% because of the government policy in issuing policies and accelerating national infrastructure development. Table 1 shows that the Indonesian Human Development Index from year to year has slightly improved because of the government effort to enhance several related sectors, such as the economy and education. When many Indonesians have the right education level, economic 48
8. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. growth is likely to increase because the growth opens up jobs that require skilled human resources. In 2019, the Indonesian Human Development Index was the highest when compared to the previous years, which was 71.92. 2000 Table 1. Human Develompent Index in Indonesia 2000-2019 2001 2002 2003 2004 2005 2006 2007 2008 67.7 2010 64.3 2011 65.8 2012 68.7 2013 69.57 2014 70.1 2015 2009 70.59 71.17 71.76 72.27 2016 2017 2018 2019 72.27 72.77 73.29 73.81 68.90 69.55 70.18 70.81 71.39 71.92 Source: Central Statistics Agency, Republic of Indonesia. Table 2 shows that the poverty variable has the lowest value of 9.220 and the highest value of 13.330 with an average value of 11.06100 and its standard deviation (level of data distribution) of 1.235794. The economic growth variable has the lowest value of 4.790 and the highest value of 6.220 with an average value of 5.39600 and the level of data distribution of 0.549489. The human development index variable has the lowest value of 66.53 and the highest value of 71.92 with an average value of 69.2380 and the level of data distribution of 1.84295. Table 2. Minimum Descriptive Statistics, Maximum, Mean and Standard Deviation N Minimum Maximum Mean Std. Deviation Poverty in Indonesia 10 9.220 13.330 11.06100 1.235794 Economic Growth 10 4.790 6.220 5.39600 .549489 Human Development Index 10 66.53 71.92 69.2380 1.84295 Valid N (listwise) 10 Bivariate Pearson Correlation Analysis Various ways can be used to guide decision making in Pearson’s bivariate correlation analysis, namely by looking at the significance value of Sig. (2-tailed) and comparing the calculated rvalue (Pearson correlations) with the r-value of the product-moment table (critical value). Also, one needs to look at the asterisk (*) contained in the SPSS program output. Table 3. Correlations Poverty in Economic Indonesia Growth Poverty in Indonesia Economic Growth Human Development Index Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) Human Development Index 1 .806** -.973** 10 .005 10 .000 10 .806** 1 -.843** .005 10 10 .002 10 -.973** -.843** 1 .000 .002 49
9. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. N 10 **. Correlation is significant at the 0.01 level (2-tailed). 10 10 Based on the output above, three conclusions can be drawn to make decisions: 1. The significant value of Sig (2-tailed) of the link between economic growth (X1) and poverty (Y) is 0.005 < 0.05, which means that there is a significant correlation between the economic growth variable and the poverty variable. Furthermore, the human development index (X2) with poverty (Y) is 0.000 < 0.05, so, there is a significant correlation between the variables of the human development index and poverty. 2. Based on the calculated r-value (Pearson correlations), the value of r calculated in the relationship between economic growth (X1) and poverty (Y) is 0.806 > critical value of 0.632. So, it can be concluded that there is a relationship between the variables X1 and Y. Furthermore, the r-value of the human development index (X2) and poverty (Y) is -0.973 < critical value of 0.632. It can be concluded that there is no correlation between the X2 and Y variable. Multiple Linear Regression Analysis A series of standard assumption tests were run to check the following requirements or assumptions before performing the analysis: test for normality, linearity test, multicollinearity test, heteroscedasticity test, and autocorrelation test. Table 4 presents the estimated multiple regression model. Table 4. Multiple Linear Regression model Variable Regression Coefficient t-scores Sig. Constanta 58.860 Economic Growth (X1) -.114 -.318 .760 Human Development Index (X2) -.681 -.6.358 .000 Normality test for each variable The normality test was implemented with the following criteria: if the significance value (Sig.) is <0.05, then the variable is not normally distributed. If the significance value (Sig.) is > 0.05, then the variable is normally distributed. Tabel 5. Tests of Normality Kolmogorov-Smirnova Statistic df Sig. Shapiro-Wilk Statistic df Sig. Poverty in Indonesia .114 10 .200* .984 10 .983 Economic Growth .324 10 .004 .808 10 .018 .103 10 .200* .964 10 .833 Human Development Index *. This is a lower bound of the true significance. a. Lilliefors Significance Correction 50
10. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. Based on the test of normality above, the Sig. in the Shapiro-Wilk normality test is known, as follows: 1. The value of poverty Sig. is 0.983 (> 0.05; the poverty variable is normally distributed). 2. The value of economic growth Sig. is 0.018 (> 0.05; the poverty variable is normally distributed) 3. The value of the human development index Sig. is 0.833 (<0.05; the human development index variable is not normally distributed). Research Hypothesis: Partial Correlation Test The hypothesis for the test is: H0: the relationship between X1 and X2 with Y as control variables is not significant Ha: The relationship between X1 and X2 with Y as a substantial control variable The basis for decision making in the partial correlation test using Sig. (2-tailed) is as follows: 1. If the significance value (2-tailed) is > 0.05, then H0 is accepted and Ha rejected 2. If the significance value (2-tailed) is <0.05, then H0 is rejected and Ha accepted From Table 6, the value of correlation is -0,843 (negative) and verification (2-tailed) is 0.002 < 0.05. It is concluded that there is a negative and significant relationship between X1 and X2 without the control variable (poverty). The negative relationship between X1 and X2, without controlling the effect of poverty, is -0.843. Once the effect of poverty is controlled, there has been an increase in the relationship to -0,432, with Sig (2-tailed) value of 0.246 > 0.05. Then H0 is not rejected. This means that the relationship between X1 and X2 with Y as a control variable, turns into insignificant. Table 6. Correlations Control Variables -none-a Economic Growth Correlation Significance (2-tailed) df Human Correlation Development Index Significance (2-tailed) df Poverty in Indonesia Correlation Significance (2-tailed) df Poverty in Economic Growth Correlation Indonesia Significance (2-tailed) df Human Correlation Development Index Significance (2-tailed) df a. Cells contain zero-order (Pearson) correlations. 51 Human Economic Development Growth Index 1.000 -.843 Poverty in Indonesia .806 . .002 .005 0 -.843 8 1.000 8 -.973 .002 . .000 8 .806 0 -.973 8 1.000 .005 .000 . 8 1.000 8 -.432 0 . .246 0 -.432 7 1.000 .246 . 7 0
11. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. Conclusion The result of the effect of economic growth and human development index on poverty in Indonesia can be summarised as follows: (a) there is a significant correlation between the economic growth variable and the poverty variable, (b) there is a significant correlation between the variables of the human development index and poverty, (c) Human development index has a negative and significant effect on poverty. The results explain the phenomenon of increasing poverty in Indonesia. In Indonesia, economic growth seems to be concentrated in specific sectors, while some other areas have relatively slow growth that poverty reduction is difficult. Huma development index could further deteriorate the poverty. 52
12. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. References Ahluwalia. (2013). Pertumbuhan Ekonomi dan Pemerataan. In Ahluwalia, Pertumbuhan Ekonomi dan Pemerataan (pp. 42-52). Jakarta: Universitas Pamulang. Berardi, N. & Marzo, F. (2015). The Elasticity of Poverty with Respect to Sectoral Growth in Africa. Banque de France Working Paper No. 538, Available at SSRN: http://dx.doi.org/10.2139/ssrn.2564105 Bigsten, A. & Levin, J. (2004). Growth, Income Distribution, and Poverty: A Review in Growth, Inequality, and Poverty: Prospects for Pro-poor Economic Development Anthony Shorrocks and Rolph van der Hoeven. Oxford: Oxford University Press. Chaudhuri, S., Jalan, J. & Suryahadi, A. (2002). Assessing Household Vulnerability to Poverty from Cross-Sectional Data: A Methodology and Estimates from Indonesia. Department of Economics Discussion Papers 0102-52, Columbia University. Datt, G. & Ravallion, M. (2002). Is India’s economic growth leaving the poor behind? Journal of Economic Perspectives, 16(3), 89-108. Friedman, J. (2002). How Responsive is Poverty to Growth ? A Regional Analysis of Poverty, Inequality, and Growth in Indonesia. RAND, 1984-1999. Hasan, R. & Quibria, M.G. (2002). Poverty and Patterns of Growth. ERD Working Paper No. 18, Asian Development Bank, Philippines. Haq, M. U. (1996). Reflections on Human Development. New York: Oxford University Press. Hoeven, R. (2004). Poverty and Structural Adjustment: Some Remarks on Trade off Between Equity and Growth. ILO Employment Paper 4. International Labor Organization. Huppi, M. & Ravallion, M. (1990). The sectoral structure of poverty during an adjustment period: evidence from Indonesia in the Mid-1980s. World Bank Working Paper 529, Washington. Kakwani, N. & Son, H.H. (2003). Pro-poor Growth: Concepts and Measurement with Country Case Studies. The Pakistan Development Review, 42(4), 417-444. Lewis, W. (1954). Economic Development with Unlimited Supplies of Labour. The Manchester School of Economic and Social Studies, 22(2), 139-191. Morris, M. D. (1979). Measuring the Condition of the World’s Poor: The Physical Quality of Life Index. London: Frank Crass. National Human Development Report (2014). The Economics of Democracy: Financing Human Development in Indonesia. National Human Development Report 2014, BPSStatistics Indonesia, Bappenas and UNDP Indonesia. Ranis, G. & Fei, J. (1961). A Theory of Economic Development. American Economic Review, 51, 533-565. Ravallion, M. & Datt, G. (1999). When is growth pro-poor? Evidence from the diverse experiences of India’s states. Policy Research Working Paper Series No 2263, The World Bank. https://EconPapers.repec.org/RePEc:wbk:wbrwps:2263. Rose, S., Abbas, S., Ali, M.F., & Azeem, M.M. (2013). Growth-poverty linkages: does sectoral composition matter for Pakistan? World Applied Science Journal, 21(6), 915-919. Saad, W. (2009). The nature of government expenditure and its impact on sustainable economic growth. Middle Eastern Finance and Economics, 1-12. Siregar, H. & Wahyuniarti, D. (2008). Dampak Pertumbuhan Ekonomi Terhadap Penurunan Jumlah Pendduk Miskin. Online paper http://deptan.go.id 53
13. Journal of Economics and Sustainability (JES), 2021, Volume 3, Issue 1, 42-53. Tambunan, T. (2001). Perekonomia Indonesia: Teori dan Temuan Empiris. Jakarta: Ghalia Indonesia. 54