Understanding the impact of mining activities and human capital improvement on achieving sustainable development goals; evidence from East Luwu, Indonesia

Anwar, Andi Faisal; Sari, Dyah Wulan; Islamiya, Haura Azzahra Tarbiyah; Ahmad, Raja Adzrin Raja; Alias, Nur Salimah Article Understanding the impact of mining activities and human capital improvement on achieving sustainable development goals; evidence from East Luwu, Indonesia Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Anwar, Andi Faisal; Sari, Dyah Wulan; Islamiya, Haura Azzahra Tarbiyah; Ahmad, Raja Adzrin Raja; Alias, Nur Salimah (2024) : Understanding the impact of mining activities and human capital improvement on achieving sustainable development goals; evidence from East Luwu, Indonesia, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 12, Iss. 1, pp. 1-16, https://doi.org/10.1080/23322039.2024.2386401 This Version is available at: https://hdl.handle.net/10419/321563 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Economics & Finance ISSN: 2332-2039 (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Understanding the impact of mining activities and human capital improvement on achieving sustainable development goals; evidence from East Luwu, Indonesia Andi Faisal Anwar, Dyah Wulan Sari, Haura Azzahra Tarbiyah Islamiya, Raja Adzrin Raja Ahmad & Nur Salimah Alias To cite this article: Andi Faisal Anwar, Dyah Wulan Sari, Haura Azzahra Tarbiyah Islamiya, Raja Adzrin Raja Ahmad & Nur Salimah Alias (2024) Understanding the impact of mining activities and human capital improvement on achieving sustainable development goals; evidence from East Luwu, Indonesia, Cogent Economics & Finance, 12:1, 2386401, DOI: 10.1080/23322039.2024.2386401 To link to this article: https://doi.org/10.1080/23322039.2024.2386401 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 19 Aug 2024. Submit your article to this journal Article views: 1272 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE Understanding the impact of mining activities and human capital improvement on achieving sustainable development goals; evidence from East Luwu, Indonesia Andi Faisal Anwar a , Dyah Wulan Sari a , Haura Azzahra Tarbiyah Islamiya a , Raja Adzrin Raja Ahmad b and Nur Salimah Alias c a Department of Economics, Universitas Airlangga, Surabaya, Indonesia; b Department of Economics, Universiti Teknologi MARA, Malaysia; c Faculty of Business and Communication, Universiti Malaysia Perlis, Perlis, Malaysia ABSTRACT Mining activities and efforts to increase human capital in East Luwu Regency, Indonesia, have not been able to contribute significantly to achieving Sustainable Development Goals, namely reducing unemployment and poverty. This study aims to determine whether the contribution of the mining sector and human capital affects the achievement of SDGs, either directly or indirectly. The novelty of this research is that it seeks to explore how much influence human capital and the mining sector in East Luwu, the largest mining center in Indonesia, have on realizing inclusive economic development. The type of research used is descriptive quantitative with a path analysis method approach using secondary time series data in the span of fifteen years, 2008- 2022, obtained from the Statistics of Indonesia (BPS). Referring to the research results, it can be concluded that the mining sector’s contribution has a negative effect on reducing unemployment and poverty in East Luwu Regency. Likewise, human capital has a negative effect on reducing unemployment and poverty. Meanwhile, the unemployment rate variable positively affects the poverty rate. Seen from the indirect effect, the mining sector and human capital can reduce poverty indirectly through the unemployment rate variable. The implication of this study is to provide new information for the government and private sector to encourage the mining sector to grow inclusively and consistently in reducing unemployment and poverty, as stated in the vision of sustainable development goals (SDGs). IMPACT STATEMENT The practical implication of this research is that it is new information as well as targets and strategies for the government and private sectors operating in the mining sector to jointly encourage a mining sector that can involve local communities in terms of labor supply and fulfilment of supply chain need to contribute to reducing unemployment and poverty. Likewise, in the aspect of increasing human capital, the quality should continue to be improved, such as the development of training and skills to be able to participate in mining activities to help vulnerable people get out of the poverty chain. Moreover, the huge government revenue from the mining sector allows the government and private sector to collaboratively contribute to improving the quality of human capital massively and achieving sustainable development, as stated in the vision of sustainable development goals (SDGs). ARTICLE HISTORY Received 8 February 2024 Revised 29 May 2024 Accepted 8 July 2024 KEYWORDS Decent work; human capital; poverty; sustainable industrialization SUBJECTS Economics; Labour Economics; Industry & Industrial Studies; Environmental Economics; Regional Development; Population & Development; Sustainable Development 1. Background The mining sector can contribute to progress toward achieving the Sustainable Development Goals (SDGs), namely to reduce poverty (Laing & Moonsammy, 2021; Mvile & Bishoge, 2024). The mining sector can create growth prospects and increase incomes as long as investments in the sector are managed for social services and adequate infrastructure development (Azubuike et al., 2023). Thus, new investment CONTACT Dyah Wulan Sari [email protected] Department of Economics, Universitas Airlangga, Surabaya, Indonesia ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. COGENT ECONOMICS & FINANCE 2024, VOL. 12, NO. 1, 2386401 https://doi.org/10.1080/23322039.2024.2386401 will continue to roll in, to increase production capacity to the maximum and encourage industrial growth. (Sagala et al., 2023). However, in contrast to Bishoge and Mvile (2020) the exploitation of mining natural resources is not always able to reduce the existing poverty rate; if not appropriately managed, countries rich in natural resources fail to get full benefits and respond effectively to the community’s needs. The existence of the mining sector does not correlate with efforts to reduce poverty. In line with Botelho Junior et al. (2023), mining sector activities increase poverty in Colombia and have a very weak correlation with achieving the first SDG, namely ‘no poverty’(SDG 1). As a result, the mining sector has grown exclusively, so it has not been able to drive the economy impressively and overcome the existing problems of unemployment and poverty. The purpose of this study is to measure the effect of the contribution of the mining sector and human capital on achieving SDGs in East Luwu Regency, Indonesia, especially on unemployment and poverty, both directly and indirectly. East Luwu Regency is one of the largest mining centers in South Sulawesi Province and the second largest in Indonesia, with an area of 198,624 hectares (Statistics Indonesia, 2023). The region’s nickel export commodity penetrated the highest share of 54.49% (yoy), much higher than the previous year, which only grew by 14.60% (yoy) in 2022 (Statistics Indonesia, 2023). However, the region faces two significant problems: high unemployment and poverty. From 2018 to 2021, the region’s unemployment rate increased by 2.03%. In 2018, the unemployment rate was only 3.81%, then increased sharply to 4.96% in 2021 (Statistics Indonesia, 2023). The same is true for poverty. In the last five years, the poverty rate in East Luwu Regency has not experienced a significant change (Statistics Indonesia, 2023). In 2018, the region’s poverty rate was 7.23% and decreased to 6.94% in 2021 (Statistics Indonesia, 2023). However, this figure is still high compared to other regions in Indonesia. As a result of efforts to increase human capital, the average length of schooling in East Luwu Regency continues to increase from year to year. In 2018, the average length of schooling in the region was only 8.45 years, then increased in the following year to 8.54 years. Entering 2022, this achievement penetrated the 8.92-year mark (Statistics Indonesia, 2023). Thus, efforts to increase human capital are fairly consistent. However, it has not been able to contribute to reducing unemployment and poverty in this region. Thus, this contradiction also confirms that existing economic development is increasingly exclusive. Previous study, Monteiro et al. (2019) found that the mining sector can contribute to increasing job creation, reducing unemployment and poverty, however, in contrast to Syahrir (2022) those who examined the contribution of the mining sector to sustainable development in four locations in Indonesia, namely precisely in East Luwu, Mimika, Kutai Kertanegara, and Muara Enim from 2000 to 2017, which found that the mining sector contributed to the degradation of environmental damage, low human capital in the mining production center, high employment dependence and unemployment rates. In line with the study by Gunawan (2023), natural resources such as the mining sector do not influence reducing the unemployment rate because the revenue obtained from the sector is considered more attractive for developing physical infrastructure projects than improving the employment sector. This is the case with Majid et al. (2020) and Pegg (2006) who confirmed that the mining sector cannot contribute to reducing poverty. Apart from this, it is important to research this issue further. By using path analysis, this study aims to determine whether there is an effect of the contribution of the mining sector and human capital to the achievement of SDGs, either directly or indirectly. The novelty of this research is that it seeks to deepen the issue of achieving SDGs in the midst of abundant mining production, as well as the government’s role in increasing human capital to reduce unemployment and poverty. In addition, this research uses updated data, which is expected to provide more actual information for the government and the private sector. The future impact of this research is to serve as a mapping and guide for the government in addressing these issues, especially in the last fifteen years, to produce economic development policy formulations in the mining sector that are more inclusive and able to contribute sustainably to the SDGs agenda. The sections of this document are organized as follows: The introduction is in Section 1, then Section 2 deepens the relevant theory and reviews the existing literature. Section 3 outlines the sample data, selection process, and methodology used. The results are described in Section 4, while Sections 5 and 6analyze and summarise the findings. 2 A. FAISALANWAR ET AL. 2. Literature review Institutional economics has significant relevance in reducing poverty, as initiated by Amartya Sen, which aligns with sustainable development goals (SDGs). The United Nations introduced this concept to achieve sustainable development worldwide (UN-Habitat, 2002). The concept of institutional economics highlights the importance of institutions in economic development. Good institutions, such as policies that support poverty alleviation, human rights protection, and an effective judicial system, can help create an enabling environment for poverty reduction. In addition, institutional economics is also related to natural resource management. Good policies and regulations can ensure that abundant natural resources are utilized sustainably, contributing to poverty reduction (Awan et al., 2022; Hirai & Comim, 2022; Vollmer & Alkire, 2022; Zhao et al., 2023; Zhou & Liu, 2022). Poverty is a classic problem that always arises in a country’s development process (Kartika et al., 2023). There is a close correlation between poverty and high unemployment rates. People who do not have permanent jobs are always included in the poor category (Arfanita et al., 2023; Dai et al., 2023). The existence of accessible natural resources is the main basis for a society’s production efforts. These natural resources are seen as the main limitation to economic growth (Kim, 2021). However, Malthusianism theory states that population growth tends to outpace the growth of food production, leading to hunger and resource shortages (Telford, 2023). The Malthusian law of population states that human population growth tends to move faster than the growth of natural resource production. This creates an imbalance between population and resource availability, resulting in declining living standards, unemployment and even poverty. (Jie et al., 2023; Noumba et al., 2022). Keynes provided his perspective on unemployment by saying that labor supply and demand will be balanced when the wage rate can be changed equally. People are willing to work for a lower wage than having no income, which will attract more employees to the company. However, only those unwilling to work for a lower wage or deliberately want to be unemployed are called unemployed (Adda & Ottaviani, 2023; Apeti & Edoh, 2023; Lim et al., 2023; Stern, 2018). Reducing unemployment and poverty requires high human capital. Increasing human capital is also one of the agendas of the SDG’s vision. To achieve sustainable economic development, education is one of the important components of human capital. It emphasises that investing in human capital can increase individual productivity and excellence and is one approach to addressing unemployment and poverty (Bird et al., 2022; Zhao & Niu, 2023). Investment in education is urgent in improving human capital, and education plays an important role in creating a more equal society. Providing equal access to education at all levels of society can reduce social inequality and provide equal employment opportunities for all individuals. In addition, it can be an effective means of overcoming poverty (Aytun et al., 2023; Azam et al., 2023; Liu et al., 2022; Pata et al., 2023; Payab et al., 2023; Wei et al., 2023). Improving access to quality education provides underprivileged individuals with opportunities to develop skills and knowledge to help them escape the cycle of poverty (Hamago et al., 2023; Shao et al., 2023; R. Zhou et al., 2022). 3. Method 3.1. Data description The type of data used in this study is secondary data, which is time series data in the last fifteen years, to be precise, from 2008–2022. The data sample used was selected based on the consideration of the most significant number of mining producers in Indonesia, namely the East Luwu Regency. In addition, it is suspected that the SDG’s achievements in this region have not been so good at reducing unemployment and poverty, so this problem is the basis for its own consideration for choosing this location as the research object. Secondary data were obtained from BPS Indonesia publications related to the SDGs achievements of districts and cities in Indonesia. The data in question include the poverty rate measured by the percentage of poor people (percent), unemployment rate measured by the unemployment rate (percent), mining sector contribution measured by the growth rate of the mining sector GRDP (billion rupiahs), and human capital measured in average years of schooling. COGENT ECONOMICS & FINANCE 3 3.2. Variables The method used in this research is path analysis. This method was chosen to trace the direct and indirect effects of various variables that have been hypothesized in this study, namely to analyze the influence between independent and dependent variables (Stage et al., 2004; Wolfle, 1980). The independent variables in question are the contribution of the mining sector and human capital to the dependent variable, namely the poverty rate through the unemployment rate as an intermediary variable (Table 1). The location of this research is in East Luwu Regency (Figure 1). This location was chosen because this area is the largest nickel production center in South Sulawesi Province and eastern Indonesia. However, at the same time, unemployment and poverty rates are still high in the region, so this is quite contradictory and not in line with the spirit of SDGs development initiated by the government. 3.3. Model specification The fundamental model used in the study is as follows: Y1¼fX1, X2 ðÞ (1) Y2¼fX1, X2, Y1 ðÞ (2) Figure 1. The map of East Luwu. Source: Statistics Indonesia (2023). Table 1. Descriptive variable. Variable Name Description Source X1 Contribution of the mining sector https://www.bps.go.id/en X2 Human capital https://www.bps.go.id/en Y1 Unemployment https://www.bps.go.id/en Y2 Poverty https://www.bps.go.id/en 4 A. FAISALANWAR ET AL. The functions of Equations (1) and (2) can be written in the following equations: LnY1¼a0þþa1X1þa2X2þe1 (3) LnY2¼b0þb1X1þb2X2þb3Y1þe2 (4) Where Y1 is unemployment, Y2 is poverty, X1 is mining sector contribution, X2 is human capital. a1, a2, b1, b2, b3, the regression coefficient of each variable X on Y1 and Y2. a0 and b0 are constant. Where e1 and e2 are error terms. 3.4. Hypotheses The hypotheses of this study, among others (Figure 2); Direct Relationship 1. The mining sector’s contribution has a negative and significant effect on the unemployment rate. 2. The mining sector’s contribution has a negative and significant effect on the poverty rate. 3. Human capital has a negative and significant effect on the unemployment rate. 4. School human capital has a negative and significant effect on poverty. 5. The unemployment rate has a positive and significant effect on the poverty rate. Indirect Relationship 1. The mining sector’s contribution has a negative and significant effect on the poverty rate through the unemployment rate. 2. Human capital has a negative and significant effect on the poverty rate through the unemployment rate. 4. Results The coefficient a0 of 95.862 indicates that if there is no change in the mining sector contribution (X1) and human capital (X2) variables, then unemployment (Y1) will remain at 95.862. The coefficient a1, which is –0.003, indicates that for every one billion rupiah increase in mining sector contribution (X1), the unemployment rate (Y1) decreases by −0.003, assuming human capital (X2) remains constant. The coefficient a2, equal to −42.718, indicates that for every one-year increase in human capital (X2), unemployment (Y1) will decrease by −42.718, assuming variable X1 remains constant (Table 2). The coefficient value of b0, which is 25.688, indicates that if there is no change in the independent variables, namely mining sector contribution (X1), human capital (X2), and unemployment (Y1), then poverty (Y2) will remain at 25.688. The coefficient value of b1, with a value of −0.026, indicates that for every one billion rupiah increase in the contribution of the mining sector (X1), poverty (Y2) decreases by −0.026, assuming human capital (X2) and unemployment (Y1) remain constant. Furthermore, the coefficient value of b2, with a value of −8.954, indicates that for every one-year increase in human capital Figure 2. Research Framework. COGENT ECONOMICS & FINANCE 5 (X2), poverty (Y2) decreases by −8.954, assuming the contribution of the mining sector (X1) and unemployment (Y1) remain constant. Finally, the coefficient value of b3, with a value of 0.134, indicates that for every one percent increase in the unemployment rate (Y1), poverty (Y2) increases by 0.134, assuming the contribution of the mining sector (X1), and human capital (X2) remains constant (Table 3). Judging from the T-test in the first model, the results show that the effect of the mining sector contribution (X1) on the unemployment rate (Y1) has a negative relationship, with a significance level of 0.979. This finding is not in line with the existing hypothesis. Furthermore, there is a negative and significant relationship between human capital (X2) and the unemployment rate (Y1), with a significance value of 0.013, so this finding aligns with the existing hypothesis. Next, the results show that the contribution of the mining sector (X1) has a negative and insignificant effect on the poverty rate (Y2) with a significance value of 0.316, so this finding is not in line with the existing hypothesis. Furthermore, the value of the human capital variable (X2) in the table shows 0.036, so human capital has a negative and significant impact on the poverty rate (Y2), and this finding is in line with the existing hypothesis. Finally, there is a positive and significant relationship between the unemployment rate (Y1) and the poverty rate (Y2) of 0.035, so this finding is in line with the existing hypothesis. Furthermore, seen from the T-test in the second model, the results show that the direct effect of the mining sector contribution (X1) on poverty (Y2) is −0.026, while the indirect effect through the unemployment rate (Y1) is −0.0004. These findings are in line with the hypothesis. Furthermore, the direct effect of human capital (X1) on poverty (Y2) is −8.954, while its indirect effect through the unemployment rate (Y1) is −5.753. This shows an insignificant relationship and is in line with the hypothesis (Table 4). 5. Discussion 5.1. Effect of mining sector contribution on unemployment rate The result shows that the effect of the mining sector’s contribution to the unemployment rate has a significance level of 0.979. Based on this value, it can be concluded that the mining sector’s contribution has no significant effect on the unemployment rate because the significance value is >0.05 but has a negative relationship. This finding is not in line with the existing hypothesis. This means that any increase in the mining sector’s contribution can reduce the poverty rate in East Luwu Regency. Several points account for this conclusion. Firstly, mining in the region has brought increased income to local Table 2. Model Y1 T test result. Variable Coefficient Std. Error t-Statistic Prob. C 95.86236 31.02353 3.089989 0.0094 X1 −0.003368 0.130487 −0.025809 0.9798 X2 −42.71824 14.84918 −2.876807 0.0139 Table 3. Y2 model T test results. Variable Coefficient Std. Error t-Statistic Prob. C 25.68829 8.102193 3.170535 0.0089 X1 −0.026698 0.025432 −1.049797 0.3163 X2 −8.954728 3.761850 −2.380405 0.0365 Y1 0.134684 0.056261 2.393922 0.0356 Table 4. Summary of findings. Influence between Variables Direct Effect Significant level Relationship In line with Hypothesis Indirect Effect Through Y1 Relationship Total Influence In line with Hypothesis X1!Y1 −0.003 0.979 Not Significant No ––−0.003 – X2!Y1 −42,718 0.013 Significant Yes ––−42,718 – X1!Y2 −0.026 0.316 Not Significant No −0.0004 Not Significant −0.0264 Yes X2!Y2 −8.954 0.036 Significant Yes −5.753 Not Significant −14,707 Yes Y1!Y2 0.134 0.035 Significant Yes ––0.134 – 6 A. FAISALANWAR ET AL. communities. Whether through the wages of direct mining workers or the business opportunities and support services that come with the growth of the mining sector. Increased individual incomes have improved living standards and reduced unemployment in East Luwu Regency. This is, of course, in line with the first SDG’s mission to reduce unemployment. Increased individual income is the key to reducing unemployment. With higher incomes, individuals and families have better access to basic needs such as food, clothing, shelter, and health services. Secondly, mining in this area has accompanied the development of roads, airports and other facilities that can improve connectivity and accessibility to previously remote areas of East Luwu Regency. This infrastructure can open up access to markets and other economic opportunities, which can go a long way in reducing the existing unemployment rate in the region. Achieving the SDGs emphasizes the urgency of basic infrastructure development, such as transport, roads, and public transport, to open up accessibility to previously isolated areas. This allows people in remote or rural areas to more easily access markets, health services, education, and employment, which in turn can reduce unemployment rates. What happened in East Luwu Regency indirectly confirms the role of SDGs point 9, namely infrastructure development, as a strategic way of reducing the unemployment rate. Hence, the interrelation of point 9 with point 8 of the SDGs is very strong. Third, along with the development of the mining sector, it has helped drive local economic development by creating a value chain involving various supporting industries in East Luwu Regency. These include companies that provide contracting services, transport, and other goods and services. This local economic growth has pretty much spread to other sectors in the region. This aligns with Rostow’s theory that exploiting natural resources in the early stages of economic growth can have a positive domino effect. For example, mineral mining or intensive agricultural activities can create employment opportunities. Expanding these sectors can increase production and investment, and reduce the unemployment rate (Mohammed et al., 2022; Sadik-Zada, 2023). Dikgwatlhe and Mulenga (2023) in their research in South Africa showed that mining factories managed by local communities can generate employment for local people, reduce unemployment rates and create better livelihoods. These findings, however, are not in line with research by Botelho Junior et al. (2023) who found that mining production in Colombia actually increased unemployment and poverty in the region. Behind the mining production, it is only enjoyed by certain groups is exclusive, and cannot contribute to reducing unemployment. The activities of the mining sector move away from the target of achieving the eighth SDGs, namely ‘decent work and economic growth’. 5.2. Human capital on unemployment rate The results showed a negative and significant influence between human capital and the unemployment rate in East Luwu Regency, with a significance value of 0.013, which is smaller than the specified significance value of 0.05. This finding is in line with the hypothesis. Thus, it can be concluded that any increase in human capital can reduce the unemployment rate in the region. There are several reasons for this. Firstly, the government’s efforts to provide education and training that is more contextualized to the needs of prospective workers have improved job seekers’knowledge of various economic sectors and job opportunities. Better knowledge helps them choose a career that suits their skills and interests. This includes surviving in the informal sector. This relates to SDG 8, which creates decent work and inclusive economic growth. Increasing employment opportunities is key to achieving this goal and reducing the unemployment rate in East Luwu District. Secondly, training has allowed job seekers to improve their technical and non-technical skills. With better skills, they become more suited to the demands of the labor market and have a better chance of getting a job. In addition, it helps job seekers in the informal sector to diversify their skills. This has opened up job opportunities in different sectors or types of jobs, reducing dependence on one type of job, including in the mining sector in East Luwu Regency; in other words, it has increased flexibility in entering the labor market. Job seekers who have undergone training have the potential to earn higher incomes. This not only improves individual welfare but can also positively impact the local economy. 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