Journal of Indonesian Economy and Business <p style="text-align: justify;"><img style="display: block; margin-left: auto; margin-right: auto;" src="/v3/public/site/images/jieb/homepageImage_en_US_(1).jpg" width="331" height="455"></p> <p style="text-align: justify;">Journal of Indonesian Economy and Business (JIEB), with registered number print ISSN&nbsp;<strong><a title="ISSN" href=";search[]=MUST=issnl=0215-2487&amp;currentpage=1&amp;size=10" target="_blank" rel="noopener">2085-8272</a></strong>; online ISSN&nbsp;<a title="Check ISSN" href=";search[]=MUST=issnl=0215-2487&amp;currentpage=1&amp;size=10" target="_blank" rel="noopener"><strong>2338-5847</strong>, </a>is a scientific, open access, peer-reviewed journal whose objectives is to publish original research papers related to the <strong>Indonesian economy and business issues</strong>. This journal is also dedicated to disseminating the published articles freely for international academicians, researchers, practitioners, regulators, and public societies.</p> <p style="text-align: justify;">The journal welcomes authors from any institutional backgrounds and accepts rigorous empirical research papers with any methods or approach that is relevant to the Indonesian economy and business context or content, as long as the research fits one of three salient disciplines: economics, business, or accounting.&nbsp;</p> <p style="text-align: justify;">The JIEB is Internationally indexed in <a href="" target="_blank" rel="noopener">SCOPUS</a>,&nbsp;<a href="">EconLit</a>,&nbsp;<a href="">ProQuest</a>,&nbsp;<a href=";user=9VyQpCoAAAAJ&amp;view">Google Scholar</a>,&nbsp;<a href="">DOAJ</a>,&nbsp;<a href="">Microsoft Academic Search</a>, and ACI (<a title="ACI" href=";id=634">ASEAN Citation Index</a>). Furthermore, this journal has been nationally accredited by the Directorate-General for Research Strengthening and Development, the Ministry of Research and Technology for Higher Education, Republic of Indonesia (Decree No. 148/M/KPT/2020) in <a href="">SINTA 1 (Indonesian Science &amp; Technology Index).</a></p> <p style="text-align: justify;"><a href=""><img style="display: block; margin-left: auto; margin-right: auto;" src="/v3/public/site/images/jieb/Akreditasi_JIEB.JPG" width="522" height="346"></a></p> <p style="text-align: justify;">&nbsp;</p> en-US <p><strong>Copyright</strong></p> <p>Upon acceptance of an article, authors transfer copyright to the JIEB as part of a journal publishing agreement, but authors still have the right to share their article for personal use, internal institutional use, and for any use permitted under the CC BY-SA license</p> <div> <p><strong>Open Access</strong></p> </div> <p>Articles are freely available to the public without any subscription with permitted reuse. For open access articles, permitted third party (re)use is defined by the following Creative Commons user licenses:&nbsp;<em><strong>Creative Commons Attribution (CC BY-SA)</strong>.</em></p> (Widya Paramita, Ph.D) (Maria Wintang Rarasati) Mon, 20 May 2024 13:01:48 +0700 OJS 60 Risk-Based Premiums of Insurance Guarantee Schemes: A Machine-Learning Approach <p><strong>Introduction/Main Objectives: </strong>This study explores the application of machine-learning techniques to risk-based premium calculations for insurance guarantee schemes within the Indonesian insurance market. This study aims to develop a risk-based premium calculation model using machine-learning techniques in the Indonesian context. <strong>Background Problems: </strong>A gap exists in determining risk-based premiums for both the life and non-life insurance sectors within the Indonesian insurance market. Identifying and understanding the key variables that significantly influence risk-based capital (RBC) is important, and this research addresses this need. <strong>Novelty: </strong>This paper is the first to apply machine learning to calculate risk-based premiums in the context of the Indonesian insurance market. The distinction between the life and non-life insurance sectors in terms of the importance of its variables and itsselection of an optimal model further enrich its unique approach. <strong>Research Methods:</strong> We employed gradient-boosted and decision-tree models to identify key factors impacting risk-based capital. Furthermore, we leveraged clustering techniques to categorize companies into distinct risk tiers, aiming to enable more precise risk-based premium rate calculations. <strong>Finding/Results: </strong>The findings reveal significant differences between the life and non-life insurance sectors in terms of key variables that impact their risk-based capital. These insights lead to the categorization of insurance companies into distinct risk tiers whichhelps to more accurately calculate risk-based premiums. <strong>Conclusion: </strong>Machine learning can serve as a powerful tool in refining insurance risk management practices, ultimately benefiting insurers, policyholders, and regulators alike.</p> Citra Amanda, Ananta Dian Pradipta Copyright (c) 2024 Journal of Indonesian Economy and Business Wed, 08 May 2024 15:58:16 +0700 Unveiling the COVID-19 Recession: The Effect of Sectoral Exposure on the Economy and Labor Market <p><strong>Introduction/Main Objectives: </strong>The impacts of the COVID-19 pandemic on economic and labor market conditions still need further research. This is because the pandemic had different and more extensive impacts than the 2008 global financial crisis. <strong>Background Problems: </strong>The lack of studies that explore the sectoral exposure of the economic and labor market to COVID-19 motivates this study to examine the problems and determine the impacts of the pandemic on the economy and labor market heterogeneity. <strong>Novelty: </strong>The sectoral exposure classification was based on sectoral risk and teleworkability indicators. Furthermore, input-output tables are used to analyze the interregional economic linkages based on economic activities in terms of sectoral exposure. To the best of the author’s knowledge, this is the first study to explore the topic in Indonesia. <strong>Research Methods: </strong>The data used are a cross-section of 34 provinces in 2020. This study uses input-output tables to examine the relationship between sectoral exposure and the economy. In addition, regression analysis is used to examine the effect on the labor market.&nbsp; <strong>Finding/Results: </strong>The industry categorized as having medium-high sectoral exposure is the key sector in Indonesia because the forward and backward linkage has a value of more than 1. It means medium-high sectoral exposure greatly affects other industries' input and output. According to the OLS result, sectoral exposure significantly impacts short-time workers and the unemployment rate.&nbsp;<strong>Conclusion:</strong>&nbsp;This study implies that sectoral exposure to COVID-19 was significant for Indonesia's economic and labor market.</p> Fitri Handayani Copyright (c) 2024 Journal of Indonesian Economy and Business Wed, 08 May 2024 16:02:58 +0700 The Relationship of Trust, Knowledge Transfer and the Person-Job and Person-Organization Fit as Moderating Effects <p><strong>Introduction/Main Objectives:</strong> The study aims to assess the relationship between trust and knowledge transfer with PJ-fit and PO-fit as moderating variables. <strong>Background Problems:</strong> There are two divergent perspectives on knowledge transfer, and trust has been posited as a potential unifying factor that could mitigate these differences. Trust, in many studies, has been regarded as a crucial factor for knowledge transfer, although there is a blurred understanding between trust and distrust. PJ-fit and PO-fit are moderating variables in the relationship between trust and knowledge transfer. <strong>Novelty:</strong> Most PJ-fit and PO-fit studies discuss trust and knowledge transfer. This makes the constructs of PJ-fit and PO-fit, as the moderating variables between trust and knowledge transfer, a novelty in this research. <strong>Research Methods:</strong> This survey analyzed the employees in companies’ information and technology divisions and collected data from 271 participants. The data was analyzed with PLS-SEM 3.29. <strong>Finding/Results:</strong> The result revealed that trust significantly impacts knowledge transfer, with the relationship being strengthened by PJ-fit. <strong>Conclusion:</strong> The optimal fit of knowledge, skills, and abilities is essential in promoting the relationship between trust and knowledge transfer in organizations that require employees who are oriented toward high-tech abilities. Therefore, recruitment based on PJ-fit may be more suitable when looking for an employee with a strong emphasis on expertise.</p> Nikolas Fajar Wuryaningrat, Ardianus Laurens Paulus, Danny I. Rantung, Deske W. Mandagi Copyright (c) 2024 Journal of Indonesian Economy and Business Wed, 08 May 2024 16:06:06 +0700 Managing Financial Life: Examining the Factors Impacting the Financial Literacy of Indonesian Students Studying Abroad <p><strong>Introduction/Main Objectives: </strong>The number of Indonesian students who study abroad has expanded significantly during the past few decades. Nonetheless, the nation has a lot of variables that would assist in the growth of overseas students leaving the country in the future. Consequently, this study aims to investigate the variables influencing the financial literacy of Indonesian students participating in international exchange programs. This study empirically examines how students' financial behavior could be affected by their financial knowledge, financial attitude, and financial culture. It also tests how financial literacy can be directly influenced by financial behavior. Additionally, the mediating role of financial behavior has been evaluated. <strong>Background Problems:</strong> Notwithstanding the rise in the number of students enrolled in international programs, and the availability of such programs in educational institutions worldwide, these students will confront numerous obstacles and difficulties. A vital skill for these students to possess is financial literacy, since there is a lot of emphasis on cost-saving when pursuing higher education in a global setting. However, studies into financial literacy are noticeably lacking, particularly in emerging nations such as Indonesia. <strong>Novelty:</strong> The current paper adds to the limited studies concerning the financial life of international students by developing an integrated framework to examine the most crucial factors impacting the financial literacy of Indonesian students participating in international exchange programs. <strong>Research Methods:</strong> An online survey was conducted to gather the primary data from the respondents. The acquired data were analyzed using PLS-SEM. <strong>Finding/Results:</strong> The research findings showed that financial literacy was significantly impacted by financial behavior, which in turn was impacted by financial knowledge, financial attitudes, and financial culture. The relationship between financial knowledge, financial attitudes, financial culture, and financial literacy was found to be significantly mediated by financial behavior. <strong>Conclusion:</strong> The present work provides theoretical and managerial contributions regarding managing the financial life of international students in Indonesia.</p> Pantri Heriyati, Louis Antonio, Mohammad Soliman Copyright (c) 2024 Journal of Indonesian Economy and Business Wed, 08 May 2024 16:08:55 +0700 Nonlinear Analysis of Growth’s Effect on Debt: Finding the Threshold <p><strong>Introduction/Main Objectives:</strong> This paper explores the nonlinear effect of economic growth on the accumulation of public debt for groups of countries, based on their income levels, by finding its threshold estimator. <strong>Background Problems: </strong>The existing literature has discussed the debt's effect on growth intensively. Thus, empirical analysis to observe the inverse relationship between both variables is needed. <strong>Novelty:</strong> This paper confirms the negative and nonlinear impact of economic growth on public debt, and finds the threshold levels of economic growth on debt in high-income countries (HIC) and low-and middle-income countries (LMIC). <strong>Research Methods:</strong> We employed OLS panel regression with data covering 62 countries from 1970 to 2015. The fixed-effect panel threshold model is used to estimate the threshold level of economic growth that affects debt accumulation. <strong>Finding/Results:</strong> We found that economic growth reduces the public debt in the long run. In HIC, we find two threshold levels of economic growth, at 2.92% and at 8.41%. Moreover, in LMIC, a single threshold is found at 11.61%. <strong>Conclusion:</strong> It is proven that maintaining robust economic growth could reduce debt accumulation in the long run, the magnitude of the impacts varies between HIC and LMIC.</p> Sugeng Triwibowo, Defy Oktaviani, Nurfika Copyright (c) 2024 Journal of Indonesian Economy and Business Wed, 08 May 2024 16:11:20 +0700