Ribut Nurul Tri Wahyuni

The COVID-19 pandemic caused many individuals to lose their jobs and face economic uncertainty, prompting a shift toward more flexible work arrangements such as gig worker work—freelance jobs based on digital platforms without formal employment contracts. To address the employment impact, the government launched the Kartu Prakerja Program as an effort to enhance skills and support labor adaptation. This study aims to analyze the general characteristics of Kartu Prakerja recipients and examine its impact on individuals’ decisions to become gig workers, as well as its effect on their earnings. The data used in this study come from the August 2024 National Labor Force Survey (Sakernas) by BPS-Statistics Indonesia, employing the Propensity Score Matching (PSM) method to reduce potential estimation bias and the Tobit model to account for censored earnings data. The findings reveal that the Kartu Prakerja Program increases the likelihood of individuals becoming gig workers but reduces their earnings. These results suggest that, although the program effectively facilitates transitions into the digital sector, further evaluation is necessary to ensure its benefits are distributed more evenly, particularly in supporting skill development and earnings growth among gig workers.

Background: The National Health Insurance-Contribution Assistance Recipients (JKN-PBI) participants in Indonesia tended to increase. However, out-of-pocket (OOP) health expenditures among participants did not significantly decrease. This phenomenon may have occurred because the impact of this program on OOP health expenditures varied by household group. Aims: This study investigated the heterogeneity impact of the JKN-PBI program across per capita expenditure quartiles and residential regions in 2024. Methods: The study used data from BPS-Statistics Indonesia. Because the determination of JKN-PBI program recipients was endogenous, this study used the Inverse Propensity Score Weighting (IPW) model. Tobit regression was also applied to accommodate the OOP health expenditure reported as a zero value. Results: Participation in JKN-PBI significantly reduced OOP health expenditures. More nominal reductions occurred in higher quartiles, whereas proportional reductions occurred in lower quartiles. This outcome indicated that households in the lower quartiles obtained greater health service advantages relative to households in the higher quartiles. The reduction in OOP health expenditure share was also greater in rural areas. Conclusion: The government must prioritize this program in rural regions and low-income households. In addition, the government needs to identify healthcare service needs by regions and income groups so that the use of the JKN-PBI card is more optimal. Keywords: National Health Insurance Program, Out-of-Pocket Expenditure, Heterogeneous Impact, Inverse Propensity Score Weighting, Tobit Regression

Research Originality: This study offers a new method to analyze district labor productivity in Indonesia.Research Objectives: This study examines the convergence of district labor productivity in Indonesia and the role of structural change in this district labor productivity growth.Research Methods: This study uses spatial convergence and spatial shift-share analysis. This study collected data from BPS-Statistics Indonesia at the district level between 2010 and 2022.Empirical Results: Labor productivity in Indonesia exhibits convergence. Neighbor districts' characteristics, such as initial labor productivity and unobserved variables, affect this convergence. The intrasectoral component has the most significant effect on labor productivity growth. The intersectoral component, caused by structural change, has almost no effect.Implications: The Indonesian government can improve intrasectoral productivity growth to accelerate labor productivity development.JEL Classification: C21, E24, R11

Analyzing air pollution caused by traffic conditions requires appropriate indicators. Currently, air pollution indicators are approximated by the number of vehicles and gas station density. However, this approach cannot provide information at a smaller level. This study aims to identify traffic congestion distribution from Google Maps data as an alternative air pollution indicator at smaller level using map digitization method. In addition, this study examines its relationship with the existing indicator called gas station density. The results show that the digitization method can map the traffic congestion distribution where most areas in West, North, and Central Jakarta are classified as high traffic. In addition, this study found that there is a strong and significant relationship of 0.58277 between traffic congestion distribution and gas station density. Thus, traffic congestion distribution and gas station density data from Google Maps can be used as an indicator of traffic-related air pollution, especially land transportation. Furthermore, this research is expected to serve as a basis for the government in determining mitigation strategies related to traffic congestion and the resulting emissions.

Road quality plays an important role, especially in rural areas where most poor households are situated. This study aims to calculate the Rural Access Index (RAI), an indicator of rural road quality (SDG indicator 9.1.1), at the district level, to evaluate the implementation of the Nawacita programme in Indonesia from 2014–2020. The RAI describes the proportion of rural residents who live within 2 km of an all-season road. This study recommends the utilisation of road network maps, urban–rural boundary maps, three road network condition datasets, and WorldPop data to calculate the RAI. The results show that during this period, the RAI increased and its inequality decreased, specifically in the regions of priority for this programme (Papua and West Papua). The results also capture a strong pattern of regional convergence. To ensure the future success of this implementation, the government can create regulations to designate several road infrastructure projects as a national strategy, as well as increase tax collection and private sector investment as sources of road infrastructure development funding.

Abstrak Saat ini, teknologi berkembang pesat di Indonesia. Salah satu bentuk pemanfaatan teknologi adalah perdagangan berbasis online (e-commerce). E-commerce dapat memberikan banyak manfaat jika dapat dilaksanakan dengan baik dan didukung oleh regulasi pemerintah. Perkembangan e-commerce sangat dipengaruhi oleh jumlah pelanggan, tetapi saat ini baru 3,18% penduduk Indonesia yang telah melakukan pembelian secara online. Penelitian ini membahas faktor-faktor yang dapat memengaruhi ‘persentase pembeli online’ di Indonesia dengan menggunakan data cross section, yaitu provinsi-provinsi di Indonesia tahun 2017. Metode yang digunakan adalah metode analisis jalur (path analysis) untuk melihat pengaruh langsung dan tidak langsung dari variabel persentase pengguna internet per jumlah penduduk, pendapatan per kapita, dan rata-rata lama sekolah terhadap persentase pembeli online. Hasilnya adalah persentase pengguna internet berpengaruh langsung terhadap persentase pembeli online. Sedangkan pendapatan per kapita dan rata-rata lama sekolah berpengaruh tidak langsung terhadap persentase pembeli online. Untuk mendukung peningkatan persentase pembeli online di Indonesia, pemerintah perlu meningkatkan anggaran untuk infrastruktur komunikasi, pendidikan, dan sumber daya manusia. Kata Kunci: E-commerce, Pembeli Online, Metode Analisis Jalur Abstract Nowadays, technology grows rapidly in Indonesia. One of the technology utilization is online shopping (e-commerce). E-commerce can provide benefits if it is implemented properly and supported by government regulations. The development of e-commerce is strongly influenced by the number of customers, but the percentage of Indonesians buying online is only 3.18%. This research discusses the influencing factors of online customers in Indonesia by using cross-section data (provinces in Indonesia in 2017). It uses the path analysis method to find the direct and indirect effect of the percentage of internet users per total population, income per capita, and educational attainment to the percentage of online consumers. The percentage of internet users has a direct effect on the percentage of online consumers. Income per capita and educational attainment have an indirect effect on the percentage of online consumers. To increase the percentage of online customers in Indonesia, the government needs to increase the budget on communication infrastructure, education, and human resources. Keywords: E-commerce, Online Customer, Path Analysis JEL Classification: C390, L810, M380

Education is an important factor in human resource investment. Education is also expected to increase in income and decrease in income inequality. This paper analyzes returns to education in Indonesia. By processing the National Labor Force Survey data from six regions in Indonesia in 2013, we suggest a robust stylised fact: returns to education are higher for the more skilled individuals (workers who have high schooling). In other words, education can reduce wage inequality. Wage inequality occures because of over-education, abilityschooling interactions and school quality or different fields of study. Based of gender, returns to education for men is lower than women. Education can reduce gender based wage gap. Therefore, government can increase investment in education sector to reduce wage inequality, including gender based wage gap. Keywords: education, wage inequality, gender, worker

Program pro-poor growth (program pembangunan ekonomi yang berihak kepada penduduk miskin) belum efektif mengurangi kemiskinan di Papua karena pemerintah tidak memiliki informasi lengkap mengenai faktor-faktor yang menyebabkan kemiskinan menurut variasi wilayah (spatial heterogeneity). Oleh karena itu, studi ini akan menganalisis faktor-faktor tersebut dengan menggunakan model Geographically Weighted Regression (GWR). Studi ini menemukan pengaruh luas lahan yang diusahakan, penggunaan irigasi teknis, sumber air minum, dan listrik terhadap kemiskinan bervariasi secara spasial. Sementara itu, multivariate K-means clustering menunjukkan kecamatan mengelompok menurut kondisi geografis. Ini menyiratkan bahwa intervensi pengentasan kemiskinan seharusnya berbeda untuk wilayah berbeda.