Articles
<![CDATA[DEVELOPMENT OF EDUCATION RETURN RATE IN EAST JAVA 2015 AND 2018 ]]>
<![CDATA[Nuelda Amalia]]>;
<![CDATA[Lilik Sugiharti]]>
<![CDATA[ East Java Economic Journal Vol. 3 No. 2 (2019) ]]>
Publisher : <![CDATA[Kantor Perwakilan Bank Indonesia Provinsi Jawa Timur ]]>
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DOI: 10.53572/ejavec.v3i2.29
<![CDATA[Education provides many benefits for the workforce, one of which is income when enter-ing the labor market. The return on educational benefits as measured by income is often referred to as the rate of return on education investment. This study aims to determinethe development of the rate of return on education investment in East Java in 2015 and2018. The data used are data from the East Java National Labor Force Survey (Sakernas) in2015 and 2018. The estimated rate of return on education investment is carried out usingthe Heckman Selection Model Method which uses the Heckman Selection Model. modifiedMincer’s Income Function Model to overcome sample-selectivity-bias. The result is thatthe rate of return on investment in education in East Java in 2015 and 2018 generallyincreased, except at the higher education level.Keywords: Return on Investment Education, Income, Profitability, East JavaJEL : I26, I25, N35]]>
<![CDATA[Pengaruh faktor demografi dan nondemografi terhadap fertilitas di Indonesia ]]>
<![CDATA[Shafira Ramadhani Nugrahaeni]]>;
<![CDATA[Lilik Sugiharti]]>
<![CDATA[ Jurnal Kependudukan Indonesia Vol 17, No 1 (2022) ]]>
Publisher : <![CDATA[Research Centre for Population, National Research and Innovation Agency (BRIN) ]]>
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DOI: 10.14203/jki.v17i1.679
<![CDATA[This study aims to analyze the effect of demographic factors (child mortality, age of first marriage, type of contraception) and non-demographic factors (economic factors represented by income; social factors consisting of mother’s education and work status; and cultural factors represented by ethnicity and religion) on fertility in Indonesia. By applying Ordinary Least Square (OLS) method, this study uses cross-sectional data from Indonesia Family Life Survey Wave 5 in 2014. OLS regression results show that demographic factors that influencing fertility in Indonesia are child mortality, age of first marriage, and type of contraception (IUD and tubectomy). Meanwhile, non-demographic factors that have an effect on fertility in Indonesia are income and mother’s education. Moreover, the significant effect of cultural factor on fertility in Indonesia is only shown partially among ethnic groups.]]>
<![CDATA[Characteristics and Determinants Of Precarious Employment In Indonesia ]]>
<![CDATA[Oni Prasetyo Utomo]]>;
<![CDATA[Lilik Sugiharti]]>
<![CDATA[ MediaTrend Vol 17, No 2 (2022): OKTOBER ]]>
Publisher : <![CDATA[Trunojoyo University of Madura ]]>
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DOI: 10.21107/mediatrend.v17i2.17015
<![CDATA[Precarious employment is indicator of non-standard work that describes workers in a vulnerable position to lose their jobs which can lead to poverty and can hinder sustainable development. The rapid growth of precarious employment rate is a serious challenge for a developing country. This study aims to analyze the factors that affect precarious workers in Indonesia. The data used in this study is Sakernas August 2019. The analytical method used in this study is logistic regression, where the independent variables are the demographic and employment characteristics of individuals along with macro conditions of regional employment. The findings of this study are that young workers, male, low-educated, unmarried status, and living in urban areas, tend to be precarious workers. Those who work in the manufacturing industry and less than one year of work experience are more likely to become precarious workers. High unemployment rates and low regional average wages also put individuals at greater risk of becoming precarious workers.]]>
<![CDATA[Pengaruh faktor demografi dan nondemografi terhadap fertilitas di Indonesia ]]>
<![CDATA[Shafira Ramadhani Nugrahaeni]]>;
<![CDATA[Lilik Sugiharti]]>
<![CDATA[ Jurnal Kependudukan Indonesia Vol 17, No 1 (2022) ]]>
Publisher : <![CDATA[Research Centre for Population, National Research and Innovation Agency (BRIN) ]]>
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DOI: 10.14203/jki.v17i1.679
<![CDATA[This study aims to analyze the effect of demographic factors (child mortality, age of first marriage, type of contraception) and non-demographic factors (economic factors represented by income; social factors consisting of mother’s education and work status; and cultural factors represented by ethnicity and religion) on fertility in Indonesia. By applying Ordinary Least Square (OLS) method, this study uses cross-sectional data from Indonesia Family Life Survey Wave 5 in 2014. OLS regression results show that demographic factors that influencing fertility in Indonesia are child mortality, age of first marriage, and type of contraception (IUD and tubectomy). Meanwhile, non-demographic factors that have an effect on fertility in Indonesia are income and mother’s education. Moreover, the significant effect of cultural factor on fertility in Indonesia is only shown partially among ethnic groups.]]>
<![CDATA[Perkembangan Tingkat Pengembalian Investasi Pendidikan Menengah di Indonesia Tahun 2015 dan 2018 ]]>
<![CDATA[Amalia, Nuelda]]>;
<![CDATA[Sugiharti, Lilik]]>
<![CDATA[ Jurnal Ekonomi dan Pembangunan Indonesia Vol. 20, No. 2 ]]>
Publisher : <![CDATA[UI Scholars Hub ]]>
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<![CDATA[This research aims to estimate returns to secondary education in Indonesia, especially senior and vocational high school, and its development in 2015 and 2018. Data from Indonesia National Labor Force Survey (NFLS) 2015 and 2018 are used here. Returns are estimated using Two-Step Heckman Method. The results are, in 2015, returns to senior high school (9,32%) are higher than vocational high school (8,89%). However, in 2018, returns to vocational high school (9,53%) are higher than senior high school (9,41%). This shift is caused by the increasing number of vocational school graduates absorbed in workforce and increasing income of vocational school workforce.]]>
<![CDATA[PERAN MODAL MANUSIA TERHADAP PERTUMBUHAN EKONOMI INDONESIA ]]>
<![CDATA[Nurlaili, Ayu Wahyuning]]>;
<![CDATA[Sugiharti, Lilik]]>
<![CDATA[ Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) Vol 7 No 3 (2023): Edisi September - Desember 2023 ]]>
Publisher : <![CDATA[LPPM STIE Muhammadiah Bandung ]]>
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DOI: 10.31955/mea.v7i3.3374
<![CDATA[Peran modal manusia terhadap pertumbuhan telah diperdebatkan dalam waktu yang lama, baik dalam hal teori dasar maupun pengujian empiris. Penelitian ini bertujuan untuk menganalisis kontribusi modal manusia terhadap pertumbuhan ekonomi. Pendekatan modal manusia dari sisi pendidikan dinilai merupakan pendekatan paling baik, serta datanya lebih mudah diperoleh. Penelitian ini menggunakan analisis data panel pada 34 provinsi di Indonesia selama periode tahun 2015 – 2022 menggunakan aplikasi STATA 15.0. Variabel persentase penduduk bekerja dengan pendidikan dasar, menengah, dan tinggi memiliki hubungan yang signifikan terhadap pertumbuhan ekonomi. Pendidikan dasar memiliki hubungan negatif, sementara pendidikan menengah dan tinggi berhubungan positif. Variabel persentase investasi terhadap PDRB berpengaruh signifikan dan positif terhadap pertumbuhan ekonomi. Variabel pertumbuhan angkatan bekerja tidak menunjukkan hubungan yang signifikan terhadap pertumbuhan ekonomi. Pemerintah Indonesia menyadari bahwa modal pendidikan manusia dalam jangka panjang dapat memberikan kontribusi dalam pembangunan negara. Meskipun kualitas pendidikan Indonesia masih perlu terus dibenahi, baik dari segi sistem pembelajaran maupun dari segi pengajar.]]>
<![CDATA[PENGARUH PENGGUNAAN KARTU KPS TERHADAP KESEJAHTERAAN MASYARAKAT MISKIN INDONESIA DALAM MENGAKSES PRORAM BLSM, RASKIN DAN BSM ]]>
<![CDATA[Pratanu, Adip]]>;
<![CDATA[Sugiharti, Lilik]]>
<![CDATA[ Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) Vol 7 No 3 (2023): Edisi September - Desember 2023 ]]>
Publisher : <![CDATA[LPPM STIE Muhammadiah Bandung ]]>
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DOI: 10.31955/mea.v7i3.3586
<![CDATA[Untuk meningkatkan ekonomi, pemerintah Indonesia menaikkan harga bahan bakar pada tahun 2013, tetapi kebijakan ini dapat menyebabkan inflasi dan berdampak buruk pada orang-orang miskin dan rentan. Untuk mengatasi hal ini, pemerintah meluncurkan Program Percepatan dan Perluasan Perlindungan Sosial (P4S) dan Program Kartu Perlindungan Sosial (KPS), yang membantu mengidentifikasi rumah tangga yang membutuhkan bantuan. Hasil penelitian menunjukkan bahwa penerbitan dan penerimaan Kartu KPS meningkatkan kesejahteraan subjektif rumah tangga miskin, dengan peningkatan setiap poin penerimaan kartu KPS meningkatkan kesejahteraan subjektif sebesar 13%. Ini adalah keuntungan dari kartu KPS, karena program sebelumnya seperti BLT memberikan bantuan dengan lebih akurat kepada rumah tangga yang membutuhkannya. Kartu KPS memastikan bahwa bantuan sosial mencapai mereka yang membutuhkannya, dan hal ini memberikan manfaat bagi masyarakat miskin.]]>
<![CDATA[Analysis of Socio-Economic Determinants on Infant Mortality in East Nusa Tenggara Province ]]>
<![CDATA[Kavit, Natalia Afriyani]]>;
<![CDATA[Sugiharti, Lilik]]>
<![CDATA[ Jurnal Ilmu Ekonomi Terapan Vol. 10 No. 1 (2025) ]]>
Publisher : <![CDATA[Department of Economics, Faculty of Economics and Business, Universitas Airlangga ]]>
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DOI: 10.20473/jiet.v10i1.66299
<![CDATA[Reducing infant mortality rates remains a key focus for the government and society. Researchers conducted an analysis of socio-economic determinants of infant mortality in East Nusa Tenggara Province using panel data from 22 districts/cities from 2017 to 2023. The Random Effect Model (REM) approach was chosen after several tests. The results show that socio-economic factors, as measured by women’s education, women’s labor force participation rate, and per capita expenditure, have a significant impact on infant mortality, while access to proper sanitation and cooking fuel did not show a significant effect on infant mortality. This research can be used as a reference in formulating policies to reduce infant mortality in NTT Province, such as equalizing access to at least 12 years of education for women in each region, increasing women’s participation in the workforce and protection against wage discrimination, increasing cigarette excise along with household financial management training, monitoring and protecting household water quality, separating the kitchen area from the bedroom.]]>
<![CDATA[Analysis of the Effect of Socioeconomic Factors on Poverty in Central Java Province ]]>
<![CDATA[Khaqiqi, Moh. Nur]]>;
<![CDATA[Sugiharti, Lilik]]>
<![CDATA[ Journal of Developing Economies Vol. 10 No. 1 (2025) ]]>
Publisher : <![CDATA[Universitas Airlangga ]]>
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DOI: 10.20473/jde.v10i1.57962
<![CDATA[Central Java, despite experiencing robust economic growth, continues to grapple with significant poverty, reflecting a broader national challenge of uneven wealth distribution. The poverty rate as of 2023 stands at 10.77%, highlighting persistent economic disparities. The study aims to analyze how socioeconomic factors like economic growth, HDI, and wage levels contribute to poverty alleviation within the region. The research uses a quantitative approach, employing regression random effect models to understand the dynamics between these variables and poverty rates over the years 2014-2023. Data were processed using Stata 17. The analysis indicates that economic growth in Central Java has an insignificant direct impact on reducing poverty. The research highlights a significant negative correlation between HDI and poverty levels. This study found that wage increases have not significantly impacted poverty reduction. Simultaneously, GDRP growth, HDI, and wages affect poverty in Central Java province. The findings suggest that merely focusing on economic growth and wage increases is not enough to reduce poverty. Comprehensive strategies that also improve human development indices and address income distribution are crucial for effective poverty alleviation.]]>
<![CDATA[Convergence Analysis of Economic Growth in South Kalimantan ]]>
<![CDATA[Sopiana, Yunita]]>;
<![CDATA[Mursinto, Djoko]]>;
<![CDATA[Sugiharti, Lilik]]>
<![CDATA[ Journal of Developing Economies Vol. 7 No. 1 (2022) ]]>
Publisher : <![CDATA[Universitas Airlangga ]]>
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DOI: 10.20473/jde.v7i1.28632
<![CDATA[The objectives of this research are 1) testing and analyzing the level of sigma convergence in South Kalimantan; 2) testing and analyzing the convergent beta, including the absolute beta convergence and conditional beta convergence. This study uses static panel data covering 13 regencies/cities in South Kalimantan observed between 2010 and 2019. The data analysis uses the ordinary least square (OLS) regression model. The results showed a sigma convergence marked by a declining variation coefficient in each regency/city. The absolute beta and conditional beta also converged. Poor areas' economic growth is faster than the prosperous regions so they catch up. There has to be close coordination between the central and local governments in formulating policies in handling government and private investment and improving workers' productivity in the agricultural and mining sectors in South Kalimantan.]]>
