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Gambar 1. Pertumbuhan, Kemiskinan dan Ketimpangan di Indonesia Tahun 2000 hingga 2011
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Perhatian ekonom terhadap masalah ketimpangan sangatlah kurang. Kondisi ini juga dilakukan oleh lembaga dunia (Bank Dunia dan UNDP) terutama di bidang kemiskinan, serta pemerintah kita. Dampak kebijakan yang bias antara kemiskinan dan penanggulangan ketimpangan sosial dapat dilihat dari data. Di Indonesia, khususnya Jawa Tengah, selama periode 2002...
Citations
... The ratio of teachers to students in primary schools and high school/vocational schools has a negative and significant effect on HDI. Furthermore, research conducted by Abdullah Rusli (2013) showed that there are only two significant variables that cause inequality i.e. wages and share of economic output received by employers. Meanwhile, two other variables are not significant i.e. urbanization and dependency ratio. ...
Banyuwangi Regency is one of the regencies in East Java that has a higher economic growth rate than East Java's economic growth. Likewise, the poverty rate in Banyuwangi in 2019 was 7.52 percent, this figure is much lower than the East Java Province average of 10.2 percent (Central Statistics Agency, 2019). Poverty in Banyuwangi Regency is contributed by several sub-districts, namely Kalibaru, Licin, Songgon, and Glenmore, where the percentage of poverty is above 10%, while other sub-districts such as Giri, Tegaldimo, and Sempu the percentage of the number of poor people is below 6%. This indicates the occurrence of economic inequality, where there are vertical and horizontal differences that cause disparities or uneven development. This study aims to see how the economic inequality in Banyuwangi Regency. The method used in this research is descriptive qualitative. The object of this research is all sub-districts in Banyuwangi Regency. The data is obtained by distributing questionnaires and conducting interviews with the Office which is directly related to indicators of economic inequality. The results of the study found that there were several sub-districts that still lacked the availability of health facilities and educational facilities, the Stunting Rate was still high in some sub-districts, the distribution of UMKM in the Banyuwangi district was evenly distributed, and there were several sub-districts whose UMKM had not yet developed, the number of unemployed was still scattered in several districts, The provision of social assistance still has the problem of mistargeting so that the achievement of the goal of social assistance is not achieved.
... According to Adelman and Moris (as cited in Arsyad, 2010) income inequality in developing countries is influenced by high population growth, inflation, investment in capital-intensive projects, and deteriorating exchange rates. Furthermore, Abdulah (2013) states that the Wage variable and the share of economic output received by entrepreneurs affect the inequality of income distribution. Growth is a process of changing economic conditions in a country on an ongoing basis to get to a state considered better for a certain period. ...
The income Distribution Inequality of Bangka Belitung Islands Province is the lowest nationally. This study aims to obtain more in-depth information regarding any variables or factors that affect the Inequality of Income Distribution in the Province of Bangka Belitung Islands. The type of research used associative quantitative research with Multiple Linear Regression and Simple Linear Regression models, as well as feasibility tests with classical assumption tests, Simultaneous and Partial hypothesis testing. The results of this study indicate that the factors affecting income distribution inequality in the Province of the Bangka Belitung Islands are economic growth, human development, poverty, and unemployment by 60.9 percent. Other factors influence the remaining 39.1 percent. Partially, economic growth has a positive and significant effect of 30 percent with a regression coefficient of 0.009. Human development has a negative and significant effect of 55.5 percent with a regression coefficient of -0.006, and poverty has a negative and insignificant effect of 25.8 percent with a regression coefficient of -0.004, unemployment has a negative and insignificant effect of 11.1 percent with a regression coefficient of -0.003. In conclusion, it turns out that the human development factor has a very large role in reducing the inequality in income distribution in the Province of the Bangka Belitung Islands. So, recommendations to the Provincial Government need to continue to improve Human Development by improving education, health, and people's purchasing power, as well as socializing the importance of Human Development in reducing the level of inequality in development outcomes to the Regency/City Government in the Province of the Bangka Belitung Islands Province.
... Salah satu bentuk pertumbuhan pendapatan. Program penanggulangan kemiskinan sebenarnya terus dilaksanakan pemerintah mulai dari inpres desa tertinggal (IDT), program kompensasi pengalihan subsidi BBM dan lain sebagainya (Abdulah, 2013). Pada tingkat nasional telah ditetapkan prioritas sasaran pembangunan nasional. ...
Development aims to improve the welfare of the people. To improve welfare, it requires economic growth that is quitte high, stable and equiable in income. High enough economic growth must be balanced with equity, so as not to create ineqalty. Growth is not a goal, but only a tool as a process to reduce proverty and redurce inequality in income distribution. Hence the reduction of inequality ofincome distribution is the essence of development results can be enjoyed fairly and equitably by all people, the problemof unequal income distribution will not arise. If the economic proformance is betteror is experiencing progress, then all people must also feel the impact of this progress in the form of an increase in the level of income. Because the distribution of income is very useful in increasing economic growth and development,it is important for us to know whar factor affect in the inequality of income didtribution in Java. This variables used are econoc growth, provincial minium wages , open employment rate, ddegree of fiscal decentralization and growth in the human development index with multiple regression analysis for 2014-2019. The results showed that the only variables affecting income inequality were the provincial minimum wage and the open unemployment rate. The open unemployment rate variable has a coefficient value of -0.0502438. This means that when the exchange rate increases by Rp.1, income inequality will decrease by 0.0502438%. The open unemployment rate variable has a coefficient value of 0.0056812. This means that when the open unemployment rate increases by one percent, income inequality will increase by 0.0056812%. Meanwhile, economic growth, the degree of fiscal decentralization and the human development index have no effect on income inequality
... This study is not consistent with [18] stated that the regional minimum wage an insignificant negative effect on income inequality in the District/Town in South Sulawesi province. However, the results of this study are the same as for [19] stated that the wage variable has significant and positive impact in Central Java province. and [20] also stated that there is a positive relationship between income inequality and the minimum wage, where the higher in the minimum wage will increase inequality. ...
... The neo-classical theory says that an increase in the minimum wage will reduce labor, unemployment increases which will ultimately have an impact on increasing poverty and inequality. Abdulah (2013) and Sungkar et al. (2015) find that minimum wage has a significant positive effect on income inequality. ...
Previous studies on the association between migration outflow and income inequality have shown mixed findings. Some find that migration outflow reduces income inequality, but others find that migration outflow increases income inequality. This study aims to analyze the effect of migration outflow on income inequality in Central Java Province with two control variables: mean years of schooling and minimum wage. Central Java was chosen as the research location because it is the province with the highest migration outflow. This study uses secondary, time series data for the period 2000-2018 consisting of income inequality as measured by the Gini ratio (percent), migration outflow (people), meanyears of schooling (years), and minimum wage (rupiah). Data were obtained from BPS Central Java and analyzed with multiple linear regression. The results show that migration outflow and mean years of schooling have a negative significant effect and minimum wage has a positive significant effect on income inequality. This findings imply that migration outflow and improvement of the quality of human resources through education can be solutions to reduce poverty and income inequality, while minimum wage actually increases inequality, which may be due to the large portion of population engaging in agriculture and the informal sector.
... Between-regional inequality is decomposed into subgroups including income, other diverse unit characteristics and heterogeneity which give rise to between-regional trends in inequality and inter-sectoral economics in an area (Kuncoro, 2011;Ramos & Coimbra, 2009). Some studies of inequality at different levels, ranging from international inequality (Ezcurra & Pascual, 2008;Habanik, Hostak, & Kutik, 2013;Postoiu & Bușega, 2015;Rodriguez-Pose & Ezcurra, 2010), inter-province outside of Indonesia (Antonescu, 2012;Bonet, 2006;Fitrawaty, Maipita, Hermawan, & Rahman, 2018;Islam & Noman, 2015;Wijerathna, Bandara, Smith, & Naranpanawa, 2014), inter-province in Indonesia (Aritenang, 2014;Fadli, 2014;Mahardiki & Santoso, 2013;Zakaria, 2013), inter-city outside of Java Island (Arham, 2014;Baransano, Putri, Achsani, & Kolopaking, 2016;Yuliani, 2015), Inter-city in Java Island (Abdulah, 2013;Kurniawan & Sugiyanto, 2013), regional (Cahyono, Subroto, & Anwar, 2017;Suseno, 2015) and inter-sub-district in a city (Nugroho, 2014). There is also research on pre-post-crisis inequality (Đoki, Fröhlich, & Bakaric, 2016), inequality after regional expansion (Dhyatmika & Atmanti, 2013) and differences in the conditions of inequality in origin district and newdistrict (Panjawa, Samudro, & Soesilo, 2018). ...
This study analyzes spatial inequality through a causal relationship between inequality and economic growth within-recidency, between-recidency and overall in Central Java.The analytical tool used is the Direct Error Correction Model causality. This study shows that spatial concentrations throughout the observation period are quite high. In the 2001-2008 period there was an increasing tendency for spatialconcentration, reflecting the decline in the distribution of the Gross Regional Domestic Product (GRDP) share of districts and cities in Central Java. We also obtained similar findings in a number of regions both within and between-recidency. Post-2008, spatial concentration tends to decrease, indicating the distribution of the Gross Regional Domestic Product share. Other findings indicate a one-way relationship shown economic growth towards inequality. Another important contribution is that economic growth in inequality only occurs in the long term. Thus there has been convergence because of the increase ineconomic growth which is able to reduce inequality in all areas of Central Java, including within and between-recidency. This proves that during the implementation of regional autonomy there is a spread effect greater than the backwash effect in Central Java, including within and between-recidency.
... Other studies related to income inequality are relatively large. Abdulah [21] conducted research on the factors that influence income inequality in Central Java. The results show that there are only two significant variables that cause inequality, namely the economic output share received by employers and wages. ...
This study aims to analyze the role of Micro Small Enterprises (MSEs) and Medium-Large Enterprises (MLEs) in addressing income inequality in all districts/cities in Aceh Province and also analyze the most dominant variables that reduce the community income gap. This study uses 2016 Economic Census of BPS province of Aceh for 23 districts/cities and Gini Ratio for community income gap variables. The results showed that the number of MSEs units, the average MSEsworkers, the total wages received by the SMEs workers, the SMEs wage average, and the district/city economic growth in 2016 had a significant effect on the income inequality in the districts/cities of Aceh Province. While the number of MSEs workers, the number of MLEs units, the number of MLEs workers, the average of MLEs workers, the total wages of MLEs workers, and the average wage of MLEsworkers have not significantly influence to the community income gap. The only factor that has a significant influence in reducing the gap in community income is the total remuneration (wages) received by MSEs workers. The recommendation that can be given to be implemented immediately for the Aceh government is to strengthen MSEs, including cooperatives as the drivers of the Aceh's economic which can absorb more labor and compensation or wages received by workers also increases. Furthermore, the Government of Aceh, in this case, the Provincial Manpower Office and the Office that manages labors all districts/cities must monitor the application of the Provincial Minimum Wage (PMW) for MSEs which have been under-emphasized for various reasons and consider.
p>East Nusa Tenggara Province is one of the provinces in Indonesia in the form of an archipelago and geographically borders directly with the State of Timor Leste. This province has a problem with a fairly high poverty rate, in fact it was recorded as the 3rd highest in Indonesia after the provinces of Papua and West Papua. Because it is an archipelagic province, the problems of disparity in regional development, income inequality and poverty cannot be avoided. The existence of this disparity symptom does not only lie in regional development, but this disparity occurs in the income and GDP-forming sectors. Therefore the main goal to be achieved in this research is to identify areas in NTT Province which are still classified as lagging behind, and how to find the economic base sector as a leading sector so that it can be used as a locomotive for regional development so that in turn it is able to reduce regional inequality, income distribution and poverty. The analytical tools used are Theil Entrophy Analysis, Klasen Typology, Location Quintient (LQ) Analysis and Dynamic Location Quintien (DLQ) Analysis. The data needed is secondary data in the form of published documents from the BPS Province of NTT from 2012-2018 for the purposes of analysis such as GRDP data, population and per capita income for each district in the province of NTT. The results of the analysis found that there were 3 regencies that were classified as developed and fast growing, 3 regencies which were categorized as developed but depressed areas,</p
This study aims to determine the impact of economic sector relations (agriculture, industrial, finance), education (literacy), provincial minimum wages and infrastructure (electricity, clean water and sanitation) on income inequality in Indonesia. The data used in this study are secondary data for 2010-2018 period from Central Bureau of Statistics and The Indonesia Database for Policy and Economic Research which is processed using panel data regression method and instrumental variables. Based on the estimation result, it shows that the variables of the agricultural sector, industrial sector, literacy and sanitation infrastructure are able to reduce income inequality in Indonesia in contrast to the result of the financial sector variables that have not been able to reduce income inequality. Meanwhile, the provincial minimum wage, electricity and clean water infrastructure variables have no effect on income inequality in Indonesia.
Sitiarjo merupakan salah satu desa rawan bencana banjir di Kabupaten Malang. Sitiarjo
memiliki profil wilayah yang rendah dibandingkan daerah sekitarnya, terdapat dua sungai, dan
terdampak air pasang laut. Kondisi tersebut menjadi faktor mendasar terjadinya banjir bandang di
Sitiarjo. Disamping faktor itu terdapat faktor lainnya yang menyebabkan bencana banjir tersebut.
Berbagai faktor menjadi pendukung banjir bandang Sitiarjo, dimana periode kebencanaannya semakin
memendek dari tahun ke tahun. Melihat hal tersebut, masyarakat Sitiarjo memiliki pengalaman yang
dihasilkan dari proses adaptasi lingkungan. Pengalaman itu merupakan mitigasi bencana banjir
bandang berbasis kearifan lokal. Penelitian ini bertujuan mengidentifikasi mitigasi banjir bandang
berbasis kearifan lokal masyarakat Sitiarjo. Penelitian ini menggunakan metode penelitian kualitatif
dengan pendekatan historis. Teknik pengumpulan data dilakukan dengan studi literatur, observasi,
wawancara, dokumentasi, dan analisis trianggulasi. Pengambilan sampel menggunakan teknik
purposive sampling. Teknik analisis yang digunakan yaitu analisis deskriptif. Hasil penelitian
menunjukkan mitigasi masyarakat Sitiarjo terdiri dari mitigasi non-struktural dan struktural. Mitigasi
non-struktural meliputi dimensi pengetahuan, nilai, solidaritas kelompok, dan mekanisme
pengambilan keputusan. Sedangkan mitigasi struktural masyarakat dapat dilihat berdasarkan dimensi
mitigasi mekanik. Mitigasi bencana berbasis kearifan lokal masyarakat Sitiarjo berkontribusi dalam
meminimalisir risiko bencana banjir bandang. Namun lambat laun kearifan lokal masyarakat mulai
memudar. Melihat hal tersebut, perlu adanya penguatan nilai kearifan lokal masyarakat dari berbagai
belah pihak. Diharapkan agar dapat menjadi upaya mitigasi bencana banjir bandang yang efektif oleh
masyarakat lokal.
