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2. Literature ReviewIncome Inequali

2. Literature Review
Income Inequality Measures: ncome inequality in the paper refers to “economic inequality” between groups in population. There are many methods the measure inequality in the literature. Popular measure of income inequality is the Gini coefficients. This ranges the income inequality for 0 to 1, which 0 is the perfect equality and 1 is the perfect income inequality. Other measures are Theils T and Theils L, which allow decomposing the income inequality into parts such as rural and urban areas Atkinson’s class of income inequality is more general and it sometime be used (Haughton & Khandker, 2009). With the about measures of income inequality have the advantage that they do know to show the effecting factors to the income inequality level. In this paper, the authors will discuss more on the regression-based approach to explain the factors of income inequality by employing development policy review and an econometric regression model.
Regression-based Approach: Income inequality can be measured by the differences of income or expenditure per capita. It is linked with skill, education, opportunities, happiness, health, life expectancy, welfare, assets and social mobility (Heshmati, 2004). The studies of income inequality have been conducted for more than the past three decades. This section examines the progress of income inequality on household studies, with special attention given to income inequality indices and regression-based composition approach. Shorrocks (1980, 1982) decomposed income inequality by income sources and population subgroups.
e mentioned “the quantitative significance of income variations associated with age, sex, race, occupation, the level of education, and so on”. He e argued that income is contributed by different sources, and that income inequality can be analyzed by the variances of these sources. Oaxaca (1973) and Blinder (1973) developed the regression-based method for measuring income inequality.
They used this method to measure inequality of wage in labor economics. They employed variables known as “individual characteristics” in their regression, and separated their models into two groups to quantify the inequality of wage income. Their model tried to make an explanation for the reason of “whites earn much higher wages than blacks and males earn substantially higher wages than females” “Discrimination coefficient” was mentioned by both of the authors to explain why the differential wagesexist in case of other “characteristics” do not change (Blinder, 1973; Oaxaca, 1973), and (Adger, 1999).
Fields & Yoo (2000) and Fields (2003) further developed the method by using income generating equation to “account for” or “decompose” inequality in a country and its change over time. Gunderson ((1989) identified the discrimination of wages between male and female. In defining the gap of wages, he proposed some methods such as narrowing defined occupation and regression wage decomposition. He applied the regression that breaks down wage differentials by the difference of “characteristics” and “structure” between male and female. Pracharopoulos and Patrinos (1994) attempted to identify the ethnic discrimination in Latin American countries where almost all of the populations are indigenous peoples. They used multivariate regression analysis method popularized by Oaxaca (1973) and Blinder (1973). Their study concluded that indigenous people are poor, illiterate, and prone to health problems and disadvantage in earning. They also explained that less education is strongly correlated to poverty.
Interestingly, their statistical results showed that much of earnings differential between indigenous and non-indigenous workers would disappear by equalizing human capital characteristics. They finally proposed that a further research should “combine the quantitative approach taken with qualitative analysis, such as the participatory-observation research approach (or participatory poverty assessment)”. Without this qualitative data, probable reasons for the discrepancy, including race, access to training, and
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2. literatur Review
langkah-langkah ketidaksetaraan pendapatan: ncome ketidaksetaraan dalam karya mengacu pada "ketidaksetaraan ekonomi" antara kelompok penduduk. Ada banyak metode mengukur ketidaksetaraan dalam literatur. Populer ukuran ketidaksetaraan pendapatan adalah koefisien Gini. Ini berkisar ketidaksetaraan pendapatan untuk 0-1, 0 yang adalah persamaan sempurna dan 1 adalah ketidaksetaraan pendapatan sempurna. Langkah-langkah lain yang Theils T dan Theils L, yang memungkinkan membusuk ketidaksetaraan pendapatan menjadi bagian seperti kelas daerah pedesaan dan perkotaan Atkinson ketidaksetaraan pendapatan adalah lebih umum dan kadang-kadang digunakan (Haughton & Khandker, 2009). Dengan tentang langkah-langkah ketidaksetaraan pendapatan memiliki keuntungan bahwa mereka tahu untuk menunjukkan faktor-faktor effecting ke tingkat ketidaksetaraan pendapatan. Dalam tulisan ini, penulis akan membahas lebih lanjut pada pendekatan berbasis regresi untuk menjelaskan faktor ketidaksetaraan pendapatan oleh mempekerjakan Tinjauan kebijakan pembangunan dan model regresi ekonometrik.
pendekatan berbasis regresi: ketidaksetaraan pendapatan dapat diukur dengan perbedaan pendapatan atau pengeluaran per kapita. Hal ini terkait dengan keterampilan, pendidikan, peluang, kebahagiaan, Kesehatan, harapan hidup, kesejahteraan, aset dan mobilitas sosial (Heshmati, 2004). Studi tentang ketidaksetaraan pendapatan telah dilakukan untuk lebih dari tiga dekade. Bagian ini mengkaji kemajuan ketidaksetaraan pendapatan rumah tangga Studies, dengan perhatian khusus diberikan kepada pendapatan ketidaksetaraan indeks dan pendekatan berbasis regresi komposisi. Shorrocks (1980, ketidaksetaraan pendapatan diurai 1982) oleh sumber pendapatan dan subkumpulan-subkumpulan populasi.
e disebutkan "kuantitatif pentingnya variasi pendapatan yang terkait dengan usia, jenis kelamin, ras, pendudukan, tingkat pendidikan, dan seterusnya". E ia berpendapat bahwa pendapatan disumbangkan oleh berbagai sumber, dan ketidaksetaraan pendapatan dapat dianalisis oleh varians sumber ini. Oaxaca (1973) dan Blinder (1973) mengembangkan metode berbasis regresi untuk mengukur pendapatan ketidaksetaraan.
mereka menggunakan metode ini untuk mengukur ketidaksamaan dari upah tenaga kerja ekonomi. Mereka dipekerjakan variabel yang dikenal sebagai "karakteristik individu" di regresi mereka, dan model mereka dipisahkan dalam dua kelompok untuk mengukur ketidaksetaraan pendapatan upah. Model mereka mencoba untuk membuat sebuah penjelasan untuk alasan "putih mendapatkan banyak upah yang lebih tinggi daripada orang kulit hitam dan laki-laki mendapatkan upah yang secara substansial lebih tinggi dari pada betina" "diskriminasi koefisien" disebutkan oleh kedua penulis menjelaskan mengapa wagesexist diferensial dalam hal lain "karakteristik" tidak berubah (Blinder, 1973; Oaxaca, 1973), dan (Adger, 1999).
Bidang & Yoo (2000) dan bidang (2003) dikembangkan lebih lanjut metode dengan menggunakan persamaan yang menghasilkan pendapatan untuk "account untuk" atau "terurai" ketidaksetaraan dalam negara dan perubahannya seiring waktu. Gunderson ((1989) mengidentifikasi diskriminasi upah antara laki-laki dan perempuan. Dalam mendefinisikan kesenjangan upah, ia mengusulkan beberapa metode seperti penyempitan didefinisikan pendudukan dan regresi upah dekomposisi. Ia diterapkan regresi yang rusak perbedaan upah oleh perbedaan "karakteristik" dan "struktur" antara laki-laki dan perempuan. Pracharopoulos dan Patrinos (1994) berusaha untuk mengidentifikasi diskriminasi etnis di negara-negara Amerika Latin yang mana hampir semua populasi adalah adat. Mereka menggunakan metode analisis multivarian regresi yang dipopulerkan oleh Oaxaca (1973) dan Blinder (1973). Studi mereka menyimpulkan bahwa masyarakat adat miskin, buta huruf dan rentan terhadap masalah kesehatan dan kelemahan dalam penghasilan. Mereka juga menjelaskan bahwa pendidikan kurang sangat berkorelasi untuk kemiskinan.
Menariknya, hasil Statistik menunjukkan bahwa sebagian besar pendapatan diferensial antara pribumi dan non-pribumi pekerja akan hilang oleh penyetaraan karakteristik modal manusia. Mereka akhirnya mengusulkan bahwa penelitian lebih lanjut harus "menggabungkan pendekatan kuantitatif yang diambil dengan analisis secara kualitatif, seperti pendekatan partisipatif-pengamatan penelitian (atau partisipatif poverty assessment)". Tanpa ini data kualitatif, kemungkinan alasan untuk perbedaan tersebut, termasuk ras, akses ke pelatihan, dan
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2. Literature Review
Income Inequality Measures: ncome inequality in the paper refers to “economic inequality” between groups in population. There are many methods the measure inequality in the literature. Popular measure of income inequality is the Gini coefficients. This ranges the income inequality for 0 to 1, which 0 is the perfect equality and 1 is the perfect income inequality. Other measures are Theils T and Theils L, which allow decomposing the income inequality into parts such as rural and urban areas Atkinson’s class of income inequality is more general and it sometime be used (Haughton & Khandker, 2009). With the about measures of income inequality have the advantage that they do know to show the effecting factors to the income inequality level. In this paper, the authors will discuss more on the regression-based approach to explain the factors of income inequality by employing development policy review and an econometric regression model.
Regression-based Approach: Income inequality can be measured by the differences of income or expenditure per capita. It is linked with skill, education, opportunities, happiness, health, life expectancy, welfare, assets and social mobility (Heshmati, 2004). The studies of income inequality have been conducted for more than the past three decades. This section examines the progress of income inequality on household studies, with special attention given to income inequality indices and regression-based composition approach. Shorrocks (1980, 1982) decomposed income inequality by income sources and population subgroups.
e mentioned “the quantitative significance of income variations associated with age, sex, race, occupation, the level of education, and so on”. He e argued that income is contributed by different sources, and that income inequality can be analyzed by the variances of these sources. Oaxaca (1973) and Blinder (1973) developed the regression-based method for measuring income inequality.
They used this method to measure inequality of wage in labor economics. They employed variables known as “individual characteristics” in their regression, and separated their models into two groups to quantify the inequality of wage income. Their model tried to make an explanation for the reason of “whites earn much higher wages than blacks and males earn substantially higher wages than females” “Discrimination coefficient” was mentioned by both of the authors to explain why the differential wagesexist in case of other “characteristics” do not change (Blinder, 1973; Oaxaca, 1973), and (Adger, 1999).
Fields & Yoo (2000) and Fields (2003) further developed the method by using income generating equation to “account for” or “decompose” inequality in a country and its change over time. Gunderson ((1989) identified the discrimination of wages between male and female. In defining the gap of wages, he proposed some methods such as narrowing defined occupation and regression wage decomposition. He applied the regression that breaks down wage differentials by the difference of “characteristics” and “structure” between male and female. Pracharopoulos and Patrinos (1994) attempted to identify the ethnic discrimination in Latin American countries where almost all of the populations are indigenous peoples. They used multivariate regression analysis method popularized by Oaxaca (1973) and Blinder (1973). Their study concluded that indigenous people are poor, illiterate, and prone to health problems and disadvantage in earning. They also explained that less education is strongly correlated to poverty.
Interestingly, their statistical results showed that much of earnings differential between indigenous and non-indigenous workers would disappear by equalizing human capital characteristics. They finally proposed that a further research should “combine the quantitative approach taken with qualitative analysis, such as the participatory-observation research approach (or participatory poverty assessment)”. Without this qualitative data, probable reasons for the discrepancy, including race, access to training, and
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