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1

Macció, Jimena, and Ann Mitchell. "Multidimensional Poverty Measurement in Segregated Cities." Revista Desarrollo y Sociedad, no. 93 (March 3, 2023): 101–37. http://dx.doi.org/10.13043/dys.93.3.

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This paper illustrates the insights that can be gained from using a multidimensional poverty measurement method based on the capability approach to analyse the scale, characteristics, and spatial distribution of poverty in segregated cities. We assess the poverty gaps between formal and informal neighbourhoods and across districts, compare the results with income-based poverty estimates, and analyse the dimensional composition of poverty and disparities across population subgroups. The results show a weaker correlation between multidimensional and income-based measures and less overlap in term
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Sarwar Awan, Masood, Muhammad Waqas, and Muhammad Amir Aslam. "Multidimensional measurement of poverty in Pakistan: Provincial analysis." Nóesis. Revista de Ciencias Sociales y Humanidades 24, no. 48 (2015): 55–72. http://dx.doi.org/10.20983/noesis.2015.2.2.

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Ahmed Hasan, Mustafa, and Eman Muhammad al-Mashhadani. "Robustness & Measurement of Multidimensional Poverty Index in Iraq." Journal of Economics and Administrative Sciences 30, no. 144 (2024): 485–500. https://doi.org/10.33095/n4w7ca27.

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Purpose: This paper aims to measure poverty in Iraq and its sub-indicators using a multidimensional methodology. It also examines the robustness and sensitivity of the estimated indicators and models the determinants of poverty through a binary logistic regression approach. Theoretical framework: Poverty is commonly measured through two primary methodologies. The first is a one-dimensional approach, which defines poverty as insufficient income to meet a specific set of needs required for a decent standard of living. The second is a multidimensional approach, which aligns with Amartya Sen's cap
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Sharma, Lalit, and Kavita Chakravarty. "Multidimensional Poverty Measurement in Haryana." Indian Journal of Human Development 9, no. 1 (2015): 89–101. http://dx.doi.org/10.1177/0973703020150106.

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Alkire, Sabina, and James Foster. "Counting and multidimensional poverty measurement." Journal of Public Economics 95, no. 7-8 (2011): 476–87. http://dx.doi.org/10.1016/j.jpubeco.2010.11.006.

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Bastos, Amélia, and Carla Machado. "Child poverty: a multidimensional measurement." International Journal of Social Economics 36, no. 3 (2009): 237–51. http://dx.doi.org/10.1108/03068290910932738.

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Lairatri Prabandari, Anestia, Ismu Rini Dwi Ari, and Wara Indira Rukmi. "Multidimensional Poverty Measurement of Kotalama Sub-District, Malang City." International Journal of Science and Research (IJSR) 10, no. 7 (2021): 1335–40. https://doi.org/10.21275/sr21723070320.

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Nazarbaeva, Elena A., Alina I. Pishnyak, and Natalia V. Khalina. "Multidimensional poverty: Methodology and calculations on Russian data." Russian Journal of Economics 8, no. (4) (2022): 352–80. https://doi.org/10.32609/j.ruje.8.81710.

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This article focuses on Multidimensional poverty index (MPI)—the alternative approach to poverty measurement. While the official monetary approach is based on a comparison of income with a certain poverty line (until 2021 in Russia it was based on the minimum subsistence level, since 2021 it has been calculated as a share of median income of the population), the MPI also includes deprivations that poor people may face. The text contains the description of the index calculation methodology, the results of its computation on Russian data (Statistical Survey of Income and Participation in Social
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Zhao, Bo, Phaik Kin Cheah, and Priscilla Moses. "Measurement and determinants of multidimensional urban poverty: Evidence from Shandong Province, China." PLOS ONE 19, no. 5 (2024): e0300263. http://dx.doi.org/10.1371/journal.pone.0300263.

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China eliminated rural poverty under current poverty standards in 2020. However, compared with rural poverty, urban poverty in China has been somewhat neglected. This paper aims to discover the changes and determinants of multidimensional urban poverty in Shandong Province, a representative province in Eastern China. Using a nationally representative panel dataset, the China Family Panel Studies, and the Dual Cutoff method, this study creates a multidimensional poverty index with four dimensions and 11 indicators to measure urban poverty in Shandong Province. This paper discovers that while th
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Thimmaiah, Navitha. "Multidimensional Measurement of Poverty in Mysore." Indian Economic Journal 62, no. 4 (2015): 1265–88. http://dx.doi.org/10.1177/0019466220150406.

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Bennett, Christopher J., and Shabana Mitra. "Multidimensional Poverty: Measurement, Estimation, and Inference." Econometric Reviews 32, no. 1 (2013): 57–83. http://dx.doi.org/10.1080/07474938.2012.690331.

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Decancq, Koen, Marc Fleurbaey, and François Maniquet. "Multidimensional poverty measurement with individual preferences." Journal of Economic Inequality 17, no. 1 (2019): 29–49. http://dx.doi.org/10.1007/s10888-019-09407-9.

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Dirksen, Jakob, and Sabina Alkire. "Children and Multidimensional Poverty: Four Measurement Strategies." Sustainability 13, no. 16 (2021): 9108. http://dx.doi.org/10.3390/su13169108.

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Empirically, official multidimensional measures of poverty often show children to be the poorest age group. Such poverty measures and their analysis can be used to directly inform policies to reduce children’s multiple deprivations. This paper introduces methods to produce official national statistics on multidimensional poverty that inform child-focused anti-poverty policies. In doing so, it recognises the importance of parsimonious, consistent measures, given practical constraints such as policy makers’ time. The paper does not recommend constructing several disjoint poverty measures which c
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Muhammad Rahim Zaidi, Siti Hajar Mohd Asri, and Mohd Azmeer Abu Bakar. "Multidimensional Poverty Among B40 in Kuala Krai, Kelantan." Journal of Asian Geography 3, no. 1 (2024): 61–69. http://dx.doi.org/10.36777/jag2024.3.1.8.

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Poverty is a phenomenon faced by an individual or a family without their own will. The poor can be identified through poverty measurement as a first step. The objective of this study is to identify the indicators that define the multidimensional poverty of the B40 group in Kuala Krai and examine the needs of the population in helping them to eradicate poverty. Poverty measurement is divided into two types: unidimensional poverty measurement, which shows individual poverty in terms of income only, and multidimensional poverty measurement, which is related to poverty in the holistic aspect of hu
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Putri, Salshabilla Herdyanti Martoni, and Shofwan. "IMPLEMENTASI MULTIDIMENSIONAL POVERTY INDEX DALAM MENGUKUR KEEFEKTIVITASAN PENGUKURAN KEMISKINAN DI INDONESIA." Journal of Development Economic and Social Studies 3, no. 3 (2024): 697–711. http://dx.doi.org/10.21776/jdess.2024.03.3.03.

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So far, measuring poverty in Indonesia still refers to the Poverty Line (GK) approach carried out by the Badan Pusat Statisitk (BPS), which is the institution given the authority to calculate poverty rates. Meanwhile, the problem of poverty today is no longer uni-dimensional but multidimensional. This research was conducted with the aim of applying the Multidimensional Poverty Index (MPI) in measuring the effectiveness of measuring the Poverty Line (GK) approach in Indonesia. Then, this research provides an outline of the advantages and disadvantages of poverty measurement in Indonesia and ana
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Nitin, Tanwar, and K. Hooda B. "Estimation of Aspect Based Multidimensional Poverty in Rural Haryana." Advances in Research 10, no. 5 (2017): 1–8. https://doi.org/10.9734/AIR/2017/34765.

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The issue of poverty estimation in India has been drawing attention since independence. The process for measuring poverty in India was initiated in early sixties, when a working group from planning commission provided a quantification of minimum food and non-food requirements of individuals for a healthy living. Theoretical developments on poverty measurement have gradually shifted from the traditional unidimensional approach to the multidimensional concept. [1] Pointed out that the study of poverty should identify and analyze attributes than monetary which directly influence the individual we
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Chandra, Kapil Kumar, and B. L. Sonekar. "Measurement and Comparison of Poverty in Abhujmadiya Tribe: Income-based and Deprivation-based Poverty Approach." Journal of Ravishankar University (PART-A) 30, no. 2 (2024): 8–17. http://dx.doi.org/10.52228/jrua.2024-30-2-2.

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The present paper is attempted to measure and compare the difference and discrepancy between the income-based and deprivation-based poverty measurement in poverty of Abhujmadiya tribes of Chhattisgarh. Two international poverty measurement approach is considered for poverty measurement of Abhujmadiya tribes, first income-based measurement developed by World Bank and second, Multidimensional Poverty Index developed by United Nation Development Program (UNDP). Research study is based on primary data of 80 household collected from 8 village of 2 block of Narayanpur district of Chhattisgarh State.
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Gallardo, Mauricio. "Measuring Vulnerability to Multidimensional Poverty." Social Indicators Research 148, no. 1 (2019): 67–103. http://dx.doi.org/10.1007/s11205-019-02192-y.

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Abstract A method to measure vulnerability to multidimensional poverty is proposed under a mean–risk behaviour approach. We extend the unidimensional downside mean–semideviation measurement of vulnerability to poverty towards the multidimensional space by incorporating this approach into Alkire and Foster’s multidimensional counting framework. The new approach is called the vulnerability to multidimensional poverty index (VMPI), alluding to the fact that it can be used to assess vulnerability to poverty measured by the multidimensional poverty index (MPI). The proposed family of vulnerability
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Ambel, Alemayehu Azeze, Harriet Kasidi Mugera, and Robert E. S. Bain. "Accounting for drinking water quality in measuring multidimensional poverty in Ethiopia." PLOS ONE 15, no. 12 (2020): e0243921. http://dx.doi.org/10.1371/journal.pone.0243921.

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The Multidimensional Poverty Index is used increasingly to measure poverty in developing countries. The index is constructed using selected indicators that cover health, education, and living standards dimensions. The accuracy of this tool, however, depends on how each indicator is measured. This study explores the effect of accounting for water quality in multidimensional poverty measurement. Access to drinking water is traditionally measured by water source types. The study uses a more comprehensive measure, access to safely managed drinking water services, which are free from E. coli contam
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Choi Gyun, 권종희, and 서병수. "Measurement of Multidimensional Poverty by Counting Approach." Korean Journal of Social Welfare 63, no. 1 (2011): 85–111. http://dx.doi.org/10.20970/kasw.2011.63.1.004.

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Alkire, Sabina, and James Foster. "Understandings and misunderstandings of multidimensional poverty measurement." Journal of Economic Inequality 9, no. 2 (2011): 289–314. http://dx.doi.org/10.1007/s10888-011-9181-4.

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Alkire, Sabina, and Maria Emma Santos. "A Multidimensional Approach: Poverty Measurement & Beyond." Social Indicators Research 112, no. 2 (2013): 239–57. http://dx.doi.org/10.1007/s11205-013-0257-3.

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Delalić, Adela, Rabija Somun-Kapetanović, and Emina Resić. "New multidimensional approaches to poverty measurement in Bosnia and Herzegovina." Croatian Review of Economic, Business and Social Statistics 3, no. 1 (2017): 1–15. http://dx.doi.org/10.1515/crebss-2017-0001.

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AbstractUnlike the standard unidimensional poverty indices, based mostly on monetary poverty measures, multidimensional poverty indices may include numerous non-monetary poverty indicators. This study utilized fuzzy and Alkire – Foster (AF) and fuzzy methodology to assess the poverty level in Bosnia and Herzegovina (B&H) and to compare the results with official poverty assessments. In addition to consumption as a monetary measure, we constructed AF and fuzzy indices by including numerous non-monetary measures that indicate housing quality, possession of durable goods and the household stru
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Chakrabartty, Satyendra Nath. "Methodological issues of Poverty Measurement." Current Research Journal of Social Sciences and Humanities 7, no. 2 (2024): 138–47. https://doi.org/10.12944/crjssh.7.2.08.

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Issues relating to defining poverty as lack of resources like income and wealth to a household or individual to meet the basic needs to maintain a reasonable standard of living in a given society have been addressed along with various approaches to measure poverty. Limitations of Multidimensional Poverty Index (MPI) including aggregation of the chosen indicators have been discussed. The paper suggests multiplicative aggregation of ratios of chosen indicators at current period and the base period to find an index of overall poverty status of a country at the C-th time period over the based peri
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Sial, Maqbool H., Asma Noreen, and Rehmat Ullah Awan. "Measuring Multidimensional Poverty and Inequality in Pakistan." Pakistan Development Review 54, no. 4I-II (2015): 685–98. http://dx.doi.org/10.30541/v54i4i-iipp.685-698.

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The key development objective of Pakistan, since its existence, has been to reduce poverty, inequality and to improve the condition of its people. While this goal seems very important in itself yet is also necessary for the eradication of other social, political and economic problems. The objective to eradicate poverty has remained same but methodology to analysing this has changed. It can be said that failure of most of the poverty strategies is due to lack of clear choice of poverty definition. A sound development policy including poverty alleviation hinges upon accurate and well-defined mea
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Phat, Huynh Dinh. "Indicators used in measuring poverty under the multidimentional approach: a case study in Quang Ngai province." Science & Technology Development Journal - Economics - Law and Management 4, no. 2 (2020): First. http://dx.doi.org/10.32508/stdjelm.v4i2.624.

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Since the concept of multidimensional poverty was initiated in Sen’s works, coupled with the national database providing increasingly complete information on meeting the basic needs of the society, the measurement and evaluation of multidimensional poverty have become popular and attracted the attention of many researchers. The multidimensional poverty line can be based on indicators that are not related to incomes or expenditures. However, it includes other dimensions such as the lack of basic social services. Hence, measuring and implementing poverty reduction policies under the multidimensi
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Lekobane, Khaufelo Raymond, and Keetie Roelen. "Leaving No One Behind: Multidimensional Child Poverty in Botswana." Child Indicators Research 13, no. 6 (2020): 2003–30. http://dx.doi.org/10.1007/s12187-020-09744-6.

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Abstract Child poverty measurement is vital for informing policies and for improving children’s lives. Nevertheless, efforts to measure (child) poverty remain dominated mainly by monetary approaches, and many countries fail to monitor multidimensional child poverty. Using the 2015/2016 Botswana multi-topic household survey, this study developed a child-centred, individual-level and composite measure that offers nationally relevant and context-specific insights into the magnitude and depth of multidimensional child poverty in Botswana. In particular, it did so through the lens of Leave No One B
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Liu, Weixia. "MEASUREMENT OF MULTI-DIMENSIONAL POVERTY OF THE ELDERLY IN CHINA." Socio Economy And Policy Studies 4, no. 1 (2023): 31–34. https://doi.org/10.26480/seps.01.2024.31.34.

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Based on CLHLS data, this paper uses the A-F method to measure multidimensional poverty among the elderly in China. In analyzing the dimensions of elderly poverty, the study emphasizes the inter-generational effects of education and economic support on poverty alleviation among the elderly. Empirical studies show that the poverty incidence rate of most indicators is decreasing, but the incidence rate of elderly psychological health poverty shows a slight rise. Inter-generational support alleviates poverty for the elderly who are in relatively higher levels of multidimensional poverty, but exac
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Tripathi, Sabyasachi, and Komali Yenneti. "Measurement of Multidimensional Poverty in India: A State-level Analysis." Indian Journal of Human Development 14, no. 2 (2020): 257–74. http://dx.doi.org/10.1177/0973703020944763.

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This article measures Multidimensional Poverty Index (MPI) in India using National Sample Survey (NSS) data on “Consumption Expenditure” for the period 2004–2005 and 2011–2012, adopting Alkire and Foster’s (2011, Journal of Public Economics, vol. 95, pp. 476–487) methodology. It considers three main indicators, namely standard of living, education and income at the level of households or persons. The results show that multidimensional poverty head count has declined from 62.2 per cent in 2004–2005 to 38.4 per cent in 2011–2012. However, separate rural and urban regional analysis clearly indica
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Cheng, Jing, and Xiaobin Yu. "Spatial and temporal differences and convergence analysis of multidimensional relative poverty in ethnic areas." PLOS ONE 19, no. 4 (2024): e0301679. http://dx.doi.org/10.1371/journal.pone.0301679.

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Reducing multidimensional relative poverty is one of the important issues in the current global poverty governance field. This article takes 12 ethnic regions in China as the research object and constructs a multidimensional relative poverty measurement system. The calculated multidimensional relative poverty index is decomposed according to provinces, cities, dimensions, and indicators. Then, the Dagum Gini coefficient and convergence analysis are used to analyze spatiotemporal heterogeneity and convergence characteristics. The results show that the multi-dimensional relative poverty situatio
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Jamal, Haroon. "Assessing Poverty with Non-Income Deprivation Indicators: Pakistan, 2008-09." Pakistan Development Review 50, no. 4II (2011): 913–27. http://dx.doi.org/10.30541/v50i4iipp.913-927.

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The approach to measure poverty in terms of financial deprivation has been widely criticised in the literature of welfare and wellbeing. It is argued that to understand the complex phenomenon of poverty or to evaluate household or individual wellbeing, a multidimensional exercise is imperative. This research quantifies the level of multidimensional poverty in Pakistan using household data of Pakistan Social and Living Standard Measurement Survey. Multidimensional poverty in terms of the popular FGT (headcount, poverty gap, poverty severity) indices is estimated for the year 2009. Indicators of
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Thimmaiah, Navitha. "Multidimensional Measurement of Poverty: A Study in Mysore." Indian Journal of Human Development 9, no. 2 (2015): 235–59. http://dx.doi.org/10.1177/0973703020150205.

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Chattier, Priya. "Multidimensional, Gender-Sensitive Poverty Measurement: Perspectives from Fiji." Contemporary Pacific 28, no. 1 (2016): 31–57. http://dx.doi.org/10.1353/cp.2016.0012.

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Permanyer, Iñaki. "Book review of Multidimensional Poverty Measurement and Analysis." Journal of Economic Inequality 14, no. 3 (2016): 353–56. http://dx.doi.org/10.1007/s10888-016-9331-9.

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Emeka, Eze, and C. Alugbuo Justin. "Nigeria's multidimensional poverty analysis: A subgroup and dimensional breakdown." World Journal of Advanced Research and Reviews 11, no. 2 (2021): 219–26. https://doi.org/10.5281/zenodo.5336840.

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This study is an attempt to analyze the nature of multidimensional poverty in Nigeria in the light of recent data. The study used data from the Nigerian standard of living and measurement survey (LSMS) 2018/2019 to estimate the overall MPI for Nigeria, which included six indices of deprivation from four dimensions: consumption, education, energy, and housing. The study also performed a decomposition of multidimensional poverty across Nigerian regions, as well as a dimensional breakdown of multidimensional poverty across Nigeria and across regions. According to the study, Nigeria's multidim
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Pratama, Siectio Dicko, and Rizal Rahadiana. "Multidimensional Poverty and its Effect on the Economy of Aceh Province." Bappenas Working Papers 6, no. 2 (2023): 209–22. http://dx.doi.org/10.47266/bwp.v6i2.202.

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The first goal of Sustainable Development Goals, eliminating poverty in all forms, is closer to multidimensional poverty rather than official poverty statistics, which are measured using the basic need approach. Examining the trend of economic growth in Aceh during the past few years reveals the limitations of this strategy. Economic improvement has little effect on the poverty rate because it is only measured in one dimension. This research measures the poverty rate from various aspects by examining the forming factors first. The formed index will then be analyzed for its properness by involv
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Abdul Rahman, Muhamad Zulfadli, Mohammad Taqiuddin Mohamad, and Muhammad Shamshinor Abdul Azzis. "Indeks Kemiskinan Multidimensi Global: Analisis Menurut Perspektif Maqasid Syariah (Global Multidimensional Povety Index: An Analysis According to Maqasid Syariah Perspectives)." UMRAN - International Journal of Islamic and Civilizational Studies 9, no. 1 (2022): 1–22. http://dx.doi.org/10.11113/umran2022.9n1.544.

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Poverty is often associated with the issue of lack of income. However, when questions such as "do children get the education they deserve?", "does a family get the right health services?" and "does the community receive the clean water and electricity supply it needs?" cannot be answered well, then it is a sign that poverty still exists from a multidimensional view. This study applies library methods, textual and contextual analysis methods by taking into the five elements of Shariah Maqasid in the context of multidimensional poverty and extracted based on inductive, deductive, and comparative
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Deffinika, Ifan, Singgih Susilo, Budijanto ., et al. "Socio-Spatial Analysis of Poverty: A Comprehensive Study on Integrating Multidimensional Poverty Indices with Geographic Conditions in Krucil District, Probolinggo, Indonesia." Journal of Population and Social Studies 33 (October 30, 2024): 651–68. http://dx.doi.org/10.25133/jpssv332025.035.

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The role of geography in population studies is represented by the utilization of space in studying social issues. The study explores the intersection of geography and population studies by employing spatial analysis to examine social problems, particularly poverty. Focusing on the Krucil District in Probolinggo Regency, East Java, Indonesia, the research integrates multidimensional indicators of well-being to provide a comprehensive understanding of poverty. The Multidimensional Poverty Index (MPI) is a comprehensive poverty measurement tool at the individual and household levels. The urgent i
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Bulanova, M. A. "Poverty assessment in Russia: dependence on the measurement methodology." POWER AND ADMINISTRATION IN THE EAST OF RUSSIA 94, no. 1 (2021): 157–69. http://dx.doi.org/10.22394/1818-4049-2021-94-1-157-169.

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Poverty reduction is one of the main objectives of the state policy in the Russian Federation. In the decree of the President of the Russian Federation No. 474 of 21.07.2020 «On the national goals of the Russian Federation for the period up to 2030,» a target is determined - reducing the poverty level by half by 2030. To measure poverty in the Russian Federation until 2021, the absolute concept was used. Within the framework of this concept, it is planned to create a minimum standard on the basis of which the level of poverty was determined. In the Russian Federation, a consumer basket is adop
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Artha, Dwirani Puspa, and Misdawati Misdawati. "ANALISIS KEMISKINAN DENGAN PENDEKATAN MULTIDIMENSI DI JAWA BARAT." Jurnal Ekonomi dan Kebijakan Publik Indonesia 10, no. 1 (2023): 65–80. http://dx.doi.org/10.24815/ekapi.v10i1.37844.

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This paper attempts different approaches to analyzing poverty in West Java. The aim is to provide an alternative multidimensional measurement of poverty using Alkire-Foster methods based on 5 dimensions, namely health, education, standard of living, employment and wealth. We estimated multidimensional poverty index (MPI) and identified the poor using the SUSENAS 2020. We constructed the MPI using 19 indicators pertaining to 5 valuable dimensions of well-being. We find that 23% of populations fall below the poverty line. Another interesting result is multidimensional poverty is significantly hi
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Acet Dönmez, Gizem. "THE MANY FACES OF POVERTY: A COMPREHENSIVE ANALYSIS ON MEASUREMENT OF POVERTY IN TÜRKİYE." Ege Akademik Bakis (Ege Academic Review) 25, no. 2 (2025): 417–36. https://doi.org/10.21121/eab.20250211.

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Although poverty statistics serve as crucial economic and social indicators, their measurement varies depending on the chosen definition of poverty. This study examines whether poverty estimations in Türkiye significantly differ based on the definition used and explores which concept of poverty is most appropriate. Utilizing the SILC micro datasets from 2014 to 2021, the study estimates two absolute poverty measures, a subjective poverty measure, and a multidimensional poverty measure. The findings reveal that poverty rates are highly sensitive to the definition applied. For instance, while th
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Soseco, Thomas, Isnawati Hidayah, and Ayu Dwidyah Rini. "Gender Determinant on Multidimensional Poverty Index: Evidence from Indonesia." Jurnal Ilmu Sosial dan Ilmu Politik 26, no. 2 (2022): 137. http://dx.doi.org/10.22146/jsp.69320.

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Poverty measurement from a non-monetary aspect is needed as low-income individuals are not always multidimensionally poor, and vice versa. The focus should also be on the gender determinant potentially related to the inequality in wage, labour market, and the return of education, which can influence the household’s ability to achieve a higher standard of living and alleviate poverty. This paper discovers the contribution of gender determinants to multidimensional poverty conditions in Indonesia. This paper used logit estimation using National Socioeconomics Survey (Susenas) 2018. The data show
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Abdul Rahman, Mariah, Nor Samsiah Sani, Rusnita Hamdan, Zulaiha Ali Othman, and Azuraliza Abu Bakar. "A clustering approach to identify multidimensional poverty indicators for the bottom 40 percent group." PLOS ONE 16, no. 8 (2021): e0255312. http://dx.doi.org/10.1371/journal.pone.0255312.

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The Multidimensional Poverty Index (MPI) is an income-based poverty index which measures multiple deprivations alongside other relevant factors to determine and classify poverty. The implementation of a reliable MPI is one of the significant efforts by the Malaysian government to improve measures in alleviating poverty, in line with the recent policy for Bottom 40 Percent (B40) group. However, using this measurement, only 0.86% of Malaysians are regarded as multidimensionally poor, and this measurement was claimed to be irrelevant for Malaysia as a country that has rapid economic development.
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Emeka Eze and Justin C. Alugbuo. "Nigeria's multidimensional poverty analysis: A subgroup and dimensional breakdown." World Journal of Advanced Research and Reviews 11, no. 2 (2021): 219–26. http://dx.doi.org/10.30574/wjarr.2021.11.2.0383.

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This study is an attempt to analyze the nature of multidimensional poverty in Nigeria in the light of recent data. The study used data from the Nigerian standard of living and measurement survey (LSMS) 2018/2019 to estimate the overall MPI for Nigeria, which included six indices of deprivation from four dimensions: consumption, education, energy, and housing. The study also performed a decomposition of multidimensional poverty across Nigerian regions, as well as a dimensional breakdown of multidimensional poverty across Nigeria and across regions. According to the study, Nigeria's multidimensi
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Salahuddin, Taseer, and Asad Zaman. "Multidimensional Poverty Measurement in Pakistan :Time Series Trends and Breakdown." Pakistan Development Review 51, no. 4II (2012): 493–504. http://dx.doi.org/10.30541/v51i4iipp.493-504.

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In the recent literature, consensus has emerged that poverty is a multidimensional phenomenon; see Alkire and Santos (2010) for a review of the major arguments. Nonetheless, the most widely used measures of poverty remain unidimensional, being based on income or caloric intake cutoffs. The logic for the use of income based measures was that it was only lack of income which led to deprivation—with sufficient income; rational agents would automatically eliminate deprivations in all dimensions in the right sequence of priorities. However, careful studies like Thorbecke (2005) and Banerjee and Duf
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Wang, Wei, Xin Luo, Chongmei Zhang, Jiahao Song, and Dingde Xu. "Can Land Transfer Alleviate the Poverty of the Elderly? Evidence from Rural China." International Journal of Environmental Research and Public Health 18, no. 21 (2021): 11288. http://dx.doi.org/10.3390/ijerph182111288.

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This study explores the impact of farmland transfer on the multidimensional relative poverty of the elderly in rural areas to provide a reference for the study of rural land transfer in China and improve the welfare system for the elderly. Based on the China Family Panel Studies (CFPS) rural sample data in 2018, this paper uses the AF multidimensional index measurement method to assess multidimensional relative poverty in rural areas. Logit regression estimation examines the single index poverty of rural older adults transferred from rural land and the impact of multidimensional relative pover
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Zailani, Muhammad Nooraiman, and Najihah Abd Razak. "Comparative Analysis of Had Kifayah and Multidimensional Poverty Index as Poverty Measurement in Malaysia." Journal of Management and Muamalah 13, no. 2 (2023): 12–21. http://dx.doi.org/10.53840/jmm.v13i2.153.

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The measurement of poverty is an essential instrument for comprehending the socio-economic well-being of a nation’s population and devising effective strategies to mitigate it. Currently, zakat institutions in Malaysia rely on the Had Kifayah (HAK) method to categorise an individual's poverty status by classifying their asnaf status. On a larger scale, the establishment of the Multidimensional Poverty Index (MPI) presents an alternative method for assessing poverty, emphasising the non-monetary dimensions of deprivation that individuals may experience. This study conducts a comparative analysi
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Melak, Surafel, and Anupama. "On the Measurement of Multidimensional Vulnerabilityto Poverty in Ethiopia." Indian Journal of Economics and Development 15, no. 3 (2019): 341. http://dx.doi.org/10.5958/2322-0430.2019.00044.1.

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Weber, Sylvain. "Multidimensional Poverty Measurement: Concepts and Applications, by Udaya Wagle." Eastern Economic Journal 37, no. 3 (2011): 431–33. http://dx.doi.org/10.1057/eej.2009.44.

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Kim, Sung-Geun. "Fuzzy Multidimensional Poverty Measurement: An Analysis of Statistical Behaviors." Social Indicators Research 120, no. 3 (2014): 635–67. http://dx.doi.org/10.1007/s11205-014-0616-8.

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