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Journal articles on the topic 'Poverty measures'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Bourguignon, François, and Gary S. Fields. "Poverty Measures and Anti-Poverty Policy." Recherches économiques de Louvain 56, no. 3-4 (1990): 409–27. http://dx.doi.org/10.1017/s0770451800043979.

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SummaryThis paper analyzes the optimal allocation of a given antipoverty budget consistent with various usual measures of poverty. It is shown that it is generally optimal to give all the budget either to the poorest or to the richest of the poor. It is only with the Sen index of poverty that it is sometimes optimal to combine both types of allocation. This property may be related to the normalization rule used in the derivation of that measure and sheds some new light on the axiomatics of poverty measurement.

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2

Kouassi, Eugene, Pierre Mendy, Diaraf Seck, and Kern O. Kymn. "Dynamic Poverty Measures." Theoretical Economics Letters 01, no. 03 (2011): 63–69. http://dx.doi.org/10.4236/tel.2011.13014.

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3

Zheng, Buhong. "Aggregate Poverty Measures." Journal of Economic Surveys 11, no. 2 (December 16, 2002): 123–62. http://dx.doi.org/10.1111/1467-6419.00028.

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4

Guan, Xinping. "Poverty and anti-poverty measures in China." China Journal of Social Work 7, no. 3 (September 2, 2014): 270–87. http://dx.doi.org/10.1080/17525098.2014.962758.

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5

Lipman, Francine. "(Anti)Poverty Measures Exposed." Florida Tax Review 21, no. 2 (2018): 389–532. http://dx.doi.org/10.5744/ftr.2017.0006.

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6

Battilocchi, Gian Luca. "Educational poverty in Italy: concepts, measures and policies." Central European Journal of Educational Research 2, no. 1 (April 28, 2020): 1–10. http://dx.doi.org/10.37441/cejer/2020/2/1/5753.

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In recent years in Italy, as a result of the initiative by the NGO Save the Children Italia and of the government action, we have witnessed the success of the notion of “povertà educativa”, as an effective way to indicate severe inequalities in education across the country. Firstly, the aim of this paper is to shed light on the different concepts and measures of educational poverty in socio-economic literature, in order to highlight specific and innovative aspects of this idea. Moreover, the paper intends to scrutinize Save the Children’s proposal in order to monitor and tackle educational poverty as well as to show how the action of the NGO has influenced the development of Italian recent government policies against child and educational poverty.

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7

Kumar, Pankaj. "A Retrospective Analysis of Measures of Poverty in India." Indian Journal of Applied Research 4, no. 8 (October 1, 2011): 637–40. http://dx.doi.org/10.15373/2249555x/august2014/167.

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8

Kumar, Pankaj, and Dr P. K. Dam Dr P K Dam. "A Review of Different Measures of Poverty in India." Indian Journal of Applied Research 4, no. 8 (October 1, 2011): 644–47. http://dx.doi.org/10.15373/2249555x/august2014/169.

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9

Zheng, Buhong. "Statistical inference for poverty measures with relative poverty lines." Journal of Econometrics 101, no. 2 (April 2001): 337–56. http://dx.doi.org/10.1016/s0304-4076(00)00088-9.

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10

Sallila, Seppo, Heikki Hiilamo, and Reijo Sund. "Rethinking relative measures of poverty." Journal of European Social Policy 16, no. 2 (May 2006): 107–20. http://dx.doi.org/10.1177/0958928706062500.

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11

Datt, Gaurav. "Distribution-Sensitive Multidimensional Poverty Measures." World Bank Economic Review 33, no. 3 (March 12, 2018): 551–72. http://dx.doi.org/10.1093/wber/lhx017.

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Abstract This paper presents axiomatic arguments to make the case for distribution-sensitive multidimensional poverty measures. The commonly used counting measures violate the strong transfer axiom, which requires regressive transfers to be unambiguously poverty increasing, and they are also invariant to changes in the distribution of a given set of deprivations among the poor. The paper appeals to strong transfer as well as an additional cross-dimensional convexity property to offer axiomatic justification for distribution-sensitive multidimensional poverty measures. Given the nonlinear structure of these measures, it is also shown how the problem of an exact dimensional decomposition can be solved using Shapley decomposition methods to assess dimensional contributions to poverty. An empirical illustration for India highlights distinctive features of the distribution-sensitive measures.

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12

Ravallion, Martin. "Toward better global poverty measures." Journal of Economic Inequality 14, no. 2 (April 6, 2016): 227–48. http://dx.doi.org/10.1007/s10888-016-9323-9.

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13

Ringen, Stein. "Direct and Indirect Measures of Poverty." Journal of Social Policy 17, no. 3 (July 1988): 351–65. http://dx.doi.org/10.1017/s0047279400016858.

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ABSTRACTPoverty can be defined and measured either directly (in terms of consumption) or indirectly (in terms of income). The relative deprivation concept of poverty is a direct concept; poverty is understood as visible poverty, that is, a low standard of consumption. The income poverty line is an indirect measure; poverty is established as low income. It is argued that recent mainstream poverty research combines a direct definition and an indirect measure. This causes there to be no logical line of deduction between definition and measurement and, along with other problems in the approach, renders the statistics produced invalid.

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14

Burkhauser, Richard V. "Deconstructing European poverty measures: What relative and absolute scales measure." Journal of Policy Analysis and Management 28, no. 4 (June 2009): 715–25. http://dx.doi.org/10.1002/pam.20468.

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15

White, Howard, Jennifer Leavy, and Andrew Masters. "Comparative Perspectives on Child Poverty: A review of poverty measures." Journal of Human Development 4, no. 3 (November 2003): 379–96. http://dx.doi.org/10.1080/1464988032000125755.

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16

Ngwane, Alfred K., Venkata S. S. Yadavalli, and Francois E. Steffens. "Poverty in South Africa: Statistical inference for decomposable poverty measures." Development Southern Africa 20, no. 2 (June 2003): 283–91. http://dx.doi.org/10.1080/03768350302959.

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17

Maiti, P., and M. Pal. "On Some Estimates of Poverty Measures." Calcutta Statistical Association Bulletin 37, no. 1-2 (March 1988): 81–90. http://dx.doi.org/10.1177/0008068319880108.

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There are now a number of poverty measures available in the literatures. Some of the measures are alternative to each other and some claimed to be superior in some sense to many others. While significant work has been done in developing the alternative measurts, not much attention has been paid to the problem of estimation of these indices. Estimation does not pose very serious problems in the large sample, but when one deals with a small sample, which may typically be the case in reality, situations become quite different. In fact usual estimators become biased for some of the indices. In this paper, alternative estimators for these cases have been proposed. Other properties of the estimators and some other relevant issues have also been examined.

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18

Schmid, F. "A general class of poverty measures." Statistical Papers 34, no. 1 (December 1993): 189–211. http://dx.doi.org/10.1007/bf02925542.

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19

Bishop, John A., K. Victor Chow, and Buhong Zheng. "STATISTICAL INFERENCE AND DECOMPOSABLE POVERTY MEASURES." Bulletin of Economic Research 47, no. 4 (October 1995): 329–40. http://dx.doi.org/10.1111/j.1467-8586.1995.tb00619.x.

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20

Reddy, Mahendra M., Kalaiselvi Selvaraj, and Sonali Sarkar. "Poverty Measurement: Time To Look Beyond Poverty Line – Do We Know How Poor Really The Poor Are?" JOURNAL OF CLINICAL AND BIOMEDICAL SCIENCES 08, no. 1 (March 15, 2018): 5–9. http://dx.doi.org/10.58739/jcbs/v08i1.8.

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Poverty leading to ill-health and ill-health pushing people to poverty is a vicious cycle. Measure-ment of poverty is important in any country as a large share of finance allocation is dependent on the number of poor people living in that respective state or region. In most of the countries poverty is expressed only in terms of proportion which says how many of them are poor with respect to the poverty line. Not much effort is actually made to express or derive further important measures which could help in giving the exact picture of poor people in the country. There are different measures which are deduced based on absolute poverty line starting from the simple measures such as poverty headcount ratio to robust measures such as Watt’s index. This article mainly emphasizes on the practical issues to be considered before measuring the poverty line and also it critically appraises the available common measures of poverty. Keywords: Poverty, Poverty line, Poverty gap

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21

Thompson, Brennan S. "Empirical Likelihood-Based Inference for Poverty Measures with Relative Poverty Lines." Econometric Reviews 32, no. 4 (April 2013): 513–23. http://dx.doi.org/10.1080/07474938.2012.690671.

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22

Korenman, Sanders, Dahlia K. Remler, and Rosemary T. Hyson. "Medicaid Expansions and Poverty: Comparing Supplemental and Health-Inclusive Poverty Measures." Social Service Review 93, no. 3 (September 2019): 429–83. http://dx.doi.org/10.1086/705319.

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23

Uprety, Pravat. "Measures, Distribution and Decomposition of Poverty: An Empirical Analysis in Nepal." Nepalese Journal of Statistics 4 (December 18, 2020): 1–16. http://dx.doi.org/10.3126/njs.v4i0.33447.

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Background: Poverty has been in existence for many years and continues to exist in a large number of countries. Poverty is “pronounced in wellbeing” where wellbeing (and poverty) in broader term, focuses on the capability of the individual to function in society and poor people often lack key capabilities, they may have not adequate income, education, or be in poor health or feel powerless or lack of political freedoms. In Nepal, despite the decreasing trend in poverty incidence, still the current prevalence is very high with the comparison of other countries. Objective: To identify, compare and decomposition of different poverty measures by rural urban area and ecological belt in Nepal. Materials and Methods: Data set of Nepal Living Standard Survey (NLSS) conducted by Central Bureau of Statistics in 2011 consisting of various variables related to food, non-food consumption, income, demographic, socioeconomics, etc., have been used for analysis. In order to measure the poverty, different measures such as head count ratio, poverty gap, poverty severity, Watts index and Sen-Shorrocks-Thon index were used. The comparisons of different poverty measures across different variables were attempted including use of appropriate poverty curves. The decomposition of poverty indices by consumption components using the Shapley value along with Lump-Sum Targeting approach has been applied. Results: Average per capita consumption is 34186.5, the head count index, poverty gap and poverty severity of Nepal are 0.2518, 0.0545 and 0.0182, respectively. The poverty measures of rural area are higher than the urban area, and the incidence of poverty is highest in mountain ecological belt. Food and non-food component allows to 46.39% & 28.42% of the total population to be non-poor of headcount index, 60.19% & 34.34% for poverty gap index and 59.96% & 38.20% for poverty severity, respectively. Conclusion: For both within and overall population, rural area has the higher impact than urban area and each measure of poverty in mountain is significantly higher than hill and terai. To reduce within group headcount index and poverty gap, policymakers should give more focus to rural area and mountain region.

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24

Maku, Olukayode Emmanuel, Afeez Taiwo Tella, and Akinola Christopher Fagbohun. "Alleviating Poverty in Nigeria: Keynesian Vs Monetary Theory of Poverty." Studia Universitatis „Vasile Goldis” Arad – Economics Series 30, no. 1 (March 1, 2020): 103–20. http://dx.doi.org/10.2478/sues-2020-0007.

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AbstractThis study comparatively investigates the impacts of fiscal and monetary policies on poverty in Nigeria from 1986 to 2018. Using the Ordinary Least Square and Standardized or Beta Coefficient approach, we found that the Nigerian political system plays a vital role on a large number of its citizens living in extreme poverty. Other factors identified as the likely causes of poverty are insurgencies, terrorism, and low productivity among others. Also, monetary policy is more important in alleviating poverty than the fiscal policy which favored the monetary school arguments. Specifically, monetary measures like exchange rate and interest rate are more significant in alleviating poverty far more than inflation rate while fiscal measures proxy with government recurrent expenditure plays a more vital role in alleviating poverty in Nigeria than others like government capital expenditure and government recurrent expenditure. The study recommended that in the case of monetary measures, there is a need for Government through the Central Bank of Nigeria, to shift their attention towards key monetary policy measures like interest rate and exchange rate compare to other monetary measures.

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25

Chtioui, Naouel, and Mohamed Ayadi. "Rank-based poverty measures and poverty ordering with an application to Tunisia." Portuguese Economic Journal 17, no. 2 (January 6, 2018): 117–39. http://dx.doi.org/10.1007/s10258-017-0140-2.

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26

Daniels, Lisa, and Nicholas Minot. "Is Poverty Reduction Over-Stated in Uganda? Evidence from Alternative Poverty Measures." Social Indicators Research 121, no. 1 (April 27, 2014): 115–33. http://dx.doi.org/10.1007/s11205-014-0637-3.

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27

Greene, Richard. "Poverty Concentration Measures and the Urban Underclass." Economic Geography 67, no. 3 (July 1991): 240. http://dx.doi.org/10.2307/143935.

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28

Pacifico, Daniele, and Felix Poege. "Estimating Measures of Multidimensional Poverty with Stata." Stata Journal: Promoting communications on statistics and Stata 17, no. 3 (September 2017): 687–703. http://dx.doi.org/10.1177/1536867x1701700309.

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In this article, we describe the multidimensional poverty measures developed by Alkire and Foster (2011, Journal of Public Economics 95: 476–487) and show how they can be computed with Stata by using the mpi command.

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29

Harker, Lisa. "Tracking poverty The need to prioritise measures." New Economy 9, no. 1 (March 2002): 21–25. http://dx.doi.org/10.1111/1468-0041.00234.

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30

Waddams Price, Catherine, Karl Brazier, and Wenjia Wang. "Objective and subjective measures of fuel poverty." Energy Policy 49 (October 2012): 33–39. http://dx.doi.org/10.1016/j.enpol.2011.11.095.

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31

Bosmans, Kristof. "Distribution-sensitivity of rank-dependent poverty measures." Journal of Mathematical Economics 51 (March 2014): 69–76. http://dx.doi.org/10.1016/j.jmateco.2014.01.012.

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32

Sawers, Larry. "Poverty weighted measures of social welfare change." World Development 16, no. 8 (August 1988): 899–901. http://dx.doi.org/10.1016/0305-750x(88)90021-6.

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33

Delhausse, Bernard, Axel Luttgens, and Sergio Perelman. "Comparing measures of poverty and relative deprivation." Journal of Population Economics 6, no. 1 (February 1993): 83–102. http://dx.doi.org/10.1007/bf00164340.

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34

Wu, Dan, Jinyang Liu, and Xiong Zhang. "Statistical Measurement of the Overall Scale of Urban Poverty in China." Scientific and Social Research 4, no. 2 (February 17, 2022): 104–10. http://dx.doi.org/10.26689/ssr.v4i2.3640.

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As China is undergoing rapid urbanization and social transformation, the research on urban poverty has become increasingly important. So far, the Chinese government has still not drawn an official urban poverty line. The statistical measurement of the overall scale of urban poverty in China is carried out based on three aspects: price adjustment, income distribution data, and main poverty-stricken population, in which the trend analysis of the poor population, the maximum likelihood estimation, and the recent price adjustment are used as measures. The arithmetic average of the urban poverty population, measured via the above three different measures, is taken to obtain the current overall scale of urban poverty in China, which is 10.816 million.

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35

CHEUNG, KELVIN CHI-KIN, and KEE-LEE CHOU. "Poverty, deprivation and life satisfaction among Hong Kong older persons." Ageing and Society 39, no. 4 (October 26, 2017): 703–21. http://dx.doi.org/10.1017/s0144686x17001143.

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ABSTRACTThis investigation examines the association of four measures of poverty (income-based, expenditure-based and asset-based poverty, and material deprivation) with life satisfaction. Perceived life satisfaction was measured among 1,410 older Chinese persons aged 65 and over. Besides life satisfaction and measures of poverty, the study assessed socio-demographic variables, financial strain, health indicators, and social and community resources. Those who faced expenditure-based poverty, material deprivation and asset-based poverty reported a significantly lower level of perceived life satisfaction, while the association between expenditure-based poverty and life satisfaction was found to be the strongest. Other factors that had an impact on life satisfaction included gender, education and marital status; financial strain; social support; the number of close family members and friends; self-rated health; functional capacity; perceived memory; pain; sleep quality; neighbourhood collective efficacy; and engagement in cultural and entertainment activities. From the theoretical perspective, the findings have strong implications for the understanding of the factors that shape the perception of quality of life in old age. Our results also have important policy implications for the official measurement of poverty, monitoring of the poverty situation and the development of anti-poverty measures to help older persons living in poverty to improve the quality of their lives.

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36

Appiah-Otoo, Isaac, and Na Song. "The Impact of Fintech on Poverty Reduction: Evidence from China." Sustainability 13, no. 9 (May 7, 2021): 5225. http://dx.doi.org/10.3390/su13095225.

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Ending poverty in all its forms by 2030 remains the first agenda of Sustainable Development Goals set by the United Nations in 2015. Motivated by this agenda, this study examined the direct and indirect effect of financial technology (fintech) and its sub-measures of third-party payment and credit on poverty measured by household per capita consumption. We used a panel of 31 provinces in China from 2011 to 2017. The results indicated that fintech and these sub-measures reduce poverty in China. The results further showed that fintech complements economic growth and financial development to reduce poverty in China.

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37

Corsi, Marcella, Fabrizio Botti, and Carlo D'Ippoliti. "The Gendered Nature of Poverty in the EU: Individualized versus Collective Poverty Measures." Feminist Economics 22, no. 4 (March 2, 2016): 82–100. http://dx.doi.org/10.1080/13545701.2016.1146408.

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38

GARCÍA-LAPRESTA, JOSÉ LUIS, CASILDA LASSO DE LA VEGA, RICARDO ALBERTO MARQUES PEREIRA, and ANA MARTA URRUTIA. "A CLASS OF POVERTY MEASURES INDUCED BY THE DUAL DECOMPOSITION OF AGGREGATION FUNCTIONS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18, no. 04 (August 2010): 493–511. http://dx.doi.org/10.1142/s0218488510006660.

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In this paper we introduce a new family of poverty measures for comparing and ordering social situations. The aggregation scheme of these poverty measures is based on the one-parameter family of exponential means. The poverty measures introduced satisfy interesting properties and the dual decomposition of the underlying exponential means induces a natural decomposition of the proposed poverty indices themselves into three underlying factors: incidence, intensity, and inequality among the poor.

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39

Salvatore, Dominick, and Fred Campano. "Globalization, Growth and Poverty." Global Economy Journal 12, no. 4 (November 6, 2012): 1850278. http://dx.doi.org/10.1515/1524-5861.1912.

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The paper examines the change in the income distribution of developed and developing countries over the recent period of globalization from 1980 to the present. The change in the income distribution of developing countries is also measured for those developing countries that globalized and those that did not. The paper finds that in terms of the three major measures of central tendency, the real personal income ratios between developed and developing countries have been substantially reduced during the 1980-2005 period of rapid globalization, especially at the mode, where the most severe poverty lies.

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40

LAYTE, RICHARD, BRIAN NOLAN, and CHRISTOPHER T. WHELAN. "Targeting Poverty: Lessons from Monitoring Ireland's National Anti-Poverty Strategy." Journal of Social Policy 29, no. 4 (October 2000): 553–75. http://dx.doi.org/10.1017/s0047279400006073.

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In 1997 the Irish government adopted the National Anti-Poverty Strategy (NAPS), a global target for the reduction of poverty which illuminates a range of issues relating to official poverty targets. The Irish target is framed in terms of a relative poverty measure incorporating both relative income and direct measures of deprivation based on data on the extent of poverty from 1994. Since 1994 Ireland has experienced an unprecedented period of economic growth that makes it particularly important to assess whether the target has been achieved, but in doing so we cannot avoid asking some underlying questions about how poverty should be measured and monitored over time. After briefly outlining the nature of the NAPS measure, this article examines trends in poverty in Ireland between 1987 and 1997. Results show that the relative income and deprivation components of the NAPS measure reveal differential trends with increasing relative income poverty, but decreasing deprivation. However, this differential could be due to the fact that the direct measures of deprivation upon which NAPS is based have not been updated to take account of changes in real living standards and increasing expectations. To test whether this is so, we examine the extent to which expectations about living standards and the structure of deprivation have changed over time using confirmatory factor analysis and tests of criterion validity using different definitions of deprivation. Results show that the combined income and deprivation measure, as originally constituted, continues to identify a set of households experiencing generalised deprivation resulting from a lack of resources.

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41

Etim, Nsikak-Abasi A., and Obasi O. Ukoha. "Robustness of the Poverty Measures: Evidence from Farm Households in Akwa Ibom State, Nigeria." Journal of Social Commerce 1, no. 1 (January 26, 2022): 21–33. http://dx.doi.org/10.56209/jommerce.v1i1.3.

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The use of a plethora of poverty indexes is sometimes fraught with difficulties. The purpose of this research was to quantitatively assess poverty and to examine the robustness of the poverty metrics. Selecting representative farm homes required a multistage sample technique, which was implemented. A total of 150 rural homes were surveyed using questionnaires. Stochastic dominance and the weighted poverty measures of Foster, Greer and Thorbecke were used in this work to examine the weighted poverty measures' resilience and sensitivity to changes in the poverty line. According to the findings, as people become older and their families get larger, the likelihood, severity, and depth of poverty increases. An asymptotic sampling distribution was utilized to infer whether poverty was larger across a variety of hypothetical poverty lines by stochastic dominance analysis. First-order stochastic dominance was found, with the Cumulative Distribution Function (CDF) of households headed by people over 60 years old lying totally above the other distribution functions (CDFs). The CDF of single families was lower than the CDF of married households, according to the findings. At any poverty level, the CDF of families with more than 10 household members stochastically dominated those with fewer family members. Many households will be lifted out of poverty if poverty-reduction initiatives are targeted at those over 60 and those with big families.

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42

Etim, Nsikak-Abasi A., and Obasi O. Ukoha. "Robustness of the Poverty Measures: Evidence from Farm Households in Akwa Ibom State, Nigeria." Journal of Social Commerce 1, no. 1 (January 26, 2022): 21–33. http://dx.doi.org/10.56209/jsc.v1i1.3.

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The use of a plethora of poverty indexes is sometimes fraught with difficulties. The purpose of this research was to quantitatively assess poverty and to examine the robustness of the poverty metrics. Selecting representative farm homes required a multistage sample technique, which was implemented. A total of 150 rural homes were surveyed using questionnaires. Stochastic dominance and the weighted poverty measures of Foster, Greer and Thorbecke were used in this work to examine the weighted poverty measures' resilience and sensitivity to changes in the poverty line. According to the findings, as people become older and their families get larger, the likelihood, severity, and depth of poverty increases. An asymptotic sampling distribution was utilized to infer whether poverty was larger across a variety of hypothetical poverty lines by stochastic dominance analysis. First-order stochastic dominance was found, with the Cumulative Distribution Function (CDF) of households headed by people over 60 years old lying totally above the other distribution functions (CDFs). The CDF of single families was lower than the CDF of married households, according to the findings. At any poverty level, the CDF of families with more than 10 household members stochastically dominated those with fewer family members. Many households will be lifted out of poverty if poverty-reduction initiatives are targeted at those over 60 and those with big families.

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43

Ravallion, Martin. "On Measuring Global Poverty." Annual Review of Economics 12, no. 1 (August 2, 2020): 167–88. http://dx.doi.org/10.1146/annurev-economics-081919-022924.

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This article critically assesses prevailing measures of global poverty. A welfarist interpretation of global poverty lines is augmented by the idea of normative functionings, the cost of which varies across countries. In this light, current absolute measures are seen to ignore important social effects on welfare, while popular, strongly relative measures ignore absolute levels of living. It is argued that a new hybrid measure is called for, combining absolute and weakly relative measures consistent with how national lines vary across countries. Illustrative calculations indicate that we are seeing a falling incidence of poverty globally over the past 30 years. This is mainly due to lower absolute poverty counts in the developing world. While fewer people are poor by the global absolute standard, more are poor by the country-specific relative standard. The vast bulk of poverty, both absolute and relative, is now found in the developing world.

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44

Landiyanto, Erlangga Agustino. "Comparison of Child Poverty Measures: Looking for Consensus." Child Indicators Research 15, no. 1 (October 28, 2021): 35–66. http://dx.doi.org/10.1007/s12187-021-09867-4.

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45

Seck, Cheikh Tidiane, and Gane Samb Lo. "Uniform Convergence of the Non-Weighted Poverty Measures." Communications in Statistics - Theory and Methods 38, no. 20 (October 13, 2009): 3697–704. http://dx.doi.org/10.1080/03610920802645387.

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46

Belhadj, Besma, and Mohamed Limam. "Unidimensional and multidimensional fuzzy poverty measures: New approach." Economic Modelling 29, no. 4 (July 2012): 995–1002. http://dx.doi.org/10.1016/j.econmod.2012.03.009.

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47

Ravallion, Martin. "On testing the scale sensitivity of poverty measures." Economics Letters 137 (December 2015): 88–90. http://dx.doi.org/10.1016/j.econlet.2015.10.034.

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48

Meyer, Bruce D., and James X. Sullivan. "Identifying the Disadvantaged: Official Poverty, Consumption Poverty, and the New Supplemental Poverty Measure." Journal of Economic Perspectives 26, no. 3 (August 1, 2012): 111–36. http://dx.doi.org/10.1257/jep.26.3.111.

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We discuss poverty measurement, focusing on two alternatives to the current official measure: consumption poverty, and the Census Bureau's new Supplemental Poverty Measure (SPM) that was released for the first time last year. The SPM has advantages over the official poverty measure, including a more defensible adjustment for family size and composition, an expanded definition of the family unit that includes cohabitors, and a definition of income that is conceptually closer to resources available for consumption. The SPM's definition of income, though conceptually broader than pre-tax money income, is difficult to implement given available data and their accuracy. Furthermore, income data do not capture consumption out of savings and tangible assets such as houses and cars. A consumption-based measure has similar advantages but fewer disadvantages. We compare those added to and dropped from the poverty rolls by the alternative measures relative to the current official measure. We find that the SPM adds to poverty individuals who are more likely to be college graduates, own a home and a car, live in a larger housing unit, have air conditioning, health insurance, and substantial assets, and have other more favorable characteristics than those who are dropped from poverty. Meanwhile, we find that a consumption measure compared to the official measure or the SPM adds to the poverty rolls individuals who are more disadvantaged than those who are dropped. We decompose the differences between the SPM and official poverty and find that the most problematic aspect of the SPM is the subtraction of medical out-of-pocket expenses from SPM income. Also, because the SPM poverty thresholds change in an odd way over time, it will be hard to determine if changes in poverty are due to changes in income or changes in thresholds. Our results present strong evidence that a consumption-based poverty measure is preferable to both the official income-based poverty measure and to the Supplemental Poverty Measure for determining who are the most disadvantaged.

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Othman, Azhana, Abd Halim Mohd Noor, and Mohamed Saladin Abdul Rasool. "A Subjective Poverty Approach as an Alternative Measurement in Identifying the Poor and Needy." International Journal of Zakat 3, no. 4 (December 31, 2018): 95–102. http://dx.doi.org/10.37706/ijaz.v3i4.109.

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Poverty can be measured directly (based on consumption) or indirectly (based on income). Both direct and indirect poverty measurement are called objective poverty measurement. Nonetheless, these indicators are not enough capture the multiple aspects of poverty. Therefore, the alternative measure of poverty is needed. Subjective poverty is an individual assessment of their own poverty status. The poor have their own understanding and interpretation of their socio-economic situation. Poverty could be analyzed in a more comprehensive and better dimension by combining objective and subjective measures in identifying the poor. The Millennium Development Goals Report (MDGR, 2015) designates that Malaysia has been successful eliminated objective poverty. Despite that, the issue of poverty still surfing especially the zakat authorities are experiencing increasing in the zakat applications categorized poor and needy each day. To avoid the situation where individuals are wrongly defined as poor or non-poor are to compile objective and subjective measures on poverty. The objectives of the study are to determine the criteria of subjective poor and to propose subjective poverty index (SPI) as an alternative poverty measurement. The empirical analysis was based of 507 zakat applicants of poor and needy in Melaka. The data was analysed using qualitative and quantitative methods in four phases of analysis. The findings confirmed that subjective poverty index (SPI) is an initial effort to explain poverty in the perspective of the poor.

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Sheikh, Muhammad Ramzan, Muhammad Tariq, and Maryam Ghafoor. "Household Poverty, Women Fertility and Child Nutritional Status in Tehsil Jahanian, Pakistan." Global Economics Review V, no. III (September 30, 2020): 97–117. http://dx.doi.org/10.31703/ger.2020(v-iii).10.

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This study measures the impact of household poverty on women fertility and the nutritional status of children. In this study, the poverty level is computed by the per capita income, while women fertility is measured by the number of children in a household. The Height- for-age Z-score (HAZ) method has been used to measure the nutritional status of children. A survey has been conducted to collect household data. The study uses the OLS method and finds that household poverty is positively correlated to women fertility rate but negatively related to the nutritional status of children. The study has suggested various policies measures for poverty, women fertility and the nutritional status of children.

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