Review of Economics and Development Studies, Vol. 7 (2) 2021, 287 - 298 287 Gender Poverty Gap: A Comparative analysis of India and Pakistan Muhammmad Siddique a, Misbah Nosheen b a PhD scholar, Department of economics, Hazara University Mansehra, KPK, Pakistan Email: siddique63@yahoo.com b HOD, Department of economics, Hazara University Mansehra, KPK, Pakistan Email: misbah_nosheen@yahoo.com ARTICLE DETAILS ABSTRACT History: Accepted 25 May 2021 Available Online June 2021 This paper attempts to estimate gender poverty gap in Pakistan using multidimensional poverty approach and compares it with India. Pakistan data have been used to compute multidimensional poverty. Findings of the paper suggest that there is gender poverty gap in Pakistan. Both India and Pakistan are suffering from poverty. Head count poverty is high in both countries but India has managed to lift more people out of multidimensional poverty. The paper recommends to design targeted oriented policies reduce gender poverty. © 2021 The authors. Published by SPCRD Global Publishing. This is an open access article under the Creative Commons Attribution- NonCommercial 4.0 Keywords: Multidimensional Poverty; gender Poverty, Deprivation; Pakistan; India JEL Classification: I130, I32 DOI: 10.47067/reads.v7i2.364 Corresponding author’s email address: siddique63@yahoo.com 1. Introduction Poverty is common, globalized curse and unique syndrome (Chosal, 2008). World community is belligerent against tenacious poverty. Process of reduction in poverty is lukewarm despite titanic measures taken by countries individually and by international agencies. Gender poverty is even more pervasive and persevered. According to Bureau of International Information Program, United States Department of State (2017), women of the developing world face poverty disproportionately. Picture of poverty is seen even bleak if one views it through the lens of multidimensional poverty. Unidimensional poverty does not cover the viscosity of deprivation suffered by poor segment of society. On the other hand, multidimensional poverty takes into account several overlapping deprivations experienced by poor people. Just like the speed of light which changes as medium through which its travels changes, scenario of poverty changes as we move from money – metric measure of poverty to multidimensional poverty -measure. According to Alkire and Jahan (2018), “for multiple overlapping deprivations the global Multidimensional Poverty Index (MPI) is suitable measure”. Review of Economics and Development Studies, Vol. 7 (2) 2021, 287 - 298 288 Umpteen empirical studies on multidimensional poverty considered household as a unit of identification (Rogan, 2016a; Klasen and Lahoti, 2016)1. Multidimensional approach for poverty suffers from some weakness. This approach assumes that all members of a household are considered multidimensional poor if household is identified as poor (Klasen and Lahoti, 2016). Women particularly in a household face inequality. They have no or limited access to economic resources. They are predominantly engaged in household caring jobs. Globally, unpaid domestic work is disproportionately carried out by female. Women, on average, spend two to ten time more time than their counterpart on domestic care work, left with insufficient time for personal care, leisure, paid work and other social and political activities (Karimli et al, 2016). In many developing nations women accept their role as unpaid domestic workers a divine right. In some Muslim societies women consider it a sin to question the authority of man. Notably, if a women in a household is not poor even then she is more vulnerable to poverty. An endoscopic examination of poverty is needed for exploratory diagnostic of intra – household disparity and female and male contribution of gender gap in poverty. Countries like Pakistan and India use to invest far less on women workers than working me although women appear to be productive than men, In India poor families particularly depends on the earning of the women for their survival (World Bank, 2016). Both countries enviably manage to reduce poverty particularly multidimensional poverty during last two decades. About 270 million people in India moved out multidimensional poverty between 2006/06 to 2015/16 (UNDP; 2020). Gender analysis of poverty could not make it place in Multidimensional poverty critique. Multidimensional poverty Index developed by Alkire and Foster (2011) is based on household’s deprivation on three dimensions – education, health and standard of living. Since MPI is calculated from information from each household, so it is possible to consider the deprivations of male and female separately. Household survey data provides information regarding the characteristics of both male and female living in respective households. In order to find the gender gap in poverty, data can be decomposed according to male and female headed households and separate regressions can be carried for these sub groups to estimate the gender poverty gap (Lastrapes & Rajaram, 2016). The present study endeavors to estimate the gender poverty gap using money – metric and multidimensional approaches by decomposing the data into male and female household heads. No previous study arguably undertook gender dimension of poverty using both money and multidimensional approaches in Pakistan. This study may contribute significantly in enhancing the understanding regarding the gender aspect of poverty and hence, may facilitate in targeting gender poverty in Pakistan. 2. Literature Review After introduction of capability approach by Sen (1976), the accent pf poverty debate has shifted from unidimensional poverty to multidimensional poverty which covers various dimensions of deprivation. Since then various approaches to estimate poverty incorporating different dimensions have been proposed. Cerioli and Zani (1990) were first to suggest a Fuzzy approach which include seven dimensions of deprivation. Cheli and Lemmi (1995) modified the Fuzzy approach and proposed a new approach called Totally Fuzzy and Relative (TFR) approach to estimate multidimensional poverty. Both approaches failed to mustered considerable support due to arbitrary aggregation adopted by these approaches. A flexible approach was proposed by Alkire and Foster in 2007 which includes three dimensions – education, health and standard of living, education has two in indicators which include year of 1 Espinoza – Delgado and Klasen (2017) used I individual – based approach to multidimensional poverty for Nicaragua. Review of Economics and Development Studies, Vol. 7 (2) 2021, 287 - 298 289 schooling and school attendance. Nutrition and Child mortality are the indicators of heath. Standard of living contains six indicators – Access to drinking water, improved sanitation, cooking fuel, type of floor of house of household, availability of electricity, Asset owned by household and fuel. This approach received tremendous support as being more dynamic and flexible. An index known as Multidimensional Poverty Index (MPI) was developed by Alkire and Santos (2007) which is very simple and easy to understand. This index is also decomposable into subgroup. The UNDP collaborated with Oxford Poverty and Development Initiative developed first global MPI in 2010 for UNDP flagship publication Human Development Report. Since then it is updated regularly to include newly released data. Globally, this index is used to compute multidimensional poverty head count and intensity both for individual countries and group of developing countries. Researches rigorously used this approach to have a clear picture of poverty. Among notable studies which used AF methodology are Batana (2008) for Sub – Saharan countries, Jamal and Harron (2007), Naveed and Islam (2010), Maqsood et al (2012) for Pakistan, Battiston et al for Latine America, Angulo et al (2003) for Colombia. Literature on multidimensional poverty is growing momentously. Multidimensional poverty approach gained currency in recent years as being innovative and much representative. It covers broad dimensions of deprivation of poor. Supporters of multidimensional poverty are of the view that unidimensional poverty is not good measure of poverty. It covers just one dimension, that is, income. Unidimensional poverty takes a household into account as a unit of measurement thus ignoring intra – household disparities. So, this approach is gender blind. It is silent on resource allocation within the household. Multidimensional measure of poverty removes this deficiency. Multidimensional poverty is broader phenomenon. “The poverty is multidimensional phenomenon” (Atkinson, 2003). “Multidimensional poverty is capable of capturing key dimensions of deprivation such as health, housing, education, schooling, and standard of livings (Chravarty, 2003; Thornbeck, 2008). These were the big reasons that the poverty paradigm has shifted from a unidimensional to multidimensional approach” (Lugo, 2016). A handsome body of literature is present on multidimensional poverty explaining the vulnerability of female. Some popular approaches have been introducing for the measurement of multidimensional poverty. Methodology which gained respectable appreciation in the literature is one proposed by Alkire and Foster (2007, 2011). The approach has been further refined by Alkire et, al (2015). Individual level poverty has been conducted by Vijaya et al (2005) identifying gender difference in poverty in Indian city of Karnataka. Concept of Multidimensional poverty received tremendous popularity in social scientists as being useful tool for policy makers. Seeing the importance of the phenomenon of multidimensional, a group of researchers especially OPHI took the responsibility to grill this measure of poverty. Brandolini (2008) conducted a study estimating multidimensional poverty for Italy, France, Germany and Britain kingdom. Kabubu et al (2010) estimated the ‘multidimensional poverty in Kenya.. Jamal (2009) worked on multidimensional for Pakistan. Results of the study are summarized, “In 2004-05, 54 percent of the population were multidimensional poor”. The paper further divulged, “In urban areas the extent of multidimensional poverty is less than in rural areas. In rural areas 69 percent were poor than in urban areas 21 percent people”. Calvi (2016) found that poverty in women increased with age and intra-household inequalities were more pronounced in India. Gender poverty gap was not visible when household data is used but it was palpable when individual level data was used. Review of Economics and Development Studies, Vol. 7 (2) 2021, 287 - 298 290 Lastrapes and Rajaram (2016) took new area of poverty and investigated effects of gender and social caste on penury in India for the period 2005-06. The paper used measures of household wealth from the National Family Health Survey (NFHS) of India. The paper used asset-based measures of poverty which were quite different from official measures. Official measures of India are based on consumption expenditures. However, main focus of the study was gender poverty and paper sorted data for head of families both for male and female. Logistic estimation results revealed that female-headed households generally and households belonging to marginalized social classes particularly were more likely to be poor than their counterparts. Marginalized social class was found to be more strongly associated with poverty. Whereas the gender of the household head is associated with poverty but not so robustly as marginalized social class. Crawford et al (2017) examined gender dimension of multidimensionality of poverty in Fiji covering environment, health and unpaid [ work dimension. Findings of the study revealed that about 91 % of women and 65 & of men were reported to be exposed to fumes related to cooking and heating. Women and men respectively on average were exposed to one hour and 45 minutes per day of perfumes related cooking and heating. Women suffered twice as more health problem as men linked to unclean cooking and heating fuel (25 percent of 12 percent). Female were more likelihood than male to be severely deprived and very deprived in raising their voice. Primary responsibility for water fetching in Fiji rests with women. Moreover, women were more than double likely than men to report no control over personal decision (5 percent of 1.4 percent). Lasimbo et al (2017) analyzed empirically multidimensional welfare deprivation of women in rural and urban South-South (SS) Nigeria using secondary data from Nigeria Demographic Health Survey (NDHS, 2013). Sample consisted of 1965 women from Alkire and Kanagaratnam (2018) computed global multidimensional index for 105 developing countries which constitute about 75 percent of world’s population which covers approximately 5.7 billion people. Some new indicators have been incorporated. Child stunting and age – specific Body Mass Index (BMI) cutoffs have been included in health dimension. A new indicator namely “child deaths within the 5 years period preceding the survey” was considered in health dimension. Tekgue and Akbulut,(2019) calculated multidimensional poverty in Turkey in four equally weighted dimensions using Survey of Living Conditions during 2006-15. The study used health, education level, employment status and household living conditions as indicators of the multidimensional poverty. Findings of the study suggested that employment led to faster reduction in gender poverty. Older individuals were vulnerable to poverty. Young cohort improved. The paper concluded that gender poverty gap existed in Turkey. 3. Methodology The present study employs Alkire and Kanagaratnam (2018) methodology to compute multidimensional poverty index for Pakistan using Household Integrated Income and Expenditure Survey (2015 -16). Alkire and Kanagaratnam (2018) methodology is the latest description of Alkire and Foster (2010) methodology which is continuously being updated for newly released data. A brief description of the dimensions, indicators and cutoff point for each dimension is illustrated in following table. Review of Economics and Development Studies, Vol. 7 (2) 2021, 287 - 298 291 Table (1) Cutoff Point for each Dimension Dimension Indicator Deprived if Not- Deprived if Read/ write Can’t read/write Can read /write Education Can’t conduct arithmetic operation Can conduct arithmetic operation Year of schooling