Targeting the Poor Women-Headed Households in the Pursuit to End Poverty: A Case Study of Zunheboto District of Nagaland in North EastIndia

 

Elizabeth Z. Awomi ¹, Wandinecia Tariang ²

 

¹ Research Scholar, Department of Economics, North-Eastern Hill University, Mawkynroh, Umshing, Shillong, Meghalaya, India

² Assistant Professor, Department of Economics, North-Eastern Hill University, Mawkynroh, Umshing, Shillong, Meghalaya, India

 

1. INTRODUCTION

Poverty is one of the major development issues that haslargely affected many nations around the world. Poverty deprives individuals not only of the means to satisfy basic requirements of well-being; it also deprives them of their choices and opportunities to maintain a better quality of life. The multidimensional aspect of poverty which encompass the state of deprivation of well-being of an individual such as low income, inaccessibility to basic goods and services, poor health and lack of education, lack of access to clean water and sanitation, inadequate security and poor quality of life. This has made the concept of poverty to be a multi-dimensional and multi-faceted phenomenon.

Over the years, the discussion on gender dimensions of poverty seemed to have grabbed the attention of many researchers and policy analysts in their study of gender and povertyaspects particularly on issues that target women in their pursuit to end poverty. Women play a very important and contributory role in many productive and income-generating activities besides partaking the role of a daughter, a wife, and a mother and also in their responsibilities in nurturing their children and looking after the welfare and well being of the family and the household. Yet women continue to be exploited and are often subjectedto a greater discrimination and deprivations that deny them the choices and opportunitiesfor a decent life Barros et al. (1997), Cagatay (1998). Women in some countries are often constrained by not only the lack of income earning opportunities but also lack access to resources or physical capital compared to the men folk World Bank. (2001). Thus, backed by a number of religious, social, and cultural traditions and rules among others prevent many women to escape the poverty trap.

The World Bank’s study on Gender and Poverty in India reflected that women are denied access to productive assets like land ownership, family inheritance and human capital such as education and skill-training, mainly because of the patriarchal societal set up World Bank. (1991). Poverty in many developing countries like India is not merely an economic phenomenon but also a social phenomenon Parikh and Radhakrishna (2005). The age-old customs and traditions in India which are largely based on religious, social and economic reasons, determines the gender-related economic gaps that have led people to accord lower status to women Arokiasamy and Pradhan (2006), Gupta et al. (2003).The social and cultural setup in India restrict women’s mobility and freedom which prevents them from getting access to education and work, and thus the participation of women in the workforce is very low vis-à-vis the workforce participation of the male counterpart Dreze and Sen (1995), Dunlop and Velkoff (1999). Moreover, the patriarchal social setup also prevents many women from having access to family inheritance and productive assets Agarwal (1997). This, therefore, increases the risk of poverty in the households particularly in those female-headed households where women are the sole and/or primary bread winners.

Thus, thepresent study lays focus on the situation of female-headed households in Zunheboto district of Nagaland and the incidence of poverty, inequality, and deprivation among these households vis-à-vis the male-headed households in the state. The study was carried out on the basis of the two laid out objectives: (i) to measure the incidence and intensity of poverty, and the income inequality among the female-headed and male-headed households, (ii) to compare the levels of poverty and the extent of deprivation among female-headed household’s vis-à-vis male-headed households through the multidimensional poverty approach.

 

2. Background of the study area

Zunheboto district is one of the eleven districts in the state of Nagaland in North-eastern region of India. According to Census 2011, population of Zunheboto stood at 1,40,757 persons, out of which80.4 per cent population live in the rural areas while the rest 19.6 per cent people reside in the urban areas. The district has a density of 112 people per square kilometre as per Census 2011 and the Sex Ratio is 981 females per 1000 male. Out of the 11 districts of Nagaland, the district of Zunheboto is ranked 3rd in terms of literacy rate and ranked 605 out of the total 640 districts of India. The 2011 literacy rate is 85.26 per cent where male literacy is 75.00 per cent and female literacy is 71per cent. The average literacy rate in urban areas is 94.50 per cent while that in the rural areas is 83per cent. There are more ‘Married’ and ‘Never Married’ male-headed households both in Zunheboto district and in the state as well belonging to this category as per 2011 Census. It may be reported that from the Census period of 1991 up to the 2011 Census, the female-headed households hold a higher proportion in the ‘Widowed’ category, ‘Divorced or Separated’ category as well as in the ‘Not Specified’ category both in Zunheboto district as well as in the State.

Further, a look at the number of people engaged in work activities, 79,466 persons were engaged as cultivators, agricultural labourers, household industry workers and other workers. Out of this, about 62per cent of workers were found in the category of main work (includes agriculture and allied activities, manufacturing industries and service sectors)[as per 2011 Census District Census Handbook Zunheboto, a main worker is a person who has worked for major part of the reference period (i.e. 6 months or more during the last one year preceding the date of enumeration) in any economically productive activity] in terms of earning more than 6 months, while almost 40 per cent were involved in the marginal activity (marginal worker is a person who worked for 3 months or less but less than six months of the reference period (i.e. in the last one year preceding the date of enumeration) in any economic activity.] in terms of earning livelihood for less than 6 months. Agriculture is seen as one of the most important economic activities where 70 per cent of population practice terrace cultivation as a means of livelihood.

In the traditional Naga society, a distinguished economic role is seen where men were engaged in activities outside the home and women were confined within their homes. Women’s contribution to the economy was indispensable in the traditional Naga society in terms of maintaining the household, carrying out work in the fields and performing all manners of drudgery. Yet their contribution towards economic subsistence was never recognised and its significance was hardly valued.

Women in the Naga society are bound by customary laws which do not allow them to inherit any ancestral property but can possess moveable property; women were not allowed to participate in any decision-making in the community.  Women’s position in the Naga society within the family was found to be much better with their participation in the family and household activities being acknowledged and highly respected. Through time, the rising number of strong women organisations has helped women to be financially better off, and they gained more economic freedom.

 

3. Review of the different aspects of incidence of poverty

Studies have pointed out that incidence of poverty among women throughout the world was in a rising path in the 1970s and 1980s Visaria (1980). Hence, the term ‘feminization of poverty’, which is referred to as, increase in the proportion and severity of poverty in women-headed households due to factors such as increase in number of divorces and low pay status of women, evolved during the same time Moghadam (1997), Medeiros and Costa (2008). During this time, women who head their own households are nearly 5 times as likely to be poor as men who head their own households Wilson (1987).  However, the current status of the incidence of poverty among women has not changed much. This implies that poverty among women is not only multidimensional but is also multi-sectoral in the form of women experiencing poverty in different ways, time, and space Bradshaw (2002).

Study by Moghadam in the year 1997, identified three reasons for feminization of poverty, which makes female-headed households poorer than male-headed households.  Firstly, a woman is at a greater disadvantage in respect of the entitlements and capabilities. The second reason is the disproportionality observed in women’s lower earnings to the heavy work burden. Lastly, the women are faced with socio-economic barriers and constraints that are prevalent not only in the cultural laws and traditions but also in the legal and the market which only increases the vulnerability of women to poverty and deprivation. Studies have also shown that lone mothers or single mothers are prone to experience greater extremes of poverty due to lack in well-being and the inability to support their families, which led to the intergenerational transmission of poverty being passed on to their children Chant (1997).

Numerous studies have shown that custom, religion, widowhood, divorce or separation, polygamy and migration are also among the causes of a rise in female headship and poverty. Study also found that widowhood, desertions, divorce, separation, and non-marriage, lead to the emergence of female-headed households Blau and Ferber (1992), Tripathy (2005). Another study conducted by Fuwa in the year 1999, in Panama, showed that as compared to male-headed households, categories of female-heads such as widows and divorced women were particularly among the disadvantaged groups in both income and non-income dimensions of poverty. Beside the socio-economic disadvantage, women’s age also play a role in contributing to poverty. Bibars (2001) showed that female headed households are more easily driven to poverty due to old age and illiteracy. According to study by Dahl in the year 2005, found that women who are married at a young age or dropped out of school are likely to live in poverty when she gets older.

Social norms, like prohibiting interracial or interethnic marriage as well as the existence of cohabiting and visiting unions are also some of the contributing factors to poverty and hardship among women Socolow (2002). The patriarchal social system is also found to impose an obligation towards women’s behaviour in Asia as they had to go through appalling conditions of being subordinated within the households. Women were expected to go through compulsory emotions and required pains thus inclined to a lower entitlement Papanek (1990). Because of patriarchy, women have been victims of violent actions, and have also suffered various kinds of discrimination both physically and mentally not only in the male-dominated society but also within the families thereby disturbing the equilibrium in the society Chadha (2014). In Africa, for example, constraints relating to customary laws and conditions like divorce or widowhood jeopardized women’s right to own land Abuom (2000). As a result, majority of marginalised population are women Bentley (2004).

The literature has exposed that because of the reasons provided above, women who are heading households are likely to face stigmatisation and gender discrimination Barros et al. (1997). A number of studies conducted in India have shown that female-headed households tend to be poorer compared to male-headed households Dreze and Srinivasan (1995), Meenakshi et al. (2000) and Shubhashis, and Wadhwa (2003). Many households which are headed by female tend to have low-income earnings and high incidence of poverty Barros et al. (1997), Blau and Ferber (1992). Such households also tend to have very low social, economic and demographic features vis-à-vis male-headed households and are thus more likely to be poor. Hoynes in the year 1995, found that women who are heading household are more likely to have lower education levels and have smaller families. As a result, women tend to earn lesser than the male and have low access to high paying jobs and productive resources such as land and capital Buvinic and Gupta (1997), Dholakia (2003), Varley (1996). Thus, women who earn less or have no mean on income fall victim violence, due to drug use, alcoholism and gangsterism Strong (1996).

Women not only are engaged in low paid jobs but also less time consuming as they have other responsibilities attached to them such as taking care of the children and maintaining the households Desai and Ahmed (1998). Furthermore, study by Nandal in the year 2005, revealed apart from low paid, most women had very little or no job security and social security benefits. Central Coast Alliance United for a Sustainable Economy of 2002found that women experienced the devastating effects of poverty because they had the responsibility to pay attention to household and child-rearing, even when both the husband and wife worked full-time. They were denied protection by any labour organizations or labour legislation thus placing them in a weak and risky working environment. Also, a pregnant woman or who gave birth, temporarily discontinues working whilst she nurses her child and is considered as a non-regular worker, therefore, countenance non-eligibility for social security benefits. Study by Omar and Ogenyi in the year 2004, found that issues like the prevalence of gender stereotypes permeate discrimination and hindered women’s opportunities to advancement in Nigerian Civil Service (NCS). A Country paper of Japan during the first ASEAN meeting in 2009 indicated the stereotypical views of gender role of women contributed to poverty among.  Gender stereotypes hamper decision-making for women.

Crocco, Cramer and Meier in their study in 2008, found that stereotypical view towards women hinders their ability and self-efficacy towards the carrier and knowledge of computer science. Moghadam further supported this, based on a study conducted in the year 2010, who argued that there is a wide gender gap in developing countries which is mainly attributed to the cultural and social values and stereotypical views when it comes to accessing new information and communication technologies for women. Hence, female employees can only accept low-risk jobs, which in turn lead to unemployment among women. As a consequence, women are caught in a vicious circle of illiteracy, ignorance, disempowerment, powerlessness as there exists gender gap in all spheres of development and hence, poverty Khasacha (1994).

In developing countries like India, women who are heading households, although they comprise a very small proportion of the total households, they constitute a significant proportion of the poor households and suffer from vulnerabilities when compared with those of male headed households Gangopadhyay and Wadhwa (2003). Generally, women in the rural areas are found to lag behind their counter parts in the urban areas mainly due to limited opportunities available to them and with agriculture being a predominant sector providing a means of livelihood, are vulnerable to poverty. Therefore, the strategy for rural development must recognise the existence of female-headed households in the context of economic development Rustagi (2006). A study conducted in Kasargod district in Kerala by Matthew in the year 2012, revealed that a fall in female rural employment was moderated by distress-driven employment. The socio-economic profile and changes in the labour market data led to economic privation overriding job preferences. Women were found to be mainly engaged in low-paid elementary occupations that led to disguised unemployment, thus highlighted the level of deprivation and distress in the society.

Tripathy in the year 2006, found that women in Orissa enjoyed limited freedom in every walk of life, and categories of women from poverty stricken rural families, scheduled caste women and tribal women were mainly vulnerable to poverty. And since most of the female-headed households were illiterate, they depended on manual work or worked as agricultural labourers. Even the children were found to provide support to the family by being engaged in various agricultural and manual activities. Yet, such families continued to remain in debt and were poverty stricken. The lack of decision-making power also puts them at a low economic status. This situation largely prevailed in the rural and tribal dominated areas of the state. A similar result was found by Panda in the year 1997, where women’s differential earnings in rural Orissawas attributed mainly due to inferiority in learning which provided lesser opportunities of earning high income. The literacy rate among the male was 57.3 per cent in comparison to the low literacy rate among women which was only 31.9 per cent which therefore increased the income and employment opportunities for men more than women.

Through the review of literature, we observed that women have been subjected to a great degree of subordination and subjugation being imposed upon their lives. We find that women are faced with social mores and domestic violence and also have lower access to resources, paid lower wages, lesser or no attainment of education and less access to credit. The traditional customs and social norms and behaviour in a society and familial pressures have not only promoted the gender biasedness but women are also seen to be not at par with men in many respects. These, in turn, permeate and drag women to unsympathetic situation be it at home or outside. Thus, women are still considered inferior to men by most cultures, especially in the underdeveloped countries. The case of disparities among men and women is mostly seen in developing countries like India and in some South-Asian and African countries as well, where women continue to face a high degree of discrimination and biasedness and a high level of inequality. The literature showed that the issue of poverty among women is almost similar in most developing world including India. The study has therefore helped to further understand the incidence of poverty and inequality in female-headed households and male-headed households in India.

 

4. Data and methodology of the study

An in-depth empirical study has been made on the basis of a primary survey to look into the incidence of poverty and levels of deprivation among the female-headed households vis-à-vis the male-headed households in Zunheboto district of Nagaland. For the purpose of the study, purposive sampling was adopted in which a total of 8 villages, taking two villages from each of the four community and rural development blocks of the district were selected. A sample of 160 households with 20 representative households from each of the 8 villages within the Community and Rural Development Block was selected.

Further, for a better understanding of the poverty scenario and also the intensity of poverty of the male-headed and female-headed households, we categorized the households into five income brackets. The categorization was done similar to the categorization set by the Ministry of Rural Development and followed by Tariang (2016) and Thomas (2004). The poverty line for the present study was set at Rs. 6150 which was arrived at following the poverty line set by the Rangarajan’s panel which was fixed at Rs. 1,229.83 per capita per month for 2010-2011 in rural areas. Thus, the poor have been defined as those having an annual household income of Rs.73, 800 for a family size of 5 members. All households, therefore, with a per capita income level below the poverty line were considered as poor.

The income classes were categorized as follows - ‘Non-Poor’ households for all households with a monthly income above Rs.6150. The second income category included all the ‘Poor’ households with a monthly income between Rs.4613 and Rs.6150. The ‘Poorer’ households were included in the third category whose monthly income ranged between Rs.3075 and Rs.4612; ‘Poorest’ households with a monthly income between Rs.1538 and Rs.3074 were included in the fourth income category. The fifth category or the ‘Destitute’ households included all those households with a monthly income which is less than or equal to Rs.1537. Thus, the five income categories are described as ‘Non-Poor’, ‘Poor’, ‘Poorer’, ‘Poorest’ and ‘Destitute’. It may be repeated here that the households in the last four income categories earn income which is below the poverty line of Rs.6150 and hence are considered as poor.

 

4.1. Poverty indices

The study also adopted specific poverty measurement tools for analysing the incidence and intensity of poverty and deprivation among the female-headed households vis-à-vis the male-headed households across the 160 representative households in the 8 sample villages of Zunheboto district of Nagaland. The Head Count Ratio and the Poverty Gap Ratio was used for measuring the incidence and intensity of poverty while the Gini Coefficient has been used for measuring the inequality in the distribution of income. Further, since the status of deprivation is likely to vary across households, the Adjusted Head Count Ratio has been used as a tool of analysis for the purpose. Various poverty indices used in the study are as follows:

The Head Count Ratio (H) as the simplest of all poverty measures of the incidence of poverty takes into account the number of poor (q) as a proportion of the total population (n). It can be expressed as,

 

H=q/n                                                                                                           Equation 1

 

The Head Count Ratio clearly measures the incidence of the percentage of population living below the poverty line. However, this poverty index has its limitations in that it does not really show the depth of how poor the poor really are.

The Poverty Gap Ratio (PGR) or the Poverty Gap Indexmeasures the intensity of poverty and determines how far below the poverty line (z) the consumption levels of the poor (H) are. The smaller the poverty gap index, the greater is the potential for poverty alleviation and the lesser resources are required to lift the poor from poverty.

The poverty gap ratio can be written as,

 

g = [(z-m) / z].H                                                                                         Equation 2

 

where, ‘m’ measures the mean income, ‘H’ is the Head Count Ratio and ‘g’ provides information about the intensity of poverty if all the poor are assured to have exactly the same income, which is less than the poverty line. However, in practice, income of the poor is unequally distributed and ‘g’ cannot be an adequate measure of poverty. Since this measure is insensitive to the redistribution of income within the poor, we further analysed the changes in inequality among the poor by taking into account of Gini Coefficient and its implications.

The Gini Coefficient measures the degree of income inequality with values ranging between 0 and 1, where ‘0’ corresponds to perfect income equality which means every individual has the same income whereas ‘1’ corresponds to perfect income inequality which implies that every individual has zero income while only one person has all the income.

It is given as

 

G = 1-Σ (X_k – X_k-1) (Y_k + Y_k-1)                                                                  Equation 3

 

where, ‘X_k’ is the cumulated proportion of the population variable,for k=0,……,n, ‘Y_k’is the cumulated proportion of the income variable, for k=0,…..,n.

The Adjusted Head Count Ratio (AHCR), otherwise known as Multidimensional Poverty Index (MPI), was developed by Oxford Poverty and Human Development Initiative (OPHI’s), Sabina Alkire and James Foster. It is a measurement of poverty that takes into account the components and also the extensiveness of poverty. For the purpose of our study, we took a special consideration of a poor household, where after identifying the poor, we further looked into how and who a poor is by measuring the severity of poverty as well as the intensity of deprivation.

The multidimensional poverty measurement involves both identification function and poverty measure that combines the information into overall extent of poverty and for counting the number of poor Bourguignon and Chakravarty (2003). The difference between the Head Count Ratio and Adjusted Head Count Ratio is that the Head Count Ratio (HCR) measures only the incidence of poverty while the Adjusted Head Count Ratio (AHCR), besides taking into account the incidence of poverty, it also measures the extent of deprivation suffered by an individual.

Adjusted Headcount Ratio is the mean of the censored deprivation score vector. Following the Alkire-Foster counting methodology of 2015, it is given as

 

                                             Equation 4

 

where, 𝑀₀ = 𝐻 × 𝐴, (both H and A are partial index) ‘𝐻’ represents the percentage of the population that is poor or the multidimensional head count ratio or the incidence of poverty. ‘𝐴’ is the intensity of poverty or the average deprivation score across the poor.

           Hence,

                          The average deprivation score across the poor is given by

 

𝐴                                                                                     Equation 5

          

‘c_i (k)’represents the share of possible deprivations experienced by a poor person’i’, ‘q’ is number of persons identified as poor, ‘𝑘’ represents the share of possible deprivations experienced by a poor person.

 

 

 

5. Results and discussions

The empirical analysis of the present study has been done both at the village and at the block level. An analysis of the distribution of households across the 8 sample villages was more biased towards the male-headed households with 58 per cent of the households being male-headed. Out of the total 160 sample households, 53 per cent of households were poor. The study indicated that 57 per cent of female-headed households fell below the poverty line compared to 50 per cent of male-headed households Table 1. There was a disparity in the distribution of poor female-headed households across villages. While not much disparity was indicated in the distribution of poor male-headed households except in the case of Vekuho village (10 per cent) and Askhuto village (25 per cent). Across the 4 Community Development Blocks, Zunheboto Block had the highest proportion of poor households with 65 per cent. While in terms of distribution of households, 3 Community Development Blocks (Tokiye Block, Akuhaito Block and Zunheboto Block) had a very high proportion of male-headed households. Only Satakha Block registered more female-headed households (53 per cent).

Table 1

Table 1 Household Distribution of Poor Across Villages and Blocks in Percentage
Villages	Blocks	Poor Households		Male-Headed Households		Poor Male-Headed Households		Female-Headed Households		Poor Female-Headed Households
Shoixe	Satakha	65.00	58.00	55.00	48.00	64.00	63.00	45.00	53.00	67.00	52.00
Zungti		50.00		40.00		63.00		60.00		42.00
Aquba	Tokiye	50.00	53.00	80.00	68.00	56.00	56.00	20.00	33.00	25.00	46.00
Lukhuyi		55.00		55.00		55.00		45.00		56.00
Askhuto	Akuhaito	40.00	38.00	60.00	55.00	25.00	18.00	40.00	45.00	63.00	61.00
Vekuho		35.00		50.00		10.00		50.00		60.00
Yemishe	Zunheboto	75.00	65.00	65.00	60.00	62.00	63.00	35.00	40.00	100.00	69.00
Sheyipu		55.00		55.00		64.00		45.00		44.00
Total		53.00	53.00	58.00	58.00	50.00	50.00	42.00	42.00	57.00	57.00
Source Based on Primary Survey

 

A study of the distribution of households across income groups showed that 47 per cent of the households belonged to the ‘Non-Poor’ category Table 2, while the remaining 53 per cent households were poor. Among the poor, 19 per cent households were in the ‘Poor’ income category and lie very close to the poverty line. 16 per cent households were found to belong to the ‘Poorer’ income category. The analysis further revealed the presence of 13 per cent households in the ‘Poorest’ income category and 5 per cent households among the ‘Destitute’ households also suffered the pangs of poverty. It was noted that two villages, Askhuto and Vekuho had the largest proportion of ‘Non-Poor’ households (60 per cent and 65 per cent respectively).

Among the ‘Poor’ category households, 3 villages namely, Aquba, Lukhuyi, and Yemishe villages had the highest number of ‘poor’ households (25 per cent). In the ‘Poorer’ income category, Lukhuyi village comprised the highest proportion of poor households (25 per cent). Only one village, Shoixe village, registered the highest proportion of poor among the ‘Poorest’ category (25 per cent). While Yemishe village registered the highest proportion of households (25 per cent) that lie the farthest from the poverty line and thus suffer from extreme poverty. These households fell in the ‘Destitute’ category. Only 3 out of the 8 villages had destitutes. To sum up, a greater percentage of poor households lay nearer the poverty line, while only 9 per cent of the poor (8 households out of 85) were in abject poverty as ‘Destitutes’.

An observation of the block-wise distribution of households across income groups showed almost half of the poor households in Tokiye block lay nearer the poverty line. Three blocks (Satakha, Tokiye and Zunheboto) registered the highest number of households in the ‘Poorer’ income category. Among the households in the ‘Poorest’ income group, Satakha village had the highest number of poor households (23 per cent). Zunheboto block registered the highest proportion of households in the ‘Destitute’ category at 18 per cent, which was a significant proportion of the poor. Significantly, it is also Zunheboto block, the more urban block that had the largest proportion of poor households (65 per cent).

 

Table 2

Table 2 Village-Wise and Block-Wise Distribution of Households Across Income Group in Percentage (%)
Villages	Blocks	Above Rs.6150 (Non-Poor)		Rs.4613-6150 (Poor)		Rs.3075-4613 (Poorer)		Rs.1538-3074  (Poorest)		Rs.0-1537 (Destitute)
Shoixe	Satakha	35.00	43.00	20.00	18.00	20.00	18.00	25.00	23.00	0.00	0.00
Zungti		50.00		15.00		15.00		20.00		0.00
Aquba	Tokiye	50.00	48.00	25.00	25.00	10.00	18.00	15.00	10.00	0.00	0.00
Lukhuyi		45.00		25.00		25.00		5.00		0.00
Askhuto	Akuhaito	60.00	63.00	10.00	13.00	15.00	10.00	15.00	13.00	0.00	3.00
Vekuho		65.00		15.00		5.00		10.00		5.00
Yemishe	Zunheboto	24.00	35.00	25.00	23.00	20.00	18.00	5.00	8.00	25.00	18.00
Sheyipu		45.00		20.00		15.00		10.00		10.00
Total		47.00	47.00	19.00	19.00	16.00	16.00	13.00	13.00	5.00	5.00
Source Based on Primary Survey

 

An analysis of the distribution of households based on the sex of the head of the households across income groups showed that the poor and non-poor were equally distributed among the male-headed households (50 per cent each) Table 3. It was also noted that 21 per cent of the male-headed households fell in the ‘Poor’ income category, while 19 per cent male-headed households lie in the ‘Poorer’ income class. There were also households in the ‘Poorest’ category (8 per cent) and only 2 per cent households fell in the ‘Destitute’ category. It was also observed that 38 per cent of the male-headed households in Zungti village recorded the highest proportion in the ‘Poor’ income class and lay very close to the poverty line. Shoixe village registered the highest proportion of male-headed households in the ‘Poorer’ income class (37 per cent). Sheyipu village and Yemishe village each registered the highest proportion of male-headed households belonging in the ‘Poorest’ and the ‘Destitute’ category respectively. In fact, the latter village is the only village among the 8 that had destitute families. The distribution of poor male-headed households followed the same pattern as that of all households in that a greater percentage of the poor households were just below the poverty line and the least were ‘Destitutes’.

In the block-wise distribution of male-headed households, 50 per cent of the total households had incomes above the poverty line. Most of the poor households were distributed closer to the poverty line; and the severity of poverty among these households is considered to be much less. Among the ‘Poorer’ income class, Satakha Block had the highest proportion of households below the poverty line at 26 per cent. Satakha block also registered the highest proportion of poor-male headed households (11 per cent) in the ‘Poorest’ income category. Only Zunheboto block had male-headed households that fell in the ‘Destitute’ category (9 per cent).

Table 3

Table 3 Village-Wise and Block-Wise Distribution of Male-Headed Households Across Income Group
Villages	Blocks	Above Rs.6150 (Non-Poor)		Rs.4613-6150 (Poor)		Rs.3075-4613 (Poorer)		Rs.1538-3074 (Poorest)		Rs.0-1537 (Destitute)
Shoixe	Satakha	36.00	37.00	18.00	26.00	36.00	(26.00)	9.00	11.00	0.00	0.00
Zungti		38.00		38.00		13.00		3.00		0.00
Aquba	Tokiye	44.00	44.00	31.00	30.00	13.00	(19.00)	13.00	7.00	0.00	0.00
Lukhuyi		45.00		27.00		27.00		0.00		0.00
Askhuto	Akuhaito	75.00	82.00	8.00	5.00	8.00	(9.00)	8.00	5.00	0.00	0.00
Vekuho		90.00		0.00		10.00		0.00		0.00
Yemishe	Zunheboto	38.00	38.00	23.00	21.00	23.00	(25.00)	0.00	8.00	15.00	8.00
Sheyipu		36.00		18.00		27.00		18.00		0.00
Total		50.00	50.00	21.00	21.00	19.00	19.00	8.00	8.00	2.00	2.00
Source Based on Primary Survey

 

The analysis of female-headed households across various income groups indicated that there were more poor female-headed households (57 per cent) Table 4. Aquba village had the highest proportion of ‘Non-Poor’ households (75 per cent). Across the different income classes, the highest proportion was registered in the ‘Poorest’ income category of households (20 per cent) followed by the ‘Poor’ income category (18 per cent). Shoixe village had the highest number of female-headed households in the ‘Poorest’ income category while Vekuho village had the highest number of female-headed households in the ‘Poor’ category. Askhuto village had the highest number of households in the ‘Poorer’ income group (25 per cent). Yemishe village had the highest number of households in the ‘Destitute’ category (43 per cent) showing that the poorest of the poor in the village were destitutes. It may be noted that all households were poor in this village.

Two Community Development Blocks, Akuhaito and Zunheboto Block, registered the highest number of households falling below the poverty line. However, these households lie closer to the poverty line, and they do not suffer from severe poverty. It is also evident that households in Satakha Block suffer much from poverty with the highest proportion of households (33 per cent) falling in the ‘Poorest’ income category. On the other hand, households in Zunheboto block seemed to experience the severity of poverty the most with over 31 per cent of the households falling in the ‘Destitute’ category; this trend was exhibited in the male-headed households too.

It may be pointed out from the analysis that although the number of female-headed households is lesser than that of male-headed households, yet the number of poor across income groups is not only more biased towards the female-headed households but also, they suffer much more extreme form of poverty.

Table 4

Table 4 Village –Wise and Block-Wise Distribution of Female-Headed Households Across Income Group
Villages	Blocks	Above Rs.6150 (Non-Poor)		Rs.4613-6150 (Poor)		Rs.3075-4613 (Poorer)		Rs.1538-3074 (Poorest)		Rs.0-1537 (Destitute)
Shoixe	Satakha	33.00	48.00	22.00	10.00	0.00	10.00	44.00	(33.00)	0.00	0.00
Zungti		58.00		0.00		17.00		25.00		0.00
Aquba	Tokiye	75.00	54.00	0.00	15.00	0.00	15.00	25.00	(15.00)	0.00	0.00
Lukhuyi		44.00		22.00		22.00		11.00		0.00
Askhuto	Akuhaito	38.00	39.00	13.00	22.00	25.00	11.00	25.00	(22.00)	0.00	6.00
Vekuho		40.00		30.00		0.00		20.00		10.00
Yemishe	Zunheboto	(0.00	31.00	29.00	25.00	14.00	6.00	14.00	(6.00)	43.00	31.00
Sheyipu		56.00		22.00		0.00		0.00		22.00
Total		43.00	43.00	18.00	18.00	10.00	10.00	20.00	20.00	9.00	9.00
Source Based on Primary Survey

 

5.1. Incidence of poverty, inequality and deprivation at the village level and block level

As we look into the incidence of poverty, indicated by the Head Count Ratio, across the 8 sample villages, it was observed that 6 villages had poverty Head Count Ratio of 50 per cent or more Table 5. Among the male-headed households, 6 villages had a poverty head count ratio of 50 per cent or more, while for female-headed households, 5 villages had a poverty head count ratio of 50 per cent or more. Among the female-headed households, Yemishe village had the highest poverty head count with all households being poor (100 per cent), thus indicating a high incidence of poverty. Among the male-headed households, Sheyipu and Shoixe villages had a high HCR of 64 per cent.

A comprehensive study of the percentage of population in poverty showed that male-headed households in 2 development blocks (Satakha Block and Zunheboto Block) had HCR over 60 per cent. While the female-headed households in Zunheboto and Akuhaito Blocks recorded an HCR of over 60 per cent. All but Akuhaito block exhibited high HCRs among both male-headed households and female-headed households.

Table 5

Table 5 Head Count Ratio of Households Across Villages and Blocks
Villages	Name of Blocks	Male-headed		Female-headed		Total HCR
Shoixe	Satakha	63.64	63.16	66.67	52.38	65.00	57.50
Zungti		62.50		41.67		50.00
Aquba	Tokiye	56.25	55.56	25.00	46.15	50.00	52.50
Lukhuyi		54.55		55.56		55.00
Askhuto	Akuhaito	25.00	18.18	62.50	61.11	40.00	37.50
Vekuho		10.00		60.00		35.00
Yemishe	Zunheboto	61.54	62.50	100.00	68.75	75.00	65.00
Sheyipu		63.64		44.44		55.00
Source Based on Primary Survey

 

The intensity of poverty among the households is found to be the highest in Yemishe village with a Poverty Gap Ratio of 0.37 followed by Shoixe village with a PGR of 0.24 Table 6. Among the male-headed households, Yemishe village registered the highest Poverty Gap Ratio of 0.25, and this village also registered the highest estimate of Poverty Gap Ratio among the female-headed households (0.59).

Looking into the Community Development Blocks, the Poverty Gap Ratio (PGR) of households belonging to Zunheboto block registered the highest number of poor households Gupta et al. (2003). The same Block also experienced the highest intensity of poverty as indicated by the PGR value of 0.29. On the other hand, a very low PGR (0.13) was recorded among the households in Tokiye Block. Furthermore, both the male-headed households as well as the female-headed households belonging to Zunheboto block registered the highest PGR of 0.23 and 0.38 respectively. The study found that, in comparison with the male-headed households, the intensity of poverty was found to be more severe among the female-headed households in all blocks.

Table 6

Table 6 Poverty Gap Ratio of Households Across Villages and Blocks
Villages	Blocks	Poverty Gap Ratio		Poverty Gap Ratio of Male Headed Households		Poverty Gap Ratio of Female Headed Households
Shoixe	Satakha	0.24	0.21	0.20	0.18	0.28	0.24
Zungti		0.18		0.15		0.21
Aquba	Tokiye	0.13	0.13	0.13	0.12	0.13	0.15
Lukhuyi		0.14		0.12		0.16
Askhuto	Akuhaito	0.16	0.15	0.07	0.06	0.28	0.25
Vekuho		0.13		0.03		0.23
Yemishe	Zunheboto	0.37	0.29	0.25	0.23	0.59	0.38
Sheyipu		0.21		0.22		0.21
Source Based on Primary Survey

 

The study also looked into the measure of instability of income between the male-headed households and the female-headed households across the 8 sample villages using the Gini Coefficient index. One of the major factors that contribute towards poverty is the level of inequality prevailing among the households. It is evident from Table 7 that there is instability of income among households across the 8-sample village. The values of Gini Coefficient generally reflected high income instability for both the male-headed as well as the female-headed households. A high estimate of Gini Coefficient was reflected in Aquba village (0.20), while Vekuho and Yemishe villages assumed very low values of 0.02 each. Further, we see that there is lesser income instability among the households in these two villages Table 7.

In case of male-headed households, Lukhuyi village had the highest estimate of the Gini Coefficient with a value of 0.33 while it was only 0.01 in Shoixe village. The income levels were unstable as shown by the high values of the Gini coefficient in Lukhuyi (0.33), Askhuto (0.23) and Aquba (0.21) villages. Among the female-headed households, the highest index of Gini coefficient was 0.45 observed in Yemishe village while Zungti village had the lowest value of Gini Coefficient 0.01. Yemishe village therefore exhibited a very high level of income instability as reflected by a Gini Coefficient of 0.45. Sheyipu village also exhibited a high level of income instability among female-headed households (0.34). Interestingly, Lukhuyi village indicated zero instability and inequality of income with a Gini Coefficient of 0.00 thus indicating perfect income equality among the poor households.

Taking into account the degree of income instability and inequality as one of the determinants of poverty among the households, the study showed the highest value of Gini Coefficient (0.10) was observed among the households belonging to Zunheboto Block. Whereas the lowest value (0.01) was observed among the households from Tokiye Block. However, among the female-headed households, the highest Gini Coefficient was observed in Zunheboto Block (0.28), while among the male-headed households, the extent of inequality was observed to be the highest in Satakha Block (0.13). The degree of income instability was more pronounced among the male-headed households, except in Zunheboto block. Further, the degree of income inequality was not severe among both male-headed households and female-headed households in all the blocks except in Zunheboto Development Block among female-headed households (0.28)

Table 7

Table 7 Gini Coefficient of Households Across Villages and Blocks
Villages	Blocks	Male-headed Households		Female-headed Households		Village level
Shoixe	Satakha	0.01	0.13	0.04	0.05	0.05	0.04
Zungti		0.11		0.01		0.03
Aquba	Tokiye	0.21	0.05	0.02	0.05	0.20	0.01
Lukhuyi		0.33		0.00		0.15
Askhuto	Akuhaito	0.23	0.07	0.11	0.01	0.15	0.07
Vekuho		0.11		0.03		0.02
Yemishe	Zunheboto	0.05	0.02	0.45	0.28	0.02	0.10
Sheyipu		0.04		0.34		0.16
Source Based on Primary Survey

 

The Adjusted Head Count Ratio (AHCR) also known as the Multidimensional Poverty Index (MPI) that was launched in the year 2010 by the United Nation Development Program (UNDP), measures the breadth and components of poverty. For the purpose of the study, we adopted the Alkire Foster method of 2011 for measuring the levels of deprivation that could exist among the households across the 8 sample villages. The interesting fact about the AHCR as compared to the traditional measures of poverty like the Head Count Index, is that unlike the Head Count Ratio which only takes into account the incidence of poverty in terms of determining the proportion of poor. The AHCR or the Adjusted Head Count Ratio takes into account the breadth, depth or the severity of poverty and deprivation by first assessing the incidence or the aggregate of poverty under each dimension and indicators assigned. Further, the AHCR breaks down the dimensions to specify the various components of deprivation and identify the intensity of poverty.

In order to determine the incidence of poverty and deprivation between the male-headed households and the female-headed households, each household has been taken as a unit of analysis rather than the village as a whole. To ensure feasibility of study, the dimensional specifications in the analysis and the choice of weights as ‘Deprived' or ‘Not Deprived’ and also the ‘Cut-offs’ ‘Dimensions’ and ‘Indicators’ has been adopted more or less from the same method of choices used by Alkire and Foster Approach to Multidimensional Poverty Measurement of 2011.

As each dimension is specified, a ‘deprived’ household is denoted by ‘D’ whereas a household that is ‘not deprived’ is denoted by ‘ND’. Equal weightage has been applied across all dimensions/indicators to obtain the results. For the purpose of the study, 3 core dimensions - ‘Health’, ‘Asset Ownership’, and ‘Education’ were chosen, and 12 indicators were selected for measuring the level of deprivation. The indicators under the ‘Health’ dimension are - Primary Health Centre (PHC), Midwife, and Pucca Latrine. Under the ‘Asset Ownership’ dimension are - T.V, Phone, Animal Yoke, and Pucca House. Under the ‘Education’ dimension are - attained Lower Primary (Std. 1-4), Upper Primary (Std. 5-7), Secondary (Std. 8-10), Higher Secondary (Std 11-12), and ‘Graduate and above’. Further, the ‘Deprivation Cut-Off’ has been set at ‘6’ being the midpoint of the 12 indicators. Therefore, any household having 6 and above up to 12 deprivations may be considered as poor and deprived.

Taking into account the incidence of poverty and deprivation indicated by the AHCR,the study showed that of all the deprived households across the 8 sample villages; 5 villages had a very high proportion of deprivation with an AHCR value of over 30 per cent Table 8. Only one village, Sheyipu village, showed a lower level of deprivation, with AHCR value of 22 per cent. Furthermore, Yemishe village has the highest number of deprived households with 65 per cent. It is also registered the highest level of deprivation with AHCR value of over 39 per cent.

The level of deprivation experienced by male-headed households was the highest in Zungti village and Shoixe village with AHCR values of over 30 per cent respectively, thus indicating that these households experienced a severe state of deprivation. However, unlike the male-headed households with lesser variation of deprivation, the female-headed households suffered from deprivation much more with the highest level of AHCR at 65 per cent in Aquba village. Furthermore, this village registered with 100 per cent of deprived female-headed households.

Looking at the Block level, Tokiye, Akuhaito and Zunheboto Community Development Blocks experienced almost the same trend of deprivation registering AHCR value of 30 per cent. Whilst households under Satakha Block registered the highest number of deprived households (53 per cent) who also experienced the highest intensity of deprivation at 32 per cent.

Therefore, households not only fell below the poverty line but also experienced severe deprivations. The study also found that the female-headed households experienced by and large, a higher degree of deprivation than the male-headed households both at the Village level and Block level.

Table 8

Table 8 Adjusted Head Count Ratio of Households Across Villages and Blocks in Percentage (%)
Villages	Blocks	Total Deprived HHS		Deprived MHHS		Deprived FHHS		Total AHCR		AHCR of MHHs		AHCR of FHHs
Shoixe	Satakha	50.00	53.00	55.00	58.00	44.00	48.00	30.00	31.88	31.06	32.89	28.70	30.95
Zungti		55.00		63.00		50.00		33.75		35.42		32.64
Aquba	Tokiye	55.00	48.00	44.00	33.00	100.00	77.00	34.17	29.79	26.56	20.37	64.58	49.36
Lukhuyi		40.00		18.00		67.00		25.42		11.36		42.59
Askhuto	Akuhaito	50.00	45.00	42.00	32.00	63.00	61.00	32.50	30.21	23.61	18.18	45.83	44.91
Vekuho		40.00		20.00		60.00		27.92		11.67		44.17
Yemishe	Zunheboto	65.00	50.00	54.00	46.00	86.00	56.00	39.17	30.42	29.49	25.69	57.14	37.50
Sheyipu		35.00		36.00		33.00		21.67		21.21		22.22
Source Based on Primary Survey

 

5.2. Head count ratio (HCR) and adjusted head count ratio (AHCR)

An attempt was also made to analyze the Head Count Ratio (HCR) and the Adjusted Head Count Ratio (AHCR). In Table 9, we observe that the values of the AHCR are much lower than that of the HCR in all villages. This trend also followed among the female-headed and male-headed poor households, except in Aquba village for female-headed households and Zungti village for male-headed households. Again, the values of the AHCR were found to be much lower than that of the HCR in all blocks. The same trend was observed among the male-headed households and in all blocks with regards to the female-headed households, except in the case of Tokiye block.

Table 9

Table 9 HCR and AHCR at the Village level and Block level
Villages	Blocks	HCR		AHCR		HCR of FHHs		AHCR of FHHs		HCR of MHHs		AHCR of MHHs
Shoixe	Satakha	65.00	57.50	30.00	31.88	66.67	52.38	28.70	30.95	63.64	63.16	31.06	32.89
Zungti		50.00		33.75		41.67		32.64		62.50		35.42
Aquba	Tokiye	50.00	52.50	34.17	29.79	25.00	46.15	64.58	49.36	56.25	55.56	26.56	20.37
Lukhuyi		55.00		25.42		55.56		42.59		54.55		11.36
Askhuto	Akuhaito	40.00	37.50	32.50	30.21	62.50	61.11	45.83	44.91	25.00	18.18	23.61	18.18
Vekuho		35.00		27.92		60.00		44.17		10.00		11.67
Yemishe	Zunheboto	75.00	65.00	39.17	30.42	100.00	68.75	57.14	37.50	61.54	62.50	29.49	25.69
Sheyipu		55.00		21.67		44.44		22.22		63.64		21.21
Source Based on Primary Survey

 

In the literature on the AHCR, both the words poverty and deprivation have been synonymously used to interpret the value of the AHCR. The Alkire and Foster method of AHCR seeks to answer the question of “who is poor” by taking into consideration the intensity of each person’s poverty. If the values of the AHCR alone were read vis-à-vis that of the HCR, could we conclude from the above data that the “poverty” in the sample villages and the blocks is much less than as reflected by the values of the HCR, even though all of these households are living below the poverty line? Could, therefore, poverty and deprivation be synonymously used in the AHCR, or just “deprivation” be a more apt interpretation of the AHCR values? Do we need to reconceptualize the AHCR? This question needs more investigation through additional and more extensive research on these two indices of poverty/deprivation.

 

6. Conclusion, discussions, and policy implications

This paper focused on the incidence of poverty, inequality, and deprivation among the female-headed households, vis-à-vis the male-headed household in Zunheboto district, Nagaland. Given the poverty line estimation provided by the Rangarajan’s panel and based on the empirical analysis of the study found the female-headed households to be poorer than the male-headed households. As out of the total 160 sample households, 53 per cent of households were poor, where 57 per cent of female-headed households fell below the poverty line compared to 50 per cent of male-headed households. Not only was the distribution of poor households found to be higher among the female-headed households, but these households also suffer from a high incidence of poverty and inequality.

The study found that in 5 of the 8 sample villages, the incidence of poverty was higher in the female-headed households than in the male-headed households. Furthermore, the female-headed households experience more intensity of poverty. Again, though in 5 of the 8 villages, male-headed households had a higher degree of income inequality, in 2 of the remaining 3 villages, the female-headed households experienced high income instability. The female-headed households also suffered from a higher degree of deprivation than the male-headed households. However, both at the village and the block levels, the values of the AHCR were less than the HCR, implying that the extent of deprivation is less pronounced than the level of absolute poverty.

One other interesting point that emerged from this study is that there were more poor households in Zunheboto Block as compared to the other 3 blocks. Further, the intensity of poverty and income inequality was more pronounced in this block as compared to the other blocks. The extent of deprivation was also similar to the other blocks, although it may be mentioned that the sample villages in this block are closer to the district headquarters than the villages of the other blocks. Therefore, one would have expected these villages to be better off. This is one phenomenon that requires further investigation.

As with the results that emerged from the study, social welfare mechanisms need to be strengthened in such a way that priorities should be set and target towards poverty alleviation programmes specifically in those villages that fall below the poverty line and are deprived. Further, it is essential to consider ways of reducing the intensity and extent of poverty, inequality, and deprivation especially among households headed by women not only in Zunheboto district but the whole of Nagaland. These poverty alleviation programmes should address to the enhancement of a poor household and specifically target poor women. Could be in terms of more opportunities for education, ensure availability of sufficient health care centres and increase their accessibility to assets and employment earning opportunities. Further with the help of the various programmes it should not only promote all round development of women in the society in general, but also in the female-headed households in particular.

 

CONFLICT OF INTERESTS

None. 

 

ACKNOWLEDGMENTS

None.

 

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