Editorial Board

A Refereed Monthly International Journal of Management

Analyzing the Interplay between Living Condition and Income Earned on the Economic Empowerment of the Women Working in Urban Informal Sector in the City of Taj: An Empirical Study

Reshmi Ganguly

Associate Professor

Lady Shri Ram College,

University of Delhi.

reshmiganguly@lsr.du.ac.in

 

Sonia Goel,

Associate Professor

Department of Economics,

Ramjas College, University of Delhi. 

sonia@ramjas.du.ac.in

https://orcid.org/0000-0002-5764-6780

Corresponding Author

 

Shreyansh Jain

Student, MA (Economics)

Delhi School of Economics,

University of Delhi.

jainshreyansh755@gmail.com

 

Abstract

Access to proper infrastructure plays a vital role in women empowerment. This helps her to carry out everyday chores more efficiently, free up time for educational opportunities, productive work, and participation in community life and decision making.

Accessibility to better living conditions at home can enhance and improve women’s ability to question, obtain knowledge and utilize right information. It further can enhance their intra household bargaining power, and their decision-making ability to optimally utilize resources for their betterment and substantially take rational decisions.

Using data from a primary survey of working women in the urban informal sector in the city of Agra, this paper explores the extent to which women have access to living conditions at home. The paper also tries to explore the relationship between the living conditions which women working in the urban informal sector enjoy at home and their economic empowerment. For this, the Economic empowerment index (EEI) and living condition Index (LCI) index have been constructed using the method of Principal Component analysis.

The main results of our paper are that access to living conditions does play an important role in improving the overall health conditions of the women, which further leads to economic empowerment. But more time in terms of hours spent working makes them time-poor and reduces their economic productivity. A lot of women welfare schemes initiated by the Government of India to provide quality housing to women is a right move in this direction. It can boost their confidence, help them to earn more income, spend more independently and hence a rise in their economic empowerment index.

Keywords: Economic Empowerment; informal sector; living conditions, Principal Component Analysis, time poor.

JEL Codes:  I26; J24; D89; J46

Introduction

Access to proper infrastructure plays a vital role in women economic empowerment (Morgan et al, 2020). This helps her to carry out everyday chores more efficiently, free up time for educational opportunities, productive work, and participation in community life and decision making. One of the ways through which these goals can be achieved is through access to good living conditions at home. To the best of our knowledge, we haven’t come across any study which investigates the relationship between economic empowerment of women and living conditions that any woman enjoys at home.

This paper thus investigates that despite being working, is economic empowerment enjoyed by the women? Further it tries to establish relationship between economic empowerment and the living conditions enjoyed by these women at home. We did this analysis by collecting primary data of women working in the urban informal sector in the city of Taj. The main results of our paper are that access to better living conditions does play an important role in improving economic empowerment of women. Although, in presence of time spent in working, it becomes insignificant on its own, it gains significance when considered as an interaction between living condition and higher income earned.  It leads to a positive rise in the economic empowerment index of working women.

 The paper is divided into the following sections. Section 2 provides brief literature on economic empowerment of women, the living conditions which she has access to and the relationship between the two.  Section 3 describes the data collection procedures and also presents descriptive statistics. Section 4 gives brief about the empirical strategy used in the study and Section 5 represents the estimation of results. Section 6 concludes the study with its results. Policy implications and limitations of the study are presented in Section 7.

Literature Review

Women’s empowerment can lead to economic development and there exists a bi-directional relationship between the two (Roy, et al, 2018). Access to economic resources and participating in meaningful decisions, not only benefit women but also their households and communities. Women are crucial contributors, implementers and beneficiaries of sustainable development. Their empowerment is fundamental to the achievement of the 2030 Development Agenda[1].

Empowering a woman is giving her the instrument that enables her to decide what she would prefer. It can be defined in terms of their right to have access to opportunities and resources and to be a person who has right to think, to feel, to choose and to participate politically, economically both within and outside the home (UN, 1995)[2].

Economic empowerment is a pre requisite for the overall empowerment of women. Income gives her a higher household decision-making power and greater control over allocation of household resources (Afridi et al, 2016; West 2006).  World Bank’s latest data estimates that women represented 23 percent of India’s formal and informal workforce in 2021 (Banerji, 2023). Among them almost 94 percent of total women workers are engaged in the informal sector, of which about 20 percent work in the urban centers (Goel et al, 2011).  We in our study will try to find out if data indicates that the women working in the urban informal sector are economically empowered or not. Informal workers, including both self-employed and wage-workers, generally earn less than formal workers, have less secure jobs, less access to social protection, and are more vulnerable to common contingencies or shocks and the position of women is more precarious (Gunther et al, 2012). Women in informal employment are over-represented in the most vulnerable employment category of contributing family workers, home-based workers doing piece-rate work in the lower tiers of supply chains and domestic workers. This is because informal sector provides the flexibility in the working hours and the location advantages that women require to incorporate market work into their family work, as well as into the social norms that majorly regulate women’s economic participation (Kabeer et al, 2013). Given the importance of the informal sector for women participation, we in our study have tried to cover the women working in the urban informal sector.

Women’s economic empowerment is not directly observable. However, one can measure it through other indicators. Swain and Wallentin (2008) measured economic empowerment through economic and financial confidence, managerial power, networks, political and social awareness, behavioral changes within the household and respondent members and education. Bhattacharjee and Goswami (2022) used a composite variable from twelve indicators for measuring women’s economic empowerment. All these encompass personal and socio-economic dimensions where former included women’s participatory role in making household decisions and latter included women’s contribution to family income and participation in the household economy, access to socio-economic resources and ownership of assets.

Access to proper infrastructure plays a vital role in women empowerment. This helps her to carry out everyday chores more efficiently, free up time for educational opportunities, productive work, and participation in community life and decision making. Sedai et al (2020) finds strong positive causal effect of power outages on all empowerment indices at the national level. Kabeer (1999) compared the impact of electrification on poor and non-poor, rural and urban women on their economic freedom, reproductive freedom and freedom to travel alone. The links between provision of safe water and sanitation services and women’s empowerment have been stressed (Dickin et al, 2021). In fact, 'pucca' houses are also considered the "symbol of women empowerment". These houses come with basic facilities like water supply and electricity[3].

Given this background, we in our study have tried to investigate the relationship between living conditions at home of women working in the urban informal sector and her economic empowerment. Our contribution in this paper is the Economic empowerment index (EEI) and the living condition index (LCI) which we have constructed.  These indices have been constructed using the Principal Component analysis method.

We make use of the special module in the questionnaire on economic empowerment of a woman and try to identify eleven questions in the questionnaire to capture the economic empowerment of women. Two, we not only make use of the special module in the questionnaire on living condition of a woman within a household, but we identify nine questions in the questionnaire to capture the living conditions. Three, our study specifically focuses on working women in urban informal sector, when other studies have focused on either all women (irrespective of working or non-working) or focused on women in both formal and informal sectors. This has substantial policy implications, as it allows us to dig out specific problems related to inadequate living conditions of working women in urban informal sector.

This paper thus investigates that despite working, do women have access to better and good living conditions at home and does living conditions have any positive (or negative) role in enhancing (or reducing) the economic empowerment of women. Our paper focuses on the city Agra. The present study seeks to answer the following research questions-

RQ 1: Despite being working, does data support that women are economically empowered?

RQ 2: Do women have access to better living conditions at home?

RQ 3: Does better living conditions at home which any woman has access to leads to improving their economic empowerment?

RQ 4: Does the amount of time spent working by a woman has any effect on her economic empowerment?

 

Data and Descriptive Statistics

The data for this study comes from a primary survey that we conducted among working women in the urban informal sector in Agra. Using a structured questionnaire, we surveyed around 285 working women by visiting slums, colonies, factories, shops, different markets and other places. Out of these 219 responses were found competent for this study. The rest of the responses were rejected which were inaccurate, incomplete or insincerely responded to. These women either work as caregiver, tailor, in beauty parlours, household help, cleaner, washer; or is self-employed pertaining to traditional businesses of Agra like Handicraft (Marble/wooden), Petha/Sweet making, Shoe making, Tourism, manufacturing of silver anklets and bracelets, rakhi, festoon and poshak making etc. Data was collected from March, 2023 to July, 2023. Apart from personal information of the respondent, the questionnaire has sections on occupational details of women, number of hours put in work, living conditions of women and income earned by the women.

Construction of Economic Empowerment Index

The questions in the questionnaire allow us to measure the extent of economic empowerment of a woman. We have eleven questions in the questionnaire to capture economic empowerment. We have categorized all these variables into three broad categories, as given in Table 1: access to resources, power to make decisions and belonging to social network. Enhanced ownership of assets, raises household wellbeing through increased female bargaining power. This increase can translate into greater participation in household spending decisions and stronger, more realistic exit options in the case of an unhappy or abusive relationship (World Bank, 2014)[4]. Similarly, when women participate in self-help groups and other participatory development programs, increased agency accompanies economic outcomes (Kandpal, et al. 2013, World Bank 2013). Positive improvement occurs along five metrics - socio-economic upliftment, education and training, marketing and entrepreneurship qualities, technology adoption and participatory research and banking/ credit aspects (Meena and Singh, 2013; UNDP, 2019).

Table 1: Variables indicating Economic Empowerment

Adopted Indicators	Questions used to construct the Economic Empowerment Index of Working women
Access to resources	Do you have a steady flow of income?
	Do you have gold Jewellery/ Fixed Deposit in your name?
	Do you have land in your name?
Power to make decisions	Do you keep your income with you?
	Do you have a bank account in your name?
	Can you spend your income on yourself without asking anyone?
	Can you utilize your savings independently?
	Do you have the freedom to decide whether to send money to your siblings/buy gifts for them?
	Have you ever bought/sold any asset(s)?
	Have you ever taken a loan in your name?
Belonging to social network	Are you a member of Self-help groups (or any such group)?

Source: Authors’ Contribution

Having categorized the variables, we have used the Principal Component Analysis (PCA) to construct the Economic Empowerment Index. PCA is a statistical method that transforms a set of correlated variables into another set of uncorrelated variables called Principal Components (PC) that explain most of the variance of the data. Eigenvalues based on the standardized correlation matrix of the data shows the proportion of variance due to each principal component. For this paper, we have used varimax rotation to maximize the variation. The first PC measures the maximum variance in the data set, the second PC measures less variance than the first PC and the third PC measures less than the second PC and so on. The contribution of each variable to the newly formed PC is called the loading. Higher loading of a variable in a PC means that variable explains most of the variance in that PC.

In total there are eleven indicators, all of which are binary with ‘1’ for “Yes”, ‘0’ for “No”. PCA was used to construct the empowerment index from these eleven indicators. The Kaiser-Meyer-Olkin value is 0.56, along with all individual values greater than the minimum score of 0.5. Thus, it satisfies the criteria of sampling adequacy for PCA analysis. Bartlett's test of sphericity was significant The Bartlett’s test of sphericity was significant (=128.67), p < .001, indicating that correlations between items were sufficiently large for PCA. An initial analysis was run to get eigenvalues for each component in the data. Four components had eigenvalues over Kaiser’s criterion of 1 and in combination explained 52.1% of the variance. The Scree plot (Figure 1) also justified retaining four components.

Figure 1

 

 

The final economic empowerment index for 219 women were calculated using weighted aggregate of first four principal components:

                        (1)

where  is the economic empowerment index of the i^th woman

  is the j^th Principal Component

is the proportion of variance for j^th Principal Component

i=1, …, 219

j=1, …,4

This index satisfies the basic principle of having higher value for women with more answers in affirmative and having lower value for women with more answers in negative to the indicator questions.

Construction of Living Condition Index

We have from our questionnaire included nine variables to calculate the living condition index. All the nine indicators are binary variables, with ‘1’ for “Yes”, ‘0’ for “No”. We agree that these variables are not an exhaustive list indicating better living conditions but we feel that from the available information, they best capture information to calculate living condition index. These nine indicators have been broadly classified into three broad categories, given in Table 2 below: access to resources that can support women in maintaining good hygiene and health, support they receive from family members and whether they get adequate rest at home. Water, sanitation and hygiene services are often promoted as critical for women’s empowerment. A greater proportion of empowered women relative to disempowered women use a water source on premises or an improved sanitation facility (Dickin et al, 2021., Keysar et al, 2019). The other two domains are considered based on the premise that economic empowerment is also defined by one’s productive ability. The unequal distribution of caring responsibilities between women and men within the household translates into unequal opportunities in terms of time to participate equally in paid activities and thus acts as a brake on the economic empowerment of women (Ferrant, et al, 2014). Similarly, domestic violence affects the victim women in their productivity level and make their life worst (Roy, 2019). Many battered women believe that the abuse is their fault. An empowering belief is that they are not responsible for the violence and rage of their abusers (Busch and Valentine, 2000). When the husband reported drinking alcohol once a week or almost every day, it was associated with an increase in the odds of women facing all types of violence (Parekh et al, 2021).

                                   

 

 

Table 2: Variables indicating Living Condition

Access to resources for maintaining good hygiene and health	Do You have access to clean washroom at your home?
	Do you access to clean drinking water at your home?
	Do you have access to water for Bathing, cleaning, cooking and washing?
Having supportive family members	Do you get any help in household work?
	Do you have harassment free condition at home?
	Do you agree that none of your family members come home drunk in the evening?
Conducive home environment to get adequate rest	Do you get minimum 7 hours of sleep?
	Do you have to share your home with maximum 4 family members?
	Do you have coolers at your home?

 Source: Author’s Contribution

 

The Living Condition Index was constructed from these nine indicators using PCA. The Kaiser-Meyer-Olkin value is greater than the minimum score of 0.5 and Bartlett’s test of sphericity was significant (=30.994), p < .001. An initial analysis was run to get eigenvalues for each component in the data. Five components had eigenvalues over Kaiser’s criterion of 1. But the Scree plot, as shown in figure 2, justified retaining three components which explained 44.9 % of the variance.

                     Figure 2                                

 

The living condition index for 219 women were calculated using weighted aggregate of first three principal components

                                  (2)

Where  is the living condition index of i^th woman

             is the proportion variance of the j^th principal component

              is the j^th principal component for the i^th woman

             i= 1, …, 219

            j= 1, …,3

The obtained index values satisfy the basic property of having higher values for women with more positive answers than for women with more negative answers to the indicator questions.

Apart from personal information and living condition of the respondent, the questionnaire had sections on income earned by the women, whether working as wage employer or self-employed, her education levels, caste, religion and others. Table 3 gives the description of data.

 

 

Table 3: Descriptive Statistics

Variable	Observations	Living Condition Index				Economic Empowerment Index
		Mean	Std. Dev	Minimum	Maximum	Mean	Std. Dev	Minimum	Maximum
Occupation
Self Employed	39	0.12	0.27	-0.54	0 .39	0.19	0.32	-0.21	1.03
Wage Earners	180	0.00	0.26	-0.80	0.41	-0.04	0.24	-0.50	0.82
Age
upto 25 years	43	-0.01	0.23	-0.54	0.40	-0.01	0.29	-0.50	0.82
upto 45 years	127	0.02	0.27	-0.80	0.41	-0.01	0.25	-0.48	1.03
Above 45 years	49	-0.01	0.26	-0.54	0.40	0.04	0.27	-0.29	0.97
Religion
Hindu	157	-0.01	0.26	-0.80	0.40	-0.02	0.25	-0.50	0.82
Muslim	24	-0.11	0.22	-0.54	0.27	-0.04	0.22	-0.29	0.65
Others	38	0.11	0.26	-0.53	0.41	0.10	0.32	-0.44	1.03
Income Categories
Less than 10000	155	-0.04	0.27	-0.80	0.41	-0.05	0.22	-0.50	1.03
Upto 20000	43	0.15	0.20	-0.21	0.40	0.13	0.31	-0.37	0.97
More than 20000	21	0.18	0.23	-0.51	0.41	0.37	0.37	-0.14	0.65
Education
Illiterate	33	0.12	0.27	-0.54	0 .39	-0.03	0.27	-0.46	0.65
Upto Primary	72	-0.03	0.28	-0.80	0.40	-0.01	0.23	-0.37	0.97
Middle& Secondary	64	0.06	0.24	-0.67	0.41	0.06	0.33	-0.48	1.03
Above Secondary	49	0.04	0.23	-0.44	0.41	0.03	0.32	-0.50	1.03
Social Groups
SC, ST, Others	91	-0.04	0.27	-0.80	0.40	-0.03	0.22	-0.50	0.74
General	96	0.03	0.26	-0.80	0.41	0.01	0.28	-0.48	0.97
OBC	32	0.04	0.24	-0.40	0.40	0.05	0.32	-0.50	1.03

Source: Authors’ Contribution

 

From Table 3, we see that there is a rise in the mean value of both the living condition index and the economic empowerment index from the less than Rs 10000 income category to more than Rs 20000 income category. This shows that with increase in income the decision-making power, access to resources women has also rises. Also, the variability in the living condition index value falls as income increase from lowest to highest income category. This shows that the negotiation or the capability of getting better conditions at home differs across women more in the lowest income category. Other members of the family also have to contribute to get better living conditions at home. It depends upon how much money in this category is used to improve their living conditions since with such low levels of income, they have to satisfy their basic needs before getting better facilities at home. With rise in income the variability in the living condition index falls showing that a considerable proportion of almost all women’s income is spent on Quality Housing (Kayser et al, 2019).  Although there is a rise in the value of EEI as one moves from lower to higher income category, the individual decision-making power is deviating much more as is evident from the higher variability in EEI.

The mean value of both the Living Condition Index and the EEI is much higher for self-employed than those for wage earners. The self-employed women in our sample are women who work out of home and don’t share work or earnings with their husbands as mentioned earlier in the paper. The money earned could be used to get better facilities at home. The variability in the EEI for both the categories is clearly seen. It depends upon how much these self-employed women are doing work on their own, managing their funds and thus have more decision-making power than other self-employed women.

We find that the mean value of LCI goes up as we move from under 25 to between 25 to 45 age group, whereas it falls with further rise in age. The age group 25-45 is the age where women usually earn more and start a better life and tries to get better living conditions at home. With the rise in age, the next generation comes in who either take over or complement the women financially in getting access to better conditions at home leading to a fall in the mean value of Living Condition Index.

The mean value of the EEI also rises with age which is evident of more and stronger decision-making power of women with rise in age. The mean value of EEI and the mean value of the LCI is almost the same across different levels of education. This does not mean that education in our sample plays no role in determining economic empowerment. It implies that there are many other factors which play a more important role in determining their economic empowerment. 

Empirical estimation

At the first level, as mentioned in the previous section, economic empowerment index and living condition index is calculated using the principal component. At the second level, we use the index of economic empowerment calculated to estimate the degree of empowerment that a woman enjoys, using Ordinary Least Square (OLS) Estimation procedure, given by the following equation:

 

                           (3)

 

OLS regression is a common regression technique for estimating coefficients of linear regression equations which describe the relationship between economic empowerment index and the right and variables. Thus, the coefficient  measures the extent of change in the value of economic empowerment index when the living index changes.

 

Z_i is a vector of control variables, which includes her age, marital status, religion, caste categories, income earned and her education levels. These variables have been included in the regression model for some reasons. With rise in income comes more economic empowerment, but it could be that even if women are earning more, it could be the case that they may not be able to enjoy economic independence, just because they are employed in a particular type of occupation, where they probably have to share their income with their husbands. Similarly, we control the marital status of women, as we expect that married women may be less economically empowered as they might have to share their resources (income or savings) with her husband or with the in-laws. We control for religion and social categories of women because it could be the case that women belonging to different social groups may enjoy different degrees of economic empowerment. We control for age as we feel that it is an important variable in explaining economic empowerment. There is in general increase in economic empowerment seen as a woman gets older.

 

 X_i is the set of variables that we have included in the model one by one to see if they show the distress situation of women and how they affect their economic empowerment. In Model I we have included the living conditions enjoyed by a woman as one of the indicators of economic empowerment. We want to investigate if better access to living conditions at home has any impact on economic empowerment of women, after controlling for these variables. Better living conditions would lead to more efficiency of women, it would help in boosting their productive ability. A house with better facility of sanitation, adequate supply of clean water can help the woman to devote more time to income earning activities. Also, supportive family members and absence of domestic violence makes her stress free and happy. This in the long-run can encourage her to grow professionally, which in turn can positively boost her decision-making power.

In Model II, we added another variable indicating for how many hours a woman works per day.  Working for longer hours is associated with more income and thus being more economically empowered. But on the other hand, it implies time away from family and hence less economic empowerment due to less involvement in family decisions.  Women often make tradeoffs throughout any given day with respect to their time, balancing their expected priorities with the barriers or limitations they face in being able to spend any additional time on tasks or activities that further their own strategic goals. Thus, the more time poor she is, the less is her economic empowerment (Eissler, et al., 2021).  Finally, in Model III, we have also tried to study the impact of the interaction effect of the living conditions which women have access to and income earned more than twenty thousand rupees per month[5]. When better living condition makes a woman free from anxiety and distress, she tends to earn more, which further enhances her economic empowerment.

 

Estimation and Results

To estimate the extent of various determinants that affect economic empowerment of working women in the urban informal sector, we run three different model.  Table 4 gives the estimation results.             

 

Table 4: Estimation Results

 

Explanatory Variables	Model 1	Model 2	Model 3
Constant	0.1439 (0.107)	0.3725 *** (0.134)	0.3751*** (0.134)
Age (in years)	0.0023 (0.002)	0.0028 * (0.002)	0.0029 * (0.002)
Married	─ 0.0045 (0.036)	─ 0.0004 (0.035)	─ 0.0001 (0.035)
Hindu	-─ 0.0901 (0.056)	─ 0.0888 (0.055)	─ 0.0886 (0.055)
Muslim	─ 0.1081 (0.075)	─ 0.1169 (0.074)	─ 0.1167 (0.074)
General	0.0139 (0.034)	0.0200 (0.034)	0.0189 (0.034)
OBC	0.0459 (0.060)	0.0487 (0.061)	0.0453 (0.062)
Primary	0.0185 (0.053)	0.0209 (0.053)	0.0212 (0.053)
Secondary	0.0035 (0.060)	0.0073 (0.060)	0.0091 (0.061)
Above Secondary	0.0156 (0.065)	0.0200 (0.066)	0.0192 (0.066)
Staying with Family	─ 0.0435 (0.047)	─ 0.0422 (0.046)	─ 0.0448 (0.046)
Migration	─ 0.0114 (0.035)	─ 0.0093 (0.034)	─ 0.0095 (0.0344)
Income above 10K and till 20K	0.1591*** (0.050)	0.1558 *** (0.048)	0.1563 *** (0.048)
Income above 20K	0.3431*** (0.071)	0.3562 * (0.215)	0.3585 * (0.215)
Wage Worker	─ 0.2089 *** (0.050)	─ 0.1986 *** (0.051)	─ 0.1974*** (0.051)
Living Condition Index	0.1646 * (0.099)	0.1153 (0.099)	0.1142 (0.100)
Working Hrs per day		─ 0.0367 *** (0.014)	─ 0.0374*** (0.014)
Living Condition Index*Income above 20K			4.4694 * (2.576)
R-squared	0.261 ***	0.288 ***	0.289 ***
Adjusted R-squared	0.203	0.228	0.225

Source: Authors’ calculations based on survey data. 

Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. 

 

Model I show that better access to living conditions has a positive and a significant impact on economic empowerment of women. But in Model III, when we considered the interaction of the living conditions and income earned more than twenty thousand rupees per month as an explanatory variable, the living condition no longer plays a significant role on its own.  But it plays a significant and positive role in explaining economic empowerment of women through the interactive term.

This is as per our expectations. Better living condition increases women’s efficiency and productivity. Access to safe drinking water and sanitation reduces water-related diseases, more healthcare savings, provides adequate time for engaging in economic activities for income. These outcomes can enable the realization of an individual’s potential for choice (Dery et al 2020). Lack of in-home toilets can have a disproportionately large detrimental effect on women. Anecdotal and qualitative evidence suggests that open defecation threatens the safety of women as it makes them vulnerable to violent crimes in secluded areas often at dark hours of the day (Hossain, et al, 2022). In addition, it also often creates health problems with dehydration and unsanitary bathroom conditions (Jagori, 2016).

Economic empowerment also requires supportive family members and domestic violence free household. For working women, the more is their family support, the higher the level of happiness they perceive, which in turn increases their income earning ability and empowerment (Pan et al, 2022). Domestic violence can result in physical and psychological impacts that affects women’s work and employment outcomes, undermining their productivity, affecting their ability to participate fully in work, spurring absenteeism and presenteeism, and may ultimately affect their retention and permanence in employment (Duvvury et al, 2021., Parekh et al, 2021., Laura, 2017). Alcohol plays an integral role in domestic contexts of violent behavior. Although, alcohol has been shown to augment aggressive behavior in both men and women, the inclination to engage in violent behavior is twice as strong for men (Laura, 2017). The concepts of choice, control, and power, central to women’s empowerment, are often points of contention in relationships with gender-stereotype imbalances, such as those in which husbands often consume alcohol.

In Model II and III, in addition to living conditions, we take into account number of hours put in work by any woman.   Women working for longer hours in the urban informal sector tend to earn more and thus should be more empowered economically. We on the contrary have got different results and highly significant one. As any woman puts in more hours to work, they become less economically empowered. Women are significantly more likely to be time poor than men. Being time poor results from the combination of two conditions. First, the individual does not have enough time for rest and leisure once all working hours (whether spent in the labor market or doing household chores such as cooking, and fetching water and wood) are accounted for. Second, the individual cannot reduce his/her working time without either increasing the level of poverty of his/her household (if the household is already poor) or leading his/her household to fall into monetary poverty due to the loss in income or consumption associated with the reduction in working time (if the household is not originally poor) (Asian Development Bank, 2015).  Alleviating women’s time poverty empower women and enable them to better claim their rights, and to take an active role in decision-making (Abdourahman, 2010).

Long working hours is also related to long commuting time to work and hence restricts the movement of women (Miles, 2002). Time spent traveling to work is considered ‘necessary time’ integral to the working day (Kalenkoski et al., 2011). But time poverty is higher for women in urban areas as long daily commutes associated with traffic congestion are a contributing factor to reduce time for rest and leisure and may directly impact health and well-being (Carmichael, et al., 2023).  In fact, women are more likely to use cheaper means of transport, often less comfortable, slower and sometimes less safe, to get to work owing partly to inequality in access to good jobs (Uteng & Turner, 2019). Improving the public transit sector is critical for gender safety, reducing pollution, assisting working and poor women, and ensuring the right to movement for everyone (Jagori, 2016).

In all the models, economic empowerment of wage workers is significantly less than that of self-employed women. This is because the impact of self-employment is more among the self-employed women in the form of social impact and economic impact. Self-employment enhances financial independence and self-esteem of women (Palanivelu, et al, 2013). This is in particular the kind of self-employed women, termed as own-account workers, that we have considered in our data set. They are the sole self-employed women, having no partnership with male family members. This makes them free from any disguised ownership role adopted by male members.

Economic Empowerment of working women increase significantly with the increase in their income.  This is observed across all categories of income, in all three models. Higher income leads to increased economic empowerment (Swain, et al, 2008). Likewise, we find age also plays a positive significant role. As woman grow one year older, her economic empowerment increases. We find this in earlier studies as well. Younger women are less likely to participate in decision making than older women (Acharya, et al, 2010). However marital status, religion, caste, migration and staying with family turned out to have an insignificant impact on women empowerment. Education also seems to have no impact on the empowerment of sampled women workers. This does not mean that education has no role to play in determining women economic empowerment. All it means is that other factors also play an important role in determining their economic empowerment.

 Discussion and Concluding Remarks

In the contemporary world of globalization, economic empowerment is the foremost pillar to be independent. As per a 2018 International Labor Organization (ILO) report, about 82 percent of the total number of working women in India are concentrated in the informal sector (Dey, 2023). Self-employment among women was up 14 percentage points to nearly 65 percent between the quarter ended June 2018 and the quarter ended December 2022 (Basole, et al, 2023). Thus, it is important to find out whether women, wage-earner or self-employed, are getting empowered or impoverished in the bargaining.

Access to safe water and sanitation is seen as particularly critical for women and girls and for making progress towards SDG 5 to ‘Achieve gender equality and empower all women and girls.’ The impact of electrification and domestic violence free household also has significant positive effects on all empowerment indices (Kabeer, 1999; Roy, 2019). All these factors have been considered by us under a composite variable termed as living condition index.

 Our findings from the estimated models suggest that the value of economic empowerment index of women increases as the value of living condition index increases. However, this is due to the positive impact of better living condition on the economic productivity of women. Income earned by women significantly increase their economic empowerment. Our results also indicate that economic empowerment of self-employed women is more than that of wage employed women in the city of Agra. However, the more time women spent away from home for work, the less is their economic empowerment.

The results indicate that it is important to make households aware of the importance of having basic infrastructures like washroom, clean water, electricity. Also, it is important to make households freer from domestic abuse. All of these can help in reducing the physical and mental stress on women that can further improve their earning capability and hence increase economic empowerment.

Policy Implications and Limitations

Policy interventions are required to provide quality housing to all women. Access to quality housing improves women’s wellbeing. The security of living in a quality home has a tangible impact on their mental health by reducing their stress, anxiety, and depression, increasing their self-esteem and satisfaction. Prime Minister Awas Yojana Urban (PMAY-U) scheme, launched in 2015, aimed to provide pucca houses with basic amenities, is one step in this direction which will help uplift the welfare of women. This will help increase women’s productivity and participation in the labor market and their economic empowerment.

Swachh Bharat Abhiyan, or Clean India Mission is a country-wide campaign initiated by the Government of India in 2014 to eliminate open defecation and improve solid waste management and to create Open Defecation Free (ODF) villages. This will help in providing a cleaner and hygienic environment to all, leading to better living conditions for women.

There are other policies that have been initiated by the Government of India to address the challenges of inadequate access to and supply of improved sanitation. Women and girls face unique cultural and biological burdens in relation to sanitation.  The Ministry of Health and Family Welfare has introduced a scheme for promotion of menstrual hygiene among adolescent girls. This will lead to benefits received by the girls who can then make their mothers, and other elderly women in the family aware of the better hygiene by availing such benefits. This will result in less absenteeism from work and more participation in work by women leading to a rise in their income.

Another initiative of the government is The Lakhpati Didi Yojana, launched in 2023, that aims to create prosperous sisters across India by providing them to be a part of the Self-Help group (SHG). Being a member of the SHG is one of the variables determining economic empowerment of women in our paper, which makes it a right move by the GOI to move towards Viksit Bharat. It makes women more informed, increases their social interaction, financial literacy and skill development, thus empowering members for entrepreneurial ventures.

Further the Shakti Scheme in Tamil Nadu and Pink slip scheme in Delhi and similar such scheme in Punjab is another step to empower women financially by providing them free of cost bus service. This makes city’s female residents feel safer and to encourage them to get jobs further away from their homes. The other states should also devise some schemes to encourage female mobility out to work. The challenge for the government, although it does make a difference to the lives of women, is the lack of a dedicated budget and an overworked fleet could jeopardize the scheme.

Although numerous women welfare schemes have been initiated by the GOI, the system often continues to compromise the health, safety, and productivity of women, and fails to advance gender equity more broadly. We are moving in the right direction and what needs to be seen is that the implementation of the various welfare measures initiated by the GOI is quick, more efficiently done so that the benefits reach the masses.

A multi-city micro analysis of public transport in terms of their availability, accessibility and affordability for women can make us achieve economic empowerment of women in a more comprehensive manner. Such future work can be further enriched by encompassing more indicators in the construction of the index of economic empowerment and living condition index.

Acknowledgement

This Article has been revised as per the suggestions received from Reviewer A of the Economic and Political Weekly.

 

 

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Endnotes:

[1]UN Women, (2016), Women and Sustainable Development Goals.

 

[2]Guidelines (1995). United Nations Population Information Network (POPIN), Department of Economic 

and Social Affairs.

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[3] https://www.business-standard.com/article/current-affairs/pm-modi-says-project-to-build-3-cr-houses-over-will-empower-women-122040800161_1.html

 

[4] World Bank Group. (2014). Voice Agency and Empowering women and girls for shared prosperity.

 

[5] More granular distribution of income was interacted with the living index but only the most significant results are reported.