Women’s Home-Based Entrepreneurship and Family Financial Position in Pakistan

Abstract

Women’s entrepreneurship is critical for fostering economic growth and inclusive development globally. Women’s home-based businesses are crucial for women with restricted mobility and employment options to earn an income in developing countries. This study considers the impact of women’s home-based entrepreneurship on their family’s financial position. We collected data from 504 women entrepreneurs in Mardan City, Pakistan using a questionnaire/interview procedure. Chi-square and logistic regression were used to analyze the predictors of family financial position. The results showed that women entrepreneurs’ age, marital status, homeownership, rural versus urban location, household size, and business income significantly affect their family’s financial position. The findings revealed that women entrepreneurs have a substantial impact on the financial position and welfare of their families consistent with the multiplier effect ascribed to women in entrepreneurship. Implications and directions for future research are discussed.

1. Introduction

Women’s home-based entrepreneurship has been considered one of the most important drivers of economic growth in developed and developing economies [1,2]. Because of its scope, including work-life interaction and educating children [3], women’s entrepreneurship has become a crucial aspect of the socio-economic transformation process [4], particularly in developing countries like Pakistan [5]. Women’s entrepreneurship is viewed as a vehicle for converting available resources into valuable goods and services while creating employment opportunities that will ultimately lead to wealth creation [6,7] and social empowerment. In addition to their economic activities, women entrepreneurs also serve as role models that inspire other women to pursue entrepreneurship [8]. Women are presumed to be poorer than men [9] in the developing world because, in patriarchal societies, men are responsible for fulfilling the financial needs of their families. Yet, this notion may be changing because women’s contributions at the household level and to the economy overall have been steadily increasing. Therefore, as women’s home-based entrepreneurial businesses continue to grow, there is a need to assess the financial impact of women’s businesses on the family’s financial position.

This study contributes to the literature on women’s entrepreneurship by focusing on women’s home-based businesses (WHBB) in the informal economy in Pakistan. Although such businesses are termed “invisible” [10], and are therefore presumed to be economically inconsequential, they have a great impact on the economic and psychological wellbeing of women and their families. Yet, WHBBs are an understudied population of women in entrepreneurship. Such businesses are typically informal and unregistered. WHBBs represent an employment option for women in a patriarchal society that renders formal labor market participation infeasible because of socio-cultural norms, lack of education, balancing work with family responsibilities, and personal safety concerns. Further, the behavior of women entrepreneurs has a multiplier effect [11] related to women’s satisfaction and work–life integration that not only affects their wellbeing but that of their households, including beneficial effects for their children. In order to understand WHBBs more fully, we investigate associations with women’s age, marital status, homeownership, rural versus urban location, household size, business type, and business income in relation to overall family financial position. This work helps in better understanding women’s HBBs in a developing country context.

Our paper proceeds as follows. We first describe the cultural context, then present a definition of WHBBs, followed by a review of the relevant literature indicating what is known about women’s entrepreneurship and WHBBs enumerating our study’s research question. Next, we explain the selection of a sample of WHBBs and discuss our procedures for data collection. Then, we detail our analytic approach and present our findings. Finally, we discuss our findings, noting limitations and suggestions for future research.

1.1. The Pakistani Context

Pakistan is the second-most populous Muslim nation in the world. The rules of Islam do not restrict women’s involvement in any sort of economic activity. Women are allowed to run their businesses, as the Prophet Muhammad’s (PBUH) first wife, Hazrat Khadija (R.A), was a famous businesswoman in Arabia [12]. Women comprise 49 percent of Pakistan’s population [13] but women’s economic participation is very low as compared to that of men [14]. “Excluding women from the labor force means that a large share of Pakistan’s greatest asset, its population, is being wasted” [15]. Generally, the contribution of women in the formal labor force is restricted or confined to the home because of socio-cultural norms, lack of education, balancing domestic responsibilities, and personal safety concerns. Further, girls face inequality in their educational pursuits, a factor that has negative economic consequences. In Pakistan, the literacy rate for women is 51.2% as compared to the literacy rate for men which is 72.5%. Likewise, in Khyber Pakhtunkhwa province, the female literacy rate is 38% while the literacy rate for men is 72% [16].

The Government of Pakistan provides opportunities for self-employment by providing training in managerial and technical skills, particularly for women who want to start a business, pursuing entrepreneurship in keeping with their interests and aspirations, but also by contributing significantly toward socio-economic development [17]. There are several organizations working to promote women’s entrepreneurship. For example, the World Bank’s We-Fi (women entrepreneurs finance initiatives) annual report 2021 [18], indicates that this program builds women’s entrepreneurial capacity, intermediaries, and ecosystems, as well as attracting investors providing capital to enhance the readiness of women owned businesses. SMEDA (Small and Medium Enterprise Development Authority) is also working to give equal opportunity to educated housewives and young girls for setting up a business venture by providing pre-feasibility, business plan development, opportunities in exhibitions, marketing assistance etc.

Furthermore, the Kashf foundation also provides sustainable microfinance services to low-income families and micro-entrepreneurs to enhance financial capabilities, especially for women to become active agents of social and economic change. The findings of a study by Yunis et al., 2019 [19], conducted in Pakistan, showed that the majority of the respondents greatly appreciated the role of the NGO sector, by rating NGOs more highly than government programs supporting women’s entrepreneurship. Recently, the “Ehsaas” cash program was launched in April 2019 to reduce inequity, invest in people, and uplift underdeveloped areas. The program is making Pakistan a “welfare state” by promoting many areas such as financial inclusion, easy access to digital services, and enhancing women’s socio-economic empowerment with a special focus on poverty eradication [20]. Nevertheless, there is ample opportunity to offer additional assistance to women entrepreneurs in general and WHBBs in particular.

1.2. Women’s Home-Based Businesses

WHBBs, following the definition used by ([21], p. 344) are:

…entities run by individuals who are both self-employed and self-managed (as opposed to individuals who are employees that work from home or do contract work). The owner-operator, who may have employees, uses residential property as a base from which the operation is run. This includes two types of businesses: those where the work occurs in the home, and those where the work occurs away from the home with the home serving as the administrative base [10].

This study examined the first type of business where the work occurs in the home. WHBBs in Pakistan are informal, small, unincorporated, and difficult to identify. This “invisibility” of such businesses allows these entities to avoid paying taxes and being regulated. Having a business that operates from the home means that it is inextricably intertwined with the family unit. Boundaries that exist between formal work outside of the home are blurred in WHBBs. If family is the oxygen that fuels the fire of entrepreneurship [22], then WHBBs represent a particularly complex milieu (i.e., business environment) because of household structure, family constellation, gender roles, and normative structures that affect women’s status and resource availability [21]. We turn our attention to the studies on women’s entrepreneurship and WHBBs in our literature review.

2. Literature Review

Women’s entrepreneurial and economic activities are considered [23] an indispensable resource for fueling economic progress [14,24]. Women’s participation in business activities is higher in the developed world than in developing nations. Pakistan has one of the lowest levels of women’s entrepreneurship because of gender inequality, socio-cultural factors [14], and limited autonomy of women compared to other countries. Improving economic outcomes for women not only enhances women’s status, but also increases their entrepreneurial success and control over the resources that contribute to women’s empowerment [25,26]. External social factors can also play a role in shaping socialization processes that can reduce inequality of opportunities and classism. Both formal and informal institutional elements can affect women’s perceptions of entrepreneurial opportunities [27]. Entry barriers to national and international markets force women to rely on paid third parties who take a share of the proceeds, ultimately reducing women’s economic success. When there is a lack of legitimate employment opportunities outside of the home, WHBB entrepreneurship offers an opportunity that can enhance their family’s social status, economic wellbeing, and create wealth for the society [28] in keeping with religious and cultural norms.

The socio-economic characteristics of women’s entrepreneurship differ significantly from that of men [29], and from region to region [30,31]. Women’s entrepreneurship is a fast-growing field of research considering variables such as entrepreneurial intentions, age, level of education, experience, family background, role models [32,33,34,35,36,37], location, homeownership, business type, and income level, all of which affect their entrepreneurial success and family financial status. The findings of Muhammad et al. 2021 [38] showed that women entrepreneurs’ household size, business experience, and the products offered, such as dairy, cosmetics, and cloth, were found to significantly predict sales volume. The increase in sales volume enhances women’s entrepreneurial incomes by contributing to their family’s financial status.

Women’s family responsibilities have direct and indirect effects on their careers and earnings. Mature women might find it easier to manage life–work interactions, such as looking after their families, because older children require less attention [39]. Furthermore, WHBBs are supported by their families in various ways that can enhance their business success [40,41]. Family support for women entrepreneurs can take the form of direct financial backing, attaining external support [9,40], emotional support [41,42,43,44], attention, and an overall positive attitude [45,46]. Furthermore, WHBB activities can be managed effectively because of flexible working hours [47].

Financial resources must also be considered [48]. WHBB entrepreneurs have limited access to formal financial resources [38,49,50] stemming from a lack of credit references, limited knowledge, lack of awareness, and religious factors. Studies have shown that family support cannot be overlooked [40,41] because of its contribution to entrepreneurial prosperity that provides emotional and financial resources to women entrepreneurs.

Cultural factors also play an important role in women’s entrepreneurship. Pakistan has cultural values that differ from the rest of the world. Women have restricted mobility to freely visit public places and participate in mixed-gender programs thereby diminishing their chances of benefitting from business and skill-building opportunities [25]. Women need permission from their parents, brothers, and husbands before going out to pursue some activities to maintain their izzat, pardah (honor and the veil, respectively), in keeping with family traditions. However, WHBB entrepreneurship contributes to alleviating poverty and promotes their family’s economic well-being as well as the general wellbeing of society [26]. Recent work has termed this the “multiplier effect” of women’s entrepreneurship [11] that ultimately leads to better education and health of their children and families. Furthermore, the “multiplier effect” has also been reported by Rachwal and Wiedermann 2008 [51] as women’s economic engagements may lead to an increase in the income and employment that increases the indirect effect of the enterprises on the development of the surroundings [52,53]. The impact of the multiplier effect on family financial position is yet to be determined. Yet, there is a dearth of studies on WHBB entrepreneurship undertaken in the unique culture of Pakistan. WHBBs can facilitate work-life equilibrium [14,54] and work–family synergy [55] while generating income for women and their families. To the best of our knowledge this is the first attempt to examine the relationship between WHBB entrepreneurs socio-economic and entrepreneurial income impact on their family’s financial position.

Research Questions

This research study poses two research questions:

(1)

What are the socio-demographic characteristics of WHBB entrepreneurs in Pakistan?

(2)

What is the relationship between socio-economic characteristics, entrepreneurial income and family financial position of WHBB entrepreneurs in Pakistan?

3. Method

3.1. Participants and Sampling Procedures

This empirical study focused on WHBB entrepreneurship in Mardan City, which is the central region with the second-largest population district in the province of Khyber Pakhtunkhwa, Pakistan [9,56]. Mardan has a population of 2.3 million, with a gender breakdown of 51% men and 49% women. About 63% of the population live in the countryside, i.e., a rural setting [13]. Participants were WHBB entrepreneurs (N = 504) engaged in manufacturing, trade, and services businesses and nearly all were working in the informal segment. All respondents in the study were at least 18 years old. The data were collected between 1 June 2019 and 31 August 2019 by a woman research associate with a master’s degree, and nine data assistants. The associate and the assistants were trained and closely supervised in the survey/interview procedure.

3.2. Sampling Strategy

A multi-stage stratified sampling procedure was used to select the sample [56]. Firstly, Khyber Pakhtunkhwa was purposively selected. Secondly, the district of Mardan was chosen because it is the second most populous district in the province [9]. Some information was available from the district government along with the researcher’s survey list of WHBB entrepreneurs. We identified 2000 respondents engaged in different WHBB activities in the rural and urban zones through a random sampling procedure. Using Yamane, T. [57] we estimated a representative sample of 391 WHBB entrepreneurs was required for a 95% confidence level and with a 5% margin of error (Equation (1)).

$$n=\frac{N}{1+N{\left(e\right)}^2}$$

(1)

n = Sample size. N = Number of women in informality, e = Level of precision, fixed as 0.05%.

The estimated sample size from the total population of women entrepreneurs was 391 but 504 respondents were actually included in the sample.

3.3. Data Collection and Survey Instruments

Data were collected using a questionnaire and/or formal interview comprised of open and closed-ended questions. Women were given a choice of completing the questionnaire or being interviewed by the research team. Interviews were used for women with no formal schooling who were unable to read the survey questions [9]. The questionnaire was also translated into the Pashto dialect which is the local language. The survey respondents who chose to fill out the questionnaire on their own were given a choice of completing an English or Pashto version. The questionnaire contained three parts, including socio-economic characteristics, demographics, and challenges faced by the respondents.

3.4. Data Analysis

3.4.1. Descriptive Analysis

Data were coded and analysed using the IBM SPSS version 26 software. Descriptive statistics for the sample are reported in

Table 1. Descriptive Results for Study Variables.

Variable	n	(%)	Variable	n	(%)
Age (Years)			Marital Status
18–30	138	27.4	Single	88	17.5
31–36	151	30.0	Married	416	82.5
37–42	106	21.0	Ownership of home
43–70	109	21.6	Own	346	68.7
Education Level			No Ownership	158	31.3
Illiterates	211	41.9	Location
Primary	88	17.5	Urban	206	40.9
Middle	63	12.5	Rural	298	59.1
High	64	12.7	Adult Family Members
Higher Secondary	42	8.3	Up to 2	160	31.7
University Degree	36	7.1	3-5	214	42.5
Household size			More than 5	130	25.8
2–5	151	30.0	Other Businesses
6–7	159	31.5	No other business	434	86.1
8–9	117	23.2	One or more businesses	70	13.9
10–15	77	15.3	Form of Business
Products/Services			Sole Proprietorship	442	87.7
Dairy products	46	9.1	Partnership	62	12.3
Grocery products	106	21.0	Business Type
Stitching products	83	16.5	Manufacturing	92	18.3
Hand embroidery	59	11.7	Trade	242	48.0
Beautician	28	5.6	Service	170	33.7
Cosmetics	42	8.3	Key Decision Makers
Meat	27	5.4	Herself	267	53.0
Cloth	113	22.4	Family	210	41.7
Monthly income			Friends	27	5.4
<PKR 8000	190	37.7	Family Financial Position
8001–15,000	144	28.6	Lower than average	159	31.5
15,001–25,000	87	17.3	Average	201	39.9
>25,000	83	16.5	Better than average	144	28.6

Note. Authors’ calculations.

.

3.4.2. Bivariate Analysis

Chi-square was used to test the relationship and strength of association among three respondent’s groups based on family financial position: below average, average, and above average. A series of cross-tabulations ($\mathbf{\chi }²$ statistic) were first estimated between family financial position and independent variables, as shown in

Table 2. Bivariate association of family financial position and independent variables.

Family Financial Position		Below Average		Average		Above Average
Variables	${\mathbf{\chi }}^2$	n = 159 (%)		n = 201 (%)		n = 144 (%)
Age (years)	23.63 **
18–30		37	(26.8)	63	(45.7)	38	(27.5)
31–36		64	(42.4)	59	(39.1)	28	(18.5)
37–42		33	(31.1)	41	(38.7)	32	(30.2)
43–70		25	(22.9)	38	(39.9)	46	(42.2)
Marital Status	56.32 **
Single		6	(6.8)	30	(34.1)	52	(59.1)
Married		153	(36.8)	171	(41.1)	92	(22.1)
Education level	18.03
Illiterate		59	(28.0)	100	(47.4)	52	(24.6)
Primary		29	(33.0)	25	(28.4)	34	(38.6)
Middle		28	(44.4)	19	(30.2)	16	(25.4)
High		21	(32.8)	26	(40.6)	17	(25.4)
Higher secondary		11	(26.2)	19	(45.2)	12	(28.6)
University degree		11	(30.6)	12	(33.3)	13	(36.1)
Ownership of Home	117.05 **
Ownership		59	(17.1)	154	(44.5)	133	(38.4)
No ownership		100	(63.7)	47	(29.7)	11	(07.0)
Location	51.03 **
Urban		30	(14.6)	93	(45.1)	83	(40.3)
Rural		129	(43.3)	108	(36.2)	61	(20.5)
Adult Family Members	8.63
Up to 2		60	(37.5)	53	(33.1)	47	(29.4)
3–5		57	(26.6)	100	(46.7)	57	(26.6)
More than 5		42	(32.3)	48	(36.9)	40	(30.8)
Household Size	18.50 **
2–5		55	(36.4)	61	(40.4)	35	(23.2)
6–7		33	(20.8)	67	(42.1)	59	(37.1)
8–9		43	(36.8)	49	(41.9)	25	(21.4)
10–15		28	(36.4)	24	(31.2)	25	(32.5)
Other Business	1.33
No other business		141	(32.5)	170	(39.2)	123	(28.3)
One or More		18	(25.7)	31	(44.3)	21	(30.0)
Form of Business	2.55
Sole Proprietorship		137	(31.0)	182	(41.2)	123	(27.8)
Partnership		22	(35.5)	19	(30.6)	21	(33.9)
Business Type	3.04
Manufacturing		28	(30.4)	38	(41.3)	26	(28.3)
Trade		69	(28.5)	100	(41.3)	73	(30.2)
Services		62	(36.5)	63	(37.1)	45	(26.5)
Women’s Monthly Business Income-(App)	40.30 **
<PKR 8000		44	(23.2)	80	(42.1)	66	(34.7)
8001–15,000		42	(29.2)	59	(41.0)	43	(29.9)
15,001–25,000		25	(28.7)	33	(37.9)	29	(33.3)
>25,000		48	(57.8)	29	(34.9)	6	(07.2)
Products/Services	19.59
Dairy		13	(28.3)	17	(37.0)	16	(34.8)
Grocery		37	(34.9)	40	(37.7)	29	(27.4)
Stitching		35	(42.2)	29	(34.9)	19	(22.9)
Hand Embroidery		22	(37.3)	22	(37.3)	15	(25.4)
Beautician		08	(28.6)	08	(28.6)	12	(42.9)
Cosmetics		13	(31.0)	19	(45.2)	10	(23.8)
Meat		05	(18.5)	10	(37.0)	12	(44.4)
Cloth		26	(23.0)	56	(49.6)	31	(27.4)
Key Decision Makers	9.03
Self		76	(28.5)	114	(42.7)	77	(28.8)
Family		77	(36.7)	79	(37.6)	54	(25.7)
Friends		06	(22.2)	08	(29.6)	13	(48.1)

Field survey, 2019. ${\mathsf{\chi }}^2$ = Chi-square. p ≤ 0.05 *; p ≤ 0.01 **.

. All variables in this analysis were categorical.

3.4.3. Logistic Regression

We investigated the socio-economic elements that affect the respondent’s family financial position. Family financial position is a rank-order dependent variable with categories, ‘Below average’, ‘Average’ and ‘Above-average’. The model is useful because of the simplicity of its interpretation. For an outcome of three categories, POM estimates two logit models together for each category with the following marginal probabilities (Equation (2)).

$$P_1=Prob \left(y=1\right), P_2=Prob\left(y\le 2\right) - Prob \left(y=1\right), P_3=1-Prob\left(y\le 2\right)$$

(2)

The dependent variable, family financial position, was subjective; respondents were asked about their family financial position using categories/levels of income of their families (i.e., below average, average, or above average). Logistic regression was for this analysis [58]. We can express the logit function of the ordinal regression model (Equation (3)). as:

$$\mathrm{In}\left(\theta j\right) =aj+{\beta }_1{x}_{1i}+{\beta }_2{x}_{2i}+\dots {\beta }_{k }{x}_{ki}$$

(3)

In(θj) = the logit function’s variable “θj”, where j is from one to (the number of categories minus 1), αj = threshold of the logit function, β₁ = coefficients of the independent variables from 1 to n, x₁ = represents independent variables.

4. Results

4.1. Descriptive Statistics

Results showed that 30% of the entrepreneurs were aged between 31–36 years and 82.5% of the participants were married (Table 1). Nearly 69% of these women entrepreneurs owned their homes and 59.1% resided in rural areas. Considering education, many of the respondents had no formal education (n = 211, 41.9% percent) while the remainder had some level of formal education: primary school (17.5%), middle school (12.5%), high school (12.7%), higher secondary school certificates (8.3%), and university degree holders (7.1%). Entrepreneurs’ business types included manufacturing (18.3%), trade (48.0%), and services (33.7%). Women earning less than PKR 8000 (As per State Bank of Pakistan, 1 PKR = 0.0070864439869 US$, 2 May 2019. URL: http://www.sbp.org.pk/ecodata/Rates/WAR/WAR-History.asp, accessed on 31 May 20219) comprise 37.7% of respondents, well below the minimum wage of PKR 15,000 announced by the government of Khyber Pakhtunkhwa for the 2018–19 session. More than half of these respondents made their own business decisions, while 41.7% involved their family member’s business decision advice. Finally, 39.9% of the respondents reported an average family financial position.

4.2. Bivariate Associations

WHBB entrepreneurs were classified into three groups based on their family financial position. Table 2 shows the bivariate associations between family financial position and the following variables: age, marital status, home ownership, rural versus urban location, household size, and monthly income were significantly associated with the family’s financial position. Business income was negatively related to family financial position. Women from families reporting below average financial positions had the highest business income while those from above average families earned the least. Women home-based entrepreneurs between the ages of 43–70 years were in the above-average category of family financial position. Most of the married women reported family financial position as average while single women tended to be in the above-average category. The entrepreneurs who owned their home and lived in an urban area belonged to the average family while those who did not own their home and lived in rural areas were mostly below-average in family income. Incomes up to PKR 25,000 was considered to represent an average family financial background. Households with fewer than nine people were mostly average families while those with more than nine people were largely in the below-average category of family financial position.

4.3. Ordinal Logistic Regression Analyses

Logistic regression was used for multivariate analyses. The threshold parameter estimates for family financial position = 1, is the cut-off value 1.101 that falls between ‘below average’ and ‘average’ while the threshold estimates for family financial position = 2, represented the cut-off value 3.617 between ‘average’ and ‘above average’. The estimates obtained in the table were ordered using log-odds coefficients. Also, to facilitate interpretation of the parameter estimates, odds-ratio estimates were calculated by taking exponent $f\left(x\right) = \left(e^x\right)$ following Gujarati, D. [58].

The chi-square statistics suggested that the model fit the data well. The Nagelkerke Pseudo $R^2$ $(R^2=$ 0.448) indicated good predictive strength for the model. As shown in

Table 3. Logistic regression results predicting family financial position.

Variables	Estimate	Odds Ratio	Std. Error	Wald
Threshold
Family Financial Position = 1	1.101	-	0.393	7.863 **
Family Financial Position = 2	3.617	-	0.425	72.543 **
Age
18–30	−0.555	0.57	0.265	4.403 *
31–36	−1.065	0.34	0.267	15.894 **
37–42	−0.321	0.73	0.280	1.313
43–70	Rc	-	-	-
Marital Status
Single	1.500	4.48	0.260	33.417 **
Married	Rc	-	-	-
Home Ownership
Yes	1.946	7.00	0.223	76.093 **
No	Rc	-	-	-
Location
Urban	1.318	3.74	0.195	45.713 **
Rural	Rc	-	-	-
Household Size
2–5	−0.322	0.72	0.292	1.221
6–7	0.003	1.00	0.292	0.000
8–9	−0.681	0.51	0.308	4.905 *
10–15	Rc	-	-	-
Business income-PKR
<8000	1.244	3.47	0.291	18.232 **
8000-15,000	0.837	2.31	0.305	7.544 **
15,001-2,5000	0.986	2.68	0.335	8.665 **
>25,000	Rc	-	-	-
Model ${\mathsf{\chi }}^2$ (12, N = 504) = 255.48 **
Pseudo R2 (Nagelkerke) = 0.488

Notes: Rc = Reference category. * p < 0.05, ** p < 0.01.

, age, marital status, home ownership, rural versus urban location, and business income were the significant predictors of family financial position. In contrast, the household size of fewer than seven members was not significant. The probability of higher family financial position decreased as age increased. Single women that owned their home and lived in an urban location were more likely to have a higher family financial position than married women that did not own a home and resided in a rural area. In addition, WHBBs who had a monthly business income of PKR 25,000 or lower were more likely to have a better family financial position than those women with monthly incomes above PKR 25,000.

5. Discussion

The findings revealed that several factors are significantly related to WHBB entrepreneurs’ contributions to their family’s financial position. Specifically, we find that women’s age, marital status, homeownership, rural versus urban location, household size, and business income played significant roles. The findings suggest complex relationships between and among the study variables in relation to family financial position. For example, education, generally associated with entrepreneurial success, did not affect family financial position or women’s business income. Women with no formal education were equally likely to be in the higher family income as women with much higher education levels. This suggests the joint effects of education and experience in entrepreneurial success as argued by Kurczewska, A., W. Doryń and D. Wawrzyniak [59]. Regarding business income, many of the women earning higher incomes came from families with below average incomes. This might indicate a compensatory model whereby women’s business income is sufficient to maintain the family’s financial position, but does not surpass that level. Since WHBBs are enmeshed and intertwined with the household and family structure, e.g., [60], examining women and their businesses helps in understanding their impact on the family’s financial wellbeing. It is not enough to simply focus on women’s business income, although this is quite important, but rather to understand the impact of WHBBs more fully and completely.

Women’s entrepreneurship can assist in alleviating poverty [61], enhancing economic wellbeing, and increasing women’s empowerment, the top priority of the U.N.’s Sustainable Development Goals [62]. The International Development Organization also allocates some resources in the form of programs/projects to nations for the enhancement of women’s status in different spheres of life [63,64,65]. These objectives can be achieved by supporting women’s entrepreneurship in the social, religious, and traditional context [66]. These entrepreneurial women can contribute to the household in partnership with their husbands, fathers, and brothers as well as by promoting socio-economic empowerment of women. A variety of women’s support programs have been started by the Pakistani Government, but many of these programs do not reach the WHBBs in the present sample.

The mean age of the respondents is 36 years, consistent with the average age of women engaged in the informal sector in Trinidad and Tobago where the average age was 37 years [67]. Women in the present study were somewhat younger than women entrepreneurs in Mauritius (41 years) [68]. The majority of respondents were married, which shows higher entry towards business [69]. Most of the respondents had no formal education, which is quite different from results in Albania where two-thirds of the women entrepreneurs had obtained university degrees [70]. This discrepancy in educational attainment is a challenge for Pakistan’s economic development. Rural residents often inhabit locations where schools are distant from their homes. Thus, traveling to school is too expensive for many families compounded by the fear of harassment if transportation is used.

The mean household size is seven members. There is a clear preference for large households, a potential strength for managing both the business and family life since more contributors and caretakers likely means more flexibility [26,38]. Yet, there are some factors in joint families that affect women’s decisions that are influenced by male family members. Because of the dominance of cultural norms and values in society, women are largely restricted to their homes. However, running a business can increase women’s status in society and reduce dependence on others. Our results showed that WHBBs can an important role in the family [24] and society, if supported financially, given proper training, and access to markets [71]. Although their businesses differ from one another in terms of investment, income earned, training, and education, each WHBB contributes to the family’s financial wellbeing and managing the challenges of work-life interactions in the extended family system. Furthermore, these women entrepreneurs can partner with family members for income-generating activities in the future [72].

Women under the age of 36 reported a significantly lower family financial position compared to women 43 years of age and older. This makes sense since the older age cohort has had more time to grow their businesses and reap higher incomes. Single women who owned their homes and lived in urban areas were more likely to be in the higher family income category but report lower business incomes. Such lower incomes likely reflect the nascent stage of their businesses. These single women entrepreneurs [73] reported fewer responsibilities compared to married women. Single women can help in raising the living standards of the family and/or become financially independent. On the other hand, married women have more responsibilities beyond their businesses, including caretaking, homemaking, and using resources for their children’s education and health. Younger women entrepreneurs want to engage in new business ventures, such as cloth and cosmetics, which generate higher profits than traditional businesses. The household size of 8–9 members had an adverse effect on family financial position with many in the lower family income category, which might reflect the dependency of the children and parents. The income earned from entrepreneurial activities is low but still represents a viable choice for women restricted to the home [74]. Yet, some WHBB entrepreneurs have achieved success, with incomes up to PKR 25,000, placing them in a higher family financial position.

The success of WHBBs does not necessarily lead to family prosperity [75], a result that was not entirely unexpected. Possible explanations might include household size, the presence of dependent children, type of business, and the entrepreneurial motives of women pursuing such business opportunities [76]. It is also not clear that women’s business income is used entirely to support their families. Although women’s economic performance does lag behind their male counterparts as a consequence of prevailing cultural and structural constraints [66,77], the economic impact of WHBBs is significantly related to family financial position. The results reveal women’s contributions to their families that can be accomplished by working in their homes, as required in a patriarchal society like Pakistan, where women do not enjoy unrestricted mobility. We conclude that WHBB entrepreneurship will enhance the family’s standard of living over time thereby increasing women’s economic and social empowerment.

6. Conclusions

The impact of women’s entrepreneurship has been difficult to assess because its effects are multifaceted, particularly when considering WHBBs in the informal economy in developing countries. This study finds that women’s business income, regardless of their earnings level, contributes to the economic well-being of their households. Yet, we know that the impact of WHBBs go well beyond their economic impact on family finances. Women’s entrepreneurship has many consequences because of the multiplier effect [11,51,52,53] derived therefrom. WHBBs affect women’s self-esteem and well-being, helps in managing work-family interactions, provides flexibility, and enhances the welfare of children. Because of the far-reaching impact of women’s entrepreneurship, WHBBs need greater financial support, better access to markets, and more training opportunities that can multiply the substantial benefits derived from such businesses.

6.1. Policy Implications

This study has theoretical and policy implications for recognizing and enhancing WHBB entrepreneurship thereby increasing women’s social and financial empowerment. The findings provide a better understanding of WHBB entrepreneurship effectiveness and its role in their family financial status in the face of economic, cultural, and institutional barriers. These economic engagements can motivate other women in the society to start and engage themselves in such businesses for financial security. The theoretical contribution derived from the study of women entrepreneurs in the developing world is the “multiplier effect” demonstrating women’s pervasive contributions to their families, households, employment and overall economic growth through wellbeing. In the patriarchal context, which influences the ideology of these women entrepreneurs, a comprehensive gendered approach to entrepreneurial support will result in an engaging entrepreneurial development policy and practice.

6.2. Research Limitations and Future Research

While this study contributes toward understanding the impact of WHBBs on their family’s financial position, there are several possible limitations. The sample in this study was obtained from the women informal businesswomen in Pakistan. All of the variables were self-reports using a cross-sectional design. This precludes making any causal statements about the findings. Most of the businesses were operating in the informal economy and were not registered with any authorities [78]. As such, the vast majority of these businesses were not paying taxes on their income. Finally, this study was carried out in Mardan City so the results will need to be confirmed in other parts of Pakistan.

There are many opportunities for additional research. Following women’s businesses over time would be useful for assessing the impact of study variables longitudinally. Future research could gather samples from different countries for comparative analysis. Is women’s empowerment increasing over time? Are business plans developed to support entrepreneurial growth? Can the multiplier effects of women’s entrepreneurship be estimated or valued? We focused on women business owners, but future research might also include customers and family members to provide stakeholder perceptions of the business. Future studies are needed to increase our understanding of WHBB entrepreneur’s motivations and the challenges facing them.