Between Paychecks: Gaps in Liquidity Management among Low-Income Women

Despite steady incomes, low- and moderate-wage earners often face financial setbacks due to short-term liquidity issues. Their tight budgets typically cover only essentials, leaving little room for unexpected expenses like medical emergencies or home repairs, as well as predictable but irregular costs like school fees. With minimal savings and limited access to affordable credit, these households frequently struggle to smooth their spending when faced with sudden financial shocks. They bridge these gaps by relying on costly informal loans, social networks, or liquidating assets. In more severe cases, families may cut back on essentials like food, healthcare, or utility payments to make ends meet. The stress from these financial constraints can deepen debt burdens and strain both mental and physical well-being.

Gender disparities further complicate the picture. In India, women are more likely than men to worry about routine expenses, such as their children’s school fees (Demirgüç-Kunt et al., 2022). They also face greater challenges in accessing emergency funds, often depending on unreliable family support. Savings-locked-     in self-help groups or informal chit funds[1]—popular among women—are often inaccessible in times of need. Understanding the magnitude of these liquidity issues and the coping strategies used by workers is crucial. High-frequency surveys conducted at different times of the year provide valuable insights into how workers manage their finances, the seasonality in liquidity issues, and the impact of liquidity shortages on borrowing and spending.

In a recent study, we examined the impact of earned wage access for women workers in a garment factory in rural Karnataka. In the first 10 months of the project  (October 2023 to July 2024), we surveyed 834 workers[2] at the end of their pay cycle. To reduce survey fatigue, we used a rotating panel design where each worker was interviewed a maximum of three times. When asked if they found it difficult to make ends meet, 22.8% of the women reported struggling, though the figure fluctuated between 16% in May 2024 and 36% in October 2023. One worker shared her experience:

“My spouse hasn’t worked for two months, and I’ve had to manage household expenses with just my salary. I cut down on vegetables and missed my regular doctor’s checkup. I even canceled plans to visit my family because I didn’t have the money.”
Another worker said, “I canceled a family trip and skipped buying new glasses. I’ve lost sleep for the past few days, worrying about money.”

Figure 1

Going by workers’ accounts, workers reduce their expenditures or defer payments to cope with liquidity shortages. On average, 27.2% of respondents reported reducing or foregoing some expenses altogether during the survey month. The average amount of foregone or reduced expenditure is INR 2,298 (median INR 1,720)[3]. More than half of these cuts were on food—for instance, workers bought smaller quantities of meat and vegetables or skipped them entirely. Other areas affected included children’s school expenses (14.6%), mobile phone recharges (15.3%), family events and travel (10.68%), loan payments (8.2%), and medical costs (7.5%).  

Some workers also borrow small interest-free loans to tide over their liquidity crunch.  On an average 17% of the women workers report borrowing for their usual monthly expenses or unplanned emergencies. They mostly borrow from family and friends (86%) and coworkers (9.5%) between paychecks and repay these loans once their next paycheck arrives.  Around 12% of the workers had to borrow as well as reduce their expenditure to make ends meet in any given month. 

In summary, it is evident from our monthly surveys on financial stress with low-income women workers that nearly one in four workers are vulnerable to short-term liquidity issues. Understanding their coping strategies and offering more accessible financial products in the formal sector could alleviate their financial stress and improve their overall financial resilience. Enhanced financial inclusion and improved financial management skills, especially for women, could ensure that fewer households are forced to choose between essential needs and unexpected financial shocks.

[1] Chit funds, popularly known as ROSCAs, can be endogenous (run and operated by women themselves) or exogenous (run by an external agent or agency).
[2] 834 ever married women workers represent our total study sample for the project.
[3] These are equivalent to USD 27.1 (mean) and USD 22.7 (median). We apply a conversion rate of USD 1 is equal to INR 84.7.

Beneath the Surface: Hidden WEE Indicators in Women’s Savings Journey

All financial responsibilities will rest on her shoulders, and she will not be able to save any money,” responded Grace, when asked “What will happen if a woman has control over family decisions?” This sentiment was a recurring theme in our WEE-DiFine-funded study, “Adapting and Validating WEE Indicators in an Experimental Study of Savings” conducted in Uganda.

The goal of our study was to identify specific measures of economic empowerment related to women’s savings behavior using two complementary modes of validation. In the first phase, content validation, we applied qualitative methods to derive a comprehensive list of WEE indicators relevant to the everyday savings practices of Ugandan women. In the second phase, construct validation, we substantiated these indicators through their statistical correspondence with women’s observed savings behaviors, including their ability to set meaningful goals, to mobilize savings toward those goals, and to use the saved money as intended. We found several factors related to WEE measurement that were extremely local and not widely discussed in existing tools.  They were, however, very prominent in our survey responses and repeatedly selected by feature selection algorithms. Our takeaway is that the local context is absolutely vital for rigorously measuring women’s economic empowerment.   

Content Validation Insights: Bringing Hidden WEE Indicators to the Forefront

The content validation phase identified over a hundred WEE indicators. Here we focus on those that appear most frequently in our survey data,and that are rarely addressed in existing WEE measurement frameworks. 

Balancing Power and Responsibility

Decision-making power is normally viewed as an indicator of empowerment, but it brings financial consequences that can undermine women’s ability to save. This is especially true in Uganda, where the communal nature of households continually introduces new responsibilities and roles for women. Many women, like Grace, discussed the burdens that come with decision-making power, recognizing that there is a point beyond which the associated responsibilities become too heavy. Decision-making power cannot be assessed as a WEE measure without an understanding of what it entails and who bears the financial costs.

Fear as a WEE Factor

Fear significantly impacts women’s sense of agency in deciding how much to save for the future.  These fears include divorce, illness, and, most prominently, a fear of aging. Many women expressed worries regarding whether relatives or children would still be available to care for them as they grew older. This uncertainty prompted them to adopt savings strategies aimed at securing their financial stability in later life, especially considering their lack of retirement funds.

Mental Accounting and the Role of Trusted Knowledge

Women can find it challenging to organize and manage their financial resources—a behavioral aspect strongly tied to mental accounting. Navigating an overwhelming and often unreliable influx of information complicates their decision-making, hindering their ability to stay focused on their financial goals. Training on savings practices, local business issues, budgeting, and related topics are highly valued in helping them achieve realistic financial objectives. Additionally, women emphasized the need for clear and straightforward information from financial providers to facilitate comparisons of products and services, enabling them to make better financial choices. 

Construct Validation: Identifying the Most Relevant WEE Indicators for Savings

Using our rich data set of over a hundred WEE variables and account-level data, we applied ML feature selection algorithms to identify the WEE indicators that resonate most with our participants throughout their savings journeys. 

The results (Table 1) clearly confirm that Grace’s observation about the burden of financial responsibilities and its relevance to savings behavior was not just a personal anecdote, but a vital issue for women in Uganda. Most new indicators discussed during the content validation phase were consistently selected across all ML feature selection algorithms and ranked among the top 5 of the 25 selected WEE constructs.

Financial responsibilities, ranked first, highlight the importance of incorporating these roles into WEE measurement within the context of financial inclusion. Attendance at training (ranked third) and ability to compare financial products (ranked fifth) emphasize the need for a comprehensive approach to assessing financial knowledge within WEE tools. These indicators also underscore the need for clear, accessible information and practical financial knowledge to help women navigate mental accounting challenges. The alignment between the fears expressed during the content validation phase and the high ranking of financial strategies for old age (ranked fourth) further reinforces the importance of including this issue in WEE measurement. As women plan for the future, their outlook—closely tied to their savings behavior (ranked second)—is shaped by concerns about financial security in later years.

Importance of Contextual Lens

Our dual validation method revealed themes underexplored in existing frameworks, emphasizing that WEE indicators must align with specific outcomes and local realities. This approach not only reflects the true experiences of women like Grace, but also honors the dignity of Ugandan women navigating their financial challenges with determination. Contextually grounded WEE measurement tools enhance our ability to understand and support their aspirations.

[1] Such as Measuring Women’s Economic Empowerment: A Compendium of Selected Tools or Measuring Women’s Economic Empowerment in Financial Inclusion.
[2] One key insight we uncovered during our qualitative interviews was the significant role of the extended family in shaping women’s agency. In Uganda’s dynamic household structure, focusing solely on the roles of husbands or immediate family risks overlooking the critical influence of the extended family and the diverse circumstances they bring to women’s lives.
[3] For example, a recently developed tool by industry experts includes decision-making power as a key WEE measure, but does not address the financial burden that accompanies such responsibilities.
[4] We employ LASSO Stability Selection, VSURF for Interpretation, VSURF for Prediction, and Boruta. By comparing the features selected by more than one ML approach we identified the features with the most stability and consistency across models.
[5] Table 1 displays the top 25 WEE indicators from over a hundred tested. Those not shown were either not selected or selected with minimal frequency. ‘Percent Times Selected’ indicates how often the construct was selected in all best performing models combined (LASSO Stability Selection, BORUTA, and VSURF Interpretation and Prediction).