Revisiting Gender Gaps in Microenterprise Performance: Evidence from Firm-Level and Household-Level Outcomes

Abstract

Micro and small enterprises (MSEs) play an important role in economic resilience in emerging economies, yet women-owned MSEs consistently report lower profits than male-owned firms. Most studies evaluate this gender gap using firm-level indicators, with limited attention to how enterprise outcomes relate to household welfare. This study examines whether female ownership is associated with both enterprise profit and household well-being by simultaneously estimating firm-level performance and household-level welfare outcomes within a single nationally representative Indonesian dataset. Using data from the Indonesia Family Life Survey (IFLS-5), four regression models are estimated for business profit, household per capita expenditure, education spending, and subjective well-being, applying Ordinary Least Squares with robust standard errors and M-estimator regressions to assess the stability of associations across specifications.

The results indicate a significant gender gap in business profit; however, female ownership is positively associated with household consumption, education expenditure, and subjective well-being. These findings suggest that in necessity-driven contexts, women-owned MSEs may play a role in supporting household welfare despite lower firm-level returns, thereby providing a basis to reconsider profit-centered measures of entrepreneurial success and informing more gender-sensitive evaluation frameworks. The analysis identifies statistical associations rather than causal effects and does not fully address potential issues such as selection into female ownership, omitted variables, and the ordinal nature of subjective well-being.

Keywords: gender gap in microenterprises; necessity-driven entrepreneurship; household welfare; human capital investment; household interference; emerging economies.

Introduction

Micro and small enterprises (MSEs) play a pivotal role in economic resilience, employment generation, and poverty alleviation across emerging economies. Empirical evidence shows that MSEs significantly enhance household income and well-being, particularly in contexts with limited formal employment (Endris & Kassegn, 2022). In Indonesia, MSEs account for approximately 99% of enterprises and employ more than 97% of the labor force, underscoring their significant role in inclusive economic development (Badan Pusat Statistik, 2024). Women constitute a substantial and growing share of MSE owners across emerging economies. However, their increasing participation in micro and small-scale entrepreneurship has not been accompanied by equivalent enterprise outcomes, as gender-based performance disparities remain persistent (Kim, 2022). A large body of research consistently documents gender gaps in firm-level performance (Allison et al., 2023; Fang et al., 2022; Islam et al., 2019).

Female-owned MSEs tend to generate lower profits, slower growth, and lower returns to capital, even after controlling for education, sector, and capital intensity (Delecourt & Ng, 2021; Tsyganova & Shirokova, 2010). Recent global evidence further confirms the persistence of gaps driven by unequal access to finance, professional networks, and growth opportunities (Aterido et al., 2013). Prevailing explanations attribute these disparities to gender disparities in MSEs’ performance across both structural constraints such as financial exclusion, unpaid care developed and emerging economies. Experimental and field burdens, and socio-cultural norms limiting women’s mobility evidence shows that female-owned MSEs generate lower and business expansion (Bullough et al., 2022; Field et al., profits and returns to capital than male-owned firms, even after 2021; Jayachandran, 2021). Empirical evidence further controlling for sector, education, and initial capital (Delecourt & highlights restricted access to capital and weaker integration Ng, 2021; Fafchamps et al., 2014).

Large-scale cross-country into formal financial systems as barriers to scaling women-led analyses further confirm systematic gender gaps in profit, enterprises (Demirgüç-Kunt et al., 2020; Sahay et al., 2015). productivity, and growth across diverse institutional contexts While these explanations are well established, they largely (Aterido et al., 2013; Kalnins & Williams, 2014). Importantly, assume that profit maximization and firm growth are the these disparities persist beyond early-stage firms, suggesting primary objectives of entrepreneurship. structural rather than transitory constraints. This profit-centered assumption may overlook differences Prevailing explanations emphasize structural barriers in entrepreneurial motivation that shape how MSEs are run disproportionately affecting women entrepreneurs. Limited and how business income is used. In many emerging access to formal finance remains one of the most consistently economies, women are more likely to engage in documented constraints (Demirgüç-Kunt et al., 2020; Sahay et entrepreneurship out of necessity rather than opportunity, al., 2015), while gender norms limit mobility, risk-taking, and particularly in contexts characterized by labor market participation in professional networks (Bullough et al., 2022; informality and economic precarity; (Block et al., 2015; Jayachandran, 2021).

Women-owned MSEs are also more Bosma et al., 2020; Williams & Williams, 2014) In such concentrated in lower-margin sectors and face binding time contexts, entrepreneurship often serves as an income- constraints due to unpaid care responsibilities, which constrain smoothing mechanism embedded in household survival growth trajectories (Field et al., 2021). Collectively, these strategies rather than as a vehicle for capital accumulation structural factors reduce profit potential. Consistent with this (Grimm et al., 2012; Vial & Hanoteau, 2015). literature, we expect: In necessity-driven entrepreneurship, business income is

H1a: Female-owned MSEs generate lower business profits commonly allocated to immediate household needs rather than male-owned enterprises, ceteris paribus. than reinvested in the firm. Evidence from development While structural explanations are empirically robust, they economics consistently shows that women’s income is more largely assume that firm growth and profit maximization are likely to be directed toward food security, education, and universal entrepreneurial objectives. A second stream of human capital formation (Duflo, 2012; Heath & Mushfiq literature challenges this assumption by emphasizing Mobarak, 2015; Prina, 2015). Research on MSEs’ behavior entrepreneurial motivation, particularly the distinction between further demonstrates that female entrepreneurs exhibit opportunity-driven and necessity-driven entrepreneurship. In different reinvestment and consumption patterns than men, many emerging economies, women are more likely to engage often prioritizing household welfare over business expansion in entrepreneurship as a response to labor market informality, (Berge et al., 2015; Fafchamps et al., 2014). Evidence from limited employment opportunities, and economic precarity Indonesia also highlights the strong overlap between (Block et al., 2015; Bosma et al., 2020). Such enterprises are household and business finances in microenterprises, often subsistence-oriented and embedded within household reinforcing the interdependence between enterprise survival strategies rather than designed for capital performance and household welfare (Yanuarta RE et al., accumulation (Grimm et al., 2012; Williams & Williams, 2014). 2023). This perspective suggests that enterprise performance may be Despite these insights, most empirical research on gender shaped not only by structural constraints but also by and MSE performance remains firm-centric, focusing primarily differences in the objectives and functions that on profit and growth indicators (Delecourt & Ng, 2021; entrepreneurship serves within the household economy. Kalnins & Williams, 2014). Such approaches risk This motivational perspective suggests that lower firm-level mischaracterizing women-owned MSEs as underperforming performance among women-owned MSEs may reflect while overlooking their broader contribution to household differences in income-use priorities rather than inferior welfare. While existing studies on household interference, managerial capability. In necessity-driven contexts, where family business systems, and women’s income allocation enterprises are often established as income-stabilization highlight the interdependence between enterprise and strategies under binding resource constraints, financial household outcomes, they rarely examine these dimensions decisions may prioritize immediate household needs over jointly within a single empirical framework. Addressing this business reinvestment. Building on this perspective, the gap, the present study simultaneously estimates firm-level literature on household interference and the Sustainable and household-level outcomes using nationally Family Business Model conceptualizes business and representative data from the Indonesia Family Life Survey household systems as mutually interdependent, with financial (IFLS). By integrating business profit with household per flows potentially shifting from the enterprise to the household capita expenditure, education spending, and subjective well- when consumption pressures are high (Svoboda, 2020). Within being, this study offers a more bounded empirical this framework, a plausible sequence can be proposed in which reassessment of gender performance differences and necessity-driven motives are associated with lower reinterprets the gender performance gap through the lens of reinvestment capacity, which in turn is linked to greater household interference (Yanuarta RE et al., 2023). allocation of resources toward household consumption and Specifically, the study examines whether lower firm-level human capital investment. Empirical evidence shows that performance among women-owned MSEs is associated with women’s income is more frequently associated with stronger household-level outcomes. By integrating objective expenditures on food security, children’s education, and and subjective welfare indicators, it advances a gender- human capital formation (Duflo, 2012; Heath & Mushfiq sensitive, contextually grounded understanding of Mobarak, 2015; Prina, 2015), while experimental studies entrepreneurial success and provides a basis to reassess document gender differences in reinvestment and capital profit-centric evaluations in gender and entrepreneurship allocation behavior in microenterprise settings (Berge et al., research in emerging economies. 2015; Fafchamps et al., 2014). Evidence from Indonesia further indicates a strong overlap between household and Literature Review business finances in microenterprises (Yanuarta RE et al., A substantial body of research documents persistent 2023). However, it is important to note that the present study does not directly observe intra-household allocation Although the data were collected in 2014–2015, they remain decisions. Therefore, this sequence should be interpreted as suitable for the present study because the analysis focuses on a proposed mechanism that is consistent with, but not directly structural patterns of household–enterprise interaction and tested by, the empirical analysis. gendered economic roles, which tend to be relatively persistent These findings suggest that enterprise performance and in necessity-driven contexts. The survey provides detailed household welfare are jointly determined outcomes. information on household demographics, labor participation, Evaluating women-owned MSEs solely through firm-centric consumption, subjective well-being, and non-agricultural metrics risks misinterpreting rational household-oriented enterprise activities. Individual, enterprise, and household income allocation as inefficiency. If women channel business modules are linked using unique household and individual income directly toward household consumption and human identifiers, enabling the construction of an integrated dataset capital investment, then household-level welfare indicators that connects enterprise-level performance with household- may diverge from firm-level profit measures. Accordingly, we level welfare outcomes. While the IFLS employs a complex expect: survey design with stratified sampling, the present analysis

H1b: Households operating female-owned MSEs are treats the data as a representative cross-section and applies associated with higher per capita expenditure than those robust standard errors to account for heteroskedasticity; operating male-owned enterprises, ceteris paribus. however, the results should be interpreted as associational Given consistent evidence that women’s income rather than fully design-based causal inference. IFLS is allocation improves educational investment and child particularly suitable for this study because it integrates outcomes (Duflo, 2012; Heath & Mushfiq Mobarak, 2015), enterprise-level variables with household-level welfare we further hypothesize: measures, enabling an empirical assessment of household

H1c: Female-owned MSEs are associated with higher interference (Strauss et al., 2016; Yanuarta RE et al., 2023). household education expenditure compared to male-owned enterprises, ceteris paribus. Sample Selection Beyond objective consumption measures, subjective well- The analytical sample consists of male and female micro being captures perceived economic security and resilience. If and small entrepreneurs operating non-agricultural household women’s entrepreneurship stabilizes household income and businesses recorded in the IFLS enterprise module. Consistent strengthens food security and educational investment, it may with the survey’s small-enterprise coverage, MSE status in this enhance perceived welfare despite lower business profit study refers to self-reported household businesses operated on (Prina, 2015). Therefore: a micro or small scale, without the formal characteristics of

H1d: Households operating female-owned MSEs report large firms. The sample selection follows a sequential higher levels of subjective well-being than those operating screening process. First, individuals not engaged in non- male-owned enterprises, ceteris paribus. agricultural household enterprise activities are excluded. These hypotheses are grounded in a dual-outcome Second, agricultural businesses are removed to maintain framework that distinguishes between firm-level and comparability in enterprise structure and income generation. household-level performance. Prior research can be broadly Third, the sample is restricted to individuals aged 18–64 who grouped into two streams. The first stream focuses on firm- are identified in the survey as the primary owner or main level outcomes, evaluating entrepreneurial success primarily decision-maker of the enterprise. Fourth, observations through profit, productivity, and growth indicators, and associated with irregular or non-continuous activities are consistently documenting gender-based performance excluded to focus on relatively stable income-generating MSE disparities. The second stream emphasizes household-level operations. Fifth, observations with missing key variables, outcomes, highlighting the role of women’s income in including enterprise performance measures and household supporting consumption, human capital investment, and welfare indicators, are removed. Finally, zero and negative broader welfare objectives, particularly in necessity-driven profit observations are excluded to allow consistent estimation contexts (Jayachandran, 2021; Sahay et al., 2015). However, of log-transformed profit models. After applying these these streams have largely developed in parallel, leaving sequential filters, the final analytical sample includes 4,064 unresolved how firm-level disadvantage and household-level entrepreneurs (2,154 male-owned and 1,910 female-owned welfare outcomes jointly manifest within the same empirical MSEs). setting. The present study addresses this gap by simultaneously estimating business and household outcomes Variables and Measures within a single analytical framework. By jointly examining This study uses variables available in the IFLS-5. Four profit, consumption, education expenditure, and subjective dependent variables correspond to four empirical models. One well-being, this approach provides a more integrated variable, business profit, represents business-level outcomes empirical perspective and enables a more precise and is measured as self-reported monthly operating revenue assessment of how gender differences in microenterprise minus monthly operating expenses as recorded in the IFLS performance relate to household welfare in emerging business module. Because the IFLS covers household-based economies. micro and small businesses, reported profits may reflect seasonal fluctuations and overlap between household and Methods business finances. However, it remains the most direct indicator available of routine business financial returns in the Data Source survey. To allow for a logarithmic transformation and reduce This study uses a quantitative, cross-sectional design distortion from non-operational or loss-making observations, based on secondary data from the Indonesia Family Life zero and negative profit values are excluded from the Survey-Wave 5 (IFLS-5), a nationally representative regression. longitudinal household survey conducted in 2014–2015 by Three variables, per capita household expenditure (monthly the RAND Corporation in collaboration with Lembaga total household consumption divided by household size (Beegle Demografi Universitas Indonesia, the Population Research et al., 2016; Deaton & Zaidi, 2002), household education Center Universitas Gadjah Mada, and SurveyMeter. IFLS expenditure (total spending on children's education), and covers more than 13,000 households and over 30,000 subjective well-being (self-reported economic well-being on a individuals across 13 provinces, representing approximately six-point Likert scale (Diener et al., 2018), represent outcomes 83% of the Indonesian population (Strauss et al., 2016). at the household level. Although subjective well-being is measured on an ordered scale, OLS is retained as the in the lowest profit quartile (q1), while male-owned firms common baseline estimator to preserve coefficient dominate the highest quartile (q4). comparability across the four outcome models and because Furthermore, Table 2 maps a strong monotonic alignment prior applied research shows that OLS generally provides between firm-level profit and household expenditure for both substantively similar directional inferences for ordinal well- genders. Among businesses in the lowest profit quartile (q1), being measures in large samples. This choice is consistent household expenditure is heavily concentrated in q1 with the study’s objective of examining directional expenditure and declines steadily toward higher expenditure associations within a unified regression framework. However, quartiles, both for female-owned and male-owned firms. A because OLS does not fully capture the ordinal structure of similar gradient persists in the q2 profit group, where subjective well-being, the results for this outcome should be expenditure remains most concentrated in q1 and interpreted cautiously and as associational rather than progressively decreases toward q4. causal. At the opposite end, the highest profit quartile (q4) exhibits The key explanatory variable is female ownership, coded the reverse pattern: household expenditure is concentrated in as 1 for female-owned MSEs and 0 for male-owned MSEs. In q4 expenditure and becomes progressively smaller toward the IFLS context, ownership refers to the individual identified lower expenditure quartiles. This holds for both female-owned in the survey as the primary owner or main decision-maker of and male-owned enterprises. These distributions indicate that, the enterprise, capturing operational control and day-to-day descriptively, higher-profit enterprises are systematically managerial authority rather than formal legal ownership associated with higher household expenditure levels. alone. This definition is consistent with the household-based Importantly, gender differences are most visible in the nature of microenterprises, where business decisions and composition and in the q3 profit group. For the q3 profit financial management are closely tied to the individual quartile, males are more numerous overall (584 males vs 432 responsible for enterprise operations. Control variables females). Yet, conditional on being in q3 profit, the expenditure include owner characteristics (age and years of education), distribution differs by gender: male-owned firms are relatively enterprise characteristics (sector, log business assets, log evenly distributed across expenditure quartiles, whereas reinvestment), and household characteristics (household female-owned firms show a clear upward concentration in q4 size, proportion of members aged ≤15, log labor income of expenditure, with expenditure progressively declining across other household members, urban–rural residence, and Java lower quartiles. This pattern suggests that, among mid-upper versus non-Java fixed effects), following established profit enterprises, female-owned MSE households are more microenterprise and welfare modeling practices (Cameron & likely to be in higher household expenditure quartiles than Trivedi, 2005). would be expected under an even distribution. Table 2 complements these distributional patterns using Data Analysis median and interquartile range (IQR). Consistent with the profit Descriptive analysis employs distribution-sensitive composition in Table 1, female-owned enterprises display measures because of the heavy-tailed distributions of profit substantially lower median profit (IDR 458,333; IQR 922,500) and expenditure. Cross-tabulations of profit quartiles and than male-owned enterprises (IDR 1,000,000; IQR household per capita expenditure quartiles (Q1–Q4) are 1,680,000). In contrast, median household per capita presented by gender of ownership. Median and interquartile expenditure is slightly higher among female-owned households range (IQR) statistics are reported for profit, household (IDR 952,608; IQR 837,083) than male-owned households expenditure, and education spending (Cameron & Trivedi, (IDR 936,350; IQR 854,526). 2005). The descriptive evidence above indicates (i) a strong Inferential analysis uses Ordinary Least Squares (OLS) positive profit–expenditure gradient for both genders, (ii) a with heteroskedasticity-robust standard errors as the baseline clear gender gap in profit distribution (female concentrated at estimator. OLS is employed to provide a consistent and low-profit, male at high-profit), and (iii) a nuanced mid–upper comparable estimation framework across all outcome segment (Q3 profit) where female-owned households are more variables, including both continuous monetary measures and concentrated in the highest expenditure quartile. These subjective well-being. Monetary variables such as business patterns motivate multivariate regressions that test whether profit, household expenditure, and education spending exhibit gender differences in household welfare persist after right-skewed distributions; therefore, log transformations are controlling for owner, enterprise, and household applied to reduce skewness and improve model fit. To characteristics. address potential model concerns, multicollinearity diagnostics were examined and found to be within acceptable Multivariate Regressions Results thresholds, and model specifications were evaluated to Table 3 reports OLS estimates with heteroskedasticity- ensure stability of the estimated coefficients. As a robustness robust standard errors for four outcome variables: business check, models are re-estimated using M-estimation with profit, household per capita expenditure, education Huber and Tukey bi-weight iterations to reduce the influence expenditure, and subjective well-being. All models are jointly of outliers (White, 1980). This approach follows established significant (Prob > F = 0.000), with explanatory power ranging practices in applied micro econometrics for large household from modest (R² = 0.042 for subjective well-being) to surveys (Cameron & Trivedi, 2005). While these methods substantial (R² = 0.312 for per capita expenditure). improve estimation reliability, the analysis is based on cross- sectional data and is intended to identify statistical Firm-Level Performance associations rather than causal relationships. Female ownership is negatively and strongly associated with business profit (β = −0.563, p < 0.001), indicating a Result and Discussion substantial gender gap in firm-level performance after controlling for owner, enterprise, household, and regional characteristics. Business assets, reinvestment-related Table 1 presents the cross-tabulation of business profit variables, education, and urban location are positively and household per capita expenditure across quartiles (q1– associated with profit, while operating outside Java is q4), disaggregated by gender of ownership. The distribution negatively associated with profit. These results are consistent reveals a clear gender asymmetry at the tails of the profit with H1a, suggesting that female-owned MSEs are associated distribution. Female-owned enterprises are overrepresented Cross-Tabulation Business Profit-Household Expenditure by Gender in Quartile Expenditure – frequency (percent) Variable Total q1 q2 q3 q4 243 159 155 89 646 female (5.98) (3.91) (3.81) (2.19) (15.89) q1 132 107 79 57 375 male (3.25) (2.63) (1.94) (1.4) (9.22) 145 142 138 115 540 female (3.57) (3.49) (3.4) 2.83 13.29 q2 165 115 109 82 471 male (4.06) (2.83) (2.68) (2.02) (11.59) Profit 76 104 117 135 432 female (1.87) (2.56) (2.88) (3.32) (10.63) q3 148 162 142 132 584 male (3.64) (3.99) (3.49) (3.25) (14.37) 26 60 77 129 292 female (0.64) (1.48) (1.89) (3.17) (7.18) q4 81 167 199 277 724 male (1.99) (4.11) (4.9) (6.82) (17.81) 1016 1016 1016 1016 4064 total (25.00) (25.00) (25.00) (25.00) (100.00) Source: Authors’ own work Summary Statistics of Business Profit-Household Expenditure by Gender Variable Gender N Median (IDR) IQR (IDR) Female 1,910 458,333 922,500 Profit Male 2,154 1,000,000 1,680,000 Total 4,064 702,083 1,343,083 Female 1,910 952,608 837,083 Expenditure Male 2,154 936,350 854,526 Total 4,064 936,350 847,750 Source: Authors’ own work Results of Regression with VCE Robust Variable profit expenditure expenditure-educ sb-wellbeing female_own -0.56300*** 0.03354* 0.80535*** 0.18005*** asset (ln) 0.07493*** 0.01351*** 0.064** 0.01168*** reinvest (ln) -0.00391 0.00349** -0.00052 -0.00096 revconsum (ln) 0.12563*** 0.0109*** 0.05878** 0.00085 sector_i1 0.12337** -0.00678 0.12213 0.03599 sector_i2 -0.01753 -0.06590** 0.28646 0.02819 size-fam 0.02799** -0.13948*** 0.88021*** 0.00164 struct-fam -0.02637 -0.41556*** 11.813*** 0.01831 pcwage (ln) 0.03615*** 0.01668*** -0.01012 0.01318** age 0.00337 0.00164* 0.04937*** 0.00162 educ 0.03562*** 0.04185*** 0.19937*** 0.03952*** java -0.25337*** 0.09054*** 0.55171** 0.06696** urban 0.24157*** 0.13211*** -0.21400 -0.00204 constant 9.88924*** 13.47719*** -1.69838** 2.14236*** N 4064 4064 4064 4064 F (8, 4055) 81.87 21.39 43.85 115.2 Prob > F 0 0 0 0 ll -6970.094 -3248.366 -12963.341 -5576.384 r2 0.271 0.312 0.251 0.042 aic 13968.187 6524.731 25954.683 11180.769 Legend: * p<.1; ** p<.05; *** p<.001 Source: Authors’ own work with lower business profits than male-owned enterprises, In contrast, female ownership is positively associated with ceteris paribus. However, this adjusted association should be household per capita expenditure (β = 0.03354, p < 0.10), interpreted with caution, as it may also reflect alternative implying a modest increase of approximately 3.3% in per capita factors such as reporting differences, residual sectoral consumption. Although small in magnitude and only marginally composition not fully captured by control variables, significant, the direction of this association contrasts with the survivorship patterns, and unobserved household or negative profit coefficient. Household size and the share of entrepreneurial characteristics. children significantly reduce per capita expenditure, whereas

Literature Review

H1a: Female-owned MSEs generate lower business profits than male-owned enterprises, ceteris paribus.

H1b: Households operating female-owned MSEs are associated with higher per capita expenditure than those operating male-owned enterprises, ceteris paribus.

H1c: Female-owned MSEs are associated with higher household education expenditure compared to male-owned enterprises, ceteris paribus.

H1d: Households operating female-owned MSEs report higher levels of subjective well-being than those operating male-owned enterprises, ceteris paribus.

Methods

Data Source

Sample Selection

Variables and Measures

Data Analysis

Result and Discussion

Multivariate Regression Results

Firm-Level Performance

Household-Level Performance

Results of Robustness Test with M-Estimator Regression Variable profit expenditure expenditure-educ sb-wellbeing female_own -0.06126** 0.03308* 0.71622*** 0.18691*** asset (ln) 0.01398*** 0.01328*** 0.0714** 0.01234*** reinvest (ln) 0.00114 0.00384** -0.00268 -0.00127 revconsum (ln) 0.90364*** 0.01079*** 0.06231** 0.00186 sector_i1 0.05076** -0.00114 0.13871 0.01841 sector_i2 0.03993 -0.06638** 0.32401 0.02121 size-fam -0.00666 -0.13603*** 0.99853*** 0.00118 struct-fam -0.06317 -0.41818*** 12.58043*** -0.00346 pcwage (ln) 0.00944*** 0.01806*** 0.00505 0.01556*** age -0.00256** 0.00197** 0.04686*** -0.00057 educ 0.01031*** 0.04104*** 0.20945*** 0.04544*** java -0.08274*** -0.09339*** 0.55063** 0.05458* urban 0.05211** 0.12909*** -0.25991 0.02121 constant 1.20411*** 13.43268*** -2.20836** 2.10839*** N 4064 4064 4064 4064 r2 0.966 0.299 0.266 0.069 Legend: * p<.1; ** p<.05; *** p<.001 Source: Authors’ own work household wage income, education, assets, and urban The stability of coefficient signs across estimators suggests residence increase it.

Taken together, these results provide that the observed dual-outcome pattern namely, lower firm- limited and suggestive evidence consistent with H1b, level profit alongside stronger household-level welfare among indicating that lower firm-level profit among female-owned female-owned pattern is less sensitive to influential MSEs is not necessarily associated with lower household observations. Although the coefficient magnitudes differ consumption. However, this relationship is notably weaker modestly from the baseline OLS estimates, such variation is than the education expenditure results, which show larger expected under M-estimation because influential observations magnitudes and stronger statistical significance, suggesting receive lower weights, while the overall directional relationships that the welfare-related effects of female ownership may be remain consistent. These results indicate that the main findings more pronounced in human capital investment than in are not driven solely by extreme values or skewed distributions. general consumption.

However, it is important to note that this robustness check does Furthermore, female ownership shows a large, and highly not address other potential sources of bias, including significant positive association with household education endogeneity, omitted variables, measurement error, or spending (β = 0.8053, p < 0.001). This effect remains robust selection into female ownership. after controlling household composition, income, and This study contributes to the literature on gender and micro business characteristics. Owner education and the proportion and small enterprise (MSE) performance by showing a of children are also strongly positive predictors. The systematic divergence between firm-level and household-level magnitude and significance of the gender coefficient provide outcomes, extending prior empirical work that has largely strong evidence consistent with H1c, indicating that female- examined gender disadvantage through profit-centered owned MSE households invest more intensively in children’s business indicators alone.

Consistent with a large body of prior human capital. research, the results confirm a significant gender gap in For subjective well-being, female ownership is again business profit: female-owned MSEs generate lower returns positive and statistically significant (β = 0.18005, p < than male-owned enterprises even after controlling for owner 0.001). While the model explains a smaller share of variance, characteristics, assets, sector, and regional factors (De Mel et the consistent positive coefficient suggests that households al., 2009; Delecourt & Ng, 2021). This finding aligns with operating female-owned MSEs report higher perceived structural explanations emphasizing unequal access to capital, economic welfare. This finding is consistent with H1d. network constraints, and sectoral segregation (Aterido et al., Across models, a consistent dual pattern emerges female 2013). In many developing economies, women entrepreneurs ownership is negatively associated with firm-level profit but operate with smaller start-up capital, have lower access to positively associated with household consumption, education formal financial services, and are often excluded from expenditure, and subjective well-being.

The divergence professional networks that facilitate information flows, credit between enterprise and household outcomes persists after access, and market opportunities. These structural controlling observable characteristics, providing multivariate disadvantages can limit the scale and productivity of women- evidence broadly consistent with the household interference led enterprises, reinforcing persistent gender gaps in framework and the study’s dual-outcome hypothesis. profitability. However, the contribution of this study lies in moving Robustness Test: M-Estimator beyond the firm-centric interpretation that has dominated Table 4 reports M-estimator regressions using Huber and much of the entrepreneurship literature, particularly the Tukey bi-weight iterations to account for influential experimental and econometric tradition that evaluates gender observations. The results confirm the baseline findings. disparities primarily through business profit, returns to capital, Female ownership remains negatively associated with productivity, and growth (De Mel et al., 2009; Delecourt & Ng, business profit (β = −0.0613, p < 0.05), indicating that 2021).

While prior research has largely focused on firm-level outliers do not drive the gender profit gap. At the household indicators such as profit, productivity, and growth, the present level, female ownership remains positively associated with findings show that lower business profit among female-owned per capita expenditure (β = 0.0331, p < 0.10), education enterprises does not necessarily imply lower household spending (β = 0.7162, p < 0.001), and subjective well-being welfare. Female ownership is positively associated with (β = 0.1869, p < 0.001). household per capita expenditure, strongly associated with education spending, and positively associated with subjective well-being. Importantly, these patterns are consistent across managerial shortcomings. both OLS and M-estimator regressions, suggesting that the The descriptive quartile analysis presented in this study main associations are less sensitive to influential provides additional evidence that is consistent with this observations and extreme values in the distribution of income interpretation.

Although female-owned enterprises are more and expenditure. However, this robustness check does not concentrated in lower-profit quartiles, household expenditure eliminate other potential sources of bias, including remains positively associated with profit for both genders. More endogeneity, omitted variables, or measurement error. importantly, among enterprises located in the mid-to-upper This divergence between enterprise performance and profit range, female-owned households are more frequently household welfare outcomes is consistent with the household represented in the highest expenditure quartile. This pattern interference framework, which conceptualizes business and suggests that, conditional on achieving moderate business family systems as mutually embedded rather than returns, female ownership is associated with relatively higher independent economic units, and offers an empirical household expenditure outcomes.

However, this descriptive illustration of how such embeddedness may generate gender- evidence does not identify the underlying allocation process or differentiated outcome patterns across business and imply a direct flow of income from enterprise to household use. household domains (Stafford et al., 1999; Yanuarta RE et al., Rather, it indicates a pattern that is consistent with the 2023). Within this theoretical perspective, decisions about possibility that enterprise income in female-owned MSEs may income allocation, reinvestment, and consumption are be more closely linked to household welfare, while alternative shaped by the interaction between business objectives and explanations such as unobserved household characteristics, household needs. Particularly in contexts characterized by sectoral differences, or reporting variation may also contribute necessity-driven entrepreneurship, enterprises are often to the observed distribution. created not primarily as growth-oriented ventures but as These results support a broader reconceptualization of mechanisms for stabilizing household income.

As highlighted entrepreneurial success in emerging economies. Traditional in the literature on subsistence entrepreneurship, such approaches to evaluating business performance emphasize businesses often serve as adaptive responses to labor- firm growth, profit maximization, and capital accumulation as market informality, income volatility, and limited social the primary indicators of entrepreneurial success. In contrast, protection systems (Block et al., 2015; Grimm et al., 2012). the present findings suggest that household consumption, Under these conditions, entrepreneurs may rationally allocate education investment, and perceived welfare should also be business income toward immediate household consumption considered as complementary evaluative dimensions when rather than reinvestment in productive assets. assessing household-based micro and small enterprises. While The empirical findings of this study indicate a positive these metrics may be appropriate for opportunity-driven association between female ownership and household ventures in advanced economies, they may inadequately education expenditure.

This pattern is consistent with, but capture the economic role of microenterprises operating under does not directly establish, the interpretation that income necessity-driven conditions. In contexts such as Indonesia, generated by women-owned enterprises may be more closely where informality remains widespread, and many households linked to investments in children’s human capital. The data lack stable wage employment, microenterprises frequently capture expenditure outcomes rather than intra-household serve as instruments of household welfare production rather allocation decisions; therefore, the underlying mechanism than purely profit-maximizing entities. cannot be directly observed. Alternative explanations may From this perspective, the contribution of women’s also contribute to this pattern, including unobserved entrepreneurship may be systematically undervalued when household wealth, sectoral sorting into activities with different evaluation frameworks rely exclusively on firm-level indicators. income profiles, variations in household composition, and By integrating firm-level outcomes with household-level potential reporting differences across respondents.

Within measures such as consumption, education expenditure, and these limits, the observed association aligns with a well- subjective well-being, this study provides a more established body of research in development economics comprehensive assessment of the economic role of women- showing that women’s control over income is often associated owned enterprises. The results demonstrate that female with higher spending on children’s education, health, and entrepreneurship can contribute significantly to household broader household welfare (Duflo, 2012; Heath & Mushfiq resilience, human capital formation, and perceived economic Mobarak, 2015). From the perspective of the household security, even when firm-level profit remain modest. interference framework, this pattern can be interpreted as This study, therefore, contributes to the growing literature suggestive of gendered intra-household decision processes in that calls for a more holistic evaluation of entrepreneurship in which resources may be oriented toward collective welfare developing economies.

By empirically documenting the and long-term outcomes. In the context of microenterprises, divergence between enterprise profitability and household this implies that the economic role of women entrepreneurs welfare outcomes, the study underscores the importance of may extend beyond firm-level performance, although such accounting for intra-household allocation dynamics when interpretations should be viewed as consistent with, rather assessing the economic impact of microenterprises. The than directly demonstrated by, the empirical analysis. findings suggest that gender gaps in firm performance cannot Evidence from experimental studies of microenterprise be fully understood without accounting for the broader socio- investment behavior further supports this interpretation. economic functions that enterprises perform within household Research has shown that male and female entrepreneurs systems. may respond differently to financial shocks, grants, or access Finally, the study contributes a novel empirical perspective to credit, with women often allocating resources more by simultaneously examining firm-level and household-level conservatively and directing a larger share toward household outcomes within a unified analytical framework.

While previous consumption and risk mitigation (Berge et al., 2015; studies have typically focused on either enterprise Fafchamps et al., 2014). Rather than reflecting inefficiency or performance or household welfare, the present analysis weaker entrepreneurial ability, these differences may reflect demonstrates that these dimensions may follow distinct patterns consistent with rational strategies shaped by patterns, particularly in gendered entrepreneurial contexts. household responsibilities, income risk, and caregiving This dual-outcome approach helps reconcile the apparent obligations. In other words, the lower level of firm-level contradiction between lower firm-level performance and reinvestment observed among women-owned enterprises positive household welfare outcomes among female-owned may reflect deliberate allocation priorities rather than enterprises. In doing so, it advances a gender-sensitive and contextually grounded understanding of entrepreneurial networks, and institutional barriers.

At the same time, the success that better reflects the economic realities of findings suggest that policy frameworks focused solely on firm- necessity-driven entrepreneurship in emerging economies. level profitability may overlook the broader welfare-related dimensions associated with women-owned enterprises. Conclusion However, these implications should not be interpreted as causal evidence that expanding support for women-owned enterprises will necessarily lead to improved household welfare This study reexamines gender disparities in micro and outcomes. Rather, policies such as improving access to small enterprise (MSE) performance by adopting a dual- finance, strengthening participation in business networks, and outcome framework that simultaneously evaluates firm- and reducing institutional barriers may be informed by these household-level indicators, thereby offering both an empirical observed patterns, while recognizing that the underlying reassessment and a broader conceptual framing of mechanisms linking enterprise performance and household entrepreneurial performance.

Using nationally representative welfare remain only partially understood. data from Indonesia, the findings confirm a persistent gender Second, the evidence that female-owned MSEs are gap in business profit: female-owned MSEs generate positively associated with household consumption, education significantly lower returns than male-owned enterprises. expenditure, and subjective well-being suggests that women’s However, the analysis reveals a contrasting pattern at the entrepreneurship may play an important role in supporting household level. Female ownership is positively associated household welfare stability. In necessity-driven contexts, with per capita household expenditure, strongly associated enterprises often function as instruments of income smoothing with education spending, and positively associated with and household resilience rather than purely growth-oriented subjective well-being.

These findings remain robust across ventures. These findings suggest that policy design should alternative estimators, indicating that extreme values or more carefully recognize this potential welfare-supporting distributional artifacts do not drive the observed divergence. function of women-owned MSEs, while acknowledging that The results suggest that gender differences in such implications are informed by observed associations rather microenterprise performance are not fully captured by profit- than definitive causal effects. In this regard, social protection based indicators alone. While female-owned enterprises are programs, conditional cash transfers, and microfinance associated with lower business profit, the evidence indicates schemes may be more effectively integrated with enterprise positive associations with selected household welfare development initiatives to strengthen both business outcomes, particularly education expenditure and subjective sustainability and household well-being. well-being.

In contrast, the association with per capita Third, the strong association between female ownership household expenditure is more modest and only marginally and education spending highlights the intergenerational impact significant. Taken together, these findings are consistent with of women’s entrepreneurship. Supporting women-led the household interference perspective, suggesting that enterprises may yield long-term human capital gains that enterprise performance and household welfare may not move extend beyond immediate firm performance. Policymakers in parallel in necessity-driven contexts. However, given the should consider entrepreneurship support as part of broader cross-sectional design, these patterns should be interpreted human development strategies, particularly in regions as associational rather than causal, and as indicative of characterized by informality and labor-market precarity. potential differences in how enterprise income relates to Fourth, evaluation frameworks for MSME development household welfare rather than definitive evidence of programs should move beyond narrow profit-based indicators. underlying allocation mechanisms.

Monitoring systems that incorporate household-level By integrating firm and household dimensions within a outcomes, such as consumption stability, education single empirical framework, this study contributes to gender investment, and subjective welfare, would provide a more and development scholarship. It offers a transferable dual- comprehensive assessment of program effectiveness, outcome approach for future research on household-based especially in gender-targeted interventions. entrepreneurship. First, it demonstrates that gender gaps in Finally, regional disparities observed in the models enterprise performance do not necessarily imply lower welfare underscore the importance of spatially differentiated policies. among female-led households. Second, it provides empirical Tailored interventions that account for urban–rural divides and evidence that women’s entrepreneurial income is closely Java–non-Java differences are necessary to ensure equitable linked to human capital investment and perceived economic entrepreneurial development. security.

Third, it advances a more gender-sensitive In sum, the study suggests that gender-sensitive evaluation of entrepreneurship that aligns with inclusive entrepreneurship policy should pursue a dual objective: development objectives in emerging economies. reducing structural barriers to firm growth while simultaneously Future research should further explore dynamic and recognizing and reinforcing the household welfare causal mechanisms linking enterprise income allocation, contributions of women’s enterprises. Such an integrated intra-household bargaining power, and long-term welfare approach aligns more closely with inclusive development goals trajectories. Nonetheless, the present findings underscore a and the broader agenda of economic resilience in emerging central implication: entrepreneurial success, particularly economies. among women in necessity-driven contexts, should be assessed not only by firm growth but also by its contribution Limitations to household resilience and well-being.

Several limitations should be acknowledged. First, although the study relies on nationally representative IFLS data, the Policy Implications analysis is based on cross-sectional estimation. As such, the The findings carry implications for entrepreneurship, results capture associations rather than causal relationships. gender, and development policy in emerging economies. From Unobserved heterogeneity, such as entrepreneurial ability, an evidence-based perspective, the results indicate a intra-household bargaining power, or social capital, may persistent association between female ownership and lower influence both enterprise performance and household welfare firm-level profit, alongside positive associations with selected outcomes. Future research could exploit the longitudinal household welfare outcomes. These patterns are consistent structure of IFLS to examine dynamic trajectories and causal with the presence of structural constraints that mechanisms using panel or quasi-experimental approaches. disproportionately affect women entrepreneurs, including Second, while the study incorporates both objective and limited access to finance, weaker integration into business subjective welfare indicators, it does not directly measure dynamics; (2) deeper examination of intra-household allocation intra-household decision-making processes or income control and bargaining mechanisms; and (3) comparative studies mechanisms.

Prior research suggests that women’s allocation across institutional contexts. Advancing these lines of inquiry patterns are closely linked to bargaining power and control will further refine the conceptualization of entrepreneurial over household resources. Incorporating measures of success and strengthen the integration of gender, household financial decision authority or joint versus individual economics, and enterprise development scholarship. ownership structures would deepen understanding of how enterprise income translates into welfare outcomes. Author contributions Third, while this study centers on Indonesia, the findings may not be fully generalizable to contexts with different Ramel Yanuarta conceived and designed the analysis,institutional environments or gender norms. Comparative collected the data, contributed data or analysis tools,cross-country analyses could test whether the dual-outcome performed the analysis, interpreted the results, and wrote thepattern identified here holds across varying levels of financial paper.

Yokazio Sharen collected the data, contributed data orinclusion, labor market formality, and gender equality. analysis tools, performed the analysis, and wrote the paper. Nurfaizah collected the data, contributed data or analysis tools,Recommendations for Future Research and wrote the paper. Future research should therefore pursue three main directions: (1) longitudinal analysis of enterprise–household

Robustness Test: M-Estimator

Conclusion

Policy Implications

Limitations

Recommendations for Future Research

Author Contributions

References

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