INTRODUCTION:

The importance of gender issues, by following the concept of sustainable development, is increasing day by day globally to attain welfare objectives in a patriarchal society in any economy. Sustainable development implies the development of the present generation without harming the development sources of future generations.

Sustainable development doesn’t relate to any single economy but to the entire world economy. In the year 2000, the following Millennium Development Goals were issued by the United Nations to adopt the concept of sustainable development of the world economy: (i) Eradicate extreme poverty and hunger; (ii) Achieve universal primary education; (iii) Promote gender equality and empower women; (iv) Reduce child mortality; (v) Improve maternal health; (v) Combat HIV/AIDS, malaria, and other diseases; (vi) Ensure environmental sustainability; (vii) Global partnership for development. Recognizing the significance of gender equality in economic development, this study focuses specifically on gender inequalities and women’s empowerment. According to the World Bank, women comprised 49.74% of the global population in 2022.

Numerous studies have explored the influence of various social and economic factors on gender disparities in patriarchal societies, highlighting the need for targeted measures and policy interventions to reduce these inequalities alongside economic progress. Some of them are discussed here, like Stotsky, Chakraborty, and Gandhi (13) who explained in their study that fiscal transfers from centre to state could not affect the gender inequalities in the states. Gender budgeting efforts have also been insufficient at the subnational government level. The author suggested further detailed fiscal investigation with the help of more demographic data and demands for a finer level of disaggregation of transfer programs. Mahanta and Nayak (9) examined gender inequality in North East India, based on secondary data and various socio-economic indicators, revealed that women remain relatively disempowered and hold a lower status than men. Significant gender gaps were observed in health, education, employment, and political participation at both state and national levels. Among the northeastern states, Meghalaya, Manipur, and Mizoram showed lower gender inequality, while Tripura, Assam, and Sikkim faced more adverse conditions. The study concluded that while education, employment, and health are enabling factors, deep-rooted gender inequality largely stems from societal mindsetsSumanjeet (14) highlighted that despite India's high growth and numerous government initiatives, significant gender gaps persist. Gender inequality continues to restrict women’s access to opportunities and negatively impacts future generations' prospects. Kishor (11) by using secondary data, found higher female illiteracy in rural areas across all states except Meghalaya and Sikkim. Bihar (53.7%) and Madhya Pradesh (48.6%) had the highest rates. Child marriages and poor maternal health services contributed to wide gender development gaps. Kohli (8) examined that gender inequality remains deeply rooted in India’s patriarchal society, evident from female feticide, infanticide, and lifelong discrimination. Despite economic growth and legal reforms, gender parity is lacking, and the child-sex ratio has worsened. Girls are still seen as burdens. True progress requires a shift in societal mindset, with educated citizens promoting gender equality for a more just and empowered society. Arora (1) found high gender inequality even in high-income and trade-open states, despite greater employment opportunities. To boost women’s role in economic growth, policies must focus on integrating them into the paid workforce.

In summary, the literature reveals widespread gender inequality in India’s patriarchal society. Unlike previous studies, this research examines the impact of social sector expenditure—both at the aggregate (General Government) and individual state levels—on gender development indicators. Based on this, the study sets the following objectives: -

1. To examine the trends and pattern of expenditure on social services incurred by General Government,

2. to examine the reduction in gender inequalities through various indicators like Literacy, Health, Employment etc., in major general category states,

3. to study the impact of the social sector expenditure (such as expenditure growth rates and elasticities) on gender development indicators of the state government individually, and

4. to find the areas, where there is a need to work and suggest policies, to bring gender equality in typical patriarchic Indian societies.

Data Sources and Methodology:

The present study is descriptive and based on secondary data which covers most of the years of the second decade of the 21st century. Simple ratios and percentages are used to examine, explain, and bring out the findings for the said objectives. Data on various variables and years has been collected, as per the availability, from various sources like: - (i) Reserve Bank of India (RBI), (ii) Handbook of Statistics on State Government Finances, 2021-22, (iii) Economic Survey of India, Various Issues, (iv) Office of the Registrar General of India, Ministry of Home Affairs, (v) Crime in India, National Crime Records Bureau, Ministry of Home Affairs, and Ministry of Health and Family Welfare.

In addition to simple ratios and percentages following formulas are used for calculations of various variables: -

(i) Compound Annual Growth Rate (CAGR) Formula: The compounded annual growth rate formula to find the compound annual growth rate is as follows:

CAGR = (Ending balance/beginning balance) ^1/n – 1

Ending balance = Value of the end period, Beginning balance = Value of the beginning, n = Number of years.

(ii) Income elasticity of Expenditure can be defined as a percentage change in expenditure (EXP) incurred by the government with respect to percentage change in income of the state/government i.e., Gross State Domestic Product (GSDP)

Percentage Change in Expenditure

Expenditure Elasticity = --------------------------------------

Percentage Change in GSDP

In the present study, expenditure elasticities are calculated for total expenditure (including revenue and capital expenditure,) by general and individual state government on social services. Assuming a Log linear relationship between expenditure and state income, following regression equation has been used to estimate expenditure elasticities for expenditure on social services: -

Ln (EXP) = α + β Ln (GSDP)-----------------------------(1)

Here, α indicates the log of expenditure when state domestic product is one, while β shows expenditure elasticity. If β > 1, expenditure grows faster than GSDP; if β = 1, it grows equally; if β < 1, it grows slower.

The study has four sections: Section 1: - covers introduction, literature review, and objectives of the study. Section 2: - details data sources and methodology. Section 3: - will make analysis of social sector expenditure and its impact on gender indicators i.e. 3.1 Health Issues, 3.2 literacy, 3.3 Employment. Section 4: - will give conclusions and make policy suggestions.

Pattern of Expenditure on Social Services by Government:

Table 1 shows the trends of expenditure on social services in absolute and relative terms. Total expenditure increased from 45.2 lakh crore in 2017-18 to 80.1 lakh crore in 2022-23. As a ratio of GSP, it was 6.7% in the year 2017-18, which increased to 8.3% in 2022-23. Similarly, share of expenditure on social services in total expenditure increased marginally from 25.2% to 26.6%.

Unfortunately, data for total expenditure on various services is not available according to gender in accounts of government at any level, may be taken as a limitation of study here.

3.1 Health Issues:

Table 2 presents Government Health Expenditure (GHE) and Out-of-Pocket Expenditure (OOPE) as percentages of Total Health Expenditure (THE). The GHE-to-THE ratio increased from 28.6% in 2013–14 to 40.6% in 2018–19—an improvement of about 12%, primarily driven by a decline in OOPE’s share from 64.2% to 48.2%. This suggests that, despite the improvement, patients continue to bear a substantial share of treatment costs, which adversely affects overall public health.

Figure 1 shows state-wise OOPE as a share of the, mostly below the national average of 48.2% (2018–19). Lowest shares were in Karnataka (33.3%), Uttarakhand (35.5%), and Chhattisgarh (36.7%) followed by other states also. Uttar Pradesh was the only state with OOPE over 70%. A declining OOPE share reflects the government’s limited commitment to health spending.

Table 1: Trends in Social Services Expenditure by General Government

Particulars

2017-18

2018-19

2019-20

2020-21

2021-22 (RE)

2022-23 (BE)

Total Expenditure

(in lakh crore)

45.2

50.4

54.1

63.5

74.5

80.1

Expenditure on Social Services (in lakh crore)

11.4

12.8

13.6

14.8

19.4

21.3

Expenditure on Social Services (as % of GDP)

6.7

6.8

7.5

8.2

8.3

Expenditure on Social Services (as % of total expenditure)

25.2

25.4

25.2

23.3

26.1

26.6

Source: Economic Survey of India, 2022-23.

Table 2: Government Health Expenditure (GHE) and Out of Pocket Expenditure (OOPE) as per cent of Total Health Expenditure (THE)

Particulars	2013-14	2014-15	2015-16	2016-17	2017-18	2018-19
GHE as per cent of THE	28.6	29	30.6	32.4	40.8	40.6
OOPE as per cent of THE	64.2	62.6	60.6	58.7	48.8	48.2

Table 3: Life Expectancy at Birth & Total Fertility Rate for Major States

States	Life Expectancy at Birth (in years)						Total Fertility Rate (TFR)
	2010-14			2014-18			2010	2020
	Male	Female	Total	Male	Female	Total	Total	Total
(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
Andhra Pradesh	66.3	70.8	68.5	68.7	71.4	70.0	1.8	1.5
Bihar	67.8	68.4	68.1	69.4	68.7	69.1	3.6	3.0
Gujarat	66.6	71.0	68.7	67.8	72.3	69.9	2.5	2.0
Haryana	66.3	71.3	68.6	67.7	72.3	69.8	2.3	2.0
Karnataka	66.9	70.8	68.8	67.9	70.9	69.4	2.0	1.6
Kerala	72.0	77.8	74.9	72.5	77.9	75.3	1.8	1.5
Madhya Pradesh	62.5	66.0	64.2	64.8	68.5	66.5	3.2	2.6
Maharashtra	69.9	73.6	71.6	71.3	73.8	72.5	1.9	1.5
Odisha	64.7	67.1	65.8	68.0	70.8	69.3	2.3	1.8
Punjab	69.7	73.8	71.6	71.0	74.8	72.7	1.8	1.5
Rajasthan	65.5	70.2	67.7	66.5	71.6	68.7	3.1	2.4
Tamil Nadu	68.6	72.7	70.6	70.2	74.2	72.1	1.7	1.4
Uttar Pradesh	62.9	65.4	64.1	64.8	65.8	65.3	3.5	2.7
West Bengal	68.9	71.6	70.2	70.7	72.6	71.6	1.8	1.4
All India	66.4	69.6	67.9	68.2	70.7	69.4	2.5	2.2

Source: Office of the Registrar General of India, Ministry of Home Affairs.

Note: Andhra Pradesh includes Telangana till the year 2014 and Jammu & Kashmir includes Ladakh till the year 2018

Between 2010 and 2020, Total Fertility Rate (TFR) declined across all states. In 2010, India's TFR was 2.5, but states like Andhra Pradesh, Kerala, Karnataka, Maharashtra, Punjab, Tamil Nadu, and West Bengal already had rates below 2.1. By 2020, the national Total Fertility Rate (TFR) had declined to 2.2, and following the same trend, Gujarat, Haryana, and Odisha also experienced a further decline, falling below the national average. The rise in female literacy and the shift from patriarchal to modern, career-oriented societies have led to late marriages and a preference for smaller families, influencing people’s decision to have children. As a result, population growth is coming under control, which will significantly contribute to India’s economic development in the future.

Table 4 presents the Infant Mortality Rates (IMR) for 2006, 2013, and 2020, along with the Child Sex Ratios (CSR) for children aged 0–6 years, based on Census 2001 and 2011. Across India and all states, IMR for female children has consistently been higher than that for males, reflecting deep-rooted gender discrimination. In 2006, Madhya Pradesh recorded the highest IMR (77), followed by Orissa (74), Uttar Pradesh (73), Rajasthan

(69), and Bihar (63), against the national average of 59. Kerala performed best with an IMR of only 16 and the highest CSR (960 in 2001; 964 in 2011), indicating greater social awareness and gender equality.

By 2013, IMR declined marginally for female children but remained higher than for males across all states. Rising literacy failed to translate into a reduction in gender bias. The same five states—Madhya Pradesh, Orissa, Uttar Pradesh, Rajasthan, and Bihar—continued to report the highest IMR, while Kerala maintained its superior position. In 2020, some positive changes emerged. Gujarat, Haryana, Kerala, and Madhya Pradesh reported lower IMR for girls than boys, showing signs of progress. Haryana, once infamous for its poor sex ratio, showed improvement, whereas Madhya Pradesh’s IMR remained higher than most states. Bihar succeeded in matching the national IMR, but Orissa, Rajasthan, and Uttar Pradesh continued to lag behind.

Overall, except for Kerala and Tamil Nadu (in 2006) and later Bihar and Haryana (in 2020), most states recorded IMRs above the national average.

Regarding CSR, India’s child sex ratio declined from 927 in 2001 to 918 in 2011 - a serious concern. States such as Gujarat, Haryana, Maharashtra, Punjab, Rajasthan, and Uttar Pradesh consistently remained below the national average, and Madhya Pradesh also joined this group by 2011. Despite economic and social progress, there has been little real improvement in gender balance, highlighting the persistent inequalities in child care and survival.

Women’s health lags behind men’s due to societal norms that prioritize family over their well-being. In patriarchal settings, they often neglect themselves while supporting families and enabling men to work. Recognizing their vital role, the Supreme Court affirmed women’s equal right to their husband’s income. Society must value and respect their contribution.

Table 4: Infant Mortality Rate (IMR) and Child Sex Ratio (CSR) of Indian States

States	Infant Mortality Rate (Per 1000 live births) (2006)			Infant Mortality Rate (Per 1000 live births) (2013)			Infant Mortality Rate (Per 1000 live births) (2020)			Child Sex Ratio (0-6 yrs.)
States	Male	Female	Total	Male	Female	Total	Male	Female	Total	2001	2011
Andhra Pr.	55	58	56	39	40	39	26	27	27	961	939
Bihar	58	63	60	40	43	42	28	33	30	942	935
Gujarat	52	54	53	35	37	36	25	23	24	883	890
Haryana	57	58	57	40	42	41	33	33	33	819	834
Karnataka	46	50	48	30	32	31	21	22	21	946	948
Kerala	14	16	15	10	13	12	12	4	8	960	964
Madhya Pr.	72	77	74	52	55	54	51	50	51	932	918
Maharashtra	35	36	35	23	25	24	18	19	18	913	894
Orissa	73	74	73	50	52	51	38	40	39	953	941
Punjab	39	50	44	25	27	26	20	24	22	798	846
Rajasthan	65	69	67	45	49	47	37	43	40	909	888
Tamil Nadu	36	37	37	20	21	21	13	13	13	942	943
Uttar Pr.	70	73	71	49	52	50	43	44	43	916	902
West Bengal	37	40	38	30	33	31	22	22	22	960	956
All India	56	59	57	39	42	40	31	33	32	927	918

Source: Economic Survey of India, Various Issues.

Table 5: Literacy Rates of Indian States

States	Literacy Rate 1991			Literacy Rate 2001			Literacy Rate 2011
States	Male	Female	Total	Male	Female	Total	Male	Female	Total
Andhra Pr.	55.1	32.7	44.1	70.9	51.2	61.1	75. 6	59.7	67.7
Bihar	52.5	22.9	34.5	60.3	33.6	47.5	73.4	53.3	63.8
Gujarat	73.1	48.6	61.3	80.5	58.6	69.9	87.2	70.7	79.3
Haryana	69.1	40.5	55.9	79.3	56.3	68.6	85.4	66.8	76.6
Karnataka	67.3	44.3	56.0	76.3	57.5	67.0	82.9	68.1	75.6
Kerala	93.6	86.8	89.8	94.2	87.9	90.9	96.0	91.9	93.9
Madhya Pr.	58.4	28.9	44.2	76.8	50.3	64.1	80.5	60.0	70.6
Maharashtra	76.6	52.3	64.9	86.3	67.5	77.3	89.8	75.5	82.9
Orissa	63.1	34.7	49.1	75.9	51.0	63.6	82.4	64.4	73.5
Punjab	65.7	50.1	58.5	75.6	63.6	69.9	81.5	71.3	76.7
Rajasthan	55.0	20.4	38.6	76.5	44.3	61.0	80.5	52.7	67.1
Tamil Nadu	73.8	51.3	62.7	82.3	64.6	73.5	86.8	73.9	80.3
Uttar Pr.	55.7	25.3	41.7	70.2	43.0	57.4	79.2	59.3	69.7
West Bengal	67.8	46.6	57.7	77.6	60.2	69.2	82.7	71.2	77.1

Source: Economic Survey of India, Various Issues.

Table 6: Gross Enrolment Ratio (per cent)

	2021-22									2020-21
States	Elementary Schools (I-VIII)			Secondary Schools (IX-X)			Senior Secondary Schools (XI-XII)			Higher Education (18-23 Year)
	Elementary Schools (I-VIII)			Secondary Schools (IX-X)			Senior Secondary Schools (XI-XII)			Higher Education (18-23 Year)
	Boys	Girls	Total	Boys	Girls	Total	Boys	Girls	Total	Boys	Girls	Total
(1)	(2)	(3)	(4)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)	(16)
Andhra Pradesh	101.1	99.1	100.1	86.3	84.5	85.4	55.2	58.3	56.7	38.3	36.0	37.2
Bihar	95.1	97.4	96.2	63.1	66.8	64.9	35.6	36.2	35.9	16.6	15.1	15.9
Gujarat	90.7	94.3	92.4	77.2	72.8	75.2	48.6	47.8	48.2	23.6	20.6	22.2
Haryana	103.0	103.4	103.2	96.0	93.2	94.7	75.1	76.0	75.5	28.9	33.7	31.1
Himachal Pradesh	105.3	107.1	106.0	93.5	94.8	94.1	93.0	95.3	94.1	33.5	44.7	38.7
Karnataka	107.2	107.0	107.1	94.6	94.9	94.7	54.6	58.8	56.6	34.8	37.2	36.0
Kerala	101.3	100.7	101.0	98.3	97.4	97.9	81.8	88.4	85.0	34.5	52.3	43.2
Madhya Pradesh	88.9	88.4	88.7	71.4	68.4	70.0	51.9	50.7	51.3	27.3	26.8	27.1
Maharashtra	103.2	105.5	104.3	94.7	92.5	93.7	72.0	70.9	71.5	36.2	33.5	34.9
Odisha	95.5	95.3	95.4	80.1	80.6	80.3	41.8	45.4	43.6	21.3	20.1	20.7
Punjab	109.4	109.8	109.6	94.8	95.4	95.1	81.2	83.1	82.1	23.9	29.1	26.3
Rajasthan	101.7	101.9	101.8	82.4	75.8	79.2	74.0	66.3	70.4	26.1	26.0	26.1
Tamil Nadu	98.4	99.2	98.8	95.7	95.5	95.6	77.3	85.9	81.5	45.4	48.6	46.9
Uttar Pradesh	96.5	99.9	98.1	72.0	66.2	69.3	52.8	48.3	50.7	22.3	24.3	23.2
West Bengal	107.8	109.1	108.5	83.4	93.2	88.2	53.7	70.6	62.0	20.3	22.3	21.3
All India	99.3	101.1	100.1	79.7	79.4	79.6	57.0	58.2	57.6	26.7	27.9	27.3

Source: Economic Survey of India, Various Issues.

At the higher education level, GER declined for both genders, with boys faring worse in most states. For girls, GER was below 45% in all states except Kerala and Tamil Nadu, and below 20% in Bihar. Bihar (16.6%), Odisha (21.3%), and Gujarat (23.6%) ranked lowest in women's higher education. Poor female GER is seen not only in low-income states but also in richer ones like Haryana, Punjab, Gujarat, and Maharashtra. As education level rises, GER drops for both genders—more sharply for boys. State-wise, GER variation is greater among girls than boys. Traditional practices like dowry still hinder girls' education. Families often save for marriage over schooling, believing sons will support them in old age. Despite progress, such deep-rooted beliefs persist, showing that changing mindsets takes more than just money or literacy.

Table 7: Number of Teachers in Higher Education Institutions (in percents)

Year	Male	Female	Total
2016-17	59.6	40.4	100
2017-18	58.1	41.9	100
2018-19	57.7	42.3	100
2019-20	57.3	42.7	100
2020-21	57.4	42.6	100

Source: Economic Survey of India, Various Issues.

Table 7 highlights women’s participation in educational institutions, revealing that their enrolment ratio remains significantly lower than that of men. Although women’s participation in higher education has improved over time, men continue to dominate educational spaces.

Table 8 presents state-wise data on the participation of female teachers in higher education. Nationally, women constitute around 40% of teachers, but in most states, their share remains below this level. Only a few states-Kerala, Punjab, Haryana, Tamil Nadu, and Karnataka-record higher participation than the national average. The remaining states have shown little progress, indicating limited efforts to strengthen women’s education, employment opportunities, and job security in academic institutions.

Overall, both nationally and across states, the representation of women teachers in higher education remains lower than that of men. Historically, women’s lower literacy rates have restricted their participation, but with a steady rise in female literacy over the past two decades, this gap is expected to narrow in the future.

Table 8: State-wise Proportion of Females among Tertiary Education Teachers or Professors (in percentage)

States	2017-18	2018-19	2019-20	2020-21
Andhra Pradesh	32.13	32.73	33.39	34.49
Bihar	19.94	19.96	20.36	21.36
Gujarat	35.76	36.41	37.25	37.76
Haryana	50.66	50.66	51.22	51.33
Karnataka	41.61	42.31	42.98	44.02
Kerala	58.86	59.41	59.74	60.77
Madhya Pradesh	39.70	39.59	39.79	39.80
Maharashtra	38.10	38.57	39.30	40.11
Odisha	33.02	33.77	34.62	35.33
Punjab	56.19	56.14	56.36	56.51
Rajasthan	37.08	36.71	36.85	36.41
Tamil Nadu	47.24	47.82	48.34	48.92
Uttar Pradesh	31.18	30.93	30.70	30.80
West Bengal	31.18	31.27	31.25	31.75
India	40.20	40.32	40.67	41.04

Source: Crime in India, National Crime Records Bureau, Ministry of Home Affairs, various issues.

Table 10: State -wise Elasticities and CAGR of Expenditure on Social Sector (From 2011-12 to 2021-22)

States

Constant

(t-value)

Elasticity

(t-value)

R-Square

[F-value]

CAGR

Andhra Pradesh

2.446

(5.266)

.644

(18.612)

.975

[346.405]

-3.1%

Bihar

-8.804

(-5.537)

1.525

(12.415)

.945

(154.135)

7.4%

Gujarat

-1.500

(-2.060)

.891**

(17.053)

.970

[290.806]

0.6%

Haryana

-5.015

(-6.038)

1.160

(18.436)

.974

[339.877]

1.4%

Karnataka

-2.658

(-3.273)

.982

(16.880)

.969

(284.929)

-0.8%

Kerala

-5.507

(-3.432)

1.198

(9.948)

.917

[98.955]

2.6%

Madhya Pradesh

-3.144

(-4.097)

1.057

(18.316)

.974

[335.48]

0.1%

Maharashtra

-6.448

(-2.976)

1.238

(8.312)

.885

[69.086]

4.1%

Odisha

-7.731

(-8.338)

1.421

(19.718)

.977

[388.812]

3.8%

Punjab

-7.048

(-1.369)

1.308***

(3.287)

.546

[10.804]

4.5%

Rajasthan

-7.942

(-8.379)

1.406

(20.040)

.978

[401.620]

4.7%

Tamil Nadu

-2.489

(-2.537)

.971

(13.930)

.956

[194.050]

0.5%

Uttar Pradesh

-3.828

(3.516)

1.099

(14.163)

.957

[200.583]

1.7%

West Bengal

-6.455

(-5.626)

1.287

(15.356)

.963

[235.799]

3.3%

India

-7.318

(-2.422)

1.284

(7.004)

.845

[49.056]

3.0%

All the values are Significant at level of 1 %, (**) significant at level of 10 %, and (***) indicates insignificant.

Note: CAGR means Compound Annual Growth Rate which are computed for social sector expenditure as a percentage of GSDP.

Source: Calculated by Author

Table 10 presents the state-wise elasticities and Compound Annual Growth Rates (CAGR) of social sector expenditure from 2011–12 to 2021–22. The table shows that only four states—Andhra Pradesh, Gujarat, Tamil Nadu, and Karnataka—recorded elasticity values of less than one. The negative CAGRs for Andhra Pradesh and Karnataka indicate that their social sector expenditure actually declined during the study period. In Gujarat, Madhya Pradesh, and Tamil Nadu, the social sector expenditure grew by less than 0.5 percent annually, showing inelastic expenditure patterns and resulting in weak or negative growth trends.

In contrast, Bihar registered the highest growth in social sector expenditure (7.4%), followed by Rajasthan (4.7%), Punjab (4.5%), and Maharashtra (4.1%). In all other states, this expenditure grew moderately—between 1% and 4% of the Gross State Domestic Product (GSDP).

However, despite significant increases in social spending in states like Bihar, Rajasthan, and Odisha, gender inequalities continue to persist at high levels. This raises concerns about inefficiency and possible corruption in the administration. If states spend heavily on the social sector but fail to reduce gender disparities, it suggests that the allocated funds are not being utilized effectively and in alignment with social development goals.

CONCLUSION AND SUGGESTION:

The study concludes that gender inequality in India remains a serious concern, particularly in the fields of education, health, and employment. Despite increasing government expenditure on the social sector, progress in women-related indicators remains uneven. States such as Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh continue to lag behind, whereas Kerala has performed significantly better due to its inclusive policies. An important finding of this study is that higher expenditure does not necessarily ensure better outcomes unless there is effective utilization of funds, proper implementation, and gender-sensitive planning.

Women continue to face challenges such as high infant mortality rates, low child sex ratios, and rising crimes against women, including trafficking—issues that reflect deep-rooted structural and cultural biases in society. According to Kishore (11), there exists a direct relationship between the declining sex ratio at birth and the increasing violence against women, particularly in the northern states of India.

Another major issue is the lack of awareness among women about government schemes. Even educated women often remain unaware of welfare programs designed for their benefit. For instance, the Indira Gandhi Single Girl Child Scholarship, which supports higher education for single daughters, is one such example that many eligible women do not know about. This clearly indicates that while policies exist, the outreach and communication mechanisms are weak.

From an economic perspective, studies by Bertay (2) and Kim (7) have shown that eliminating gender inequality can significantly boost per capita income, economic growth, and productivity. Therefore, women’s empowerment is not merely a matter of social justice but a prerequisite for sustainable economic development.

To reduce gender disparities, the study suggests that the government should make targeted investments by allocating special budgets for women’s health, education, and maternal welfare, along with ensuring outcome-based monitoring. Large-scale awareness campaigns through various media platforms and mandatory orientations on women-related schemes in schools, colleges, and local governance institutions are essential to improve awareness and access. Vocational and digital training programs should be expanded to enhance women’s employability, while entrepreneurship must be encouraged through easy access to credit, subsidies, and markets. Legal reforms are also needed to ensure fairness and provide real protection for victims of gender-based violence, along with the establishment of grievance redressal centers in every region. Changing social mindsets is equally important, requiring sustained campaigns to reshape gender perceptions both within families and in society, while addressing exploitation that occurs among women themselves. In higher education, special emphasis should be placed on increasing women’s participation through scholarships, mentoring, and leadership development programs. Moreover, institutional strengthening through real-time monitoring, gender audits, and the use of gender-disaggregated data in policy formulation and implementation is crucial. Finally, particular attention must be given to improving women’s nutrition and health facilities by strengthening nutritional programs, healthcare centers, and maternal care services to ensure their overall well-being and enable them to contribute effectively to the economy and society.

Ultimately, economic growth alone cannot eliminate gender disparities. True progress requires inclusive governance, accountability, and cultural transformation. As an academic woman, I have observed that even well-educated women often lack awareness of the schemes meant for them. Therefore, clear communication, community outreach, and structural reforms are essential to ensure genuine and sustainable women’s empowerment.

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Received on 23.04.2025 Revised on 26.06.2025

Accepted on 04.08.2025 Published on 07.11.2025

Available online from November 20, 2025

Res. J. of Humanities and Social Sciences. 2025;16(4):281-289.

DOI: 10.52711/2321-5828.2025.00046

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.

	Self employed	Regular wage/salary	Casual Labour
2017-18	52	23	25
2018-19	52	24	24
2019-20	54	23	24
2020-21	56	21	23