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Unlocking Women’s Workforce Potential in India: Quantifying the Labour Market Impact of Formalising Part-time Employment and Gender Equality in Unpaid Care Work

In this paper, we investigate the macroeconomic and labour market implications of gender equality in unpaid care work and the formalisation of part-time employment in India. The unequal distribution of unpaid care responsibilities significantly limits women’s labour force participation, perpetuating gender disparities in employment and economic outcomes. Using the McCall-Mortensen macroeconomic job search framework, this paper models the potential impacts of policy interventions on female labour force participation rates (LFPR).  A key contribution of the paper is to derive quantitative estimates via model simulation. We find that formalising part- time employment contracts and equalising the time burden of unpaid care work between genders predict a 6-percentage point increase in female LFPR, raising the current rate from 37% to 43%. The findings underscore the critical need for formalising part-time employment contracts in India. Equalizing the burden of unpaid care would require raising public investment in childcare and eldercare infrastructure, and policies promoting paid parental leave and tax incentives for shared care. Drawing on best practices from the advanced world, the study emphasises the role of flexibility in enabling women to balance professional and domestic responsibilities.

Why India’s job crunch is on a longer spell

Why India’s job crunch is on a longer spell By comparing data from two periods from the NSSO’s Periodic Labour Force Survey (PLFS), 2020-21 and 2023-24, the shifting unemployment patterns can be better understood. These changes provide us with a clearer picture of labour force participation, economic recovery, and the specific obstacles different demographic groups encounter

Unemployment is a multifaceted challenge that affects individuals across various demographic groups, including gender, age, and the length of their job search. A comprehensive understanding of unemployment spells – the period during which individuals remain unemployed while actively seeking employment – is vital for effective policymaking, economic analysis, and workforce planning. This can be attained by analysing the percentage of the population within distinct timeframes, based on how long individuals have been unemployed. By comparing data from two periods from the NSSO’s Periodic Labour Force Survey (PLFS), 2020-21 and 2023-24, the shifting unemployment patterns can be better understood. These changes provide us with a clearer picture of labour force participation, economic recovery, and the specific obstacles different demographic groups encounter.

A key finding among males is the notable rise in long-term unemployment. In 2020-21, a significant portion of unemployed men (37.5%) were in the 6-12 months and 15.4% in the less than or equal to 6 months unemployment category. By 2023-24, this number decreased to 25.9% and 12.2%, suggesting that a significant share of previously short-term unemployed males is now experiencing longer job search durations. Specifically, the percentage of males in the 1-2-year unemployment category rose sharply from 23.9% to 30.9%. This shift indicates that many men are facing difficulty in securing jobs beyond the initial months of unemployment, and similar trends are visible in both the 2-3 year and over 3-year categories.

Shifts in the labour market – such as automation and changes in demand for certain industries – have likely resulted in longer job search times for men. Additionally, the post-COVID restructuring of industries has altered the types of skills employer seek, leaving a segment of the male workforce either underemployed or struggling to adapt to new sectors.

While females still experience shorter unemployment spells than their male counterparts in the 6-12 month and the less than or equal to 6 months unemployment category, the 2023-24 data reveals a clear trend toward longer job searches. In 2020-21, 35.4% of unemployed women had been seeking work for 6-12 months. By 2023-24, this figure dropped to 21%. However, the percentage of women unemployed for more than two years increased substantially, from 10.7% in 2020-21 to 16.3% in 2023-24. The rise in long-term unemployment among women can be attributed to several factors. During the pandemic, many women, particularly those in caregiving roles, were disproportionately affected by job losses, leading to longer unemployment spells. Additionally, gendered labour market segregation – where women are often concentrated in sectors like retail, hospitality, and education – may contribute to extended job search times, especially since these sectors were hit hardest by the pandemic.

Among younger individuals (15-29 years), the data reveals a concerning trend. While the proportion of youth unemployed for less than or equal to 6 months decreased between 2020-21 and 2023-24 (from 14.7% to 11.8%), there was a significant increase in the length of unemployment lasting more than one year. Specifically, the percentage of young people unemployed for 1-2 years increased from 23.% to 32.1%. A similar upward shift is observed in both the 2-3 years and over 3 years categories.

This shift reflects the growing challenges faced by young job seekers in an increasingly competitive and complex job market. The youth labour market is heavily influenced by factors such as educational attainment, skill gaps, and the availability of entry-level positions. The rise in long-term unemployment among young people can be attributed to several key factors: slower recovery of the job market post-pandemic, mismatched skills and job requirements, and heightened competition for limited opportunities. Moreover, technological advancements like automation and digitalisation have exacerbated the issue.

Evolving industry demands

For middle-aged individuals in the 30-45 age group, the data reveals significant changes in short-term and long-term unemployment patterns. In 2020-21, this group had the highest proportion of individuals unemployed for 1-2 years (25.4%), and 23.2% were unemployed for 2-3 years. By 2023-24, long-term unemployment became even more pronounced, with 41.4% now unemployed for more than 3 years. This shift is driven by the transformation of industries and the growing demand for advanced, technology-driven skills. Middle-aged workers, while experienced, often find their qualifications outdated. Family responsibilities may also limit their ability to pursue retraining or relocate, compounding their challenges.

Older workers encounter significant barriers to re-entering the workforce. While the percentage of individuals (aged 46-60) unemployed for less than 6 months decreased from 20.1% in 2020-21 to 17.3% in 2023-24, long-term unemployment in both the 1-2 year and 2-3 year categories remained significant. Older workers face unique challenges when re-entering the workforce, including age discrimination, declining industry relevance, and a lack of modern digital skills, all of which make it more difficult to secure employment. For individuals aged 60 and above, the situation is even more challenging and severe. The percentage of this group unemployed for over 3 years increased sharply from 22.6% in 2020-21 to 47% in 2023-24.

The data from 2020-21 and 2023-24 reveal a complex and evolving unemployment landscape, with significant shifts across gender, age, and the duration of unemployment. Long-term unemployment is rising across all demographic groups, highlighting the need for policies that support skill development, reduce labour market barriers, and create greater employment opportunities for workers at all stages of their careers. There is another factor that needs to be accounted for, where some sections of the employable youth are looking forward to maintaining life-work balance rather than going all out to grab and slog for whatever employment opportunities are available. This phenomenon will potentially leave such youth unemployed for longer periods.

As economies continue to recover and adapt to new technological realities, it is essential to provide targeted support for the most vulnerable groups in the labour market, including youth, women, middle-aged workers, and older workers. By focusing on reskilling, enhancing job market accessibility, and addressing specific demographic challenges, policymakers can help foster a more inclusive, resilient, and sustainable labour market for all.

Palash is fellow at National Council of Applied Economic Research, New Delhi; Wankhar is a retired Government of India officer) Disclaimer: The views expressed above are the author’s own. They do not necessarily reflect the views of DH.

Intimate Partner Violence and Women’s Economic Empowerment Evidence from Indian States

Domestic violence is a global phenomenon. We study the interplay of determinants of a woman’s risk of facing intimate partner violence (IPV) for the case of India—using information from up to 235 thousand female survey respondents and exploiting state-level variation in institutions, law enforcement and attitudes. Unless in paid and formal employment, a woman’s economic activity is associated with a higher risk of IPV. However, household and other characteristics, such as higher agency within the household, higher education of the husband, lower social acceptance of IPV, and normalization of reporting incidences of violence counter this association. At the state level, the presence of more female leaders, better reporting infrastructure for victims of IPV, and higher charge-sheeting rates are associated with a lower risk of IPV

How origin country corruption shapes immigrants’ political trust

The question of whether immigrants from countries with low levels of political trust bring those attitudes with them to their host societies has long been debated. This column leverages survey data from 38 countries, and exploits variation across countries, cohorts, and survey rounds, to show that immigrants exposed to institutional corruption during early adulthood (ages 18-25) before migrating exhibit higher levels of political trust in their destination country. This effect is confined to national political institutions and does not extend to supra-national bodies or interpersonal trust. Elevated trust persists over time, translating into greater electoral participation and political engagement.

The integration of immigrants into host societies remains a recurring concern for both policymakers and the public. A common narrative holds that immigrants from countries with weak institutions and high corruption bring these norms with them, eroding trust in political systems. This fear has shaped debates on immigration policies, with some advocating for restrictions to protect institutional integrity (Borjas 2014, Clemens and Pritchett 2019).  What if the story is more complex? Could exposure to corruption in home countries actually foster greater trust in host-country institutions?

In a recent study (Aksoy et al. 2024), we examine this question using data from eight waves of the European Social Survey (2004–2018), which includes a range of questions on political trust in the destination country. Our analysis covers 38 European countries. To measure immigrants’ exposure to corruption in their home countries, we use data from the Varieties of Democracy (V-DEM) project.

Our empirical strategy leverages variation within origin countries, within host countries, and across age cohorts. Simply put, we compare immigrants with similar observable characteristics, originating from the same country, living in the same host country, but exposed to differing levels of corruption in their home countries prior to migration. This is achieved by incorporating fixed effects for origin-host country pairs, origin country by year, host country by year, and age cohorts.

Main results

We find that immigrants’ exposure to corruption in early adulthood (i.e. at ages 18-25) in their origin country is an important determinant of the trust they place in the parliaments, political parties and politicians of their country of immigration. Strikingly, exposure to more corruption in the origin country affects trust in the political institutions of the host country positively, not negatively (Figure 1). An immigrant from a highly corrupt environment is six percentage points more likely to trust these institutions compared to someone from a less corrupt country – a significant difference, given that average trust levels hover around 61%.  Importantly, this trust is specific to national political institutions. Immigrants’ broader social trust or trust in supranational organisations, such as the United Nations, remains unaffected. Additionally, the impact of corruption exposure persists over time, indicating that early-life experiences shape enduring attitudes (consistent with Eichengreen et al. 2021 and 2024).

Figure 1 Impact of corruption exposure on political trust

Figure note:  This figure presents OLS estimates of the baseline model, where the independent variable is Corruption Exposure18-25, corresponding to the cumulative V-DEM Corruption Index in the country of origin when individuals are between ages 18 and 25. Each line represents a separate regression with a different outcome variable. The Political Trust Index is defined as the average trust in parliament, political parties, and politicians. The regressions include a comprehensive set of fixed effect, control for demographic and labour market characteristics (see Table 1 in the paper for details). Whiskers corresponds to two-way clustered standard errors by host and origin country.
Data Sources: European Social Survey and V-DEM.

Media consumption as a mediating factor

Interestingly, this increase in trust is not uniform and is strongly influenced by media exposure in the host country. Immigrants who consume more host-country media – such as newspapers, television, or online sources – tend to develop a more nuanced understanding of institutional quality. This additional information reduces reliance on their home-country experiences as a reference point, tempering their levels of trust. Specifically, immigrants with high media consumption in the destination are likely more exposed to institutional shortcomings and political controversies in their host countries, diminishing the contrast with their previous experiences.

Political engagement and broader impacts

There is, in addition, a link between increased political trust and political engagement. Immigrants exposed to corruption in their home countries are more likely to vote or participate in political organisations in their host countries (Figure 2). This suggests that the heightened trust translates into tangible political involvement, further integrating such immigrants into the democratic fabric of their new societies.

Figure 2 Impact of corruption exposure on political behaviour

Note: This figure presents OLS estimates of the baseline model, where the independent variable is Corruption Exposure18-25, corresponding to the cumulative V-DEM Corruption Index in the country of origin when individuals are between ages 18 and 25. Each line represents a separate regression with a different outcome variable. The Political Action Index refers to the average of the following outcomes: voting in the last national election (coded as “1” if individuals voted and “0” otherwise), working for a political party (coded as “1” if individuals worked for a political party and “0” otherwise), and contacting a politician or government official in the last 12 months (coded as “1” if individuals contacted and “0” otherwise). The regressions include a comprehensive set of fixed effects, control for demographic and labour market characteristics (see Table 4 in the paper for details). Whiskers corresponds to two-way clustered standard errors by host and origin country. Data Sources: European Social Survey and V-DEM.

Political trust among immigrants vs natives

Interestingly, natives exposed to corruption during their formative years respond differently. While immigrants develop greater trust when encountering better institutions abroad, natives exposed to corruption exhibit lower trust in their own institutions. This divergence underscores the unique role that migration plays in shaping political trust through comparative experience. For second-generation immigrants, however, the patterns align more closely with those of natives, as their trust levels are shaped by host-country conditions rather than foreign reference points.

Why does this happen? 

We interpret this result through the ‘reference point hypothesis’, which draws on insights from Kahneman and Tversky’s prospect theory (Kahneman and Tversky 1979). Immigrants from corrupt regimes form low expectations about political institutions, based on their formative experiences. On encountering stronger institutions in their host countries, they perceive these institutions more positively relative to their previous experiences.

The effect we identify is amplified when the gap between home and host countries is wider. Immigrants from countries with weaker democratic practices or lower income levels display notably higher trust in host-country institutions compared to those from countries with more similar conditions. This suggests that significant contrasts between home and host environments play a critical role in shaping immigrants’ perceptions.

Concluding remarks

Political trust is essential for effective governance and societal stability. Trust in institutions encourages compliance with public policies, political engagement, and overall integration into civic life. Distrust, on the other hand, can lead to disengagement, civil unrest and support for populist movements (Levi and Stoker 2000, Papaioannou 2013). Fostering trust among immigrant populations is thus critical to achieving social cohesion and democratic resilience.

Our findings challenge common fears about immigrants from corrupt countries eroding trust in political systems. In fact, such immigrants often show higher confidence in host-country institutions. Policymakers can build on this trust by promoting active democratic engagement through political education and media literacy initiatives, helping immigrants contribute more effectively to their new communities.

Empirical Evidence of Crime against Women in Assam

The article focuses on different types of crimes against women in Assam. The objective is to prospectively analyse the factors leading to major crimes in different districts of the state. The recent report on Crime in India Report, 2021 the National Crime Records Bureau highlights that Assam has reported the highest rate of crimes against women in India for the last five consecutive years. The trend of increasing crimes against women in Assam is also pointed out in the gender-based violence information in the National Family Health Survey-5, 2019–20. Among all, domestic violence dominates the total crime against women in the state. The causal relationship between violence against women and other sets of variables indicates that empowerment and confidence in one’s own rights can result in lower crime against women and an improved standard of living.

Crime against women is one of the most significant hindrances to the achievement of equality, development, and peace. No woman in the world is secure against violence (Nussbaum 2005). According to the United Nations Declaration on the Elimination of Violence against Women (1993), “violence against women” is any act of gender-based violence that results in or is likely to result in physical, sexual, or psychological harm or suffering to women, including threats of such acts, coercion, or arbitrary deprivation of liberty, whether occurring in public or private life. This definition clearly points out that non-violent practices also form violence as these impact women’s capabilities to the same or even deeper extent as actual bodily violence. The World Health Organization (WHO) highlights violence against women as a human rights issue and a significant threat to women’s health and well-being. 

In India, violence against women begins even before birth. As Nobel Laureate Amartya Sen mentioned the concept of “missing women” to highlight the gender bias in mortality, which results in a huge deficit of women in substantial parts of Asia and Africa. In India, gender-based violence is deeply institutionalised, which develops under the veil of religion, culture, and social norms (Johnson et al 2007). As Patel (2015) echoed, the fear of crime being an alarming issue among women across India, influences vulnerability due to increasing crime and having a dignified life. The patriarchal social structure and cultural roles of women and men root violence against women in multiple forms (Russo and Pirlott 2006). Deeply rooted in a male-dominated society, violence against women is often primarily associated with their social status and their communal, ethnic, and caste identities.

The article focuses on different types of crimes against women in Assam. The primary objective is to prospectively analyse the factors leading to the major crimes in different districts of the state. It also addresses the question of the reporting of crimes and the actual incidence of crimes in the districts of Assam. Assam, being one of the remotest and landlocked northeastern states of the country, needs special focus for any issues related to development. Assam has always been assumed to be the gateway to northeast India. The present government’s initiatives to improve the connectivity infrastructure in the entire northeast have opened various opportunities for development. However, the recent Crime in India Report, 2021 by the National Crime Records Bureau (NCRB) highlights that Assam has reported the highest rate of crimes against women in India for the last five consecutive years. The trend of increasing crimes against women in Assam is also pointed out in the gender-based violence information in the National Family Health Survey-5 (NFHS), 2019–20.

The article is organised as follows: Following the introduction, we first provide a summary of the data sources and methodology. We then on to explains the results by analysing how the trend of crime against women changed over time from 2011 to 2021 in Assam and comparing it to India. The further section presents the crimes at the district level in terms of both reporting and actual incidence; which explains the determinants of the incidence of violence suffered by women in Assam. Finally, the article’s primary findings are summarised in Section 6, which also looks at how important these findings are for understanding the element that results in the rising rate of crime and violence against women in Assam.

Data Source and Methodology

The primary database for the study are the NCRB and NFHS. The NCRB report is the only and most comprehensive databank available to the Government of India on the subject. The data is collected by the State Crime Records Bureau (SCRB) from the District Crime Records Bureau (DCRB) and sent to the NCRB every year. The statistical information in the report contains cognisable crimes reported in police stations during the reference year. The data on major crimes against women in Assam in the NCRB report include dowry, rape, human trafficking, kidnapping and abduction of women, insults to modesty, and domestic violence. The NFHS provides information on population, health, and nutrition for India and each state and union territory. It also provides district-level estimates for many important indicators. In the present study, violence against women is analysed based on the NFHS data. Violence against women includes sexual and physical violence.

Crime against Women in Assam

Despite the high underreporting rate of crime against women, Mukherjee et al (2001) highlighted that crime reporting is still useful for broad groupings of regions in terms of crime rate. They also mentioned that underreporting of crime varies not only across time and space but also across types of crime against women. Therefore, although the crime reporting data is not sufficient to set a narrative about the region, it definitely provides important source information at the policy level. The total crime rate for 2021, computed as the total number of crimes recorded per 1 lakh persons, ranges from 5 to 169 among the states and union territories of India. Figure 1 highlights the rate of crime against women in different states of India. It is clearly observed that the rate of crime against women is the highest in Assam (168.872), followed by Odisha (138.157) and Haryana (120.188) among all the states and Union Territories in India. According to the NCRB report, Assam is the state with the highest rate of crime against women in India for the fifth consecutive year.

Figure1: Rate of Crime against Women in India at the State Level?

Source: NCRB Report, 2021

One significant reason for the high numbers in the state could be improved reporting of such crimes. There is often a gap between reported crime rates and the actual incidence, particularly in cases involving crimes against women. Velasco et al. (2021), in their study on Mexico, highlighted that the increase in reported crimes against women can be attributed to new trends in women’s empowerment. This includes the expansion of social programs, a rise in the number of women serving as heads of households, the establishment of specialized prosecutors for crimes against women, and reduced procedural barriers due to reforms in the criminal justice system, transitioning from an inquisitorial to an accusatory model.

Figure 2(a)

Source: NCRB data between 2011-2021, compiled by authors. 

Considering the six major crimes against women, which are rape, dowry, human trafficking, kidnapping and abduction, insult to modesty, and domestic violence, the table 1 shows the trend of major crimes against women in Assam over the period from 2011 to 2021. The trend shows a steady increase from a crime rate of 75 in 2011 to 147 in 2021. According to the NCRB’s Crime in India Report, 2021, the majority of cases of crime against women in Assam were registered under “Cruelty by Husband or His Relatives” followed by “Kidnapping and Abduction of Women.” The rate of total crime against women (Indian Penal Code and State Level Laws) in 2021 is 168.3, which is the highest among all states and UTs; and the charge sheet rate in 2021 will be 52.9.

Figure 2(b)

Source: NCRB data between 2011-2021, compiled by authors. 

The figure 2 (b) highlights the trend of dowry-related crimes in Assam, which according to the NCRB data are incidences of dowry and dowry death. There has been a sharp drop in the rate of dowry cases in 2020 (3.4) as compared to 2019 (9), which again increased to 4.5 in 2021. According to the NCRB’s Crime in India Report, 2021, the number of dowry cases registered under the Dowry Prohibition Act, 1961 in Assam is 582, which is the fifth highest. And the number of dowry death cases filed under Section 304B of the Indian Penal Code (IPC) is 198, which is the ninth highest among all the states and UTs. 

Figure 2(c)

Source: NCRB data between 2011-2021, compiled by authors. 

In figure 2c, it can be observed that from 2020 to 2021, there has been an increasing growth in the crime rate of rape. The rate of rape cases, including rape (Section 376), attempt to commit rape (Section 376/511), and murder with rape or gang rape, has increased from 12.6 in 2020 to 13.4 in 2021. According to the NCRB’s Crime in India Report, 2021, the rate of rape cases reported under Section 376 IPC in Assam is 10.0 (per one lakh of the population) for 2021, which is the fourth highest after Rajasthan (16.4), Haryana (12.3), and Arunachal Pradesh (11.1%) among all states. And the rate of cases under “Attempt to Commit Rape” (Section 376/511 IPC) is 3.3, which is the highest among all states and UTs.

Figure 2 (d) 

Source: NCRB data between 2011-2021, compiled by authors. 

In Figure 2 (d), it is highlighted that there has been a sharp decline in the rate of human trafficking cases in 2020, followed by an increase in 2021. In support of the abovementioned statement, using the NCRB data, it can be observed that the rate of human trafficking cases filed under Sections 370 and 370A has come down to 0.4 in 2020 from 0.9 in 2019 but increased to 0.5 in 2021. However, the rate has been steady from 2017 to 2019 (around 0.9). According to the NCRB’s Crime in India Report, 2021, the rate of human trafficking cases (per lakh population) under Section 370 in Assam is 0.4, which is the third highest after Goa (0.7), Telangana (0.3), and Maharashtra (0.2).

Figure 2 (e)

Source: NCRB data between 2011-2021, compiled by authors. 

In Figure 2 (e), it is highlighted that there has been a sharp drop in the rate of kidnapping and abduction cases in 2020 compared to the previous year, but it has gradually increased. In support of the abovementioned statement, using the NCRB data, it can be observed that the rate of kidnapping and abduction has come down to 31.7 in 2020 from 41.9 in 2019 but increased to 33.6. However, the rate has been increasing from 2017 to 2019, followed by a drop in 2020, but it has again risen in 2021. According to the NCRB’s Crime in India Report 2021, the rate of abduction and kidnapping of women in total (per lakh population) in Assam is 33.3, which is the highest among all states and second highest only after Delhi.

Figure 2 (f)

Source: NCRB data between 2011-2021, compiled by authors. 

In Figure 2 (f), it is highlighted that there has been a decline in the rate of “Insult to Modesty” cases in 2021 compared to 2020. In support of the abovementioned statement, using the NCRB data, it can be observed that the rate of “Insult to Modesty” cases has come down to 27.9 in 2020 from 29.7 in 2019 and declined further to 27.4 in 2021. However, the rate has been increasing from 2017 to 2019, followed by a drop from 2019 to 2020. According to the NCRB’s Crime in India Report 2021, the rate of “Insult to Modesty” (per lakh population) in Assam is 1.1, which is quite low compared to other states and UTs.

Figure 2 (g)

Source: NCRB data between 2011-2021, compiled by authors. 

From Figure 2 (g), it can be observed that from 2020 to 2021, there has been a growth in the rate of domestic violence. The rate has been increasing, with a drop in 2020 (67.4). The rate of domestic violence, including cases of cruelty by a husband or his relatives (Section 498A) and the Protection of Women from Domestic Violence Act 2005, has increased from 67.4 in 2020 to 76 in 2021. According to the NCRB’s Crime in India Report 2021, for the rate of cases of cruelty by a husband or his relatives under Section 498A, Assam has the highest among all states and UTs.

Crime across Districts

The distribution of districts in Assam as per different crime rates is highlighted in Figure 3. The figure clearly shows that domestic violence dominates the total crime against women in the state. According to the NCRB data for 2021, Dhubri district has the highest number of total reported crimes against women, followed by Morigaon and Guwahati city. However, the rate of domestic violence is highest in Morigaon district, followed by Dhubri. Since the NCRB compiles only the reported crimes against women, a higher rate of domestic violence may indicate the empowerment of women. In the first 10 districts with the highest rate of total crime against women, there is a significant gap in the rate of domestic violence and other types of crime. However, towards the lower end of the total crime rates, there is not much difference in the different types of crimes in the districts. The districts with a lower crime rate for women consist of hilly, remote, and mostly tribal-dominated districts. In some exceptional districts, like South Solamar, there is a huge difference in domestic violence and other crime rates. In Karimganj, too, the rate of domestic violence is exceptionally high as compared to the other reported crimes. Since Figure 3 only shows the reported crimes, this also indicates that, due to the remoteness and lack of empowerment, women are not reporting crimes in these regions.

Apart from domestic violence, insult to modesty and kidnapping and abduction are also two of the most significant crimes in the districts of Assam. Insult to modesty is highest in Barpeta district, and kidnapping and abduction are highest in Guwahati city. Rape and related crimes are also significantly contributing to the total crime rate in different districts. Hailakandi has the highest rate of rape and related crimes, followed by Dhubri.

Figure 3: District-wise Crime against Women Reported in Assam (Crime Rate) 

Source: NCRB report 2021

Figure 4: District-wise Percentage of Violence Against Women in Assam

Source: National Family Health Survey (2019–2021)

Against the reported crime rate of the NCRB data, National Family Health Survey (2019–2021) data also provide data on some indicators of violence against women. Figue 4 highlights the percentage of sexual and physical violence against women in different districts of Assam. The difference between NCRB and NFHS is that the first is reported, and the second is the real occurrence of crime against women, which indicates that districts with a high report and a lower occurrence of crime against women indicate better law and order for women and empowerment of women in those districts. The figure shows that Hilakandi district tops the list, followed by Karimganj and Cachar. Both figures 3 and 4 mostly follow the same or close to the same ranking, except for some districts. In Kamrup metropolitan District, the occurrence of crime is very low as compared to the crime reported in Guwahati city. Darrang district also has a high report rate and a lower occurrence of crime against women.

Vulnerability due to Different Forms of Violence against Women in Assam: Factors Determining Violence 

This section discusses the model determining the factors of violence against women in Assam. A simple regression model is used to highlight the factors determining violence against women in Assam. One limitation of the model is that it considers only married women in the state. Here, the dependent variable is the total violence against women, which is the sum of sexual and physical violence. The set of independent variables consists of the highest level of education of the women, the highest level of education of the husband, the work status of the women, whether the husband drinks alcohol or not, religion, caste, whether urban or rural area, autonomy over some amount of household income, bank account, and owning any property alone or jointly.

While finding the determinants of violence against women, one needs to see whether they are reported at a police station or in front of the investigator. The women need to be brave enough to disclose the facts about their own vulnerabilities, considering stereotypes and norms in our society. This is clearly reflected in the model as well. It is expected that a higher level of education must have resulted in a lower rate of violence among women, but according to the model, women with a higher education level have significantly higher chances of suffering either sexual or physical violence. This actually indicates that a higher level of education makes women more empowered to report the violence they have suffered. Further to this, a lack of education makes women unaware of their rights and tolerant of the violence they suffer. Silence remains a prevalent community response to violence against women, and not only do the victims contribute to this silence but also those who know about the violence and choose to be silent and passive (Jenkins 1996). This is an important issue because public attitudes of indifference or passivity can help to maintain a climate of social tolerance (Biden 1993).

Another significant factor leading to higher-level violence against women is work status. Ideally, working women should have lower chances of facing physical or sexual violence. However, according to the model, working women suffer a scientifically high rate of violence. This interpretation is also biased due to the level of confidence and empowerment among the working women; the reporting rate of their violence suffered is higher as compared to the women not working. Mukherjee et al (2001) also observed that working women have probably greater exposure to the risk of violence outside the home. However, in the present model, the explanation for the high rate of violence suffered by working women is highly related to their exposure to the outside world and their empowerment as compared to those not working. Gracia and Herrero (2007) are also of the view that in order to lower social tolerance and create an environment of social responsibility towards domestic violence, public awareness and education are needed, which will also address the condition of mistrust between people and diminish the social control of concentrated disadvantage and disorder.

Table 1: Model of Determinants of Total Violence against Women in Assam

Notes: ***, **, and * are significant at 1, 5, and 10 percent. ® is the reference category.
Source: Author’s calculation based on the NFHS-5 unit-level data.

Further to this, partners’ alcohol consumption has a significantly higher impact on violence against women. This supports the previous study of Luca, Owens, and Sharma (2015), which found that prohibition on alcohol drinking behaviour is associated with a statistically significant higher reduction in the rates of cruelty by husbands and sexual harassment. Among the religion groups, Muslims have significantly higher chances of facing any kind of violence against women as compared to the Hindu religion.

Conclusions

Crime and/or violence against women, being the most important factor in assessing women’s well-being and status, should be considered in analysing the overall development of a society. In order to reduce crime against women, the first and foremost requirement is proper reporting of such crimes. Assam is the top state in India in terms of crime against women. Within the state, in Kamrup metropolitan district, which vastly is Guwahati city, violence actually identified (based on Graph 4) is lowed but reported to be very high (based on Figure 3). This may indicate comparatively higher empowerment of women as compared to other districts of the state. However, districts like Dhubri, Hailakandi, Morigaon, and Barpeta are showing a high rate of crime. The causal relationship between violence against women and other sets of variables also indicates that empowerment and confidence in one’s own rights can result in lower crime against women and an improved standard of living. As model results suggest, at the policy level, prevention of alcohol drinking and focusing on education and providing earning employment can be expected to create an environment of lower social tolerance and collective responsibility towards reducing domestic violence. The development and propagation of violent behaviour in general and specifically towards women are, in most cases, interlinked with cultural factors. In a stereotyped family, women are raised with a persistent attitude of being weak and in need of physical, social, and economic protection, which leads them to be exploited at almost every stage of their lives.

This article was published in EPW’s Vol. 59, Issue No. 51 (21 Dec, 2024)

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