Afghanistan Gender Monitoring Survey Baseline Report1 FEBRUARY 2023 1 The AGMS interviews were conducted in September and October 2022. As such, this baseline survey provides a reference point on the status of women just prior to the introduction, in December 2022, of new restrictions on their work in government ministries and in non-governmental organizations. ©2023 The World Bank 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org The Afghanistan Gender Monitoring Survey (AGMS) is part of Afghanistan Futures—the World Bank’s program of research, monitoring, and analytical reports on the state of the Afghan economy and society. Afghanistan Futures seeks to inform the international policy dialogue as the international community assesses how it can support the people of Afghanistan. This AGMS Baseline Report joins the monthly Economic Monitor, regular surveys on private sector, household welfare and gender, and sectoral reports that inform the Afghanistan Development Update—a biannual flagship report. The AGMS Baseline Report was prepared by a technical team that included Sarah Haddock, Cesar Cancho, M. Virginia Ceretti, Chiara Pasquini, and Anais Dahmani-Scuitti. Survey collection was administered by a local survey firm. Sistemas Integrales supported the calculation of sampling weights. iv   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Contents Introduction 1 Highlights 2 Methodology 3 Sample 3 Questionnaire 5 Respondent Characteristics 7 Main Findings 8 1. Women’s Rights and Decision-Making Power 8 2. Mobility 11 3. Food Security 12 4. Women’s Work and Child Labor 14 5. Access to Services 16 6. Safety and Mental Health 18 Future Work 21 Annex 22 Comparative Statistics of “Alone” / “Not Alone” Groups 22 1   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Introduction T hrough various decrees from the Interim Taliban Administration (ITA), women and girls have been systematically excluded from public and political domains, and restricted in their freedom of expression, access to education, and some forms of employment. As the restrictions continue to mount, it is increasingly important to safely consult with women and girls on their needs and priorities. This report presents the main results of the Afghanistan Gender Monitoring Survey (AGMS), conducted by the World Bank. The AGMS is intended to provide a snapshot of women’s own perceptions of their situation and to bring the voices of Afghan women into data collection efforts to inform the humanitarian-development response. The AGMS interviews were conducted in September and October 2022. As such, the research findings do not reflect the situation in the country after the ITA announced its decision to bar women from working in government ministries and non-governmental organizations (NGOs) in December 2022. Nevertheless, the findings do capture the situation of women and girls following the bans on girls’ secondary and higher education and women’s mobility and clothing (Figure 1). A rapid follow-on survey with AGMS respondents will be fielded in March 2023 and additional rounds of the full AGMS will be conducted as regular follow-on to the semi-annual Afghanistan Welfare Monitoring Survey (AWMS), also carried out by the World Bank. This first round of data collection will provide an important baseline from which to assess the additional impacts of the December bans. The first round of the AGMS was conducted by phone and interviewed 3,825 women from across the country. The AGMS interviewed women from households included in the second round of the AWMS, hereafter referred to as “AWMS R2.”2 The AWMS is a nationally representative survey conducted with household heads over the phone and its second round took place between June and August 2022. At the end of the AWMS R2, the household head was asked for consent to conduct a separate survey with the “most knowledgeable female” in the household, hereafter referred to as “MKF.” Because of this selection method, the AGMS is nationally representative of MKFs at the household level, but not of all Afghan women. The AGMS complements other ongoing data collection efforts by (a) collecting nationally representative data primarily from women respondents and (b) generating data along specific domains of concern for Afghan girls and women that are not otherwise monitored, including rights and decision-making power, mobility and access to services and resources, wellbeing, and women’s work. Some outcomes cannot be compared with pre-ITA times (i.e., questions around women’s mobility, rights, and mental health, as these were purposively designed for this study), but, when possible, outcomes were compared to other data sources (i.e., Afghanistan Living Conditions Survey 2013–14, Income, Expenditure and Labor Force Survey 2019–20, and AWMS R2 [male perspective]). Lastly, the survey also tracked surveillance—that is, it assessed if respondents were alone during the survey or in the presence of other household members that could potentially have listened and/or influenced responses. 2 Reference to the first round of AWMS will be reported as “AWMS R1.” 2   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Figure 1: Timeline of Data Collection and Bans on Women Interim Taliban Administration Income, Expenditure and Afghanistan Welfare Monitoring Survey R1 Islamic Hijab Decree Afghanistan Gender Labor Force Survey October 2021-December 2021 May 2022 Monitoring Survey, October 2019-September 2020 (phone survey) Baseline (in person) September 2022-October 2022 Ban on Girls' Return (phone survey) to Secondary Ban on Girls' Secondary Education Education September 2021 March 2022 2019 2020 2021 2022 Income, Expenditure and Labor Force Survey Mahram Policy Bans on University June 2021-August 2021 December 2021 Education and (in person, incomplete) Women’s Work in Public and NGO Afghanistan Welfare Monitoring Survey R2 Sectors June 2022–August 2022 December 2022 (phone survey) Highlights • Afghan women are concerned about the future of their rights. Almost all women interviewed identified achieving human rights for women as a top priority for the future of the country and identified the right to education and the right to work as the most important rights for women. • Women report restrictions on mobility out of their dwellings, and the vast majority only leave their places of residence accompanied by a male relative. Women also have limited decision-making power within the household, even on matters like their own health. Despite these constraints, over half of women reported that they are still able to carry out the activities they normally conducted before the decrees that restricted their mobility and clothing. The biggest exceptions are their ability to participate in education/training and to engage in income-generating activities outside the home. • Households are most in need of food aid. Women confirmed the high levels of food insecurity reported by the World Bank and other international organizations, adding that there is a bias against women in the allocation of scarce food resources within the household in these times of crisis. • Findings on women’s income-generating activities are consistent with the AWMS R2 results, indicating that most working-age household members are supporting income-generating streams to navigate the crisis. Most working women are involved in household farming/livestock and/or family businesses, but activities seem to be of short-term, low-quality, and seasonal nature. • Access to public services for women remain available, as evidenced by a majority of women reporting effective access to health services, access to mobile phones, and access to identification (Tazkira). • Women however are experiencing large hidden tolls from the economic and social crises, including severe mental ill-health (depression and anxiety), and a large share of women report feeling unsafe at home, signaling that they are likely facing abuse within their households. Women themselves have accepting attitudes toward gender-based violence (GBV) and are often left without options to escape the violence or receive care. 3   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Methodology Sample The AGMS interviewed women from households included in the second round of the AWMS. The AWMS is a nationally representative survey conducted with household heads over the phone and its second round took place between June and August 2022. At the end of the AWMS R2, the household head was asked for consent to conduct a separate survey with the most knowledgeable woman in the household, defined as a female aged 14 and above who can answer questions about other household members and the household’s overall economic situation and wellbeing. If consent was given, the household head was asked to provide the name and contact information of the most knowledgeable female household member, or “MKF.” In 148 cases, the AWMS R2 respondent was a woman, identified as the female head of household, and she herself was automatically selected as the AGMS respondent. In all other cases enumerators spoke with the male household head to identify the appropriate female household member. The AGMS was conducted over the phone in September and October 2022 and reached 3,825 women. Out of the 5,800 households surveyed in the AWMS R2, 5,433 consented to be included in the AGMS. A pilot was conducted with 191 households out of the 5,433 to test the survey process and questionnaire—these surveys are not included in the final AGMS sample. The remaining 5,242 households constitute the sampling frame for the AGMS. A total of 3,825 phone surveys were successfully completed (Figure 2). A total of 1,417 interviews were not completed; the main reasons being Figure 2: AGMS Sample 5,800 AWMS R2 households 367 AWMS 5,433 AWMS R2 respondents did not HHs consented for call-back to consent to call-back the most knowledgeable woman 191 MKFs Remaining interviewed in 5,242 HHs AGMS pilot constitute AGMS sample 1,417 HH 3,825 MKFs interviews not successfully interviewed completed Note: AGMS = Afghanistan Gender Monitoring Survey; AWMS R2 = Afghanistan Welfare Monitoring Survey Round 2; HH = household; MKF = most knowledgeable female. 4   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt that the phone number was not working (51 percent of Table 1: Survey Outcomes non-completed surveys, n=727), the call was refused Status Unique case (17 percent of non-completed surveys, n=238), or that the call was not answered (15 percent of non- Completed 3,825 completed surveys, n=218). The full survey outcomes Completed but rejected by quality 11 are explained in Table 1. assurance process Incompleted 8 The AGMS is nationally representative and includes respondents from all 34 provinces of Afghanistan. Incompleted interview due to 110 Sampling weights were used on account that not all language issue AWMS R2 households consented to be contacted for Ineligible 2 the AGMS, and not all households that consented could be surveyed. Map 1 depicts the geographical Number not working or inactive 727 breakdown. Because of the selection method Number rang but the call dropped 53 followed, the survey is nationally representative Number rang but was not 218 of the MKFs at the household level, but not of all answered/number busy Afghan women. The adjustment of sampling weights reduced the biases of the AGMS sample, although the Refused 238 sample is still slightly less poor and more educated Rescheduled 45 than the sample from the Income, Expenditure and Labor Force Survey (IELFS) 2019–20, the last nationally Wrong number 5 representative official survey conducted in the Total 5,242 country that interviewed close to 18,000 households. Map 1: Number of Respondents by region Northeast North 475 492 East Central 643 West-central 1,075 West 335 301 South 301 Southwest 203 5   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt To assess how the final weighted estimates coming from the AGMS compared to those coming from the IELFS 2019–20, five variables that were collected in the IELFS and that could be mapped to the AGMS sample via the common telephone number were compared: urban/rural, welfare quintile, education level of the household head, share of women, and average age. This contrast analysis presents differences that are attributable to the composition of the sample, even after readjustment of the weight. In addition, a variable that was collected in the AGMS was compared to the same one collected in the IELFS 2019–20: household size. The results of these contrasts show that the AGMS sample initially had a similar urban–rural distribution as the whole IELFS 2019–20 sample, but is skewed slightly toward less poor and more educated household heads (Figure 3). In any event, the differences in welfare and education levels are not large enough to introduce crippling biases to the results and every category considered has a substantial representation. Figure 3: Contrast Analysis of IELFS 2019–20 and AGMS September–October 2022 Sociodemographic Variables 80 IELFS (2019-2020) AGMS (Sept–Oct 2022) 70 67.0 Share / Age / Household size 60 59.4 49.5 50 49.0 40 30 25.1 20.1 22.3 21.1 20.0 21.6 20.0 17.9 20 25.0 20.0 20.0 20.0 19.9 11.7 10.4 20.2 10 16.6 15.2 7.3 9.4 7.8 0 7.2 Urban share Poorest Quintile 2 Quintile 3 Quintile 4 Richest No formal education Primary schooling Secondary schooling Tertiary schooling Female Average age Members Location Household welfare Household head education Individual Household characteristics characteristics Source: Elaboration based on IELFS 2019-20 and AGMS. Questionnaire The questionnaire was designed to obtain information about women’s wellbeing, access to services, and a range of other outcomes relevant to their living conditions.3 The questionnaire contains sets of questions about employment, food security, household needs, and health that mirror the questions in the AWMS R2 to allow gender comparisons and triangulation. A subset of questions mirrors that of the AWMS R2 and allows for comparisons with that of their male counterparts in the same households (AWMS R2 respondents). The mobility, mental health, women’s rights, decision-making, safety, and child marriage modules were designed purposively for this study, and when possible, use questions that have been tested in other studies in Afghanistan. The survey also tracked surveillance: at the end of the survey, enumerators were asked to assess if the respondent conducted the survey alone or if she was in the presence of other household members who could potentially listen or influence responses; enumerators were also given the option to report they could not tell. Box 1 further describes methodology and outcome differences depending on whether the respondent was assessed to be alone or surveilled. 3 The questionnaire follows World Bank data privacy corporate policies. 6   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Box 1: Survey Surveillance At the end of the survey, enumerators were asked the following question: “Was anyone else present (other than the respondent) as you were conducting the survey?”. Answer options were: • No, I am sure the respondent was alone • There was someone with the respondent but could not tell who • There was one or more men listening • There was one or more women listening • There were both men and women listening • A man stepped in during the survey and answered the questions • Another woman stepped in during the survey and answered the questions • Cannot tell A respondent is considered alone only if the enumerator answered “No, I am sure the respondent was alone.” For all other times, she was considered being heard/influenced. In 56 percent of cases, the enumerator considered the respondent being alone. In the remaining 44 percent of cases, the respondent was considered being with someone: “Could not tell who” (17 percent); “one or more men listening” (13 percent); “one or more women listening” (5 percent); “both men and women listening” (5 percent); “a man stepped in and answered some questions” (2 percent); “a woman stepped in and answered some questions” (0.5 percent); enumerator could not tell if there was someone else (1.5 percent). Answering the survey while in the presence of someone else was more common among rural respondents, respondents who could not read or write, and Pashto-speaking respondents. After running comparative statistics, the narrative of results does not change across the two groups (“alone” / “not alone”), with differences in most cases of only a few percentage points. The annex to this report references where significant differences are found. While a more in-depth study would be needed to establish causality, it suggests that some women whose privacy was not guaranteed during the survey may have adjusted some of their answers. The questionnaire was designed by the World Bank and administered by a local survey firm. The survey was administered in Dari and Pashto, using a computer-assisted telephone interview questionnaire based on an Open Data Kit app. All enumerators were women, working remotely from within the country. Households were informed of the reason for their selection and the purpose of the survey. Before starting the survey, enumerators spoke with the household head to confirm the identification of the MKF and their permission to proceed. An additional consent was then sought from the female respondent. All completed interviews were compensated with a phone credit worth Af 150 (about US$1.7) upon completion of the survey. The average survey duration was 36 minutes. Only surveys that passed the quality assurance process were included in the final dataset.4 4 A quality assurance team performed audio audits to verify interview authenticity, check that questions were asked properly, and that refusals to participate were genuine. Feedback was given to enumerators to improve their performance. Once collected, data were checked for inconsistencies and text answers were recoded when applicable. 7   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Respondent Characteristics In close to two-thirds of cases, the MKF was the spouse of the household head (64 percent).5 In other cases, she was the daughter (17 percent) or daughter-in-law (9 percent). In only 4 percent of cases, the MKF was the household head herself (Figure 4). The average respondent was 31 years old (with a median of 30) and 83 percent were married. Only 36 percent of respondents were literate, defined as able to read and write, with a higher concentration of those literate in urban areas compared to rural (51 percent versus 29 percent). Figure 4: MKF’s Relation to Household Head 80% 64% 60% Respondents (%) 40% 20% 17% 9% 4% 3% 2% 1% 1% 0% Self Spouse Child Daughter-in-law Mother Sister Sister-in-law Other relative The average AGMS household had 9.3 members (9.9 in rural areas and 8 in urban areas). A significant share, 17 percent, of the households reported having to flee/forced to displace from their place of origin in the past 12 months. The main reasons cited for displacement included armed conflict (86 percent), natural or human-made disasters (7 percent), and generalized violence (5 percent). In addition, 25 percent of households had at least one person who had to relocate within the past 12 months; the main motivators for relocation being to search for work or economic opportunities (52 percent) and find cheaper or free housing (22 percent). Rural populations tended to be more affected by forced displacement (18 percent versus 13 percent), while relocation was slightly more common for urban populations (27 percent versus 23 percent). Fifteen percent of households reported having at least one member with a form of disability, with the most common being difficulty walking or climbing steps (compared to 24 percent of households that reported having one member with disability in IELFS 2019–20, though using a different set of screening questions).6 5 In AWMS R2, out of around 24,000 female household members, 47 percent were daughters of the head of household, 23 percent were the spouse, 6 percent granddaughters, 6 percent daughters-in-law, 6 percent sisters-in-law, and 6 percent mothers-in-law. Only 1 percent of women were the head of household. The difference between the AWMS R2 female population and AGMS is due to the fact that MKFs were not chosen randomly, as AWMS R2 respondents were more likely to identify the spouse as the most knowledgeable female in the household. 6 Following World Bank definition, a person with disability would have moderate or severe functional limitation in one of the tested domains (vision, hearing, walking, self-care, memory/concentration, communicating). 8   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Main Findings 1. Women’s Rights and Decision-Making Power A resounding majority of respondents—96 percent—strongly agreed that achieving human rights for women is a top priority for the future of the country. Women were asked the extent to which they agreed with the following statement, “I believe achieving human rights for women is among the top priorities for the future of my country.” Human rights were defined to the respondents as: “When we talk about human rights, we refer to rights inherent to all human beings, regardless of race, sex, nationality, ethnicity, language, religion, or any other status. Human rights include the right to life and liberty, freedom from slavery and torture, freedom to express opinion, the right to work and education, the right to freely decide who to marry with.” The share of women expressing strong agreement was the same across urban and rural. Amidst current restrictions on women and girls, the rights to education and work were the most cited among respondents. Women were asked which rights were most important to them (Figure 5). Without being prompted by enumerators and allowing for multiple responses, women prioritized the right to education (78 percent), the right to work and earn money (50 percent), the right to be free in public without harassment (31 percent), the Figure 5: Women’s Rights by Priority Right to education 81% 77% Right to work and earn money 56% 47% To be free in public/no harassment 40% 27% Right to choose a husband 22% 21% Right to participate in government 17% 10% Urban Rural Right not to be beaten (by family) 9% 8% Freedom to choose how to dress 9% 6% Right to travel without mahram 3% 2% Access to health care and services 1% 2% None of these 1% 2% Other 1% 1% Freedom to use internet 2% 1% Right to divorce or not to marry 1% 1% 0% 20% 40% 60% 80% 100% Respondents (%) 9   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt right to choose a husband (21 percent), and the right to participate in government (12 percent). Responses were mostly consistent across urban and rural respondents, but urban women were slightly more concerned with women’s right to education, work, access to public space, and participation in government. Over half of women (60 percent) reported that, in the Fall of 2022, they are still able to carry out the activities they normally conducted before the May 2022 decrees. Note that these results precede the December 2022 ban on women working in public and NGO sectors. Women were asked about any activities they were doing six months ago that they can no longer do, either because they are no longer permitted to or because they feel unsafe doing so. Sixty percent said that they can still do what they want (58 percent urban and 61 percent rural). The two activities that women most reported they can no longer do were participate in education/training (cited by 11 percent of respondents) and engage in income-generating activities outside the home (10 percent of respondents). Fewer than 10 percent of women reported no longer being able to participate in social activities, savings groups, or in household farming (Figure 6). Figure 6: Women’s Participation in Activities I can still do what I want 60% Education and training 11% Income-generating activities outside the home 10% Social activities 9% I can no longer do any of these activities 8% Household farming, planting, harvesting 7% Don't know 5% Savings groups 5% 0% 10% 20% 30% 40% 50% 60% 70% Respondents (%) Seventy percent reported that women in their household wear a burka when outside the home. Among those women reporting wearing burka (Figure 7), 37 percent said that they do so due to new rules advising and/or enforcing women’s use of burka. The new restrictions on dress code appear to have a bigger effect on urban women, 46 percent of whom cited the new rules as the reason for wearing burka, compared to 34 percent of rural women. The majority of those who reported wearing burka—58 percent—said that women have always worn a burka. This share was higher, 61 percent, among rural respondents, compared to 49 percent among urban respondents. Women held divided opinions on whether child marriage is increasing in their communities. Early marriage, or child marriage, was defined as the marriage or union between two people in which one or both parties are younger than 18 years of age.7 Respondents were asked whether they perceived any shifts in their communities (“In the last 6 months, have you perceived a shift in your community towards early marriage (including exchange marriage) for young women/girls?”) and responses were split fairly evenly: 48 percent of women reported that there were no significant changes (with more urban women believing so), 24 percent reported that they thought early marriage was decreasing, and 23 percent reported feeling that early marriage was increasing. Only 2 percent of women indicated that a girl in the household had married in the past six months. The girl’s average age at marriage was 15 (with a range from 12 to 17 years) and in over 87 percent of cases, the girl moved out of the house when she married. 7 The AGMS included a measure of the descriptive norm (how women think people are behaving). Future rounds of data collection may include a measure of the injunctive norm (how women think other people feel about child marriage) and the respondent’s own attitudes toward child marriage. 10   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Figure 7: Use of Burka and Reasons for their Use 100% All Urban Rural 80% 77% 70% Respondents (%) 61% 60% 56% 58% 49% 46% 40% 37% 34% 20% 4% 4% 4% 0% Wear burka Most women have There are new rules Other always worn burka advising and/or enforcing burka for women For those wearing burka Women have limited decision-making power within Figure 8: Women’s Participation in Intra- the household, even on matters like their own Household Decision-Making health, and they appear to be losing economic agency over time. AGMS respondents were asked a 60% series of questions adopted from the Demographic and Health Survey (DHS) 2015 to gauge their intra- 52% 50% 49% household bargaining power: “Who usually decides 47% how the money you earn will be used: you, your spouse, or you and your spouse jointly?”; “Who usually Respondents ages 15 to 49 (%) 40% makes decisions about health care for yourself: you, your spouse, you and your spouse jointly, or someone else?”; “Who usually makes decisions about making 30% major household purchases: you, your spouse, you and your spouse jointly, or someone else?”. 20% The questions were asked to all AGMS respondents, but analysis is restricted to married and/or employed 10% women ages 15 to 49 to improve comparability with the DHS. Only 52 percent of employed women interviewed in the AGMS reported participating in 0 Own earnings Own health Major decisions concerning their own earnings. Women’s 8 (employed (married household women only) women only) purchases self-reported participation in decision-making on (married women only) their own health and on major household purchases is at 49 percent and 47 percent, respectively9 (Figure 8). 8 The 2015 DHS questioned employed women about their self-reported decision-making regarding own earnings, in which 75 percent reported participating in decisions related to their own earnings. The sample is not strictly comparable to employed women in the AGMS. 9 The 2015 DHS questioned married women about their self-reported decision-making regarding own health and household purchases, in which 48 percent and 42 percent made decisions on their own health and household purchases, respectively. The sample is not strictly comparable to married women in the AGMS. 11   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt 2. Mobility Women’s mobility remains very limited. Women reported that they leave their compound/dwelling on average 2.3 days out of the week and that they only leave their neighborhood 4.1 days out of the month. Urban women are slightly more mobile outside their neighborhoods; they report leaving 5.3 days out of the month whereas rural women only leave 3.6 days in the month. It is worth noting that AGMS respondents, being the “most knowledgeable female,” may be more mobile than other women in their households. On average, women reported going to the local market once in the past month (Figure 9). Women’s low mobility captured in the AGMS is consistent with information collected in the ALCS from 2013–2014. Back then, all married women (though based on slightly different groups) reported leaving their dwellings only 1.9 days per week (7.8 per month), with minimal differences between urban and rural areas. Figure 9: Women’s Average Mobility (days) 6 5.3 All Urban Rural 5 4.1 4 Number of days 3.6 3 2.6 2.3 2.2 2 1.4 1 0.9 0.6 0 Did you leave your Did you leave your Did you go to your compound/dwelling? community/neighborhood? local market? (last 7 days) (last 30 days) (last 30 days) Women are most often accompanied by a male Figure 10: Women Accompanied by a Male relative when they leave their compound/dwelling. Relative When Leaving Home Seventy percent of women said they are usually or 80% always accompanied by another person when they leave their compound/dwelling (Figure 10). Eleven 70% percent of women said that they are sometimes accompanied (15 percent of urban women and 9 60% percent of rural women), while another 11 percent of women said that they are never accompanied Respondents (%) (16 percent of urban women and 9 percent of rural women). 40% Women are most often accompanied by their spouse (35 percent) or children under 12 (36 percent), (Figure 11). In urban areas, women are also more 20% accompanied by other adult female household 11% 11% 7% members and teenage girls after spouse and children under 12. 1% 0% Never Rarely Sometimes Always Not applicable, does not go out 12   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Figure 11: Person Accompanying Women When Leaving Home 40% 36% 35% 30% Respondents (%) 20% 20% 16% 12% 11% 10% 4% 2% 1% 0% Children Spouse Other female Teenage Teenage Other male Female Female Male relative under 12 household relative relative household relative non-relative outside of member (boy) (girl) member outside of (adult) household (adult) (adult) household (adult) (adult) 3. Food Security Household coping strategies are indicative of persistent acute food insecurity and this finding echoes AWMS R2 and other international organizations’ reports.10 Widespread household food deprivation is evidenced by reliance on lower quality food, the need to borrow to buy food, and food rationing. Women in the AGMS reported slightly higher adoption of dietary changes and borrowing strategies as coping mechanisms to face the reduction in food available, compared to male respondents in the AWMS R2, and also reported a higher use of food rationing strategies than men did. AGMS respondents reported that 88 percent of them rely on lower quality food and 69 percent must borrow to buy food. When reported by women, reliance on rationing strategies that reduce caloric intake, such as skipping meals or reducing meal size, has increased since AWMS R1 and is higher than reported by men in AWMS R2 (Figure 12). This discrepancy between genders could indicate that women have more information about the household coping strategies, possibly due to their unequal involvement in domestic work such as cooking. Figure 12: Household Coping Strategies 100% AGMS (Sept–Oct 2022) AWMS R2 (Jun–Aug 2022) 88% 84% 80% 75% 73% 69% Households (%) 61% 59% 60% 54% 56% 40% 39% 20% 0% Reduced quality / Borrowed food or Limit portion size Reduced number Reduced amount so Cheaper food money to buy food meals per day children could eat Dietary change Borrowing Rationing strategies 10 World Food Programme. 2021. Afghanistan Food Security Update. September 10. 13   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt When food is short, children are prioritized over adults, and then male family members seem to have preference over female family members, leaving women to eat last. The AGMS collected information about potential age and gender biases in household food access in the face of resource scarcity.11 If the household reported not having enough food, in 54 percent of cases, male family members are fed before female family members, while females only have precedence over male family members in 6 percent of cases (in the remaining cases females and males have equal priority). As expected, children have precedence over adults in 89 percent of cases and 18 percent of households would prioritize girls over boys, while 13 percent would prioritize boys over girls. Food aid was cited as the most needed type of support among both urban and rural women. When asked what type of support would be most helpful for their household, women responded in-kind food aid (77 percent), followed by cash transfers (54 percent) and work/jobs programs (10 percent). Results are similar to responses reported by AWMS R2 respondents (Figure 13). Women were also asked a hypothetical question about how they would use a cash transfer, and 90 percent of women said they would use it to buy food for the family (close to the 87 percent reported by AWMS R2 respondents). Figure 13: Support That Household Reported Needing 77% In-kind food 75% Cash transfer 54% 46% Work / jobs program 10% 10% In-kind other than food (e.g., clothes, soap, bedsheets) 9% 5% Access to health services 3% 2% Small business grants 3% 1% Access to schools 2% AGMS (Sept–Oct 2022) 1% AWMS R2 (Jun–Aug 2022) Agriculture inputs 0% 2% Loan schemes for women 1% 0% 1% Access to higher education 1% 1% Medicine 1% 1% No assistance needed 2% 0% 20% 40% 60% 80% 100% Households (%) 11 The primary outcome indicator from this question is a dummy variable capturing whether the mean rank order in which female members are fed (weighting adult women and girls equally) is equal to or greater than the rank order in which male members are fed (weighting adult men and boys equally). 14   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt 4. Women’s Work and Child Labor Over half of women responding to the AGMS reported that they are doing some type of income-generating activity, a share even larger than the one reported by the AWMS R2. The AGMS collected information about women’s activities in the last seven days, including labor activity even for an hour. Fifty-six percent of AGMS respondents (ages 15 to 65) indicated being engaged in income-generating activities (Figure 14),12 10 percentage points higher than that reported by the AWMS R2.13 Higher shares of rural women report having income- generation activities compared to women in urban areas (62 percent versus 44 percent). The differences reported in the AGMS and the AWMS R2 could be explained by women being more likely to report their own labor activities, compared to the reporting of household heads in the AWMS R2. In addition, there are differences in the questions used and the time of the year used as a reference, which may have impacted the final estimates.14,15 Still, the results reported are substantially higher than those reported in official statistics from the IELFS 2019–2020 (11.2 percent for women 14+ years old) and indicate that most working-age household members are supporting income-generating streams to navigate the crisis. Future rounds of the AWMS and AGMS will try to understand the drivers of women’s engagement in income-generating activities, as well as the impact of the December bans. While more women appear to be working, it is important to note that activities are of short-term, low- quality and seasonal nature. When asked about activities women engaged in, in the last seven days (Figure 14), 29 percent reported working in their household’s farm or with livestock or poultry, 24 percent reported running and/or helping run a business of any size for themselves or with others, 18 percent reported working in the production of durable goods, 15 percent reported working for a wage, salary, commission, or any in- kind payment (including doing paid domestic work or paid farm work), and only 4 percent reported working as apprentices. Work in agriculture and family-owned business is especially common among rural respondents. Figure 14: Women’s Engagement in Income-Generating Activities in the Past Seven Days 60% 56% Respondents (%) 40% 29% 24% 20% 18% 15% 4% 0% Engaged in Work on Work in own Production of Work for wage Apprenticeship income-generating household farm or household durable goods activities business Respondents ages 15 to 65 All respondents Note: Green bars correspond to answers provided by all respondents, not restricted to ages 15 to 65. 12 The variable “engaged in income-generating activities” is a dummy equal to 1 when a respondent claimed to have done any type of work in the last seven days. 13 For the women’s labor comparison, the AWMS R2 sample was restricted to the respondents that were part of the AGMS. 14 AGMS labor questions: “In the last 7 days, did you work for a wage, salary, commission, or any payment in kind; including doing paid domestic work or paid farm work even if for one hour?”; “In the last 7 days, did you run a business of any size for yourself or the household or with partners, even if for one hour?”; “In the last 7 days, did you help in any kind of business run by this household, even if for one hour?”; “In the last 7 days, did you work as a paid or unpaid apprentice even if just for one hour?” (Not included in computation of employment); “In the last 7 days, did you work on your household’s farm or work with livestock or poultry, even if for one hour?”; “In the last 7 days, did you produce any durable goods - such as clothes, carpets, kilims, furniture, etc. - for own use by household members?” 15 AWMS R2 labor questions: “In the last week, did [name] work for pay for any business, organization, or person that does not belong to this household, even if only for one hour?”; “In the last week, did [name] do any farm work on own land or land of others - such as cultivating, harvesting crops, land preparing - or tend any livestock or poultry?”; “In the last week, did [name] do any non-agricultural work, on own account or in a business that belongs to this household, or one of the household members, even if only for one hour? For instance, in trading, running a shop, driving a taxi, tailoring, carpentry, carpet weaving, making handicrafts, etc.?”; “In the last week, did  [name]  produce any durable goods - such as clothes, carpets, kilims, furniture, etc.- for own use by household members?”. 15   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Among women who are not working, the main reasons were maternity/child rearing/domestic work (43 percent), followed by lack of jobs (38 percent) and illness (16 percent). Only 7 percent of women reported being prohibited from working by a household member (Figure 15).16 Mobility was not reported as a reason for not working. Figure 15: Reasons Cited by Women for Not Engaging in Income-Generating Activities Maternity, child rearing leave, domestic work 43% No jobs available 38% Own illness 16% Unemployed 8% Prohibited by household 7% Out of the labor force 5% Education, training 2% Temporary workload reduction 1% Security situation 1% Bad weather 1% 0% 10% 20% 30% 40% 50% Respondents not engaged in income-generating activities (%) Across all sectors, 52 percent of AGMS respondents reported a decrease in their monthly earnings as compared to six months before; 36 percent reported no changes in salary and only 11 percent reported an increase. Figure 16 indicates the difference in reporting between MKFs in the AGMS and respondents in the AWMS R2 (who are predominately male), suggesting that male spouses may overestimate women’s earnings dynamics, or had incomplete information on the economic returns to activities that women may have been previously doing. It is also worth noting the seasonality effect, where increased demand in female labor (and associated variation in earnings) can correspond to fall/winter months and work inside the home, compared to the summer months captured by the AWMS R2. Figure 16: Women’s Earnings Compared to Six Months Ago 60% AGMS (Sept–Oct 2022) AWMS R2 (Jun–Aug 2022) 52% income-generating activities (%) 50% Respondents engaged in 40% 38% 36% 33% 30% 29% 20% 11% 10% 0% More than before About the same Less than before Survey findings indicate that child labor may also be increasing. When asked if any children below the age of 14 started to work in the last six months, 80 percent of AGMS respondents indicated that no children below 14 were currently working, 17 percent indicated that at least a boy started to work, 2 percent that at least a girl did, and 1 percent that both boys and girls did, with higher male child labor in rural areas. Most recent official figures from the National Statistics and Information Authority (2020) indicated that 12.4 percent of children 5–11 years old were employed. 16 Multiple answers allowed. 16   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt 5. Access to Services Before the December bans, most women—83 percent—reported that they themselves, as well as everyone in the household who needed to, were able to access health services. The majority of respondents—87 percent— reported that the nearest health facility was staffed with at least one female health worker. When a woman or a child could not access health services (Figure 17), the most common reason cited was lack of money (69 percent), followed by supply stock-outs (15 percent). When looking at the AGMS households in AWMS R2, 82 percent had at least one adult female member or child who needed medical attention—among these, 87 percent reported that all members could access health services. Figure 17: Access to Health Services and Barriers to Access a. Access to health services b. Barriers to access health services 100% 80% 69% Households who needed health services (%) 83% not access health services (%) 80% Households who could 60% 60% 40% 20% 15% 40% 3% 2% 2% 2% 1% 1% 0% 20% 17% rt e ay ff t r ey e ou fa bl po ta iv aw on la l/s ns oo k- ns ai em oc ed pe na et tra av st rn ex sio ar av m No n/ Tu lc o es th ra tio to ica of ah 0% no ica as pr ed Everyone At least one M d w ed No M No Di st in need in need could m Co No could access not access Slightly less than half of all women (49 percent; 62 Figure 18: Regular Access to Phone percent urban and 43 percent rural)17 own their phone 70% (Figure 18). Because the AGMS respondents were All 62% the most knowledgeable women in the household, 60% Urban this could be an overestimate of phone ownership Rural 49% among the average woman. Some women (18 percent; 50% 43% Respondents (%) 13 percent urban and 20 percent rural) reported 26% 40% 37% having regular access to somebody else’s phone. A 33% substantial portion of women—33 percent—said that 30% there is no phone available or that there is a phone, 13% 20% but their access is restricted (26 percent urban and 37 20% 18% percent rural). Forty percent reported using the phone 10% every day (51 percent urban and 35 percent rural), 32 percent said that they use a phone at least once a 0% week, 15 percent of women said they use a phone less No phone / Has own Access to phone available phone someone than once a week, and 13 percent reported not using a but no access else's phone phone at all in the past three months (Figure 19). 17 If respondent was assessed “alone” during the survey, she was more likely to possess her own phone (56 percent of cases), as compared to those “not alone” (40 percent of cases). This may reflect a larger autonomy for “alone” respondents. 17   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Figure 19: Phone Usage 60% All Urban Rural 51% 50% 40% Respondents (%) 40% 35% 32% 34% 30% 28% 20% 15% 15% 16% 13% 13% 10% 8% 0% Never Less than once a week At least once a week Almost every day A majority of women—74 percent—reported having a Tazkira (national identity card in paper, booklet, or electronic), with e-Tazkiras being more common in urban areas and paper identity documents more common in rural areas (Figure 20). Still, more than one-quarter of women—26 percent—do not have any Tazkira (16 percent urban and 30 percent rural). It is worth noting that because AGMS respondents were in most cases a prominent female in the household, they might present higher possession of identity documents than other women in the household. The Tazkira, Afghanistan’s national identity card, is required for access to certain services, to register mobile SIM cards (and thus access mobile banking), and to access other documentation such as birth, marriage, and death certificates, as well as passports. For girls and women, Tazkira and marriage certificates are crucial for securing rights to inheritance, marital property, and mahr (dowry), and for verifying girls’ age at marriage. Figure 20: Possession of National Identity Card (Tazkira) 60% 55% All Urban Rural 50% 50% 45% 40% 39% Respondents (%) 30% 30% 26% 23% 20% 16% 14% 10% 0% Does not have Paper or old booklet Tazkira E-Tazkira 18   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt 6. Safety and Mental Health Perceptions of safety reported by women are similar to those reported by respondents in AWMS R2, which indicate that public security has improved over the past year (Figure 21). Respondents were asked, “In the current environment, do you and others in your household feel more or less safe as compared to 12 months ago?”. There are significant differences between urban and rural, with urban women reporting lower perception of safety than rural women. When asked if household members were subject to any form of attack/violence in the past six months,18 88 percent of respondents reported that no members (female nor male) were. When women were asked to evaluate their own feelings of safety, they reported feeling more insecure when walking in their village during the nighttime than during the day (Figure 22). Figure 21: Women’s Perception of Public Safety Compared to 12 Months Ago 50% 46% 45% AGMS (Sept–Oct 2022) AWMS R2 (Jun–Aug 2022) 40% Respondents (%) 30% 22% 22% 20% 16% 14% 13% 10% 8% 9% 6% 0% Much less safe Somewhat less safe Neither more Somewhat more safe Much safer nor less safe A large share of women feel insecure in their own Figure 22: Women’s Feelings of Insecurity homes, with 28 percent of women reporting that 10 they feel domestic insecurity. Women were asked, “In the last six months, were there any times when you 9 On a scale from 1 to 10, with 10 being most insecure felt unsafe in your home?”. This question is often used 8 to screen for intimate partner violence (IPV) in primary care settings and has been applied in GBV phone 7 surveys. Women’s experience of IPV was already high 6 in the country—the 2015 DHS found that 53 percent of Afghan women reported having experienced physical 5 or sexual violence, the vast majority of whom do not 4.2 4 seek help nor tell anyone about the violence. 19,20 3 2.8 2 1 During the day At night 18 Period already under Taliban control. 19 Central Statistics Organization (CSO), Ministry of Public Health (MoPH), and ICF. 2017. Afghanistan Demographic and Health Survey 2015. Kabul, Afghanistan: Central Statistics Organization. https://www.rhsupplies.org/uploads/tx_rhscpublications/Afghanistan_-_2017.pdf. 20 In line with the empirical evidence from other countries, declines in household incomes and increases in poverty-related stress experienced in recent months may have worsened IPV. IPV may also be increasing if men or mothers-in-law apply violence to enforce the ITA’s new restrictions on women, or if they perceive more widespread social acceptability of IPV and that this is an expected or desired behavior (Heise, Lori. 1998. “Violence Against Women: An Integrated Ecological Framework.” Violence Against Women 4 (3):262–290. https://doi.org/10.1177/1077801298004003002.) 19   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Figure 23: Places Women Go When They Feel Unsafe at Home 60% 59% Respondents (%) 40% 35% 20% 6% 1% 1% 0% No place to go Relative's home Neighbor’s home A shelter in Friend's home the community When women do feel unsafe in their homes, they have few options. Results show that 59 percent of women report not having a place to go. Another 35 percent say they would go to a relative’s home and 6 percent would seek refuge at a neighbor’s home (Figure 23). Despite of their strong support for women’s rights, close to half of women maintain accepting attitudes toward GBV. Women were asked for their opinion on whether they thought a husband was justified in beating his wife if she went out without telling him, neglected the children, argued with him, refused sex, or burned the food (question adapted from the DHS questionnaire). Nearly 48 percent of women expressed the feeling that husbands were justified in beating their wives for at least one reason (Figure 24). More rural women found wife beating acceptable compared to urban women (54 percent versus 32 percent). Figure 24: Women’s Attitudes Toward Wife Beating 60% All Urban Rural 54% 48% Respondents ages 15 to 49 (%) 40% 33% 34% 34% 31% 32% 29% 29% 28% 26% 20% 19% 18% 16% 15% 15% 13% 6% 0% If she goes out If she neglects If she argues If she refuses If she burns For at least without telling him the children with him to have sex with him the food one reason Women report high levels of anxiety and depression. Devastated by decades of war, instability, and poverty, many Afghans suffer the mental health consequences of trauma. Even before August 2021, women suffered disproportionately. According to a 2021 national survey on depressive and anxiety disorders,21 women suffer more than men from psychological distress, impairment due to mental health, post-traumatic stress disorder, and suicidal behaviors and suicidal thoughts. 21 Kovess-Masfety et al. 2021. “A national survey on depressive and anxiety disorders in Afghanistan: A highly traumatized population.” BMC Psychiatry 21:314. https://doi.org/10.1186/s12888-021-03273-4. 20   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt A validated mental health symptoms screener was used to provide an ultra-brief and accurate measurement of the core signs/symptoms of depression and anxiety. Scores are rated as normal (0–2), mild (3–5), moderate (6–8), and severe (9–12).22 The total mean score reported by Afghan women is 5.7 (standardized score=0.47), with a marginal difference with a score of 6.1 (standardized score=0.51) for those between the ages of 35 and 44 (Figure 25). Women’s scores suggest high levels of anxiety and depression; close to half of Afghan women present mental health symptoms falling between moderate and severe (Figure 26), and present symptoms of anxiety and depression. Figure 25: Women’s PHQ-4 Score (Measuring Depressing and Anxiety) 1.00 0.80 Standardized score 0.60 0.53 0.50 0.45 0.47 0.42 0.40 0.20 0.00 Little interest or pleasure Feeling down, Feeling nervous, Not being able to stop Overall index in doing things depressed, or hopeless anxious, or on edge or control worrying Note: PHQ-4 = Patient Health Questionnaire for Depression and Anxiety Figure 26: Mental Health by Disorder and Severity 60% 50% 48% 45% 40% Respondents (%) 37% 30% 26% 22% 20% 16% 10% 0% Anxiety Depression Normal Mild Moderate Severe Overall mental health symptoms 22 The Patient Health Questionnaire for Depression and Anxiety (PHQ-4) was developed and validated by Kroenke, Spitzer, Williams, & Löwe 2009. Questions include “little interest or pleasure in doing things”; “feeling down, depressed, or hopeless”; “feeling nervous, anxious, or on edge”; and “not being able to stop or control worrying.” Answers to each question are given on a four-point Likert-type scale ranging from 0 to 3. The total score is determined by adding together the scores of each of the four items. Scores are rated as normal (0–2), mild (3–5), moderate (6–8), and severe (9–12). A total score of 3 and above for the first two questions suggests anxiety. A total score of 3 and above for the last two questions suggests depression. For ease of interpretation, scores have been standardized to be between 0 and 1 in Figure 25. 21   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Future Work T he AGMS will continue as a key part of the World Bank’s ongoing consultation with Afghan women to understand their needs and priorities. Future rounds will continue to closely monitor the rapidly evolving situation of women in the country to inform the humanitarian-development response. An abbreviated follow-on phone survey among AGMS respondents will be fielded in March 2023 to assess the additional impact of the December 2022 bans on women’s wellbeing, mobility, and their access to services. Subsequent rounds of the full-length AGMS will be conducted as a regular follow-on to the semi-annual AWMS. 22   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt Annex Comparative Statistics of “Alone” / “Not Alone” Groups Table A1 displays indicators for which respondents who were assessed “alone” during the interview reported differently from respondents assessed “not alone.” For each indicator, the impact of the surveillance status is tested by regressing the indicator on the status of being alone, alongside key demographic characteristics that were found to correlate with the “alone” status (Pashto, literacy, and household location). The table only displays coefficients that were significant at the 95% confidence interval (p-value smaller than 0.05) or at the 99% confidence interval (p-value smaller than 0.01). Indicators with a difference across groups of less than 2 percentage points are omitted. Table A1: Comparison of Indicators Reported by Respondents Assessed “Alone” and “Not Alone” Indicator Respondent Respondent Difference Coefficient1 p-value assessed assessed in means “alone” “not alone” (t-test) (mean) (mean) Women’s rights Right to participate in government 0.093 0.161 0.068*** -0.086 0 Right not to be beaten (by family) 0.098 0.066 -0.033*** 0.038 0.003 Women’s activities Can no longer participate in savings groups 0.036 0.069 0.033*** -0.037 0.0003 Can no longer participate in household 0.057 0.081 0.024** -0.027 0.015 farming, planting, harvesting Can no longer participate in ANY activity 0.069 0.09 0.021* -0.028 0.018 Mobility Accompanied by children under 12 0.386 0.316 -0.070*** 0.098 0.00002 Food security Coping strategy: worked more or longer hours 0.07 0.102 0.031** -0.042 0.003 Coping strategy: reduced amount or skipped 0.427 0.478 0.051** -0.055 0.012 meals Coping strategy: did nothing to compensate 0.115 0.083 -0.032** 0.038 0.007 for loss of income 23   A fg hanistan Gender Monitoring Survey: Bas e line Re po rt  continued) Table A1 ( Indicator Respondent Respondent Difference Coefficient1 p-value assessed assessed in means “alone” “not alone” (t-test) (mean) (mean) When food short: male have precedence over 0.569 0.514 -0.055** 0.045 0.048 women When food short: children have precedence 0.91 0.863 -0.047*** 0.037 0.016 over adults Women’s labor Worked in production of durable goods in last 0.153 0.22 0.068*** -0.072 0.00004 7 days Reason for not working: maternity/child 0.445 0.355 -0.090*** 0.076 0.015 rearing/domestic work Reason for not working: unemployed 0.116 0.044 -0.072*** 0.066 0.00001 Access to services Any household member in need could access 0.848 0.795 -0.053*** 0.049 0.008 health facility If needed, adult women in household could 0.844 0.788 -0.056** 0.057 0.014 access health facility If needed, girls in household could access 0.901 0.824 -0.077*** 0.074 0.007 health facility If needed, boys in household could access 0.895 0.839 -0.056** 0.059 0.03 health facility Reason for not accessing health facility: no 0.096 0.2 0.104** -0.113 0.037 medication Respondent owns a phone 0.562 0.397 -0.165*** 0.119 0 There is a phone, but respondent’s access is 0.084 0.148 0.063*** -0.054 0.0003 restricted No phone available 0.182 0.265 0.083*** -0.081 0.00001 Have not used a phone in last 3 months 0.104 0.164 0.061*** -0.052 0.0006 Have used phone almost every day in last 3 0.451 0.34 -0.111*** 0.082 0.0002 months Have an e-Tazkira 0.274 0.182 -0.092*** 0.048 0.005 Safety When unsafe: seeks refuge at a neighbor’s home 0.065 0.045 -0.020** 0.026 0.015 When unsafe: no place to go 0.566 0.62 0.054** -0.052 0.021 Mental health Anxiety 0.507 0.439 -0.068*** 0.093 0.00001 Severe mental health symptoms 0.244 0.184 -0.060*** 0.081 0.00003 1 Controlled for “alone” and demographic characteristics. * p < 0.1; ** p < 0.05; *** p < 0.01.