G²LM|LIC - A Tough Call: Understanding the Impact of Mobile Technology on Women’s Work, Gender Gaps, and Social Norms

Mobile phones can help individuals access information, networks, and resources, allowing them to benefit both socially and economically. Yet in many lower-income countries, women lag men in phone ownership and usage for a variety of economic and normative reasons. To boost women’s phone ownership and usage, the Government of Chhattisgarh implemented the Sanchaar Kranti Yojana (SKY) program in 2018, using the 2011 census population data as an eligibility criterion. Gram panchayats (GPs) in which the largest village fell below the population threshold of 1,000 were ineligible to receive the program benefits. We use this population cutoff to shortlist 279 treatment gram panchayats and 408 control gram panchayats in 13 districts across the state. We collect three datasets for each gram panchayat and they are as follows. Individual Surveys In each GP, we aimed to conduct surveys with 15 female (18-45 years of age) and 15 male (18-50 years of age) respondents. Within the 687 GPs, we were able to conduct the full 30 surveys in 682 GPs (99.3 percent) and completed some surveys in a further 2 GPs (0.3 percent). This dataset has all individual-level responses. Household Surveys In the male survey, we collect information about the rest of the household. This information is not available for households where only a female respondent was surveyed. Community Leader Surveys We conducted key informant interviews (KIIs) with select community leaders from the largest village in each of the sampled gram panchayats. During scoping activities, we targeted multiple community leaders including the Sarpanch (a locally elected leader), the Sachiv or vice-president (a bureaucrat and another elected leader), and the Gram Rojgar Sahayak (GRS), the main local official tasked with implementing India’s public works program, NREGA. The four leaders we ultimately surveyed had the best ability to accurately answer questions outlined in our community leader survey and the most time for our survey questions. These are the ASHA or Mitanins, Anganwadi Workers (AWW), Ward Members who are part of the GP Council, and the village criers, known as Kotwal. Often when they were unavailable, we surveyed the “representative”, someone who is deputized to carry out similar functions. In some instances when the ASHA worker was busy, we conducted these surveys with more Anganwadi workers. The Anganwadi workers were administered the exact same survey as the ASHA worker. Similarly, village criers and ward members responded to the same survey. Speedtest Surveys Enumerators conducted speed test using Speedtest.Net when they were in the GPs. We tried to ensure coverage across the two main network providers, Jio and Airtel, using different SIM cards. These were either conducted on their own or with the Community Leader Surveys and we have more than 1 speed test per GP. Data Collection Data collection was carried out by IDinsight’s field team. Throughout data collection, the Inclusion Economics India Centre (IEIC) research team conducted ongoing data quality checks, including high-frequency checks, spot checks, in-person back checks, phone back checks, and audio audits. These all fed into a live dashboard created by IDinsight to track productivity and data quality throughout data collection. Sampling procedure SKY eligibility was based on a population threshold using the 2011 Indian Census. Mobile coverage was extended to covered communities, and smartphones were distributed to one adult female per household in GPs with a population of at least 1,000 in their largest village. GPs just under this population threshold were ineligible. To maximize power, our data collection strategy focused on GPs closest to the discontinuity. We determined our sample as follows: First, we shortlisted the 13 districts that had the highest rates of SKY implementation, excluding the capital district of Raipur, where we had run a randomized controlled trial in many SKY-eligible GPs. Then, using 2011 Indian census data and local randomization approaches described in Cattaneo et al. (2023), we identified a window around the population discontinuity within which one might possibly assume that treatment is as good as randomly assigned. We find that when dropping GPs that have just one village, the local randomization approach admits GPs where the population of the largest village is 99 more and less than 1000. This yields a sample of 687 GPs. The realized sample is smaller than 687 since some GPs were not surveyable (e.g. due to safety issues due to left-wing extremism or challenges in obtaining permission from local leaders). Within these selected GPs, we used voter rolls to randomly sample 15 women aged 18-45 from the individuals associated with polling booths within the GP and attempted to survey the woman and a randomly selected male household member. Results We investigate two approaches to closing digital gender gaps. The first is a statewide program, which distributed...

移动通信设备能够帮助个人获取信息、网络和资源，从而在社会和经济层面受益。然而，在众多低收入国家，由于多种经济和规范因素，女性在手机拥有和使用方面落后于男性。为了提升女性的手机拥有率和使用率，查蒂斯加尔邦政府在2018年实施了Sanchaar Kranti Yojana（SKY）计划，以2011年的人口普查数据作为资格标准。人口超过1,000人的最大村庄所在的村议会（GPs）不符合接受计划福利的资格。我们利用这一人口门槛，从该州13个区的279个治疗村议会和408个控制村议会中筛选出279个处理村议会和408个控制村议会。我们对每个村议会收集了三个数据集，具体如下。个体调查：在每个村议会中，我们旨在对15名女性（18-45岁）和15名男性（18-50岁）受访者进行调查。在687个村议会中，我们能够在682个村议会（99.3%）中完成全部30次调查，并在另外2个村议会（0.3%）中完成部分调查。此数据集包含所有个体层面的回应。家庭调查：在男性调查中，我们收集有关家庭其他成员的信息。对于只调查了女性受访者的家庭，这些信息不可用。社区领袖调查：我们对样本村议会中最大村庄的选定社区领袖进行了关键信息访谈（KIIs）。在范围界定活动中，我们针对包括萨帕anch（地方选举领导人）、萨奇夫或副总统（官僚和另一位选举领导人）以及Gram Rojgar Sahayak（GRS），即主要负责实施印度国家公共工程计划NREGA的主要地方官员在内的多个社区领袖。我们最终调查的4位领袖具备最佳能力，能够准确回答我们社区领袖调查中概述的问题，并且有最多时间回答我们的调查问题。这些领袖包括ASHA或Mitanins，Anganwadi工作者（AWW），村议会成员，以及被称为Kotwal的村公告员。当他们在场时，我们调查了“代表”，即被委派执行类似功能的人。在某些情况下，当ASHA工作者忙碌时，我们使用更多的Anganwadi工作者进行这些调查。Anganwadi工作者接受了与ASHA工作者完全相同的调查。同样，村公告员和村议会成员回答了相同的调查。速度测试调查：在村议会中，调查员使用Speedtest.Net进行速度测试。我们试图通过使用不同的SIM卡确保覆盖两大主要网络运营商Jio和Airtel。这些测试要么单独进行，要么与社区领袖调查同时进行，并且每个村议会中有多于一次的速度测试。数据收集：数据收集由IDinsight的现场团队执行。在整个数据收集过程中，Inclusion Economics India Centre（IEIC）研究团队进行了持续的数据质量检查，包括高频检查、现场检查、面对面回溯检查、电话回溯检查和音频审计。所有这些都反馈到了由IDinsight创建的实时仪表板中，以在整个数据收集过程中跟踪生产力和数据质量。抽样程序：SKY的资格基于2011年印度人口普查中的人口门槛。移动覆盖扩展到受覆盖社区，智能手机分发给每个村议会中最大村庄人口至少为1,000的家庭中的一名成年女性。人口略低于此门槛的村议会不符合资格。为了最大化效力，我们的数据收集策略集中在最接近不连续点的村议会。我们确定样本如下：首先，我们筛选出13个实施SKY计划率最高的区，排除首府地区达拉特，因为我们已经在许多SKY合格村议会中进行了随机对照试验。然后，使用2011年印度人口普查数据和Cattaneo等人（2023年）中描述的当地随机化方法，我们在可能假定治疗与随机分配相同的情况下，确定了围绕人口不连续性的一个窗口。我们发现，当排除只有一个村庄的村议会时，当地随机化方法允许人口最多的村庄人口在995至1,000之间。这产生了687个村议会的样本。实际样本小于687，因为一些村议会不可调查（例如，由于左翼极端主义的安全问题或从地方领导人那里获得许可的挑战）。在这些选定的村议会中，我们使用选民名册，从与村议会内投票站相关的人员中随机抽取15名18-45岁的女性，并试图调查这位女性和随机选定的男性家庭成员。结果：我们研究了两种缩小数字性别差距的方法。第一种是全省范围内的计划，该计划向受覆盖社区扩展移动覆盖，并向每个家庭中至少一名成年女性分配智能手机。第二种是SKY计划，该计划以2011年的人口普查数据为基础，针对人口超过1,000人的最大村庄所在的村议会，实施随机对照试验。