COVID-19-Related Shocks in Rural India 2020, Round 2 - India

Abstract
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An effective policy response to the economic impacts of the COVID-19 pandemic requires an enormous range of data to inform the design and response of programs. Public health measures require data on the spread of the disease, beliefs in the population, and capacity of the health system. Relief efforts depend on an understanding of hardships being faced by various segments of the population. Food policy requires measurement of agricultural production and hunger. In such a rapidly evolving pandemic, these data must be collected at a high frequency. Given the unexpected nature of the shock and urgency with which a response was required, Indian policymakers needed to formulate policies affecting India's 1.4 billion people, without the detailed evidence required to construct effective programs. To help overcome this evidence gap, the World Bank, IDinsight, and the Development Data Lab sought to produce rigorous and responsive data for policymakers across six states in India: Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh.

Geographic coverage
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Jharkhand, Rajasthan, Uttar Pradesh, Andhra Pradesh, Bihar, and Madhya Pradesh

Analysis unit
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Household

Kind of data
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Sample survey data [ssd]

Sampling procedure
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The samples for these surveys were drawn from surveys and impact evaluations previously conducted by the World Bank, the Ministry of Rural Development, India and IDInsight. A detailed note on the sampling frames is available for download.

Sampling deviation
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Details will be made available after all rounds of data collection and analysis is complete.

Mode of data collection
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Computer Assisted Telephone Interview [cati]

Research instrument
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The survey questionnaire consists of the following modules:
- Module 0: Introduction
- Module 1: Agriculture
- Module 2: Migration
- Module 3: Consumption
- Module 4: Labour and Income
- Module 5: Access to Relief
- Module 6: Health

Response rate
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~46%. The response rate does not include attempts made to invalid numbers. There were 972 such numbers in the sample. The response rate includes the 443 partially completed surveys.

{'Abstract': '为有效应对COVID-19大流行对经济造成的影响，制定政策需要广泛的数据以指导方案的设计和应对措施。公共卫生措施需依赖疾病传播、公众信念以及卫生系统承载能力的相关数据。救济工作则依赖于对人口各阶层所面临的困境的理解。粮食政策需对农业生产和饥饿状况进行测量。在这样的快速演变的疫情中，这些数据必须以高频率收集。鉴于冲击的意外性和应对的紧迫性，印度政策制定者在缺乏构建有效方案所需详细证据的情况下，需要制定影响印度14亿人口的策略。为了帮助克服这一证据缺口，世界银行、IDinsight和开发数据实验室致力于为印度六个州的决策者提供严谨且及时的数据：达拉特兰邦、拉贾斯坦邦、北方邦、安得拉邦、比哈尔邦和中央邦。', 'Geographic coverage': '达拉特兰邦、拉贾斯坦邦、北方邦、安得拉邦、比哈尔邦和中央邦', 'Analysis unit': '家庭', 'Kind of data': '样本调查数据 [ssd]', 'Sampling procedure': '这些调查的样本来源于世界银行、印度农村发展部和IDInsight先前进行的调查和影响评估。有关抽样框架的详细说明可供下载。', 'Sampling deviation': '详细数据将在数据收集和分析的所有阶段完成后提供。', 'Mode of data collection': '计算机辅助电话访谈 [cati]', 'Research instrument': '调查问卷包括以下模块：
- 模块0：介绍
- 模块1：农业
- 模块2：移民
- 模块3：消费
- 模块4：劳动与收入
- 模块5：救济获取
- 模块6：健康', 'Response rate': '~46%。该响应率不包括对无效号码的尝试。样本中有972个此类号码。响应率包括443份部分完成的调查。'}