Data Dictionary

Additional Information

Field	Value
Data last updated	September 20, 2023
Metadata last updated	August 22, 2024
Created	August 11, 2023
Format	CSV
License	Open Data Commons Attribution License
Data extraction page	https://www.nabard.org/auth/writereaddata/tender/1608180417NABARD-Repo-16_Web_P.pdf
Data insights	The dataset offers valuable insights for researchers, policy makers, and journalists interested in the economic status of households in India. It enables research on various topics, such as the impact of economic growth on household income, the correlation between household indebtedness and financial well-being, and the effectiveness of government programs targeting economic improvement for households.Key questions that can be addressed using the dataset include the average monthly income of households in each state, and how it compares to the average monthly household consumption expenditure. Additionally, it identifies the state with the highest proportion of households reporting savings, as well as the average savings made by saver households in each state. The dataset reveals states with the highest incidence of household indebtedness, the proportion of households associated with any Micro Finance Institution, and the average landholding size in each state.
Data last updated	2016-17
Data retreival date	2016-17
Datastore active	True
Frequency	One Time
Granularity	State
Has views	True
Id	818b169d-cc30-43c0-9425-edb97deeb42e
Idp ready	True
Lgd mapping	yes
Methodology	National Financial Inclusion Survey (NAFIS) used a multi-stage stratified random sampling methodology to select households for the survey. This methodology involved several stages of sampling to ensure that the survey sample was representative of the rural population in India.The first stage involved dividing the country into various strata based on geographical, demographic, and socio-economic characteristics. These strata were further divided into smaller sampling units, such as villages or wards.In the second stage, a sample of these units was selected using a probability proportional to size (PPS) method. The size of the sample was determined based on the desired level of precision and the estimated population size of each stratum.In the third stage, a sample of households was selected from each selected unit using a systematic sampling method. In this method, every kth household was selected for the survey, where k was determined based on the size of the sampling unit and the desired sample size.The use of multi-stage stratified random sampling allowed for the selection of a representative sample of households from across the country, which ensured that the survey results were reliable and could be generalized to the entire population of rural India.
No indicators	9
Package id	37e176c0-1f82-4839-834a-9b1b22784bfb
Position	0
Size	1.7 KiB
Sku	nabard-nafis-st-ot-ify
State	active
States uts no	29
Url type	upload
Years covered	2016-17
Methodology	National Financial Inclusion Survey (NAFIS) used a multi-stage stratified random sampling methodology to select households for the survey. This methodology involved several stages of sampling to ensure that the survey sample was representative of the rural population in India.The first stage involved dividing the country into various strata based on geographical, demographic, and socio-economic characteristics. These strata were further divided into smaller sampling units, such as villages or wards.In the second stage, a sample of these units was selected using a probability proportional to size (PPS) method. The size of the sample was determined based on the desired level of precision and the estimated population size of each stratum.In the third stage, a sample of households was selected from each selected unit using a systematic sampling method. In this method, every kth household was selected for the survey, where k was determined based on the size of the sampling unit and the desired sample size.The use of multi-stage stratified random sampling allowed for the selection of a representative sample of households from across the country, which ensured that the survey results were reliable and could be generalized to the entire population of rural India.
Indicators
Similar Resources
Granularity Level	State
Data Extraction Page	https://www.nabard.org/auth/writereaddata/tender/1608180417NABARD-Repo-16_Web_P.pdf
Data Retreival Date	2016-17
Data Last Updated	2016-17
Sku	nabard-nafis-st-ot-ify
Dataset Frequency	One Time
Years Covered	2016-17
No of States/UT(s)	29
No of Districts
No of Tehsils/blocks
No of Gram Panchayats
Additional Information
Number of Indicators	9
Insights from the dataset	The dataset offers valuable insights for researchers, policy makers, and journalists interested in the economic status of households in India. It enables research on various topics, such as the impact of economic growth on household income, the correlation between household indebtedness and financial well-being, and the effectiveness of government programs targeting economic improvement for households.Key questions that can be addressed using the dataset include the average monthly income of households in each state, and how it compares to the average monthly household consumption expenditure. Additionally, it identifies the state with the highest proportion of households reporting savings, as well as the average savings made by saver households in each state. The dataset reveals states with the highest incidence of household indebtedness, the proportion of households associated with any Micro Finance Institution, and the average landholding size in each state.
IDP Ready	Yes
LGD Mapping	Yes