Data Dictionary

Column	Type	Label	Description
id	int4	index
year	text	Year
state_name	text	State
state_code	text	State code
consm_exp	numeric	Average Household Monthly Consumption Expenditure
prop_saving	numeric	Households Reporting Savings
avg_saving_yr	numeric	Average Savings made by Saver Households
prop_hh_indebt	numeric	Incidence of Indebtedness among Households by States
prop_hh_microfin	numeric	Households associated with any Micro Finance Institution
avg_land_size	numeric	Average Landholding Size
hh_income_monthly	numeric	Average Monthly Household Income
agri_hh_income_monthly	numeric	Average Monthly Agricultural Household Income

Additional Information

Field	Value
Data last updated	June 5, 2024
Metadata last updated	June 6, 2024
Created	unknown
Format	CSV
License	No License Provided
Created	4 months ago
Frequency	One Time
Size	257
Additional info	nan
Data extraction page	https://www.nabard.org/auth/writereaddata/tender/1608180417NABARD-Repo-16_Web_P.pdf
Data insights	The NABARD All India Rural Financial Inclusion Survey (NAFIS) for Meghalaya offers valuable insights into the economic landscape of rural households. Researchers and policymakers can explore topics such as the relationship between economic growth and household income, the impact of household indebtedness on financial well-being, and the efficacy of government initiatives targeting economic upliftment. Key questions that can be addressed using the dataset include comparisons of average monthly household income and consumption expenditure, identification of states with high savings rates, analysis of household indebtedness, assessment of microfinance institution association, and variations in average landholding sizes across states.
Data last updated	2016-17
Data retreival date	2016-17
Datastore active	True
Granularity	State
Has views	True
Id	543019a1-3a88-4f8a-990d-b05a78e925d7
Idp ready	True
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	fa8b16a6-231b-4c8a-ab3b-fcff1b5a4740
Position	0
Sku	nabard-nafis-st-ot-meg
State	active
States uts no	1
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.
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-meg
Dataset Frequency
Years Covered	2016-17
No of States/UT(s)	1
No of Districts
No of Tehsils/blocks
No of Gram Panchayats
Additional Information	nan
Number of Indicators	9
Insights from the dataset	The NABARD All India Rural Financial Inclusion Survey (NAFIS) for Meghalaya offers valuable insights into the economic landscape of rural households. Researchers and policymakers can explore topics such as the relationship between economic growth and household income, the impact of household indebtedness on financial well-being, and the efficacy of government initiatives targeting economic upliftment. Key questions that can be addressed using the dataset include comparisons of average monthly household income and consumption expenditure, identification of states with high savings rates, analysis of household indebtedness, assessment of microfinance institution association, and variations in average landholding sizes across states.
IDP Ready	Yes