The objective of this three-year panel survey is to provide the Government of Nepal with empirical evidence on the patterns of exposure to shocks at the household level and on the vulnerability of households’ welfare to these shocks. It covers 6,000 households in non-metropolitan areas of Nepal, which were interviewed in mid 2016. Being a relatively comprehensive and representative (rural) sample household survey, it can also be used for other research into living conditions of Nepali households in rural areas. This is the entire dataset for the first wave of the survey. The same households will be reinterviewed in mid 2017 and mid 2018. The survey dataset contains a multi-topic survey which was completed for each of the 6,000 households, and a community survey fielded to a senior community representative at the village development committee (VDC) level in each of the 400 PSUs.
Kind of data
Sample survey data [ssd]
All non-metropolitan areas in Nepal. Non-metropolitan areas are as defined by the 2010 Census.
Unit of analysis
Household, following the NLSS definition.
Producers and sponsors
Full Bright (Pvt) Ltd
UK Department for International Development
The sample frame was all households in non-metropolitan areas per the 2010 Census definition, excluding households in the Kathmandu valley (Kathmandu, Lalitpur and Bhaktapur districts). The country was segmented into 11 analytical strata, defined to correspond to those used in the NLSS III (excluding the three urban strata used there). To increase the concentration of sampled households, 50 of the 75 districts in Nepal were selected with probability proportional to size (the measure of size being the number of households). PSUs were selected with probability proportional to size from the entire list of wards in the 50 selected districts, one stratum at a time. The number of PSUs per stratum is proportional to the stratum's population share, and corresponds closely to the allocations used in the LFS-II and NLSS-III (adjusted for different overall numbers of PSUs in those surveys).
In each of the selected PSUs (administrative wards), survey teams compiled a list of households in the ward based on existing administrative records, and cross-checked with local leaders. The number of households shown in the list was compared to the ward population in the 2010 Census, adjusted for likely population growth. Where the listed population deviated by more than 10% from the projected population based on the Census data, the team conducted a full listing of households in the ward. 15 households were selected at random from the ward list for interviewing, and a further 5 households were selected as potential replacements.
Deviations from sample design
During the fieldwork, one PSU in Lapu VDC was inaccessible due to weather, and was replaced by a ward in Hastichaur VDC using PPS sampling on that stratum (excluding the already selected PSUs). All other sampled PSUs were reached, and a full sample of 6,000 households was interviewed in the first wave.
Of the 6,000 originally sampled households, 5,191 agreed to be interviewed. Of the 13.5% of households that were not interviewed, 11.1% were resident but could not be located by the team after two attempts, 0.9% were found to have outmigrated, and 1.4% refused. The 809 replacement households were drawn in order from the randomized list created during sampling (see above).
Dates of collection
Mode of data collection
Computer Assisted Personal Interview [capi]
The household questionnaire contained 16 modules: the household roster; education; health; housing and access to facilities; food expenses and home production; non-food expenditures and inventory of durable goods; jobs and time use; wage jobs; farming and livestock; non-agriculture enterprises/activities; migration; credit, savings, and financial assets; private assistance; public assistance; shocks; and anthropometrics (for children less than 5 years). Where possible, the style of questions was kept similar to those used in the NLSS-III questionnaire for comparability reasons. In some cases, new modules needed to be developed. The shocks questionnaire was developed by the World Bank team. A food security module was added based on the design recommended by USAID, and a psychosocial questionnaire was also developed by social development specialists in the World Bank. The section on government and other assistance was also redesigned to cover a broader range of programs and elicit information on details such as experience with enrollment and frequency of payment.
The community questionnaire was fielded to a senior community representative at the VDC level in each of the 400 PSUs. The purpose of the community questionnaire was to obtain further details on access to services in each PSU, to gather information on shocks at the community level, and to collect market price data. The questionnaire had six modules: respondent details; community characteristics; access to facilities; educational facilities; community shocks, household shocks; and market price.
These are the raw data entered and checked by the survey firm, formatted to conform to the original questionnaire numbering system and confidentialized. The data were cleaned for spelling errors and translation of Nepali phrases, and suspicious values were checked by calling respondents. No other transformations have taken place.
The data are confidential, thus names, addresses and GPS coordinates have been redacted.
Data may be used with the citation below. Prospective users are kindly requested to contact the World Bank at the above email address and provide a brief description of the planned use of the data, and to share copies of any publications created with the data.
Nepal Household Risk and Vulnerability Survey, Wave 1, 2016. Social Protection and Jobs Global Practice, The World Bank. Data downloaded from [url] on [date]
Disclaimer and copyrights
While all due care has been taken to ensure that the data are free of errors and omissions, the original collectors of the data, the Microdata Library, and the relevant funding agencies bear no responsibility for any use of the data or for interpretations or inferences based upon such uses.