Data on the Effectiveness of Malaysian Government Assistance Program on Urban B40 Households during COVID-19 Pandemic

This data article presents the data on the effectiveness of the Malaysian government assistance program on urban B40 households during the COVID-19 pandemic. Survey questionnaires were administered by a team of enumerators to a total of 706 urban B40 households in Malaysia for data collection. Data were collected based on six regional locations namely northern, central, eastern, and southern parts of Peninsular Malaysia and East Malaysia. The survey was conducted in six Malaysian states selected based on regional location covering the Peninsular and West part of Malaysia viz. Johor, Pahang, Selangor, Pulau Pinang, Sabah and Sarawak. The Department of Statistics Malaysia (DOSM) utilized a simple random sampling method to identify the eligible participants from each state based on the sampling frame identified. Data were collected by a team of enumerators from October 2020 until May 2021. The datasets contain reliable data on the socio-economic profile and government assistance programs during the COVID-19 pandemic on urban B40 households as the data sampling is representative of the population in Malaysia. The data provides important information on the different types of government assistance programs received by the urban B40 Households in Malaysia. The findings could be useful to evaluate the effectiveness of the financial aid received during a crisis.

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Identifier
DOI https://doi.org/10.17632/my3y7nv8ns.2
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-ic-ual7
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:255945
Provenance
Creator Zaidi, M
Publisher Data Archiving and Networked Services (DANS)
Contributor Mohd Azlan Shah Zaidi
Publication Year 2022
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/licenses/by/4.0; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Representation
Resource Type Dataset
Discipline Other