Page 388 - Special Topic Session (STS) - Volume 4

STS2319 Lakshman N. R. et al.
Context of Study and Setting: Labor Force Survey (LFS) in Viet Nam
This study builds on empirical evidence from Viet Nam on how a switch to
CAPI would affect interview length, costs, and data quality. The study was
conducted as part of an ADB statistics capacity building project that aims to
improve data collection and management of national surveys in support of
the Sustainable Development Goals (SDGs) using information and
communication technology tools, such as CAPI.
The study focuses on one of the major surveys implemented by Viet Nam’s
General Statistics Office (GSO), the LFS. The survey is implemented on a
quarterly basis to obtain estimates of the country’s labor market and serves to
lay the groundwork for labor policies. The LFS survey instrument builds on
previous versions and is continuously updated based on the
recommendations of the International Labor Organization (ILO). The survey
consists of 71 questions grouped into three main sections, namely (a)
household and resident information (b) respondent characteristics, and (c)
questions for classifying economic status. The sampling frame of this survey is
based on the 2014 Intercensal Population and Housing Survey and the sample
is drawn from a two-stage stratified sample, while the enumeration areas (EAs)
are selected proportional to the size of the two independent sub-sample
frames (urban and rural). The sample is nationally representative for 63
provinces/cities and can be disaggregated quarterly down to 6 major
economic regions, the cities of Hanoi and Ho Chi Minh,
and rural and urban areas.

Research Objective
Using a randomized roll out of CAPI and PAPI LFS surveys, with a focus on
Ho Chi Minh, the study aims to provide answers to the following questions:
1. What effect does CAPI have on interview time?
2. Does CAPI help reduce the number of errors made in the questionnaire
and are there implications for recruitment of enumerators when
switching from PAPI to CAPI?
3. What are the cost implications of switching to CAPI?

Relevance
Data collection methods have a bearing in the data sets provided for
analysis. The implications are even greater for national statistics systems or
offices where quality of data is crucial for them to come up with meaningful
insights to serve long term policy. As such, it matters to look at ways to
improve data collection. This study sheds light on the practicality and
advantage of transitioning to CAPI by looking at tangible benefits such as
interview length or time and the reduction in errors. Furthermore, it also
potentially provides policy input on other variables involved in data collection
such as the important characteristics to consider for the hiring enumerators.

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