GBU College Logo
Sign in with GBU Microsoft

Evaluating Census Data Quality Governance through Post Enumeration Surveys: A Comparative Study of Three National Statistical Systems

Journal of Logistics, Informatics and Service Science | 2026

Paper Details

Authors: Khatiwada P.P.; Shrestha B.; Samir K.C.

DOI: 10.33168/JLISS.2026.0612

Journal: Journal of Logistics, Informatics and Service Science

Year: 2026

Publisher: Success Culture Press

Document Type: Article

Open Access: All Open Access; Gold Open Access

Cited by: 0

Abstract

The Post-Enumeration Survey (PES) is one of the most effective methods for assessing census accuracy because it measures the extent of both undercounting and overcounting. This study examines data quality management practices in three nations that conducted their recent census operations. All these countries underwent a rapid digital transition during the COVID-19 pandemic. The study demonstrates how digital tablets and GIS systems have attracted stakeholder interest by providing reliable national policy data derived from PES results of these nations past censuses. The analysis further proves that net under-count rates of 2.58% in Nepal, 2.75% in Bangladesh, and 3.3% in South Africa. The new technologies have improved data pipeline processes, but still fail to count all children, including those from underrepresented communities. The results indicate that a country's stage of technological advancement does not guarantee the elimination of coverage errors, which tend to occur during periods of rapid urban growth and population movement. The PES system requires a transformation from its current function as an error-detection tool into a forward-looking service science framework, underpinned by data quality governance, to support fair resource distribution through census data. The change is necessary to develop digital workflows and automated algorithms that can effectively handle the economic diversity present in developing countries. © 2026, Success Culture Press. All rights reserved.

Keywords

Census accuracy; Census innovation; Coverage and content error; Digital data capture; Informatics