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International Standards and Contemporary Technologies
Quality Assessment of the Population and Housing Census 2014 Republic of Moldova Supported by UNFPA Moldova and the Swiss Agency for Development and Cooperation United Nations Regional Workshop on the 2020 World Programme on Population and Housing Censuses: International Standards and Contemporary Technologies Tbilisi, April 2018
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Summary Introduction Post Enumeration Survey (PES) Results
Problems and challenges faced Conclusions
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Evaluation of the quality – support from the UNFPA and SDC
General issues Population and Housing Census 2014 (PHC 2014) – 12 – 25 May 2014 PHC 2014 – second Census after Independence and the first PHC Traditional Census. The reference period – 12th May 2014 at a.m Evaluation of the quality: Post Enumeration Survey Administrative data – electricity data Evaluation of the quality – support from the UNFPA and SDC The first PES Residents from residential dwelling from the territory under control of the Goverment No previous experience of the staff Limited human resources Decision to conduct the PES – 3 months before Census
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PES PES - aim Coverage evaluation Content evaluation
Evaluation of PHC procedures Evaluation of EAs delineation
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Independency PES – was led by Statistical Methods Unit and Social Statistics Department Totally independent from Census operations PHC fieldwork was completed and Census material was collected Best Census enumerators – assigned to different EAs Only PES team knew in advance the sampled EAs
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PES – data collection I Mobile teams’ distribution
90 enumerators grouped in 9 mobile teams Average load per team – 10 EAs Each team - coordinated by 1 supervisor Supervisors – NBS staff Daily progress reporting to head office 16 – 29 July
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PES – data collection II
Gender Birth date Civil status Variabiles to define resident status Education level Relation to the head Questionnaire - simplified version of PHC one:
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PES – data processing C MAKSA C MARCSA C MARX CARL MARX CARLA MARCS
CARLA MARCSA CARLA MARSCA CARLA MARXA CARLO-MARCSA K MARCSA K MARKSA KARL MARX KARLA MARKSA KARLA MARXA MARCSA Started after 23 months of data collection Manual data entry in CSPro application Double data entry Need of standardization for string variables – up to 53 different spellings for the same street name
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PES – data linkage I Lack of unique persons’ ID
Used variables: name, address, date of birth, sex and household head First attempt – deterministic method – 7 months of work without acceptable results Probabilistic method – using RELAIS – 4 months of work Model used – Fellegi-Sunter
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at the circumscriptie level (the third level) – 10.1%
PES – data linkage II at the EA level % at the country level – 0.6% at the section level (the second level in PHC data collection hierarchy) – 6.1% at the circumscriptie level (the third level) – 10.1% at the locality level (the lowest level of administrative division in the Republic of Moldova) – 2.1% at the raion level (the first level of administrative organization) – 0.9%
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Electricity data (GNF) - characteristics
Owner – private company Monthly consumption per dwelling/household, in kW Analyzed period – one year before Census Aim – estimation of over-coverage Limited number of variables for data linkage – name and address
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Estimation methodology
assessment of the under-coverage (under-coverage rate) assessment of the over-coverage (over-coverage rate) estimation of the true population estimation of the coverage indicators (census omission, erroneous inclusion and net undercounts and rates) Dual System Estimation
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2.7% of non-resident were enumerated
The main results 11.8% of residents were not covered (app. 302 thousand residents). Biggest under-coverage rate – Chisinau city (43.6%) 2.7% of non-resident were enumerated Estimated residents’ number: by PHC – 2562 thousands persons by PES – 2824 thousands persons The number for Chisinau city was corrected from to thousands persons
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The net undercount rate
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Content quality indicators
Variables Rate of agreement, (%) Sex 97.8 Age, 10 years group range 96.7 Marrital status 88.8 Education level 57.4 Presence of person in the household 91.8 Persons abroad 95.1
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Problems and challenges of the PES
Limited time to proper design and conduct PES (no pilot) No any previous experience Very limited staff Unknown budget at the moment when decision was taken Manual preparation of the sample frame Missing addresses in rural area and low quality maps Challenges determined by using of mobile teams No reconciliation visits The limits of some EAs were changed during data collection. For others the IDs were changed The probabilistic linkage - done by only two persons during 4 months, working 12 hours a day
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Problems in using of admin data
Few variables available for data linkage (name and address) Non updated names of the persons Only name of the owner is mentioned in the database Various spellings of the same address The electricity data territorial identifier doesn’t correspond to the official administrative division of the country Unusual values in the database
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Problems in PHC 2014 identified through PES
The delineation of EAs was done mainly based on the list of dwellings and not on the map – some problems in EAs identification Maps were of poor quality (with orthophoto in black and white) No EAs database – info was kept into different Excel files. Duplications of EAs IDs For some EAs - limits were changed during the data collection Manual data entry – no control over persons’ ID between questionnaires
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Conclusions and recommendations
Preparation for the next PHC and PES should start earlier with detailed and adequate planning of human, technical and financial resources Dedicated human resources should be allocated for PES The preparation of the fieldwork (mapping, address system, methodology for EAs delineation, GIS) should start immediately EAs delineation should be done using GIS technologies at the address point level It is highly recommended to include the reconciliation visits as the phase of the PES in the initial planning For the assessment of over-coverage it can be also used other alternative sources (e.g. Labor Force Survey); A system of daily monitoring for both PHC and PES should be developed
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Thank you! Valentina Istrati Lilian Galer Head, Demographic Statistics
and Population Census Division Lilian Galer Head, Statistical Methods Section
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