Lilian Galer , [email protected] Ala Negruta, [email protected]
description
Transcript of Lilian Galer , [email protected] Ala Negruta, [email protected]
The Improvement of HBS in the Republic of Moldova
European Conference on Quality in Official Statistics, Rome, Italy
Lilian Galer, [email protected] Negruta, [email protected]
Areas of improvement
Questionnaire improvements Sampling improvements
The HBS The HBS is an important source of economic and social
data, it provides data on: Measures of living standards Consumption and income structure Weights for consumer price index Various estimates for the National Accounts
The HBS can inform economic and social policy and monitor the impact of government reforms
It is a continuous activity of the NBS, with household interviews conducted throughout the year, and households completing both a general interview and a ‘diary’ in which households report consumption and income
Questionnaire improvements (I)
In 2004 and 2005 the NBS conducted various experiments in order to improve the questionnaire design, such experiments guided the changes implemented in 2006
The main questionnaire changes affected the following areas: Changes in the reference period of some income sources
and expenditure items Modification of Diary - improved layout of the diary (the
questionnaire booklet that helps the household to record income and expenditure transactions)
Re-adjustment of the definitions of employment indicators and household members
Questionnaire improvements (II) Reference period
Indicators Before 2006 From 2006
1. Cash incomes of household’s members current month current month
2. Incomes from individual agricultural activity current month last 12 months and current month
3. Expenditures for individual agricultural activity current month last 12 months and current month
4. Expenditures for utility services current month for all types of utilities
current month and the last 12 months for
some types (central heating, wood, coal, gas)
5. Expenditures for food products procurement current month Half a month
6. Consumption of products from own production and the ones received for free
current month On a weekly basis during the month
of interview
The HBS used to rely on current monthly expenditure to estimate household consumption expenditureWhile this provides good national average estimates, it can be misleading when our purpose is to compare households’ living standards
Example of expenditure for central heating in 2007 98% of households with central heating reported such
expenditure when asked about expenses in the last 12 months
But only 52% of households with central heating reported expenditure in the current month
When assessing living standards we should include the average monthly expenditure and not how much the household spent in January or July
This problem occurs when we deal with ‘seasonal’ consumption items and more generally for items that are purchased at a frequency lower than one month
When using only the current month expenditure we over-estimate the level of inequality
Questionnaire improvements (III) Reference period
Collected information can now be used to produce both accurate averages for the National Accounts, weights for the consumer price index, and distributional data for poverty analysis. In particular poverty and inequality data have improved
There is a reduced household burden for the participation to the survey (the household needs to spend less time to complete the required information)
Improvement in the measurement of some key statistics (remittances and agricultural income)
Employment data are now collected ensuring comparability with definitions used in the Labour Force Survey
Questionnaire improvements (III) Effects of questionnaire changes
Both income and consumption are now estimated at much higher levels than in 2005
This is in line with estimates from the National accounts
0
200
400
600
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1000
1200
1400
2004 2005 2006 2007
medii lunare pe o
persoană, lei
CBGC CN
Questionnaire improvements (IV) Effects of questionnaire changes
Old HBS sample design
Probability, stratified, two stage sample Sample frame:
I stage – electoral divisions II stage – electoral lists
Stratification: Cities Towns Rural area
Sample size: I stage – 45 PSUs II stage – 36 households/quarter/PSU
Necesity of improvements in sampling
The low quality of the sample frame Exhaustion of the lists from sample frame Big design-effect (only 45 PSUs) Bias generated by multiple replacement of
non-respondents Reliability of the main estimates assured
only at the national level and residence area
General characteristics of EMDOS
EMDOS – Master Sample for the Social Surveys Starting from 01.01.06 the HBS and LFS are carried
out on EMDOS Probability, stratified, two stage sample (excepting self
representing cities where it is one stage) EMDOS covers 219 localities grouped in 150 PSUs,
including: 97 in rural area; 53 in urban area;
Reliability of the main estimates at the level of statistical zones;
It is used for others surveys in social sphere
Sampling stages
At the I stage – PSUs’ selection with the probability proportional to there size. Sample frame – list of administrative-territorial units of primary level (PSUs): CUATM.
At the II stage – simple random sampling of households in each selected PSU (exception Chisinau city – proportionally stratified sampling for HBS). Sample frame – list of households addresses (SSUs): list of electricity consumers provided by the electricity companies and updated with using of special listing procedure.
Stratification criteria
Geographic: North (Balti separately) Center South Chisinau Transnistria
Residence area: Urban Rural
Settlements’ size: Big communes Small communes
Sample size
Number of PSUs and households per quarter
Nr of PSUs in the old sample
Nr of households /
quarter in the old sample
Nr of interviewers in the old
sample
Nr of PSUs in EMDOS
Nr of households/
quarter in EMDOS
Nr of interviewers in EMDOS
HBS 45 1620 45 150 2442 150
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Changes in sampling (geographical coverage)
HBS 1997 - 2005
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EMDOS from 2006
PSUs Rotation≈ 20% of PSUs are replaced annually with new onesExcept for the self-representing PSUs:
Chisinau mun. Balti mun. Comrat mun. Cahul town Soroca town Ungheni town
Reasons: Better geographical coverage over time; Avoiding the necessity of complete PSU’s replacement after a
certain period Provide a good continuous comparability of estimates over
time, etc.
Panel and households rotation within PSUs
The panel reflect all the changes encountered within the same households during a period of time.
HBS - panel for 5 years
Households’ rotation: HBS – ½ of households are in for 5 consecutive
years, and ½ are interviewed only once
Grossing up of Surveys Data
Developing and implementation of statistical weights computational procedures, which include:
Base weights calculation and analysis; Non-responses adjustment procedures; Poststratification
Reliability estimation
For the computation of estimates reliability characteristics is used a special variance estimation technique – BRR with the following main advantages:
It allows to estimate variance for complex sample design (taking into consideration design effect);
It can be used for all types of estimators, such as means, sums, proportions, etc.;
Relatively simple to use as it is implemented in most specialized statistical softs – STATA, WesVar, SAS, R, etc.
Reliability of income estimates, by quarters (HBS 2005-2007)
2%
3%
4%
5%
6%
7%
8%
400 500 600 700 800 900 1000 1100 1200 1300
Income per capita, lei
CV,
%
2005 2006 2007
Q I
Q IV
Q III
Q 2 Q IQ I Q II QIV
Q III
Q IV
Q IIIQ II
Design Effect over time (HBS 2005-2007)
5.2
3.9
5.55.9
3.0
1.5 1.7 1.9 1.7
2.5
1.91.5
0
1
2
3
4
5
6
1 q2005
2 q2005
3 q2005
4 q2005
1 q2006
2 q2006
3 q2006
4 q2006
1 q2007
2 q2007
3 q2007
4 q2007
Desi
gn E
ffect
Further activities
More attention to non-sampling errors Using of auxiliary data on electricity for
poststratification Data matching Small Area Estimation Analysis of panel data Further questionnaire improvements to capture
in a better way self-employment in non-agriculture, tax and social contribution payments
Thank You for Your Attention!