The Improvement of HBS in the Republic of Moldova

European Conference on Quality in Official Statistics, Rome, Italy

Lilian Galer, lilian.galer@statistica.mdAla Negruta, ala.negruta@statistica.md

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

800

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

ÊÚÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚÊÚ

ÊÚ ÊÚÊÚ

ÊÚÊÚ

ÊÚÊÚ

ÊÚ

ÊÚÊÚ

ÊÚ

ÊÚÊÚ

ÊÚÊÚ ÊÚ

ÊÚÊÚÊÚÊÚÊÚÊÚÊÚÊÚÊÚÊÚ

ÊÚÊÚ ÊÚÊÚ

ÊÚ ÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚ

Changes in sampling (geographical coverage)

HBS 1997 - 2005

ÊÚ

ÊÚÊÚ ÊÚ

ÊÚ ÊÚ ÊÚ

ÊÚ

ÊÚÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚÊÚ

ÊÚ

ÊÚ

ÊÚ ÊÚÊÚÊÚ

ÊÚ

ÊÚÊÚ

ÊÚÊÚÊÚ

ÊÚ

ÊÚÊÚÊÚÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚ ÊÚÊÚ

ÊÚ

ÊÚ

ÊÚÊÚ

ÊÚÊÚÊÚÊÚ

ÊÚ ÊÚ

ÊÚ ÊÚ ÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚÊÚ

ÊÚÊÚÊÚ

ÊÚ ÊÚÊÚÊÚÊÚ

ÊÚ ÊÚÊÚ ÊÚ

ÊÚÊÚÊÚ ÊÚ

ÊÚ ÊÚ

ÊÚÊÚÊÚÊÚ

ÊÚÊÚÊÚÊÚÊÚ

ÊÚÊÚÊÚ

ÊÚÊÚÊÚÊÚ

ÊÚ ÊÚ

ÊÚ ÊÚ

ÊÚ

ÊÚÊÚ

ÊÚÊÚ

ÊÚ

ÊÚ ÊÚÊÚ

ÊÚ

ÊÚÊÚ

ÊÚ

ÊÚÊÚÊÚÊÚÊÚÊÚ

ÊÚ

ÊÚ

ÊÚÊÚ

ÊÚÊÚÊÚ

ÊÚÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚ

ÊÚ

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!