Transcript Poverty measurement in the Republic of Moldova Poverty line evolution 1993 – Minimal consumer budget 2000 – Subsistence level 2004 – first absolute poverty.

Poverty measurement
in the Republic of Moldova
Poverty line evolution
1993 – Minimal consumer budget
2000 – Subsistence level
2004 – first absolute poverty line approved by
Strategy of economic growth and poverty reduction
(SCERS)
 2006– revised absolute poverty line
!!!Starting with 2005 MDG poverty indicators
!!! The National Development Strategy “Moldova 2020” sets forth the
major objective to escape 149 thousand of citizens from poverty by
2020, or over 20% of those who are currently in poverty.
Poverty rate evolution
2004 2005
2006
2007
2008
2009
2010
2011
Total
26,5
29,1
30,2
25,8
26,4
26,3
21,9
17,5
Urban
22,7
22,1
23,7
17,0
16,4
12,4
9,4
7,1
Rural
31,2
36,0
35,9
33,4
37,6
38,7
33,0
27,3
Extreme
poverty rate
14,7
16,1
4,5
2,8
3,2
2,1
1,4
0,9
International
line 4,3$ PPP
-
-
34,5
29,8
30,4
29,5
26,8
23,4
Absolute
poverty rate
Why poverty estimators has been
revised in 2006?
HBS was substantially modified in two main areas:
 the way in which households are selected
(sampling frame and sampling areas): better
coverage and no substitution of hhs
 data collection tools (questionnaires): better
coverage of expenditures, reduction of recording
period for food products, introduction of
reference period for some goods (6 and 12
months), adjustment of occupation definitions,
etc.
Computation of poverty line
 “Basic
need” approach:
- Food component
- Non-food component
 Food component is based on the need to meet certain minimum
nutritional requirements (2282 calories per day). Based on HBS data
all the items consumed in the food basket by a specified population
group. Their relative weights are also based on actual consumption
patterns observed in the data. The population of interest to be the
lower part of the distribution, from the second to the fourth
deciles. In fact focusing on the population located in the low end of
the welfare distribution, we are more likely to reflect the preferences
of the poor as well as the prices that they face.
 Non- food component is computed as a mean multiplier among
households whose expenditure lies within a small interval around
the food poverty line .
Computation of poverty line
 Consumption expenditures are used as indicator of wellbeing
The following adjustment were made:
 for items, whose purchase is infrequent, but still more frequent
than once a year, expenditure are captured through appropriate
recall periods (6 and 12 months),
 items, which generally are purchased within intervals longer
than one year (namely durable items) are excluded from
consumption aggregate,
 imputation of actual consumption and use of services by
correcting for subsidies that are not uniformly received by all
households;
 correction for price differences over time and across different
areas of the country (namely urban and rural areas);
 adjustment of expenditure measured at the household level to
identify individual consumption levels.
Computation of consumption expenditure
Poverty rate varies a lot depending on the
items included in the consumption expenditure
Total
Urban
Rural
food
87,7%
78,2%
94,7%
plus beverages
85,0%
74,2%
92,9%
plus clothes
64,5%
53,2%
72,9%
plus dwelling
34,6%
20,3%
45,1%
plus equipment of dwellings
31,1%
17,7%
40,9%
plus health
25,3%
14,4%
33,3%
plus transport
22,7%
12,1%
30,5%
plus communication
19,5%
10,0%
26,6%
plus miscellaneous/Total poverty rate
16,6%
8,2%
22,8%
Correction for price differences
 The official consumer price index properly corrects for
inflation, but does not take into account regional price
differences.
 Based on HBS data is possible to construct a CPI for food
products, as the survey provides information on budget
shares for all households, but it does not collect
information on prices themselves and the implicit prices is
obtained by dividing expenditure by quantities purchased.
 Combining HBS data and official CPI for services and
non-food items is possible to construct a Paasche price
index at the level of each survey area and for each month
of the survey, and it does correct both for price differences
over time and across regions
Correction for price differences
 The index by month computed using HBS
data and the official CPI are very similar
Month
Cities
HBS implicit price index
Towns
Villages
Overall
Official CPI
Food
January
February
March
April
May
June
July
August
September
October
November
December
1,06
1,05
1,08
1,08
1,14
1,18
1,10
1,10
1,03
1,08
1,15
1,15
0,97
0,98
1,01
1,04
1,09
1,04
1,00
0,95
0,96
1,02
1,03
1,05
0,94
0,95
0,96
0,98
0,98
0,97
0,94
0,89
0,91
0,96
0,98
1,00
0,97
0,98
1,00
1,01
1,04
1,03
0,99
0,96
0,94
0,99
1,03
1,05
0,98
0,99
1,00
1,02
1,03
1,03
0,99
0,96
0,97
0,99
1,02
1,04
Total
1,10
1,01
0,95
1,00
1,00
Correction for price differences
correction for price differences had a significant impact on poverty
rate, without correction to price differences there is an underestimation
of urban poverty and an over estimation of rural ones.
Poverty rate by residence area
45
40
35
%
30
25
20
15
10
5
0
2006
2007
2008
Urban, without price correction
Rural, , without price correction
2009
2010
Urban
Rural
2011
2012
Thank you for attention!