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Diapositiva 1

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Patrimony poverty. We know how many poor households exist. However: Where are they? ... Discriminant analysis applied to other information sources (with ... – PowerPoint PPT presentation

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Title: Diapositiva 1


1
URBAN POVERTY ESTIMATES IN MEXICO
MONICA OROZCO
2
  • Households income survey
  • Probabilistic sample
  • Precise income information
  • Rural-urban coverage
  • Official poverty estimates for 2000

3
Patrimony poverty
Capabilities poverty
Nutrition poverty
4
We know how many poor households exist.
However Where are they? Indirect estimates we
lose precision
we obtain location
5
Indirect estimates Discriminant analysis applied
to other information sources (with geographical
reference). Previous experience with
Oportunidades in more than 50,000 communities.
6
Household income
POOR HOUSEHOLDS
NON POOR HOUSEHOLDS
STANDARD
STANDARD
Maximize variance among groups
Minimize variance within group
7
80
70
60
poor households
50
40
2.10
1.00
.656
.378
.148
-.058
-.271
-.492
-.739
-1.81
Marginality index
8
But community is to big in the case of cities
for policy and operational purposes
Percentage of
Urban
poor
Locality
households in
households
poverty
(urban)
lt 2,500
65.5
8.3
2,500 - 4,999
39.5
19.7
5,000 - 14,999
27.9
21.1
15,000 - 49,999
18.2
15.7
50,000 - 99,000
11.2
5.2
100,000 - 499,999
7.5
16.1
500,000 - 999,999
5.0
6.5
1,000,000 and more
5.5
7.4
Total
13.3
100.0
9
  • The best data come from the Populatio Census
    (complete coverage)
  • 2 problems
  • Confidentiality
  • Linkage of statistical data with geographic
    location

10
Link the information of the households in each
block to the map of each city 976,000
blocks in 4,028 localities Aggregate estimates by
block number of households in poverty in each
block Associated variables household members,
age structure, female household head, dwelling
characteristics Define clusters of blocks that
concentrate poverty
11
Block without poor households 42
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