Transcript An Innovative Measurement Method of Basic Needs Mixing Objective and Subjective Information Work in Progress Christophe Muller DEFI, AMSE, Aix-Marseille University July 2011

An Innovative Measurement Method of Basic Needs
Mixing Objective and Subjective Information
Work in Progress
Christophe Muller
DEFI, AMSE, Aix-Marseille University
July 2011
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1. Introduction
▪ A proper notion of poverty in society
–
Corresponds to the well-thought opinions of citizens
–
Conflicts with current approaches of poverty lines and poverty statistics
–
•
Expert opinions
•
Biological benchmarks
•
Arbitrary statistics (1 $ a day, half median...)
What people think poverty means
▪ Uses of Self-Reported Basic Needs
–
Poverty and income distribution analyses
–
Individual and household decision models
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Potential issues with self-evaluated basic needs
- COMPARABILITY ACROSS RESPONDENTS
- NON INDEPENDENCE FROM OUTCOMES TO EXPLAIN
•
Application to assistance system
•
Financial Incentives to lie
-
LESS RELIABLE THAN OBJECTIVE MEASURES
-
COMPARING SELF-ASSESSED NEEDS WITH CONSUMPTION FOR EACH HOUSEHOLD (I.E. DISTRIBUTION
MATCHES) YIELDS TOO NOISY RESULTS TO BE USABLE
- HARD TO OBSERVE ACCURATELY
- INSINCERE ANSWERS
- UNCLEAR TO RESPONDENT
- NO CLUES
- ERRATIC INDIVIDUAL EFFECTS
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Potential advantages of self-evaluated basic needs
-THERE IS RELIABILITY (~ 0.5)
- HOW TO BEST EXTRACT THE RELEVANT CORE INFORMATION
- NO CONSENSUS ON THE POVERTY LINE METHOD ANYWAY
•
Unreasonable methods are not rare
•
Using nutritional minima is unrealistic for many countries
- NOT SUBJECT TO THE IGNORANCE OF INDIVIDUAL SITUATIONS BY EXTERNAL OBSERVERS
-UTILITY-CONSISTENT IF INDIVIDUALS KNOW WHAT IS BEST FOR THEM
- DO NOT ALWAYS REQUIRE EQUIVALENCE SCALES
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2. Context and Data

Republic of Mauritius in 2006/7
–
2006 Household Budget Survey
–
Nutritional Poverty Profile
–
Request for adaption of poverty statistics to an advanced development stage

A Special Survey for Measuring Subjective Basic Needs
–
2008 Living Condition Survey
–
Collaboration CSO-UNDP
–
Aim: getting better poverty lines anchored on realistic basic needs
–
Sub-sample of 2006 Household Budget Survey

Uses of the new poverty lines
–
Official poverty statistics
–
Targeting statistics
–
Design and improvement of social policies in Mauritius
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Our Strategy for Basic Needs Indicators

Selecting logically consistent answers
–
An observed household is deemed consistent when:
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either (1) its consumption is in excess of its self-stated basic needs AND it declares itself as nondestitute in a considered qualitative question;
–
or (2) its consumption is below its self-stated basic needs AND it declares itself as destitute in a
considered qualitative question.
–
For different categories of goods

Controlling for individual erratic effects
- Concentrating on food basic needs: the better observed needs and consumption
-
Aggregating to use a central tendency as anchor for the poverty line estimation
-
Excluding outliers and mistakes
-
Controlling for individual effects:
* A new econometric method for cross-section regressions
* Extracting individual effects from other basic needs equations
3. Estimated Basic Needs
Consistent
household (%)
Mean Self-assessment
household food basic
needs
(LCS Nov2008) (Rs)
Average household
expenditure on food
(HBS2006/07)(Rs)
Ability of household to
meet daily basic food
needs?
61.1
4170
5997
Does household consume
“riz ration”?
27.7
4438
4860
Is household self sufficient
in fish/meat/chicken
consumption?
28.2
4571
4823
Does household have to
borrow money to buy
food?
28.1
4462
4971
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A New Method for Individual Effect Control
•Taking advantage of similar phenomena simultaneously
measured for the same individuals
• Self-Assessment of basic needs for several consumption
categories: food, housing, clothing, health, education
•SMij, j= 1,...5 are the goods, i is the individual index
• The model: SMij = gj(Xi) fi uij
•Xi are typical independent variables,
•fi is the unobserved individual effect variable
• uij are error terms
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• Simple estimators of individual effects fi can be
generated from each secondary good equation
Empirical analogs of:
ln(SMij ) – Mean(ln(SMij)) - gj(Xi) + Mean(gj(Xi) )
•For j different from 1
•To include in the ln(SM1) equation for food.
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Correlates of Consistent Log Food Basic Needs
Number of obs =
920 R-squared
= 0.4793
ei_cloth |
ei_housing |
ei_health |
Coef. Std. Err.
t
.0959786 .0171521
.0965442 .0248727
.0208055 .0127216
age |
room |
sex |
n13 |
n410 |
n1116 |
n1721 |
n2259 |
n60 |
.0016652 .0013742 1.21 0.226
.0016167 .0074483 0.22 0.828
-.1685794 .0472513 -3.57 0.000
.0923126 .0240365 3.84 0.000
.0687213 .0181334 3.79 0.000
.1238146 .0183668 6.74 0.000
.1175631 .0185373 6.34 0.000
.152178 .0125792 12.10 0.000
.1980666 .0254644 7.78 0.000
district_d~2 |
district_d~3 |
district_d~4 |
district_d~5 |
district_d~6 |
district_d~7 |
district_d~8 |
district_d~9 |
district_~10 |
.0792172
.1448836
.2223407
.2521609
.1573245
.0275595
.2928428
.2066021
.0630789
.0809322
.0819476
.0802721
.083598
.0841895
.0435975
.0860717
.0919369
.0845483
P>|t|
5.60 0.000
3.88 0.000
1.64 0.102
0.98
1.77
2.77
3.02
1.87
0.63
3.40
2.25
0.75
0.328
0.077
0.006
0.003
0.062
0.527
0.001
0.025
0.456
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building_d~2 |
tenure_dum~1 |
tenure_dum~3 |
.0173235 .0265064 0.65 0.514
.060169 .0454859 1.32 0.186
.0426515 .0536443 0.80 0.427
educ_no~y |
educ_high |
educ_co~e |
.0172653 .0292946
.0195854 .0291216
.0151804 .0567269
0.59 0.556
0.67 0.501
0.27 0.789
activit~1 |
activit~2 |
activit~4 |
.0595621 .0360397
.0626847 .0416989
.1103974 .0553114
1.65 0.099
1.50 0.133
2.00 0.046
cooklpg_du~y |
lcsmarital~1 |
car_dummy |
van_dummy |
dcab_dummy |
mcycle_dummy |
.030092
.0199681
.0156389
.0630376
.0133242
.0440583
lsp_sq |
lsp |
-2.92e-09 3.79e-10
.0000894 9.43e-06
savings |
priority_~p1 |
priority_e~4 |
priority_e~5 |
priority_e~8 |
reqsocialaid |
check1 |
telephone |
urbanrural |
_cons |
.0087989 .0238832 0.37
.0503988 .0308288 1.63
.0343247 .0323022 1.06
.0330141 .0434224 0.76
.0320459 .0384065 0.83
-.0343265 .0314591 -1.09
-.0820029 .0311165 -2.64
-1.44e-08 6.21e-09 -2.32
-.0862697 .037277 -2.31
7.536526 .1631736 46.19
.042303 0.71 0.477
.041463 0.48 0.630
.0375727 0.42 0.677
.0651886 0.97 0.334
.0798519 0.17 0.868
.0260842 1.69 0.092
-7.69 0.000
9.48 0.000
0.713
0.102
0.288
0.447
0.404
0.276
0.009
0.021
0.021
0.000
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Poverty Line Estimation
- Accounting for consumer substitutions
-Based on an estimated food Engel curve
- Linearized QAIDS
- Mean self-assessment of their food basic needs by consistent
households → defining food poverty thresholds: ZF
si = α + β ln(xi) + γ [ln(xi)]2 + Ni’ δ + εi,
- Food budget share of household i = si
- Total expenditure of household i = xi
- Household and environment characteristics = Ni
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Robust regression estimates
Independent Variables
Log total expenditure
Squared Log total
expenditure
Children 1-3
Children 4-10
Children 11-16
Adults 17-21
Adults 22-59
Elderlies 60 and over
District 1
District 2
District 3
District 4
District 5
District 6
District 7
District 8
District 9
Education of the head (years)
Intercept
Coefficient
(standard errors)
.113
( .0544)
-.0147
(.00302)
.0219
(.00312)
.0213
(.00220)
.0197
(00225)
.0148
(.00263)
.0230
(.00166)
.0434
(.00264)
-.0235
.00685
-.0271
(.00692)
-.0161
(.00717)
-.0223
(.00681)
-.0112
(.00712)
.00799
(.00599)
-.0306
(.00599)
-.0277
(.00788)
-.0166
(.00812)
-.00196
(.000326)
.571
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Solving for the poverty line
Once the parameters are estimated the poverty line, Zj is obtained by solving in Z
the following equation:
ZF/Z = Concentrated intercept + β ln(Z) + γ [ln(Z)]2
For example with a Newton method
Poverty line for Mauritius: 2217 Rupees a month.
For Rodrigues: 1556 Rupees a month.
7.06 percent of households are under the poverty line.
The poverty rates:
7.79 percent in the whole Republic
7.54 percent in Mauritius Island
15.2 percent in Rodrigues.
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Table 1: Estimated Poverty Rates (%)
Region
Republic of Mauritius
2006
Tunisia
1995
Gambia
2003
General poverty
line
Nutritional
poverty line
Nutritional poverty line
Urban
5.7
4.07
13.87
39.6
Rural
8.9
6.30
25.86
67.8
Comparison of general poverty profile and nutritional poverty profile :
Table 2 – Headcount poverty rates by urban & rural regions
Head-count index (%)
Poverty gap measure (%)
Poverty severity measure (%)
Watts poverty measure (%)
Island of Mauritius
Island of
Rodrigues
Republic of Mauritius
7.54
(0.443)
1.49
(0.119)
0.477
(0.0527)
1.84
(0.160)
15.2
(1.90)
3.76
(0.572)
1.39
(0.275)
4.85
(0.791)
7.79
(0.433)
1.57
(0.117)
0.506
(0.052)
1.94
(0.157)
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Table 2 –Headcount poverty rates by household size
Republic of Mauritius
Household size
1
2
3
4
5
6 and more
7 and more
8 and more
General
poverty line
Nutritional
poverty line
9.16
6.41
4.09
6.42
7.27
15.0
NA
NA
1.35
1.01
2.56
3.88
5.2
14.5
NA
NA
Tunisia
Gambia
Nutritional poverty line
3.59
3.54
6.85
11.45
14.91
22.02
27.81
7.2
11.2
15.6
25.3
35.6
40.5
65.5
NA
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•Higher general poverty for households led by :
 Unemployed heads
 Separated heads or widows
 Female heads
 Elderly heads
 Little educated heads
Other categories of households especially affected by general poverty are:
 Large size households
 Households dwelling in disadvantaged areas in terms of the Relative
Development Index used in Mauritius to characterized disadvantaged
area.
Higher levels of poverty measures than with nutritional profile, while still
realistic.
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5. Conclusion

A NEW METHOD MIXING SUBJECTIVE AND OBJECTIVE INFORMATION TO ESTIMATE
BASIC NEEDS AND POVERTY LINES

MORE REALISTIC THAN CURRENT METHODS, EXCEPT FOR EXTREMELY POOR
COUNTRIES: ELICITING THE WELL-THOUGHT OPINION OF THE POPULATION

MATCHING A SPECIAL SURVEY WITH TYPICAL HOUSEHOLD BUDGET SURVEY

SELECTION OF CONSISTENT ANSWERS USING DESTITUTION INFORMATION

A NEW METHOD FOR CONTROLLING FOR INDIVIDUAL EFFECTS IN CROSS
SECTIONS

LARGE NUMBER OF INDEPENDENT VARIABLES IN BASIC NEEDS EQUATIONS,
INCLUDING INDIVIDUAL EFFECTS, LIVING STANDARD, DEMOGRAPHICS, HUMAN
CAPITAL, ENVIRONMENT, COLLECTION CHECKS, RELATIVE INCOME…

CENTRAL TENDENCY FOOD TO ANCHOR POVERTY LINE INSTEAD OF MATCHING
DISTRIBUTIONS OF NEEDS AND CONSUMPTIONS

YIELDS AN ‘OBJECTIVE’ CORE FROM SUBJECTIVE DATA

APPLICATION TO POVERTY ANALYSIS AND SOCIAL POLICY IN MAURITIUS
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