Multidimensional poverty in developed countries: German experiences (Empirical Applications based on SOEP-Data)
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1 Multidimensional poverty in developed countries: German experiences (Empirical Applications based on SOEP-Data) Peter Krause / Christoph Jindra Workshop on Measuring Human Development June 14, 2013, GIZ, Eschborn, Germany
2 Content I Motivation Why using multiple poverty measures? Advantages to conventional income based poverty analyses? II Database & Methods Database: German Socio-Economic Panel Study (SOEP) Methods: Multiple Poverty Index (MPI), Alkire/Foster (2011) Multiple Dimensions (n-items) [level of aggregation]: HH-Income (2-5/6) [H] Health (1) [Ind] Education (1) [Ind] Work-Intensity (1) [H] Housing (1) [H] SWB (1) [Ind] 2
3 Content III IV Results I Review on income based poverty analyses [total population, 1984(1995) 2011] One-dimensional vs. multi-dimensional approaches Longterm development, Age profiles (for periods) Robustness (n-of items/dimensions) Cardinal Approaches (Multiple FGT-Measures) Results II Review on income based poverty analyses [respondents population, 1994/5 2011] Six Dimensions: Developments and Age profiles Weighting (Reducing impact of income on patterns of deprivation) 3
4 Content V Discussion Advantages and shortcomings of multidimensional poverty measures Tasks for further developments: Identification: 1st Cutoffs / 2nd cutoffs (absolute/relativ lines; time) Weighting of dimensions Aggregation: Correlation based poverty measures Final Remarks References Many thanks to OPHI Jose Manuel Roche.., Sabina Alkire, a.o. for sending us a new version of their MPI-Stata-programs!!! 4
5 I Motivation Motivation Why using multiple poverty measures? Advantages to conventional income based poverty analyses? How can we handle multiple deprivation measured at different aggregation levels on different scaling? Outline Empirical application Review of conventional income poverty measures Lonterm development & age profiles Applications of multi-dimenional poverty measures 5
6 II Database & Methods Database: German Socio-Economic Panel (SOEP) Database Infrastructure for the German Socio-Economic Panel SOEP(core) Representative annual longitudinal household survey since 1984 Regular Inclusion of new subsamples in 2010: households, with persons SOEP-IS (SOEP Innovation Sample) Established in 2011 (based on subsamples of SOEPcore) Inclusion of innovative survey modules, experiments and tests [SOEP-Pretests] [SOEP-RS (related studies)] 6
7 II Database & Methods Methods: Multidimensional Poverty Index (MPI) 7
8 II Database & Methods Methods: Multidimensional Poverty Index (MPI) 8
9 II Database & Methods Methods: Multidimensional Poverty Index (MPI) 9
10 II Database & Methods Methods: Multidimensional Poverty Index (MPI) 10
11 II Database & Methods Methods: Multidimensional Poverty Index (MPI) 11
12 III Results I Income Poverty Measures for Income related poverty items [Total population] Household-Net-Income, equivalized (rev. OECD-Scale); price levels of 2010 (sep. adjustments for prices between East and West till 1998); Type of Incomes Monthly Income (Screener) Annual Income (previous year) Imputed Rent Annual Income (previous year) Type of Poverty Definitions Cutoff: 60%-median of equiv. HH-Net-Income Current year / anchored in time (lagged income reference level for absolute impacts on income poverty) Measures Head Count [H], FGT 12
13 III Results I Income Poverty Montly & annual incomes longterm development of poverty rates percent 25,0 22,5 20,0 17,5 15,0 12,5 10,0 7,5 5, pov(h) HH-Inc/month pov(h) HH-Inc/p.year mpov(hi) HH-Inc(2D) mpov(mo) HH-Inc (2D/50) mpov(hu) HH-Inc(2D) 13
14 Age 0-08 Age 9-17 III Age 0-08 Age 9-17 Results I Income Poverty Age 0-08 Age 9-17 Age 0-08 Age 9-17 Montly & annual incomes longterm development of poverty rates 35 in percent hheqr_pov60 m050_per_age h1_per_age h0_per_age mean hheqr_pov60 mean m050_per_age mean h1_per_age mean h0_per_age 14
15 Age 0-08 Age 9-17 III Age 0-08 Age 9-17 Results I Income Poverty Age 0-08 Age 9-17 Age 0-08 Age 9-17 Montly & annual incomes longterm development of poverty rates 25 in percent hheqr_pov60 d2m050_per_age d4m050_per_age d6m050_per_age mean hheqr_pov60 mean d2m050_per_age mean d4m050_per_age mean d6m050_per_age 15
16 IV Results II Multidimensional Poverty Deprivation Measures: [Respondents, age 18+ ] Income (5) [Household level]: Monthly Income (Screener) [currrent & anchored in time] Annual Income (previous year) Imputed Rent [currrent & anchored in time] Annual Income (previous year) [currrent] Health (1) [Ind. Level]: Handicaps in everyday activities & low health atisfaction Education (1) [Ind. Level]: Left school without graduation, no vocational training [casmin] Work-Intensity (1) [Household level]: No individual in the household working or in education at working age [laeken] Housing(1) [Household level]: Less than 20sqm/per>3y bad condition missing of sanitary equipment Subjective Wellbeing (SWB) (1) [Ind. Level]: Life satisfaction 0-3 [Scale 0-10] 16
17 IV Results II Multidimensional Poverty Deprivation Measures: percent 25,0 5 Non-Income Dimensions 20,0 15,0 10,0 5,0 0, Dep_Health Dep_Educ Dep_WI Dep_Housing Dep_SWB 17
18 IV Results II Multidimensional Poverty Deprivation Measures: Income (5) [H], Resp. 18+ percent 25,0 22,5 20,0 17,5 15,0 12,5 10,0 7,5 5,0 2,5 0, hheqr_pov60 af_i5m050 af_i5h1 af_i5h0 18
19 IV Results II Multidimensional Poverty Deprivation Measures: Income (5) [H] 25 in percent hheqr_pov60 i5m050_per mean hheqr_pov60 19
20 IV Results II Multidimensional Poverty Deprivation Measures: Health [Ind] percent 30,0 25,0 20,0 15,0 10,0 5,0 0, Dep_Health H-Inc&Health(mc1[union]) M0-Inc&Health(mc50,w50) H-Inc&Health(mc100,[intersection]) 20
21 IV Results II Multidimensional Poverty Deprivation Measures: in percent 30 Health [Ind] Dep_Health_age M0-Inc&Health(mc50,w50)_age Dep_Health_ M0-Inc&Health(mc50,w50)_ 21
22 IV Results II Multidimensional Poverty Deprivation Measures: percent Education [Ind] 35,0 30,0 25,0 20,0 15,0 10,0 5,0 0, Dep_Educ M0-Inc&Educ(mc50,w50) H-Inc&Educ(mc1[union]) H-Inc&Educ(mc100,[intersection]) 22
23 IV Results II Multidimensional Poverty Deprivation Measures: Education [Ind] 40 in percent Dep_Educ_age M0-Inc&Educ(mc50,w50)_age Dep_Educ_ M0-Inc&Educ(mc50,w50)_ 23
24 IV Results II Multidimensional Poverty Deprivation Measures: Work-Intensity [H] percent 30,0 25,0 20,0 15,0 10,0 5,0 0, Dep_WI M0-Inc&WI(mc50,w50) H-Inc&WI(mc1[union]) H-Inc&WI(mc100,[intersection]) 24
25 IV Results II Multidimensional Poverty Deprivation Measures: Work-Intensity [H] in percent Dep_WI_age M0-Inc&WI(mc50,w50)_age Dep_WI_ M0-Inc&WI(mc50,w50)_ 25
26 IV Results II Multidimensional Poverty Deprivation Measures: Housing [H] percent 35,0 30,0 25,0 20,0 15,0 10,0 5,0 0, Dep_Housing H-Inc&Housing(mc1[union]) M0-Inc&Housing(mc50,w50) H-Inc&Housing(mc100,[intersection]) 26
27 IV Results II Multidimensional Poverty Deprivation Measures: Housing [H] in percent Dep_Housing_age Dep_Housing_ M0-Inc&Housing(mc50,w50)_age M0-Inc&Housing(mc50,w50)_ 27
28 IV Results II Multidimensional Poverty Deprivation Measures: Subjective Well-Being (SWB) [Ind] percent 30,0 25,0 20,0 15,0 10,0 5,0 0, Dep_SWB M0-Inc&SWB(mc50,w50) H-Inc&SWB(mc1[union]) H-Inc&SWB(mc100,[intersection]) 28
29 IV Results II Multidimensional Poverty Deprivation Measures: Subjective Well-Being (SWB) [Ind] 10 in percent Dep_SWB_age M0-Inc&SWB(mc50,w50)_age Dep_SWB_ M0-Inc&SWB(mc50,w50)_ 29
30 IV Results II Multidimensional Poverty All Dimensions, Impact of Income (100,75,50,25,15,0 percent) percent 60,0 50,0 40,0 30,0 20,0 10,0 0, i100m0 i100h(u) i100h(i) i075m0 i075h(u) i075h(i) i050m0 i050h(u) i050h(i) i025m0 i025h(u) i025h(i) i015m0 i015h(u) i015h(i) i000m0 i000h(u) i000h(i) 30
31 IV Results II Multidimensional Poverty All Dimensions, Impact of Income ([M0] 100,75,50,25,15,0 %) percent 15,0 13,0 11,0 9,0 7,0 5,0 3,0 1,0-1, i100m0 i075m0 i050m0 i025m0 i015m0 i000m0 31
32 V Discussion Multidimensional poverty measures Advantages Ability to put together items at different aggregation levels: individual / household / region Therefore we can overcome shortfalls in established poverty analyses: Working poor Intra-household variation of poverty (due to pool-assumption) We can include variables at regional levels to combine opportunities and constraints [health, labor market, education system] with visible indicators of deprivation for inividuals and households We are able to include subjective measures to show us, whether the existing frames are able to provide us with sufficient chances [constraints] 32
33 V Discussion Tasks for further developments: Identification: 1st Cutoffs / 2nd cutoffs (absolute/relativ lines; time) Problems of cardinality Weighting of dimensions Aggregation: Correlation based poverty measures (Final ) Remark The main difference between income-based poverty analyses and multidimensional poverty approaches are not the number of dimensions, which are taken into account The main differences is wether we adress all kind of welfare aspects to one monetary unit (which is easier to handle for measurement), or whether we deal with different dimensions and different measures at the same time. Again... many thanks to OPHI Jose Manuel Roche, Sabina Alkire!!! 33
34 Thank You!
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