ETHNO-CULTURAL DIVERSITY AND

MULTIDIMENSIONAL POVERTY

DIFFERENTIAL IN CAMEROON

 

plan

• Research issue;

• Objectives;

• Review of the literature

• Methodology;

• Results;

• Policy implications.

I-RESEARCH ISSUE

identify the criteria which permit to distinguish between the poor and the non poor.

the welfarist and basic needs schools (Asselin, Dauphin, 2002; Ruggeri, 1997).

cultural differences; interpretation of the world.

(Bollinger, Hofstede;1987; Davison, Jordans, 1996; Xiadong Deng, 2003)

Sen’s capacity / functioning theory

(Asselin, Dauphin, 2002; Duclos, 2002 )

II – OBJECTIVES 

to identify the indicators judged as being the determining factors in welfare

to gather these indicators according to the similarities they have between them in order to discover the cultural differential of the main facets of poverty;

II- OBJECTIVES

to determine the cultural differential of the interrelations between different facets of poverty.

to capture the cultural differential of the determinants of poverty.

III-REVIEW OF THE LITERATURE

identification of multidimensional poverty indicators (Asselin et Dauphin; 2000)

identification of the dimensions or facets of poverty

(Bevan, Sandra, 1997; Razafindrakoto et Roubaud, 2001).

III- REVIEW OF THE LITERATURE

indices of multidimensional poverty

(Bourguignon, Chakravarty 2002; Chakravarty, Mukherjee et Ranade ,1997)

III- REVIEW OF THE LITERATURE

expressed by

P(X;z) =

decomposable index according to sub-groups and attributes

n

i

k

j j

ijj zXa gn

1 1

1

III- REVIEW OF THE LITERATURE

indicators of multidimensional poverty

(Asselin, 2002)

Ci= K

j

jj

k

k

k

jki

kk

k

kIW

1 1,

IV – METHODOLOGY

• IV-1: empirical research framework

IV-2: Structural modelling

• IV-3: Multi-groups modelling

IV-1: empirical research framework

1-the database selected for the analysis

2-Cameroon’s ethno-cultural map

3-Multiple Correspondence Analysis (MCA)

1:The database selected for analysis • Section 0:General information on the household• Section1:Composition of the household and characteristics of household

members• Section2:The health of household members (12 questions)• Section 3: Schooling of household members • Section4:Activities of household members • Section 5: Birth, Mortality, Fecundity . Section 6:Anthropometry and vaccination • Section 7:Housing and household equipment • Section 8:Household migrations • Section 9:Accessibility to basic infrastructures • Section 10:Perceptions and self-evaluation on living conditions and

poverty • Section 11: Non agricultural family entreprises • Section 12: Agriculture and rural activities• Section 13:Household non food retrospective expenditures

1- The database selected for the analysis

Research Interest

37 poverty indicators from this database.

2-Cameroon’s ethno-cultural map

2-Cameroon’s ethno-cultural map

Research Interest

distribute the research sample between the four ethnic groupings.

3-Multiple Correspondence Analysis (MCA)

Interpretation of MCA results for research

3-Multiple Correspondence Analysis (MCA)

Interest of MCA for research 5 dimensions of poverty

-poverty of existence (pexi) = 4 variables

-monetary poverty (pom) = 3 variables

-human poverty (ph) = 2 variables

-infrastructural poverty (pif) = 9 variables

-subjective poverty ( pg) = 3 variables 21 indicators deserving of interest

IV-2: Modelling Structural Equations with Pooled Data

definition

multivariate analysis method which combines

factorial analysis and regressions

2 – graphical representation

pexi

ph

pm

pif

pg

S0710exi S0711exi S0712exi S0713exi

S103pg

S108pg

S109pg

deptpom

dpedpom

S101fina

S0210ph

S0310ph

Temp10ifTemps11ifTemp8ifDist8if Temp1if Dis10if Dist6if Dist1ifTemp6if

E30

E27

E17 E18 E19 E20 E21 E25E24E23E22

E6

E5

E4

E3

E31

3-Algebraic Representation

Edx ijija

Xij is the value taken by indicator j on individual i

dj is the latent variable

Ei is the error term which captures the part of Xij not explained by the latent variable

4– Estimation Method

maximum likelihood method

F[S Σ(θ)]=ln│Σ(θ)│+tr[SΣ(θ )-1]-ln│S│+ t.

5– SEM Results.

The estimated coefficients

- confirm the nature of multidimensional poverty

-autogradation is a function of the order of importance of (ph, pif, pexi)

IV –3. Multi-groups modelling

• 1-partition of the population

• 2-formulation of hypotheses.

• 3-Hypothesis testing

1-partition of the population

maximize within group homogeneity and between group heterogeneity

descending method was applied .two cultural spaces relative to the poverty

phenomenon

- bantou-semitique

- Soudano-semibantou

2-formulation of hypotheses

models in both spaces are said to be nested H1: differences in the determinants of

perception; H2: differences in the interactions between

dimensions H3: differences in the levels of dimensions

H4: differences in indicators.

 3-Hypothesis Testing Method

Comparing nested models Principles: constrained and unconstrained

Comparison of the constrained model with the unconstrained one is based on the χ2 test.

  -        

V– THE RESULTS

• 1-The objective differences

• 2-Cultural Mechanisms

1-The objective differences

bantou-sémitique soudano-semibantou means S.E. C.R. P means S.E. C.R. P pexi 0,33333 0,01722 19,35176 0,00000 0,46466 0,02098 22,14527 0,00000 pif 0,26263 0,01608 16,33623 0,00000 0,21025 0,01714 12,26432 0,00000 pom 0,45200 0,01819 24,85532 0,00000 0,56890 0,02083 27,30595 0,00000 ph 0,55065 0,01817 30,29685 0,00000 0,46466 0,02098 22,14525 0,00000

2-Cultural Mechanisms

The Subjective Differential . (H1)

Regression Weights

bantou-sémitique Soudano-semibantou

loadings S.E. C.R. P loadings S.E. C.R. P pg <-- pexi 0,01114 0,02459 0,4529 0,6506 0,03672 0,01821 2,01607 0,04379 pg <-- pif 0,21824 0,08883 2,4568 0,0140 0,15215 0,04677 3,25324 0,00114 pg <-- pom 0,00742 0,0255 0,2912 0,7709 0,0019 0,02378 0,07989 0,93633 pg <-- ph 0,10599 0,03969 2,6706 0,0076 0,22489 0,0232 9,69251 0,00000

2-Cultural mechanisms

Differences in determinants (H2)

Covariances

Espace bantou-semitique

Espace soudano-semibantou

Estimate P Estimate P Pexi <--> Pif 0,00622 0,0416 0,04817 0,00000 Pexi <--> Pom 0,07274 0,00000 0,09741 0,00000 Pexi <--> Ph 0,0652 0,00000 0,0817 0,00000 Pif <--> Pom 0,00676 0,0340 0,04273 0,00000 Pif <--> Ph 0,0044 0,7887 0,0365 0,00000 Pom <--> Ph 0,03792 0,0000 0,06276 0,00000

VI – POLICY IMPLIMENTATIONS

Taking into account the multidimensional nature of poverty

A prudent decentralization of poverty measurement and of poverty reduction strategies.