ETHNO-CULTURAL DIVERSITY AND MULTIDIMENSIONAL POVERTY DIFFERENTIAL IN CAMEROON

1. ETHNO-CULTURAL DIVERSITY AND MULTIDIMENSIONAL POVERTY DIFFERENTIAL IN CAMEROON

2. plan • Research issue; • Objectives; • Review of the literature • Methodology; • Results; • Policy implications.

3. 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 )

4. 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;

5. 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.

6. 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).

7. III- REVIEW OF THE LITERATURE • indices of multidimensional poverty (Bourguignon, Chakravarty 2002; Chakravarty, Mukherjee et Ranade ,1997)

8. III- REVIEW OF THE LITERATURE • expressed by P(X;z) = • decomposable index according to sub-groups and attributes

9. III- REVIEW OF THE LITERATURE • indicators of multidimensional poverty (Asselin, 2002) Ci=

10. IV – METHODOLOGY • IV-1: empirical research framework IV-2: Structural modelling • IV-3: Multi-groups modelling

11. IV-1: empirical research framework 1-the database selected for the analysis 2-Cameroon’s ethno-cultural map 3-Multiple Correspondence Analysis (MCA)

12. 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

13. 1- The database selected for the analysis • Research Interest 37 poverty indicators from this database.

14. 2-Cameroon’s ethno-cultural map

15. 2-Cameroon’s ethno-cultural map • Research Interest distribute the research sample between the four ethnic groupings.

16. 3-Multiple Correspondence Analysis (MCA)Interpretation of MCA results for research

17. 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

18. IV-2: Modelling Structural Equations with Pooled Data • definition multivariate analysis method which combines factorial analysis and regressions

19. E6 E5 E4 E3 S0710exi S0711exi S0712exi S0713exi pexi deptpom E31 dpedpom pm E30 S103pg pg S101fina S108pg E27 S0210ph ph S109pg S0310ph pif Dist8if Temp8if Temps11if Temp10if Temp6if Temp1if Dis10if Dist6if Dist1if E17 E18 E19 E20 E21 E22 E23 E24 E25 2 – graphical representation

20. 3-Algebraic Representation 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

21. 4– Estimation Method • maximum likelihood method F[S Σ(θ)]=ln│Σ(θ)│+tr[SΣ(θ )-1]-ln│S│+ t.

22. 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)

23. IV –3. Multi-groups modelling • 1-partition of the population • 2-formulation of hypotheses. • 3-Hypothesis testing

24. 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

25. 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.

26. 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.   -        

27. V– THE RESULTS • 1-The objective differences • 2-Cultural Mechanisms

28. 1-The objective differences

29. 2-Cultural Mechanisms • The Subjective Differential . (H1)

30. 2-Cultural mechanisms • Differences in determinants (H2)

31. VI – POLICY IMPLIMENTATIONS • Taking into account the multidimensional nature of poverty • A prudent decentralization of poverty measurement and of poverty reduction strategies.