1. 1 Michel Tenenhaus & Carlo Lauro A SEM approach for composite indicators building Michel Tenenhaus & Carlo Lauro

2. 2 Economic inequality and political instability Data from Russett (1964), in GIFI Economic inequality Agricultural inequality GINI : Inequality of land distributions FARM : % farmers that own half of the land (> 50) RENT : % farmers that rent all their land Industrial development GNPR : Gross national product per capita ($ 1955) LABO : % of labor force employed in agriculture Political instability INST : Instability of executive (45-61) ECKS : Nb of violent internal war incidents (46-61) DEATH : Nb of people killed as a result of civic group violence (50-62) D-STAB : Stable democracy D-UNST : Unstable democracy DICT : Dictatorship

3. 3 Economic inequality and political instability (Data from Russett, 1964) 47 countries

4. 4 GINI FARM RENT GNPR LABO Agricultural inequality (X 1 ) Industrial development (X 2 ) ECKS DEATH INST Political instability (X 3 ) 1 2 3 + + + + - + + + + - Economic inequality and political instability

5. 5 Building composite indicators 1.Separately for each block (without taking into account the other blocks). 2.For each block, taking into account all the other blocks (multi-block data analysis). 3.For each block, taking into account the causal model (Structural Equation Modelling).

6. 6 1. Using SEM for factor analysis Measurement model 1 2 3 1 2 3

7. 7 ULS algorithm S = Observed covariance matrix for MV Goodness-of-fit Index (Jöreskog & Sorbum): = PCA when

8. 8 First result This solution is not admissible because

9. 9 A solution The variance of residual e2 is fixed to a small value

10. 10 Result 2 The variance of residual e2 is fixed to a small value:

11. 11 Bootstrap Results Regression Weights: Composite indicator

12. 12 Principal component analysis with SEM The variance of the residuals are fixed to 0 :

13. 13 Result 3 The variance of the residuals are fixed to 0 :

14. 14 Bootstrap Results Regression Weights: Conclusion

15. 15 Result 4 The variance of the residuals are fixed to 0 :

16. 16 Bootstrap Results Regression Weights: Composite indicator

17. 17 2. Using SEM for multi-block data analysis

18. 18 Result 5 This solution is not admissible because

19. 19 Result 6 Var(e2) is fixed to a small value

20. 20 Result 7 MacDonald (1996) proposal All Var(e) are fixed to 0:

21. 21 Bootstrap Results Regression Weights: Conclusion

22. 22 Result 8 MacDonald (1996) Proposals: (1) All Var(e) are fixed to 0: (2) Composite indicator:

23. 23 3. Causal model estimation using SEM-ULS

24. 24 Result 9 This solution is not admissible because

25. 25 Result 10 Var(e2) is fixed to a small value

26. 26 Bootstrap Results Regression Weights: Conclusion

27. 27 Result 11 Var(e2) is fixed to a small value Composite indicator:

28. 28 Bootstrap Results Regression Weights: Conclusion

29. 29 Conclusion Agricultural inequality and Industrial development are drivers of political instability Russet hypotheses are validated: Other composite indicators:

30. 30

31. 31 Conclusion Agricultural inequality above the average Industrial development below the average DICTATORSHIP