1. Replacing Representative with Real Households in Dynamic CGE Analysis of Poverty John Cockburn Bernard Decaluwe with contributions of Nabil Annabi Ismael Fofana Veronique Robichaud Fatou Cissé Marie Helene Cloutier Luc Savard JC Dumont André Patry Dorothee Boccanfuso

2. Plan of the presentation Motivation The integrated micro simulation approach versus the representative household approach. How to develop an integrated CGE microsimulation model A sequential dynamic CGE model The decomposition method An illustration

3. Motivation CGE models are particularly well suited to simulating the impacts of macroeconomic policies and shocks on microeconomic income distribution and poverty. Such models are particularly useful when: (1) shocks or policies are transmitted through the functioning of markets and have wide-ranging impacts on prices of factors, goods and services, (2) when the interdependence between production sectors on the one hand and economic agents on the other hand is important, (3) and, lastly, when the retroaction effects between market signals and agents’ behavior play a major role in the magnitude of the final impacts.

4. Motivation However, in order to study impacts on income distribution and poverty, these models are useful only if they incorporate detailed information on how households earn and consume their incomes.

5. Motivation To do that we need information on : initial factor endowments, their accumulation over time, the functioning of factor markets, the consumption preferences of households, and disaggregate information on the variations in prices of consumer goods and services.

6. The representative household approach Distributive impacts are captured simply through extending the disaggregation of the representative households in order to identify as many household categories, generally corresponding to different socio-economic groups, as possible.

7. The representative household approach : Difficulties The RHA provides no information On poverty impacts (as the poor may be found in many different socio- economic groups and in varying proportions) On intra-group distribution.

8. The representative household approach : Difficulties Kirman (1992) recalls that this hypothesis is not very realistic given that: 1. no justification exists to affirm that the aggregation of individual choices necessarily leads to the same solution as the choice of a representative individual, 2. there is no guaranty that the reaction of the representative household entails that any change in the model will be the same as the aggregated reaction of the individuals it represents, 3. lastly, the representative household approach may interfere with the individual preferences weak principle.

9. How to measure poverty in a representative household approach New distribution Initial distribution Poverty line contribution (distribution fixed): 2+4 Poverty line contribution : 4 Distribution contribution (poverty line fixed): - 1 Distribution contribution: - 1-2 Income contribution : P0-P1 ( RH ) Figure 2: Poverty line, income and distribution effects on poverty Source: Decaluwé et al. (1999) Source: Decaluwé et al. (1999) 4 2 3 1 Initial poverty level: 1+3 New poverty level: 3+4 Income Share of people

10. How to develop an integrated CGE microsimulation model ?  The methodology uses both a standard representative-household CGE model and data from a nationally-representative household survey with complete information on household incomes and expenditures.  The method mainly requires the reorganization and reconciliation of household survey data with the Social Accounting Matrix (SAM) underlying the initial CGE model.

11. How to develop an integrated CGE microsimulation approach ? This process entails three steps: (i) reorganization of the household survey data into household-specific income and expenditure vectors defined in terms of the household income sources and expenditure categories used in the initial CGE model, (ii) Integrating and reconciling these vectors with the original SAM through adjustments in one or both, and (iii) introducing all survey households in the initial CGE model.

12. How to develop an integrated CGE microsimulation model

13. How to develop an integrated CGE microsimulation model. FactorsH1AgentsBranchesGoodsAcc.Total Factors120 H110040140 Agents203050 Branches195 Goods755 40195 Acc.35540 Total12014050195 40

14. How to develop an integrated CGE microsimulation model. Recalculate household vectors using survey Consistency: Y=C+S for each household Total is a weighted sum of: Factor payments: skilled/unskilled wages, returns to capital/land In-transfers: dividends, public transfers Out-transfers: income tax, other transfers Consumption: by goods account Savings

15. How to develop an integrated CGE microsimulation model. Weight Factor Payment In- transfers Total income (I) Out- transfers Consump- tionSaving Total Expend. (E)I-E H110002463015105300 H2800200 5105200 ….. …. H3500120050106044016600 Total (MN) Pop.1203015025100251500 Original (MN)Pop.100401403075351400

16. How to develop an integrated CGE microsimulation model. Factor sH1H2…. H350 0 Agent s Branche s Good s Acc.Total Factors120 H1.024.006.003 H2.0160 …. H3500.06.012.072 Agents20.01 5.004…..004845 Branche s195 Goods.01.008…..04857540220 Acc..00 5.004…..0192530 Total140.03.016…..07240195 40

17. Why a dynamic micro simulation model Several reasons but in this paper we look at the accumulation effect of capital through time

18. Efficiency (reallocation) effect Accumulation effect ● ● ● ● ● s(GDP/L) s(PIB/L)’ GDP/L GDP/L’ A B D E C K/L’ K/L* Y/L* Y/L’ Y/L c  (K/L) Accumulation effect of trade liberalisation Figure 1: Accumulation effect in the Solow model Figure 1: Accumulation effect in the Solow model Source: Baldwin and Wyplosz, 2003. Source: Baldwin and Wyplosz, 2003.

19. An illustration : the Senegal Case Static Module Activities/products Firms Households (3278) Trade (CES,CET & Ex.D) Government Equilibrium. Dynamic Module Static expectations Capital accumulation Investment Demand Labor Supply Growth Transfers, SG, CAB…

20. Dynamic equations in the model 1. 2. 3. 4. 5. 6. Model equations Model equations

21. Investment demand 7. Capital price and user cost 8. 9. Investment equilibrium 10. Model equations (cont.) Model equations (cont.)

22. The Decomposition techniques Datt and Ravallion (1992) : Changes in poverty measures can be decomposed into growth and redistribution components. Decomposition with reference to time (region / country). Poverty measure where z : the poverty line  t : the mean income L t : vector of parameters describing the Lorenz curve at date t

23. The level of poverty may change due to: - change in the mean income relative to the poverty line. - change in relative inequalities. Growth component of change in poverty measure is defined as the change in poverty due to a change in the mean income while holding the Lorenz curve constant at some reference level. The redistribution component is the change in poverty due to a change in the Lorenz curve while keeping the mean income constant at the reference level. The decomposition techniques (cont.)

24. Change in poverty over dates “t” and “t+n” is decomposed as follows (r is the reference year): Growth and redistribution components are given by: The decomposition techniques (cont.)

25. The residual is the difference between the growth (redistribution) components evaluated at the terminal and initial Lorenz curves (mean incomes) respectively: The residual is the result of interaction between the two effects and disappears if we use the average of the initial and final year values as the reference. The deecomposition techniques (cont.)

26. Kakwani, N. (1997) defines the average growth and inequality effects as: Change in poverty is then decomposed as follows: The decomposition techniques (cont.)

27. 2. Senegal 1996 Social Accounting Matrix

28. 3. Household income composition: ESAM I (1995) Note: * Figures in brackets represent the shares in factor income

29. Poverty and inequality in the BaU path (%)

30. Poverty change decomposition (1996-2015)

31. Poverty change decomposition given the baseline poverty line  Growth contribution is positive in both cases (K & DR)  Distribution contribution is negative but smaller than growth effects.

32. V. Trade liberalisation effects: Sectoral V. Trade liberalisation effects: Sectoral and Macro effects and Macro effects  Expansion of the export oriented industry and service sectors in the long run.  Positive gains in terms of real GDP and welfare in the long run.

33. V. Trade liberalisation effects: income, V. Trade liberalisation effects: income, welfare, poverty and inequality welfare, poverty and inequality  Income losses are greater among rural households.  Adverse effects in the SR but substantial poverty decreases in the LR.  Income distribution worsens.

34. V. Trade liberalisation effects: V. Trade liberalisation effects: Income growth curves Income growth curves  Income gains are more equal in rural areas than in urban areas.  Tariff removal and accumulation effects benefit non-poor households more.

35. Future works and extension Saving behaviour of households Labor markets dynamics Accumulation of human capital by households Technical progress and liberalisation Liberalisation, FDI and accumulation of capital Etc.