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 CisséMarie Helene Cloutier

Luc Savard JC Dumont André Patry

Dorothee Boccanfuso

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

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.

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.

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.

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.

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.

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.

How to measure poverty in a How to measure poverty in a

representative household approachrepresentative 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 Figure 22: : Poverty line, income Poverty line, income and distribution effects on povertyand distribution effects on poverty

Source: Decaluwé et al. (1999)Source: Decaluwé et al. (1999)

44

22

33

11

Initial poverty level: 1+3

New poverty level: 3+4

Income

Share of

people

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.

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.

How to develop an integrated CGE microsimulation model

Aggregate household categories in SAM

40520105Acc.

40

40

Acc.

501510520Agents

195

195

Goods

19550704030120Total

195755352020Goods

195Branches

702050Rw

401030Rl

301020Urb

120120Factors

TotalBranchesAgentsRwRlUrbFactors

How to develop an integrated CGE microsimulation model.

Factors H1

Agents

Branches

Goods

Acc.

Total

Factors 120 120

H1 100 40 140

Agents 20 30 50Branches 195 195

Goods 75 5 75 40 195

Acc. 35 5 40

Total 120 140 50 195 195 40

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

How to develop an integrated CGE microsimulation model.

WeightFactorPayment

In-transfers

Total income (I)

Out-transfers

Consump-tion Saving

Total Expend. (E) I-E

H1 1000 24 6 30 15 10 5 30 0

H2 800 20 0 20 5 10 5 20 0

….. ….. ….. ….. ….. ….. ….. ….. ….. ….

H3500 1200 50 10 60 4 40 16 60 0

Total (MN) Pop. 120 30 150 25 100 25 150 0

Original (MN) Pop. 100 40 140 30 75 35 140 0

How to develop an integrated CGE microsimulation model.

Factors H1 H2

….

H3500

Agents

Branches

Goods

Acc.

Total

Factors 120 120H1 .024 .006 .003H2 .016 0 .016…. …. …. ….H3500 .06 .012 .072

Agents 20.015

.004

….

.0048 45

Branches 195 195

Goods .01.008

…. .048 5 75 40 220

Acc..005

.004

….

.0192 5 30

Total 140 .03.016

…. .072 40 195 195 40

Why a dynamic micro simulation model

Several reasons but in this paper we look at the accumulation effect of capital through time

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/Lc

(K/L)

Accumulation effect of trade liberalisation Accumulation effect of trade liberalisation

Figure 1: Figure 1: Accumulation effect in the Solow modelAccumulation effect in the Solow model

Source: Baldwin and Wyplosz, 2003.Source: Baldwin and Wyplosz, 2003.

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…

Dynamic equations in the model

1.

2.

3.

4.

5.

6.

Model equationsModel equations

, 1 , ,1tr t tr t tr tKD KD Ind

1

1

1

, 1 ,

1

1

1

1

1

1

t t

t t

t t

ntr t ntr t

t t

LS ng LS

A tc A

IG g IG

XS g XS

TG g TG

Investment demand

7.

Capital price and user cost

8.

9.

Investment equilibrium 10.

2, ,

1,

tr t tr t

trtr t t

Ind R

KD U

tr

tr ,tt

trtr

PCPinv

t tU Pinv ir

t t tr ,t ttr

IT Pinv Ind IG

Model equations Model equations (cont.)(cont.)

The Decomposition techniquesThe 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

Lt : vector of parameters describing the Lorenz curve at date t

t t tP P z / , L

• 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 techniquesThe decomposition techniques (cont.)(cont.)

• 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 techniquesThe decomposition techniques (cont.)(cont.)

t n t

change in growth redistribution residualpoverty component component

P P G t,t n;r D t,t n;r R t ,t n;r

t n r t rG t,t n;r P z / ,L P z / ,L

r t n r tD t,t n;r P z / ,L P z / ,L

• Kakwani, N. (1997) defines the average growth and inequality effects as:

• Change in poverty is then decomposed as follows:

The decomposition techniquesThe decomposition techniques (cont.)(cont.)

12 t n t t t t n t n t t nG t ,t n P z, ,L P z, ,L P z, ,L P z, ,L

12 t t n t t t n t n t n tD t ,t n P z, ,L P z, ,L P z, ,L P z, ,L

t n t

change in growth redistributionpoverty component component

ˆ ˆP P G t,t n D t,t n

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

38 38

13

52

89

29

73

32

69

41

50 54

0

10

20

30

40

50

60

70

80

90

100

1996 2015 1996 2015 1996 2015

Urban Rural All

Headcount ratio Gini

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0 144000 288000 432000 576000 720000

Poverty line (CFA franc)

Gro

wth

an

d d

istr

ibu

tio

n

Poverty line

Growth (Datt & Ravallion)

Distribution (Datt & Ravallion)

Distribution (Kakwani)

Growth (Kakwani)

Poverty change decomposition (1996-2015)Poverty change decomposition (1996-2015)

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

Headcount ratio Poverty gap Severity ofpoverty

Growth component (DR)

Growth component (K)

Redistribution (DR)

Redistribution (K)

Residual

Poverty change decomposition given the Poverty change decomposition given the baseline poverty linebaseline poverty line

Growth contribution is positive in both cases (K & DR) Distribution contribution is negative but smaller than growth effects.

Urban Rural All 1996 2015 1996 2015 1996 2015

Income -6.39 -4.07 -6.90 -4.32 -6.50 -4.13

Capital income -6.48 -4.52 -6.49 -4.51 -6.49 -4.52 Labour income -6.59 -2.80 -6.59 -2.80 -6.59 -2.80

Land income -11.28 -6.45 -11.23 -6.39 -11.23 -6.39 Real consumption -0.05 4.05 -1.43 2.03 -0.58 3.45

Welfare (EV) -0.08 1.81 -0.93 1.27 -0.26 1.69 Headcount ratio 0.16 -7.41 0.17 -1.42 0.17 -2.04

Poverty gap 0.66 -7.06 1.93 -2.66 1.78 -2.95

Poverty severity 0.98 -7.79 2.96 -3.61 2.81 -3.68

Inequality (Gini) 0.10 0.67 0.71 0.84 0.77 1.02

V. Trade liberalisation effects: income, V. Trade liberalisation effects: income, welfare, poverty and inequalitywelfare, 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.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.05 0.14 0.23 0.32 0.41 0.50 0.59 0.68 0.77 0.86 0.95

PercentilesUrban Rural

V. Trade liberalisation effects: V. Trade liberalisation effects:

Income growth curvesIncome growth curves

Income gains are more equal in rural areas than in urban areas.

Tariff removal and accumulation effects benefit non-poor

households more.

Future works and extension 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.