Analyzing the poverty and distributional impacts of macro shocks in developing
countries
A Microsimulation Approach
Poverty Reduction and Equity GroupPoverty Reduction and Economic Management Network
World BankApril 2011
2
Outline
Background
Approach
Model Basic structure and data requirements Methodology Standard outputs Limitations and assumptions
Illustrative results
Conclusions Applications to date Moving forward
3
Background
In wake of financial crisis: Urgency to design policy to mitigate impact of crisis but… … lack of real time micro data on employment and distributional impacts
High demand by client countries and regional teams for: Projections of short-term and medium-term impacts (Ex-ante) Identification of most vulnerable and affected groups
Microsimulation model (FY09-FY10) Development by PRMPR Application to Bangladesh, Mexico, Mongolia, Philippines and Poland (Partial application to Egypt)
Following crisis: Broader demand for microsimulation model to project employment and distributional
impact of macro shocks Collaboration with ADePT to design and develop simulation module
4
Approach
What is needed? To account for multiple transmission mechanisms To capture impacts:
▪ Over the entire income/consumption distribution▪ At the individual and household levels
Proposed approach Micro-simulation model
▪ Similar to methods outlined in Bourguignon et al. (2008)▪ Macroeconomic projections (not CGE)▪ Microeconomic data from household/LF surveys
Focus on▪ Labor markets (employment and earnings)▪ Non-labor income (remittances)▪ (Prices – food/non-food, other)
Main outputs▪ Individual level: Information on LF/employment status and labor earnings▪ Household level: Information on per capita (labor/non labor) income and consumption
Results▪ Employment impacts▪ Poverty and distributional impacts
5
Model
6
Basic structure
Micro data(Household/LF
survey)
Baseline(Pre-shock, t)
“Treatment”(Crisis)
Benchmark
Predictions(t+1…t+n)
Impa
ct (2
)
Macro projections(t+1…t+n)
Impact (1)
7
Data requirements
Control variables Macroeconomic projections (country teams)
▪ Total and sectoral GDP growth▪ International remittances growth▪ Inflation (general and food)▪ Exchange rate (local currency/USD)
Macroeconomic parameters (calculations from historical data)▪ Output elasticity of employment (total and sectoral)▪ Output elasticity of labor force participation (total and sectoral)
Population growth rate (by age group and gender)
Microeconomic data Survey with data on:
▪ Individual and household-level labor and non-labor income▪ Individual-level labor market outcomes
Poverty line(s)
8
Model overview
Baseline (Calibration)
Micro data
LF status modelEarnings equation
Migration/remittances
Rule: Best fit to micro data
estimate
Population growth
Simulation
Macro projections
∆ in LF status (ind)∆ real earnings (ind)∆ remittances (HH)
Populationpredict
Rule: Replicate macro proportional changes at
micro level
Assessment of impacts
Price data
Income and consumption
(individuals and HH)
adjust
Input
Output
Income/consumption distributions
Poverty and inequality measures
Results
15
Typical outputs
Datasets Original (baseline) dataset Simulated dataset(s)
Results Employment and earnings estimates Poverty and inequality aggregates Poverty profiling
▪ Poverty profiling of “new poor”▪ Poverty profiling for specific groups/areas
Distributional analysis▪ Growth incidence analysis▪ Transition matrices
16
Limitations and assumptions
Limitations Level of disaggregation
Level of sectoral/regional disaggregation dependent on available level of disaggregation for macro projections
Labor market dynamics Structural relationships remain constant
▪ Validity of MNL and earnings (pre-crisis) estimates
No explicit modeling of changes in composition of employment within sectors▪ Changes in the proportion of formal/informal employment within each sector are due to individual transitions
Assumptions Immobility of factors of production (including labor) between regions and
between urban/rural areas No (additional) internal or external migration
Labor income and profits grow at same rate within each sector Constant marginal propensity to consume
Needed only if poverty is consumption-based
17
Illustrative results
18
Summary of main findings(on impact of financial crisis)
In Bangladesh, Mexico, Philippines and Poland, slower or negative GDP growth generally translated into:
Aggregate employment and poverty impacts Employment rates/levels fell due to the crisis…
▪ … with sectoral impacts varying by country Incomes were affected through both labor earnings and remittances…
▪ … although the mix varied across countries Poverty was expected to increase…
▪ … but there was little impact on aggregate measures of inequality Poverty profiling: Crisis vulnerable
New poor had specific characteristics that distinguished them from chronic poor and non-poor
Implications for design and targeting of safety net and crisis response packages Distributional impacts
Large impacts in middle of income distribution, associated with employment/earnings shocks
Implications for political economy of crisis response
Changes in total and sectoral employment
19
2010
Decline in employment levels (shown) and employment rates
Significant cross-country variation in sectoral impacts Manufacturing
affected in all countries but to different degrees
Services as fall-back sector in BD, in contrast with Philippines, Mexico, and especially Poland
Philippines Mexico Bangladesh Poland
(3.50)
(3.00)
(2.50)
(2.00)
(1.50)
(1.00)
(0.50)
-
0.50
1.00
% change in employment between benchmark and crisis
Agriculture Manufacturing/Industry Services
20
Changes in household income
2010
Decline in household income associated with reductions in both labor and non-labor incomes
Significant cross-country variation in relative importance of shocks to different income sources, reflecting variation in relative importance of different transmission mechanisms
Distributional implications
Total HH Income HH Labor Income HH Remittances
-10.0
-9.0
-8.0
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
% change in household income between benchmark and crisis
Philippines Mexico Bangladesh Poland
21
Poverty Headcount Poverty Gap Gini
-5.0
0.0
5.0
10.0
15.0
20.0
% change in poverty/inequality indicators between crisis and benchmark
(numbers in parentheses represent pct. point change)
Philippines Mexico Bangladesh Poland
Changes in poverty and inequality
2010
Increase in level and depth of poverty, especially in MX…
… but little impact on aggregate inequality
Caution: Impact in relative (%) versus absolute (PP) terms
(1.5)
(3.9)
(1.2)
(0.7)
(3.4)
(0.3)
(0.001)
(0.012)
(-0.004)
(0.4)
(0.2)
(-0.002)
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2010
HH of new poor households relatively more skilled than those chronic poor households…
… but less skilled than the average HH
Similar pattern across countries
Characteristics of the crisis-vulnerable (I)
Philippines Mexico Bangladesh Poland0
20
40
60
80
100
120
% of crisis-vulnerable household heads who are low-skilled(0-9 yrs of education)
Crisis-vulnerable Structurally poor Entire population
23
2010
New poor relatively more likely to reside in urban areas than chronic poor…
… but less likely to reside in urban areas than the average household
Similar pattern across countries, but differences more acute in Philippines and MX (higher level of urbanization? higher rate of poverty reduction in urban areas in recent years?) and no differences in Poland (higher level of penetration of off-farm activities in rural areas)
Characteristics of the crisis-vulnerable (II)
Philippines Mexico Bangladesh Poland0
10
20
30
40
50
60
70
80
90
% of crisis-vulnerable living in rural areas
Crisis-vulnerable Structurally poor Entire population
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Distributional impacts:Growth Incidence Curves
-8.0
0-7
.00
-6.0
0-5
.00
-4.0
0-3
.00
-2.0
0-1
.00
0.0
0
% C
han
ge
0 10 20 30 40 50 60 70 80 90 100
Percentile
Urban Rural-6
.00
-5.0
0-4
.00
-3.0
0-2
.00
-1.0
00
.00
% C
ha
ng
e0 10 20 30 40 50 60 70 80 90 100
Percentile
Urban Rural
Philippines Bangladesh
-16.00
-14.00
-12.00
-10.00
-8.00
-6.00
-4.00
-2.00
0.00
% C
ha
ng
e
0 10 20 30 40 50 60 70 80 90 100
Percentile
Urbano Rural
Mexico
On average larger losses in urban areas, where employment impacts are highest
But important distributional impacts within rural and urban areas as well (except for Philippines)
BD: Remittances MX: Most severe
employment losses
PO: Farm versus non-farm employment (rural areas)
Poland1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
UrbanRural
25
1 2 3 4 5 6 7 8 9 10 -
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Distributional impacts:Transition Matrices
Philippines Bangladesh
1 2 3 4 5 6 7 8 9 100.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Mexico
1 2 3 4 5 6 7 8 9 10 -
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
1 2 3 4 5 6 7 8 9 10 -
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Poland
Most people remain within decile but
Important movements up and esp. down – particularly in middle of distribution
MX: Largest impact on poor
PO: Largest movements “up” at bottom due to UI
26
Conclusions (I):Main applications to date
Crisis monitoring: Identification of main transmission mechanisms Identification of possible “leading indicators” to monitor the likely poverty impact
of an economic crisis▪ E.g. manufacturing employment/job losses, wages, aggregate remittance flows, change in
relative price of food Design of policy response:
Identification of affected/vulnerable individuals/households/groups SP for the new poor?
▪ Effectiveness of traditional/existing SN programs and automatic stabilizers Political economy implications of distributional impacts (esp. impacts on urban
middle class) Poverty/Distributional impact of policy response:
Safety nets versus automatic stabilizers (e.g. Mexico and Poland)
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Conclusions (II):Main applications to date (publications)
(Stand alone) Country notes Bangladesh (PRWP 5238) Philippines (PRWP 5286) Mongolia (Policy Note, 2010) Poland (Policy Brief, 2010)
Contributions to country reports Mexico
Philippines Overview and summary of findings
Economic Premise (March 2010) Summary piece in EUVox.org (April 2010) Gender impacts Distributional Impact of the Financial Crisis (forthcoming Fall 2011)
Webpage Poverty Reduction and Equity Group (PRMPR)
28
Conclusions (III):Moving forward
Possible extensions, depending on the country context Commodity/food price changes More disaggregated treatment of sectors
▪ Export/non-export▪ Formal/informal
More sophisticated treatment of remittances and internal migration
Timeline Launch of ADePT SIM 1.0 over summer 2011
▪ Basic features▪ Manual
Dissemination and training▪ BBLs▪ Training at HQ + customized country/regional training events on demand (e.g. Egypt, Mexico,
Tunisia) (Possible customization on demand)