Jan Walliser Senior Economist The World Bank

1. Poverty Analysis Macroeconomic Simulator (PAMS) and PSIA with an application to Burkina Faso Jan Walliser Senior Economist The World Bank

2. Outline of the Presentation • Introduction • PAMS: Inputs and Outputs • A brief tour of PAMS • A Set of Policy Experiments

3. Introduction: why “macro”PSIA? • Changes in the macro frameworksuch as the fiscal, inflation and exchange rate targets? How do they affect the poor? • Exogenous shocks such as trade shocks, capital flows volatility, changes in foreign aid and foreign payment crises? How can policy mitigate these effects on the poor?

4. Introduction: why “macro” PSIA? • Improving public expenditure targeting? How can public expenditure be better targeted? • Structural reforms such as trade policy, privatization, agricultural liberalization? How are the poor affected?

5. Modeling Implications and Challenges • Maintain simplicity of macroeconomic consistency frameworks (e.g., RMSM-Xs or other country-based models) • Link macro-consistency frameworks directly with household survey data

6. The Logic of PAMS • Three Recursive Layers Consistent with Incidence Approach • Macro-framework: GDP, national accounts, taxes & government spending, BOP, prices • Labor model breaking down population by skill level and economic sectors using categories from HHS • Model to simulate income changes by group, allowing calculation of poverty incidence and inter-group inequality

7. General Structure : 3 Layers Top-down HHL "micro-simulation" approach Macroeconomic Model Macro Accounting (RMSM-X), CGE (123), Econometric Layer 1: Macro Sectoral Disaggregation, Factor Markets  Linkage Aggregate Var For k representative groups of households Layer 2: Meso Household Survey (HHS), i individual households, Macro "consistent" changes in real household incomes and change in the distribution of welfare Layer 3: Micro (yi) with poverty line, z,  indicator of poverty Pi for each household i and indicators of within-group inequality (e.g., Gini, etc.)

8. Limitations • Not all policy challenges covered • PAMS best suited to simulate poverty and distributional implications of: • PRSP-PRGF macro baseline scenarios • Sensitivity analysis along the base case • Sectoral growth scenarios • Average tax burden (standard incidence analysis) • Average social transfer

9. PAMS: Inputs and Outputs • Micro input • Macro input • Micro-Macro Linkage

10. PAMS: Micro Input • Household Survey Data • Expenditure or income • Size of household • Household weight in population • Data arranged by socioeconomic groups of representative households

11. PAMS: Macro Input • Macro framework from any macro consistent model (IMF macro projections, World Bank’s RMSM-X model, other domestic macro models) Aggregate variables (GDP, BOP, fiscal accounts, monetary accounts, inflation)

12. PAMS: Micro-Macro Linkages • Labor market module breaks down the economy into sectors: rural/urban, formal/informal, tradable/non-tradable • Labor supply is driven by exogenous factors • Labor demand is demand is broken down by sector, skill level and location and depends on sector demand and real wages • Labor model produces wage income by representative households of SEG and location based on income aggregates, group-specific tax and transfer variables

13. PAMS: Micro-Macro Dynamics • Base year as starting point • Simulation of macro variables/population • Simulation labor demand and supply, wages and incomes by groups • Simulation of changes in HH-level income data to calculate poverty indicators assuming unchanged intra-group distribution of incomes

14. PAMS: Outputs • 1. Standard macroeconomic Indicators • 2. Standard poverty and inequality indicators (P0, P1, P2, Gini, etc.) • 3. Poverty decompositions: Growth, inequality and population effects with respect to P1 and P2

15. PAMS: Outputs • 4. Pro-poor growth indicators • Pro-poor growth index (Kakwani and Pernia, 2000) • Growth Incidence Curve (Ravallion and Chen, 2003) • Poverty Equivalent Growth Rate (Kakwani and Son, 2003)

16. Macro-Framework PAMS House H. Survey DEBT Results RMSM-X MEMAU Int. PAMS Micro Meso Assum PAMS

17. Simulation with PAMS Update Macro Update Earning & Trans. Module Pov. & Ineq Simul. Scen. Household survey Pov. & Ineq Baseline Scen. Iteration Process

18. Country Applications

19. PAMS: Burkina Faso • 1994, 1998, 2003 HHS • Longstanding macroeconomic Program with IMF • HIPC CP in 2000 (original) and enhanced (2002, with topping up) • Growth rates averaging 5 percent • Largely rural population

20. PAMS: Burkina Faso • Poverty rates (1998) of 45 percent based on national poverty line (which is below $1/day) • Cotton as major cash crop – 50-60 percent of exports, and significant growth of cotton production • Cereal production stabilized due to promotion of small-scale irrigation

21. PAMS development • Work started before 2003 HHS in context of PRSP • Interest in having better handle on poverty projections using macro-growth projections • Home-grown excel-based macro-model (IAP) with technical assistance of GTZ • Collaboration on PAMS based on 2003 HHS • PAMS model linked to IAP output tables

22. PAMS development • PAMS model linked to IAP output tables with support from local GTZ adviser and team • Close collaboration with macro forecasting division in Ministry of Economy and Development • (Political) challenge: integration of 2003 HHS because of weaknesses in data analysis

23. SEGs and Poverty, 1998-2003

24. Macro baseline scenario

25. Poverty baseline scenario

26. Inequality-growth tradeoff

27. 20-percent decline in cotton prices

28. 20 percent decline in cotton volume and cotton price

29. Increased primary sector contribution to growth

30. Lessons learned • Strong payoffs of building a close early collaboration with the government forecasting team • Close collaboration with the local GTZ technical assistance crucial • Close involvement of World Bank country office staff essential • Need to make greater allowance for the collection and analysis of poverty data when embarking on PAMS modeling