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Poverty Analysis Macroeconomic Simulator (PAMS) and PSIA with an application to Burkina Faso Jan Walliser Senior Economist The World Bank Outline of the Presentation Introduction PAMS: Inputs and Outputs A brief tour of PAMS A Set of Policy Experiments Introduction: why “macro”PSIA? Changes in the macro framework such 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? 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? Modeling Implications and Challenges Maintain simplicity of macroeconomic consistency frameworks (e.g., RMSMXs or other country-based models) Link macro-consistency frameworks directly with household survey data 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 Top-down HHL "micro-simulation" approach General Structure : 3 Layers Layer 1: Macro Macroeconomic Model Macro Accounting (RMSM-X), CGE (123), Econometric Sectoral Disaggregation, Factor Markets Linkage Aggregate Var For k representative groups of households Layer 2: Meso y k , Lk , wk , Pk Household Survey (HHS), i individual households, Macro "consistent" changes in real household incomes and change in the distribution of welfare yi wi Li Ei R( wi Li Ei ; Ai ) / P(Ci ; p) Layer 3: Micro yi yi , 1 yi , Li f (Y ), wi g (Y , A) (yi) with poverty line, z, indicator of poverty Pi for each household i and indicators of within-group inequality (e.g., Gini, etc.) 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 PAMS: Inputs and Outputs Micro input Macro input Micro-Macro Linkage PAMS: Micro Input Household Survey Data Expenditure or income Size of household Household weight in population Data arranged by socioeconomic groups of representative households 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) 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 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 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 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) PAMS Macro-Framework PAMS House H. Survey DEBT Results RMSM-X MEMAU Int. PAMS Meso Assum Micro Simulation with PAMS Update Macro Update Earning & Trans. Module Pov. & Ineq Simul. Scen. Household survey Pov. & Ineq Baseline Scen. Iteration Process Country Applications PAMS: Implementation Process Identification Country Specific Application 1/ Operationalization 2/ Country Calibration6/ National Team Training 3/ Official Delivery Follow up Activities 5 15 3*5=15 N.D N.D X X X X X X X X X X X X X X X X X X Region contact Definition TOR Processing HHS Set Interface Pov. M. N.D 5/ N.D 15 5 5 Burkina Faso X X X X Mauritania X X X Cameroon X Djibouti X Ethiopia X Albania X X X Indonesia X X X Rwanda Mali Benin Guinea X X X X X X Timing (days)4/ Dissemination and Validation Set Update the Interface Program Macro M. X X 1 The PAMS development phase started in October 2001 and its first application to a pilot country was October 2002. 2 At this stage, the National Team becomes part of PAMS Community of Practice (the network puts together countries applying PAMS as well as the WB Region). 3 A course delivered in 3 Modules. The first is the "Introduction to PAMS", the second is "Modeling with PAMS". The training is delivered by means of Face-to-Face and Videoconferenc the third is the "Advanced Training on PAMS and delivery." 4 This is a rough estimate of the average number of days required to complete the task. 5 Not defined. 6 Includes data consistency check as well. 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 19 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 20 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 21 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 22 SEGs and Poverty, 1998-2003 Share of Population Share of Poor Poverty Headcount 1998 2003 1998 2003 1998 2003 Rural area. Urban area 86.3 13.7 79.5 20.5 94.1 5.4 91.0 9.0 62.2 21.1 52.7 20.9 Public sector (Urban) Agricultural tradable (Rural) Other agricultural non-tradable (Rural) Family helpers and others (Rural) Non labor force (Rural) Private formal tradable (Urban) Private formal non-tradable (Urban) Informal (Urban) Unemployed (Urban) 4.1 16.8 65.3 0.6 3.6 1.0 1.9 5.6 1.1 3.6 18.3 59.6 0.7 1.0 0.8 2.6 7.4 6.0 0.7 16.4 74.6 0.3 3.3 0.1 1.2 2.3 1.0 0.3 18.6 71.0 0.6 0.8 0.1 0.9 3.4 4.3 9.1 53.1 61.8 30.3 50.4 8.1 33.3 22.8 47.8 3.4 47.1 55.3 42.0 38.8 7.7 15.7 21.5 33.1 23 Macro baseline scenario Selected macro indicators Real GDP growth 1/ Primary sector 1/ Secondary sector 1/ Tertiary sector 1/ Fiscal revenue 2/ Public expenditure 2/ Exports of goods 1/ CPI (percentage change) 2003 Act. 2004 Proj. 2005 Proj. 2006 Proj. 2007 Proj. 8.0 10.8 10.4 5.5 11.3 22.0 10.7 2.1 4.8 1.8 6.3 6.1 12.0 22.5 15.8 2.2 5.3 4.5 6.7 5.3 12.5 22.7 16.4 2.2 5.2 4.5 6.6 6.8 13.0 22.9 8.5 2.0 5.2 4.5 6.6 6.8 13.5 23.6 6.3 2.0 24 Poverty baseline scenario Poverty Incidence National Rural Urban Demographic structure Annual growth rate 3/ National Rural Urban Share of population Rural Urban 2003 Act. 2004 Proj. 2005 Proj. 2006 Proj. 2007 Proj. 46.4 53.1 20.5 44.1 51.4 19.7 42.4 49.6 17.9 40.3 47.6 16.0 39.2 46.6 15.4 5.1 4.6 7.8 2.4 1.9 4.3 2.4 1.9 4.3 2.4 1.9 4.2 2.4 1.9 4.2 79.5 20.5 79.1 20.9 78.8 21.2 78.4 21.6 78.0 22.0 25 Inequality-growth tradeoff 2003 2004 2005 2006 2007 Poverty Gap Growth elasticity Inequality elasticity Inequality/Growth Tradeoff -2.0 2.8 1.4 -2.1 3.1 1.5 -2.1 3.3 1.6 -2.2 3.6 1.6 -2.2 3.8 1.7 Square Poverty Gap Growth elasticity Inequality elasticity Inequality/Growth Tradeoff -2.5 4.7 1.9 -2.4 5.0 2.1 -2.4 5.3 2.2 -2.4 5.6 2.3 -2.3 5.8 2.5 26 20-percent decline in cotton prices 2. 0% 1. 5% 1. 0% 0. 5% 0. 0% -0. 5% -1. 0% -1. 5% -2. 0% -2. 5% 2003 2004 2005 Gini-Total 2006 2007 P0 27 20 percent decline in cotton volume and cotton price 3.0% 2.0% 1.0% 0.0% -1.0% -2.0% -3.0% -4.0% -5.0% -6.0% 2003 2004 2005 Gini-Total 2006 2007 P0 28 Increased primary sector contribution to growth 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% -1.0% -2.0% -3.0% -4.0% -5.0% 2003 2004 2005 2006 2007 2008 2009 Gini-Total 2010 2011 2012 2013 2014 P0 29 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 30