Presentation on theme: "Monitoring the Social Impact of the Economic Crisis in West & Central Africa Quentin Wodon Development Dialogue on Values and Ethics Presentation at HDN-PREM."— Presentation transcript:
Monitoring the Social Impact of the Economic Crisis in West & Central Africa Quentin Wodon Development Dialogue on Values and Ethics Presentation at HDN-PREM Workshop June 11, 2009
Context Large impact from the economic crisis Examples include : (1) Food prices (many countries had increases in prices of 35% or more, and food prices remain higher than before); (2) Remittances (expected drop of 4.4% in 2009 from base level of $20 billion); (3) Prices of export commodities (drop in oil prices; cotton; others); (4) wealth effects (Nigerias stock exchange index has fallen 60%, Kenyas 40%); (5) risk of drop in ODA; etc.
Context Limited data and analytical capacity Examples include : (1) Most countries have one LSMS or extended CWIQ survey every 5 years or so; (2) Many countries lack income and employment modules in their surveys; (3) Statistical offices are cash-trapped, dont have funds for M&E and are donor dependent; (4) Existing economic indicators are often not nationally representative (inflation data for capital city only); (5) analytical capacity to use existing data is weak; etc.
Suggestions 1. Do the best with what you have - this includes using simulation-based M&E; 2. Implement light data collection mechanisms that are low cost but nevertheless informative; 3. Rely on qualitative data even if it is small scale and not statistically representative (and progressively build statistical and analytical capacity, as well as culture of M&E and evaluation)
1. Do the best with what you have - this includes using simulation-based M&E Illustration: Likely Impact of food price crisis Example 1: Impact on aggregate poverty measures Example 2: Geography of impact Example 3: Macroeconomic multiplier impacts Example 4: Targeting of policy responses Question: what is the level of analysis or monitoring needed given the type of policies considered? Answer: In many cases, the existing data is enough to answer the policy questions with reasonable accuracy
Example 1: Impact on Headcount of Higher Food Prices
Example 2: Likely Geography of Impacts
Choice of poverty indicator matters often more than getting perfect M&E data HeadcountPoverty Gap
Example 3: Multiplier effects Using SAMs
Example 4: Policy Responses: Subsidies CD curves show share of consumption of a good by cumulative share of population ranked by consumption Best goods to subsidize are those with highest CD curve (Kerosene, and to a lower extent firewood and bus transport) CD curves can also be used for balanced budget tax reforms
2. Implement light data collection mechanisms that are low cost & informative 4 examples (1) Economic Crisis and mechanisms of solidarity survey in Senegal Cost at $35,000 for 1,000 observations in greater Dakar area Link with national household survey (predicted consumption) Various modules on impacts (quantitative & subjective) Modules on 4 types of responses or coping strategies: 1) household (labor supply, expenditures); 2) state-funded programs; 3) NGOs and FBOs; and 4) private transfers (2) Evaluation of Liberia & SL cash-for-work programs Cost at $20,000 or less for 1,000 individuals Light questionnaire with info on 3 main topics: 1) household characteristics (to predict consumption and targeting performance); 2) labor supply (to assess substitution effects); and 3) perceptions regarding infrastructure projects funded
2. Implement light data collection mechanisms that are low cost & informative 4 examples (3) Individual perceptions and priorities of the population surveys Implemented in Burundi & DRC at time of PRSP preparation Cost of $50,000 for 3,000 individuals in Burundi General questions on well-being, priorities, etc., and possibility to add special modules (coffee in Burundi) And (4) Special modules added to already planned surveys Burkina Faso 2003 survey (after 2002 coup in Cote dIvoire) included special module on remittances to assess shock
3. Rely on qualitative data even if it is small scale and not statistically representative 2 examples (1) PRSP preparation in Cape Verde No new survey data with good consumption information Rapid qualitative assessments with focus groups: key issue is unemployment, but not in all areas, plus feedback on social programs implemented by governments (2) Participatory poverty monitoring in CAR PPA key to understand challenges confronted by population (issues of conflict and governance, incl. inn service delivery) Concept of participatory monitoring for PRSP implementation
And build statistical and analytical capacity, as well as culture of M&E and evaluation