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P ROJECTIONS AND N EEDS FOR T IMELY AND F REQUENT D ATA

P ROJECTIONS AND N EEDS FOR T IMELY AND F REQUENT D ATA. Sergio Olivieri April 20, 2011. Outline. Motivation Projections & data needs Main messages. I. Motivation. Why do we need projections? When a macro-shock hits a country, data analysis is crucial to design alleviation policies

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P ROJECTIONS AND N EEDS FOR T IMELY AND F REQUENT D ATA

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  1. PROJECTIONSAND NEEDSFOR TIMELYAND FREQUENT DATA Sergio Olivieri April 20, 2011

  2. Outline • Motivation • Projections & data needs • Main messages

  3. I. Motivation • Why do we need projections? • When a macro-shock hits a country, data analysis is crucial to design alleviation policies • Even without a macro-shock, data analysis is relevant to design medium term-development strategies (e.g. PRSP) • Different kind of questions • What is the main constraint? • Lack of “better” data: comprehensive, frequent & timely data • What is the alternative? • Projections or ex-ante impact evaluations • Why is “better” data so important?

  4. II. Projections & data needs • Projections • Several approaches (*) In terms of data and time O = Overall impacts; D = Distributional impacts • Accuracy of projections • Data that feeds the estimation model • Assumptions of the model

  5. II. Projections & data needs • Data requirements: Comprehensiveness Comparison of some basic data requisites by method

  6. II. Projections & data needs • Data requirements: Comprehensiveness • Overall impacts on poverty and inequality Poverty & Inequality Results – Bangladesh Source: Habib et. al (2010)

  7. II. Projections & data needs • Data requirements: Comprehensiveness • Distributional impacts: Growth Incidence Curves Complex models: Micro-simulation or Top-down Source: Habib et. al (2010 (a)) and Habib, et. al (2010(b)) Philippines Bangladesh

  8. II. Projections & data needs • Data requirements: Comprehensiveness • Distributional impacts: Characteristics of crisis-vulnerable Complex models: Micro-simulation or Top-down % of crisis-vulnerable household heads who are low-skilled (0-9 yrs of education)

  9. II. Projections & data needs • Data requirements: Timely & Frequent data • Less timely & frequent data  less accurate projections Elasticity of employment to output by sector: Mexico Source: Own estimations based on INEGI (2008-09) and SEDESOL (2010) • 2009 • Based on actual data of GDP and ENOE 2009 • More inelastic during the financial crisis except “Other Industries” • 2010-11 • Longer-term elasticity estimated over 2003-08 data

  10. III. Main messages • Why is “better” data so important for projections? • It is important because: • In terms of Comprehensiveness: • Complexity of technique  answer question • In terms of Timeliness & Frequency: • Quality and accuracy of projections

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