growth diagnostics under uncertainty: comments on peru and paraguay case studies
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Growth Diagnostics Under Uncertainty:Growth Diagnostics Under Uncertainty:Comments on Peru and Paraguay Case StudiesComments on Peru and Paraguay Case Studies
Competitiveness and Growth in LACCompetitiveness and Growth in LACIDB, II Discussion SeminarIDB, II Discussion Seminar
Washington, DC20-21 September 2007
Augusto de la Torreand
Daniel Lederman
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OutlineOutline
The good
Room for improvement
Final thoughts: GD method and uncertainty
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The GoodThe Good
A “disciplined” approach for setting policy priorities with multiple storylines
Peru: getting monkeys on new and taller trees through a process of industrial policy, exchange-rate protection, reducing (perception of) risk of expropriation, and possibly labor market reform
Paraguay: getting monkeys on new and taller trees through improvements in infrastructure and governance
Approach relies on well thought out descriptive statistics and underpinned by existing empirical papers
No new evidence (linking explanatory variables to growth) is presented
Significant reliance of GD process on results of cross-country regressions
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Room for ImprovementRoom for Improvement
Some alternative stories are dismissed too readily
Education in Peru: levels versus quality and skill mismatches
Finance in Peru or Paraguay: interest rates vs. financial system quality
Fuzzy distinction between correlates and constraints to growth
Export structure is endogenous, and can be due to multiple causes
Unexplored hypotheses
Poor integration between Lima and the Andes – a latent constraint?
If policy-making process matters, then even Peru needs to keep an eye on governance issues and politics
Check consistency of method and recommendations
RER depreciated dramatically during the 1980s and export structure did not change in Peru
Expand discussion and be more cautious
A venture-capital Development Bank for Peru? Devil is in the details
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The GD Method and UncertaintyThe GD Method and Uncertainty
GD method rests on good judgment –“argumentation” rather than formal or mathematical logic
Preponderance of evidence rather than formal proofs
A degree of uncertainty is at the heart of “argumentation”
Model uncertainty
Inconclusive evidence to reject one model over another
Even if chosen “model” is correct, methodology does not explicitly recognize margin of error around claims and recommendations
Problem of Type I and Type II errors
Layers of constraints or “nested” constraints
Uncertainty in policy implementation
Perhaps a diversified “portfolio” of reform agendas is optimal after all
ENDEND
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