1. Growth Diagnostics Under Uncertainty: Comments on Peru and Paraguay Case Studies Competitiveness and Growth in LAC IDB, II Discussion Seminar Washington, DC 20-21 September 2007 Augusto de la Torre and Daniel Lederman

2. 2 Outline The good Room for improvement Final thoughts: GD method and uncertainty

3. 3 The 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

4. 4 Room 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

5. 5 The 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

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