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What’s good

What’s good. Good knowledge of literature Humble Care in rethinking R&S specification and using robust evaluation methods Sensitivity tests One of the most careful aid-growth studies. Major concerns. Data mining? 1970-2000 timeframe vs. others Black box problem/fragility

courtney-fischer
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What’s good

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  1. What’s good • Good knowledge of literature • Humble • Care in rethinking R&S specification and using robust evaluation methods • Sensitivity tests One of the most careful aid-growth studies

  2. Major concerns • Data mining? • 1970-2000 timeframe vs. others • Black box problem/fragility • Credibility of instrument • History of new techniques undone

  3. See also Dalgaard and Hansen 2001

  4. Four realities, one best-fit line • Anscombe, F.J. 1973. Graphs in Statistical Analysis. The American Statistician

  5. Dalgaard, Hansen, and Tarp 2004 “deep determinant”

  6. Aid/GDP vs. Aid/GDP×tropical area fraction, Dalgaard, Hansen, and Tarp (2004) dataset Roodman, Through the Looking-Glass and What OLS Found There

  7. Inside AJT’s black box • Elaborate weighting could opaquely increase dependence on handful of observations • Low-aid countries that look like high-aid ones and v.v. • Again Jordan-driven? • Need pictures • List low- and high-aid countries and their weights

  8. Assumption needed to show causality Simplifying, Population foreign aid/capita  growth We assume: Population affects growth only through aid. That plus data—an observed correlation between population and growth—leads to: B. Aid affects growth. Population “instruments” aid. Actual instrument is more complex, based on population.

  9. Not discussed?

  10. History of new techniques undone(read AJT!) • Cross-section OLS • Panels • 2SLS • Difference GMM (Hansen & Tarp 2001) • System GMM (Dalgaard, Hansen, & Tarp 2004) • Now? Propensity score methods • Return to cross-section

  11. Panel vs. cross-section • Hansen & Tarp 2001 argue presence of fixed country-level factors that simultaneously influence aid and growth (fixed effects) makes Burnside & Dollar inconsistent • Panel methods: studying variation over time within countries, not variation across countries • Contrarily, AJT assumes no fixed effects • …or at least that its controls suffice to capture them (while B&D’s don’t?) • Allows cross-section methods • My point: not “gotcha,” but: • Circling back suggests fundamental difficulties

  12. Gödel’s incompleteness theorem Heisenberg’s uncertainty principle A mathematician’s perspective:I am an aid regression skeptic

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