1 / 13

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

egan
Download Presentation

What’s good

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related