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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 • Credibility of instrument • History of new techniques undone See also Dalgaard and Hansen 2001 Four realities, one best-fit line Anscombe, F.J. 1973. Graphs in Statistical Analysis. The American Statistician Dalgaard, Hansen, and Tarp 2004 “deep determinant” 15 Aid/GDP vs. Aid/GDP×tropical area fraction, Dalgaard, Hansen, and Tarp (2004) dataset JOR7881 10 JOR7477 ZMB9497 GMB8689 ZMB9093 HTI9497 MWI9093 GMB9093 NIC9093 PNG7477 PNG7073 MLI8689 JOR7073 NER8689 GMB7881 PNG7881 NIC9497 NER9093 MLI9093 PNG8285 GMB8285 TGO9093 TGO8285 MWI8689 MLI9497 SEN8689 MWI9497 BFA9093 MLI7881 TGO8689 ZMB8689 BFA7881 MLI8285 MLI7477 BFA9497 TGO9497 BWA7881 PNG8689 NER7477 UGA9093 SEN9093 PNG9093 EGY7477 BWA7477 SLE9497 NER8285 NER9497 JOR8689 ETH9093 NER7881 CIV9497 SYR7881 BFA8689 MWI7881 JOR9093 NIC8689 SEN9497 GHA8689 UGA9497 ETH8689 BFA7477 TGO7881 BWA7073 MDG9093 COG9497 BFA8285 ZMB8285 SYR7477 BWA8285 UGA8689 SLV8689 ZMB7881 MDG9497 BWA8689 HND8285 SLV8285 MDG8689 HND9093 TGO7477 ETH8285 SEN8285 BOL9497 NIC8285 GHA9093 BOL8689 GMB9497 HND8689 MWI8285 TUN7073 EGY9093 ZAR8689 SEN7881 BOL9093 PNG9497 KEN8689 MLI7073 KEN9093 HTI8689 NER7073 HND9497 CMR9497 ZWE9093 ETH9497 JAM8285 BFA7073 MWI7477 MWI7073 CIV9093 BWA9093 SEN7477 GHA9497 JAM8689 SYR8285 ZWE9497 CRI8285 NIC7881 SEN7073 SLV9093 EGY7881 KEN8285 CMR7477 SLE9093 CMR7073 COG7881 HTI8285 GMB7477 ETH7881 MDG8285 KEN7881 JOR9497 SLE8689 ZAR7881 CMR9093 SLE8285 JAM9093 ZWE8285 ZAR9093 GAB7073 TUN7477 CMR7881 ZAR7073 COG7477 COG8285 CRI8689 ZWE8689 MMR7881 JAM7881 TGO7073 GAB9497 KEN9497 KEN7073 ZMB7477 GHA8285 EGY7073 ZAR7477 HND7881 HTI9093 LKA7881 ZAR8285 ETH7477 LKA8285 HTI7881 UGA8285 EGY8285 BOL8285 LKA8689 PAK7073 LKA9093 IDN7073 MDG7881 MMR8689 GAB9093 HTI7477 GAB8285 ZAR9497 MMR8285 SLE7881 KOR7073 PAK7477 GHA7881 BWA9497 MDG7073 SLV9497 KEN7477 DOM8285 GHA7073 MAR7881 BOL7881 EGY9497 MDG7477 COG9093 MAR7073 EGY8689 CIV7073 CMR8689 LKA7477 MAR8285 PAK7881 SYR8689 DZA7073 JAM9497 CIV8689 ETH7073 MAR9093 POL9497 SYR7073 TUN7881 GAB8689 CMR8285 HND7477 UGA7881 GTM8689 COG7073 SLV7881 TUN8689 BOL7073 COG8689 POL9093 ZWE7881 TUN9093 BOL7477 PRY7073 MMR7477 UGA7073 LKA9497 PAK8285 TUN8285 GHA7477 MAR7477 PAK8689 LKA7073 DOM7073 GAB7477 DOM7881 MMR7073 PHL8689 COL7073 PRY7477 PER9093 MAR9497 SYR9093 GTM9093 NIC7477 PHL9093 CIV7477 DOM8689 GTM9497 ZMB7073 PRY8285 CRI9093 IDN7477 PAK9093 PRY8689 CIV7881 TUR7073 GAB7881 PHL7073 UGA7477 IND7477 IND7073 PRY9497 PRY9093 PER8285 NIC7073 PAK9497 PRY7881 NGA7073 PHL9497 CRI7881 MAR8689 GTM8285 TUR7881 TUR9093 IND7881 PER9497 HND7073 SLE7477 MMR9093 GTM7881 PHL8285 CIV8285 ECU9093 PER7073 ROM9093 TUN9497 DZA7477 CHL7073 DOM7477 ECU7073 ECU9497 PER7881 PER7477 ROM9497 DOM9497 IDN9093 SLV7477 GTM7477 IDN7881 PER8689 PHL7477 BGR9497 KOR7477 IND8285 MMR9497 DOM9093 GTM7073 PHL7881 MYS7073 TUR8285 ECU7477 ECU8285 IDN8689 THA7073 THA8285 CRI7073 ECU8689 THA7881 HUN9497 SYR9497 JAM7073 THA8689 IDN8285 JAM7477 DZA7881 DZA9497 IND9093 IND8689 POL8285 CHL7477 DZA9093 BRA7073 CRI7477 THA9093 IDN9497 THA7477 MYS8285 SLV7073 BGR9093 KOR7881 DZA8689 COL7477 ECU7881 MYS8689 MYS7477 THA9497 HUN7881 HUN9093 TUR7477 TUR9497 URY7073 URY8689 URY9497 CHL9497 DZA8285 IND9497 NGA9497 MYS9093 NGA9093 CHL8285 CHN9093 CHN8689 KOR8285 POL7881 TUR8689 CHL7881 CHL9093 MEX7073 COL9497 NGA7477 TTO8689 MYS7881 CHN9497 CHN8285 IRN9497 IRN9093 KOR9093 ROM7881 ROM7477 URY8285 URY7881 URY9093 BRA7477 COL8285 CRI9497 NGA8689 TTO7881 TTO9497 COL7881 TTO8285 ARG8285 ARG7881 ARG7477 ARG7073 BGR7881 BRA8285 BRA7881 BRA9497 CHN7881 CHN7477 COL9093 HUN7477 HUN8285 IRN8689 IRN8285 IRN7881 IRN7477 KOR8689 MEX8285 MEX7881 MEX7477 MEX9497 NGA8285 POL7477 POL8689 ROM8689 ROM8285 TTO9093 URY7477 VEN8285 VEN7881 VEN7477 VEN7073 NGA7881 BRA9093 BRA8689 MEX9093 MEX8689 VEN8689 VEN9497 ARG9497 BGR8285 IRN7073 KOR9497 ZWE7477 VEN9093 COL8689 TTO7477 ARG8689 MYS9497 ARG9093 CHL8689 BGR8689 HUN8689 SLE7073 TTO7073 HTI7073 ZWE7073 0 5 JOR8285 -5 GMB7073 -5 0 5 Aid/GDP * Tropical Area Fraction Roodman, Through the Looking-Glass and What OLS Found There 10 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 Assumption needed to show causality Simplifying, Population foreign aid/capita growth We assume: A. 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. Not discussed? 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 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 A mathematician’s perspective: I am an aid regression skeptic Gödel’s incompleteness theorem Heisenberg’s uncertainty principle
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