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”

ARG7073ARG7477ARG7881ARG8285ARG8689ARG9093ARG9497

BFA7073

BFA7477

BFA7881

BFA8285BFA8689

BFA9093BFA9497

BGR7881BGR8285BGR8689BGR9093BGR9497BOL7073BOL7477BOL7881BOL8285

BOL8689BOL9093BOL9497

BRA7073BRA7477BRA7881BRA8285BRA8689BRA9093BRA9497

BWA7073BWA7477BWA7881

BWA8285BWA8689BWA9093

BWA9497CHL7073CHL7477CHL7881CHL8285CHL8689CHL9093CHL9497CHN7477CHN7881CHN8285CHN8689CHN9093CHN9497

CIV7073CIV7477CIV7881CIV8285CIV8689

CIV9093

CIV9497

CMR7073CMR7477CMR7881CMR8285CMR8689

CMR9093CMR9497

COG7073COG7477COG7881COG8285

COG8689COG9093

COG9497

COL7073COL7477COL7881COL8285COL8689COL9093COL9497CRI7073CRI7477CRI7881

CRI8285CRI8689CRI9093CRI9497DOM7073DOM7477DOM7881DOM8285

DOM8689DOM9093DOM9497DZA7073DZA7477DZA7881DZA8285DZA8689DZA9093DZA9497ECU7073ECU7477ECU7881ECU8285ECU8689ECU9093ECU9497

EGY7073

EGY7477

EGY7881EGY8285EGY8689

EGY9093

EGY9497ETH7073ETH7477ETH7881ETH8285

ETH8689ETH9093

ETH9497GAB7073

GAB7477GAB7881GAB8285GAB8689GAB9093GAB9497GHA7073GHA7477GHA7881GHA8285

GHA8689GHA9093

GHA9497

GMB7073

GMB7477

GMB7881GMB8285

GMB8689

GMB9093

GMB9497

GTM7073GTM7477GTM7881GTM8285GTM8689GTM9093GTM9497HND7073HND7477

HND7881

HND8285HND8689HND9093HND9497

HTI7073

HTI7477HTI7881HTI8285HTI8689

HTI9093

HTI9497

HUN7477HUN7881HUN8285HUN8689HUN9093HUN9497IDN7073

IDN7477IDN7881IDN8285IDN8689IDN9093IDN9497IND7073IND7477IND7881IND8285IND8689IND9093IND9497IRN7073IRN7477IRN7881IRN8285IRN8689IRN9093IRN9497JAM7073JAM7477

JAM7881JAM8285JAM8689JAM9093

JAM9497

JOR7073

JOR7477JOR7881

JOR8285

JOR8689JOR9093

JOR9497KEN7073KEN7477KEN7881KEN8285

KEN8689KEN9093KEN9497KOR7073

KOR7477KOR7881KOR8285KOR8689KOR9093KOR9497LKA7073LKA7477LKA7881LKA8285LKA8689LKA9093LKA9497MAR7073MAR7477MAR7881MAR8285

MAR8689MAR9093MAR9497

MDG7073MDG7477MDG7881MDG8285

MDG8689MDG9093MDG9497

MEX7073MEX7477MEX7881MEX8285MEX8689MEX9093MEX9497

MLI7073

MLI7477MLI7881MLI8285

MLI8689MLI9093MLI9497

MMR7073MMR7477MMR7881MMR8285MMR8689

MMR9093MMR9497

MWI7073MWI7477

MWI7881

MWI8285

MWI8689

MWI9093

MWI9497

MYS7073MYS7477MYS7881MYS8285MYS8689MYS9093MYS9497

NER7073

NER7477NER7881NER8285

NER8689NER9093

NER9497

NGA7073NGA7477NGA7881NGA8285NGA8689NGA9093NGA9497NIC7073NIC7477

NIC7881NIC8285

NIC8689

NIC9093NIC9497

PAK7073PAK7477PAK7881PAK8285PAK8689PAK9093PAK9497PER7073PER7477PER7881PER8285PER8689PER9093PER9497PHL7073PHL7477PHL7881PHL8285PHL8689PHL9093PHL9497

PNG7073PNG7477PNG7881

PNG8285PNG8689PNG9093

PNG9497

POL7477POL7881POL8285POL8689POL9093POL9497PRY7073PRY7477PRY7881PRY8285PRY8689PRY9093PRY9497ROM7477ROM7881ROM8285ROM8689ROM9093ROM9497

SEN7073SEN7477SEN7881SEN8285

SEN8689SEN9093

SEN9497

SLE7073SLE7477SLE7881

SLE8285SLE8689SLE9093

SLE9497

SLV7073SLV7477SLV7881

SLV8285SLV8689

SLV9093SLV9497SYR7073

SYR7477SYR7881

SYR8285SYR8689SYR9093SYR9497

TGO7073

TGO7477TGO7881

TGO8285TGO8689TGO9093TGO9497

THA7073THA7477THA7881THA8285THA8689THA9093THA9497TTO7073TTO7477TTO7881TTO8285TTO8689TTO9093TTO9497

TUN7073TUN7477TUN7881TUN8285TUN8689TUN9093TUN9497TUR7073TUR7477TUR7881TUR8285TUR8689TUR9093TUR9497

UGA7073UGA7477UGA7881UGA8285

UGA8689

UGA9093UGA9497

URY7073URY7477URY7881URY8285URY8689URY9093URY9497VEN7073VEN7477VEN7881VEN8285VEN8689VEN9093VEN9497

ZAR7073ZAR7477ZAR7881ZAR8285ZAR8689

ZAR9093ZAR9497

ZMB7073ZMB7477

ZMB7881ZMB8285

ZMB8689

ZMB9093

ZMB9497

ZWE7073ZWE7477ZWE7881

ZWE8285ZWE8689ZWE9093ZWE9497

-50

510

15A

id/G

DP

-5 0 5 10Aid/GDP * Tropical Area Fraction

Aid/GDP vs. Aid/GDP×tropical area fraction, Dalgaard, Hansen, and Tarp (2004) dataset

Roodman, Through the Looking-Glass and What OLS Found There

• 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

Inside AJT’s black box

Assumption needed to show causality

Population foreign aid/capita growth

Population “instruments” aid.Actual instrument is more complex, based on population.

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.

Simplifying,

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