This document summarizes a discussion of a paper that examines whether humanitarian aid crowds out development aid using dynamic panel data analysis. The discussant notes that the paper found a small crowding-in effect of humanitarian aid on development aid, contrary to expectations. Issues raised for consideration include the channels through which humanitarian aid may impact development aid, differences in how countries define and report humanitarian aid expenditures, and potential methodological issues around the use of a gravity model framework, treatment of zero values, endogeneity, and choice of instruments.

1. Does Humanitarian Aid Crowd Out
Development Aid?
A Dynamic Panel Data Analysis
Discussant
Rajan Krishna Panta
Arndt-Corden Department of Economics
Crawford School of Public Policy
4 November, 2013
1

2. Context and overview of the paper
•
Different historical backgrounds of humanitarian
assistance and development assistance: Second
World War and Marshall Plan
•
Funding gap
•
Crowding-in effect of humanitarian aid on
development aid though small
•
Methodology
2

3. Issues for consideration
• Channels of effects of humanitarian aid on development
aid: what is the hypothesis? Why did we get the opposite
results than expected?
• 0.7 % of GNI/aid target
“Each economically advanced country will progressively increase its
official development assistance to the developing countries and will
exert its best efforts to reach a minimum net amount of 0.7 per cent of
its gross national product … by the middle of the Decade.” (UN, 1970)
• Large cross-country variations
3

4. 4

5. 5

6. Issues for consideration: Lack of definition
• Some countries include rehabilitation measures, other do
not; that there is a difference between DAC reports,
Country reports and the Reliefweb reporting on
humanitarian aid expenditures
• Humanitarian assistance is rarely just the concern of a
single aid department; other, often ministries are
involved, and humanitarian aid programmes are at times,
linked with a government’s broader objectives and
policies. This can lead to disagreement among donors
and humanitarian actors as to what humanitarian aid is
for, and how performance can be measured.
6

7. 1995 Bilateral Humanitarian Aid Expenditures except emergency food aid (in $ million)
Country
Definition (as of 1997)
DAC
Relief
web
Country
Report
Belgium
Prevention of conflicts; emergency aid; rehabilitation
16
9
14
France
Not Clearly Defined
138
24
24
UK
Disaster preparedness; Disaster Relief; Refugee Relief
182
151
237
Nether
lands
Prevention; Emergency Aid; Rehabilitation; Aid for the recipient
and displaced people
350
264
276
Luxem
bourg
Not Clearly Defined
7
5
7
Finland
Emergency Aid; Aid to refugees; Aid to democratising efforts;
others
23
20
20
Source: http://www.cred.be/centre/publi/164e/ch3.htm

8. Issues for consideration (estimation)
• Appropriateness of gravity model framework
• Lot of independent variables are either zero or missing. For eg. Out
of total observations, only 1/3 of humanitarian aid values
• Dealing with zero values
- Ad-hoc solution method : though log(0) is undefined
log(0+0.00001) is not. For small x, log(x+0.00001)= logx
- Poisson model
- Heckman sample selection model
• Endogeneity
- which are the endogenous variables and what are the
instruments
- Reporting of first stage regressions
8