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Econometric Features of Models Used in Aid Allocation Studies

Ågren, Sandra LU (2019) STAH11 20182
Department of Statistics
Abstract
Research of aid allocation deals with a dependent variable, received aid expressed in absolute
or relative terms, that is equal to zero for numerous observations. This is because donor countries
tend to target specific countries for their allocation, leaving the rest of the countries without any
development assistance. The special characteristic requires non-linear methods with censoring,
truncation or selection bias of the data.

Using a panel covering Swedish aid recipient countries between 1998-2016, three commonly used
models in aid allocation are examined; a multiple linear regression on a truncated data set, Heckman’s
two step model and the Tobit model. The models are estimated with a set of political and
altruistic... (More)
Research of aid allocation deals with a dependent variable, received aid expressed in absolute
or relative terms, that is equal to zero for numerous observations. This is because donor countries
tend to target specific countries for their allocation, leaving the rest of the countries without any
development assistance. The special characteristic requires non-linear methods with censoring,
truncation or selection bias of the data.

Using a panel covering Swedish aid recipient countries between 1998-2016, three commonly used
models in aid allocation are examined; a multiple linear regression on a truncated data set, Heckman’s
two step model and the Tobit model. The models are estimated with a set of political and
altruistic variables that are frequently used as explanatory factors to aid allocation, with share of
Swedish aid as dependent variable.

With around 13 % of the total observations below threshold, the models yield similar parameter
estimations. The results from Heckman’s two step model and the multiple linear regression are
almost, but not exactly, the same. This can partly be explained by the information each model
has of the dependent variable, and partly by a small selection bias.

In general, the parameters have approximately the same impact on the dependent variable. However,
the estimations in the Tobit model are slightly different from the other models. Countries in
sub-Saharan Africa, the educational level and the expected lifespan in the recipient country have
a significant effect on the share of Swedish aid received according to the Tobit model, but not in
the other models. This is mainly explained by the different estimation methods in the models. (Less)
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author
Ågren, Sandra LU
supervisor
organization
course
STAH11 20182
year
type
M2 - Bachelor Degree
subject
keywords
Heckman's two step model Tobit model Multiple linear regression Aid allocation
language
English
id
8968590
date added to LUP
2019-02-07 08:17:41
date last changed
2019-02-07 08:17:41
@misc{8968590,
  abstract     = {{Research of aid allocation deals with a dependent variable, received aid expressed in absolute
or relative terms, that is equal to zero for numerous observations. This is because donor countries
tend to target specific countries for their allocation, leaving the rest of the countries without any
development assistance. The special characteristic requires non-linear methods with censoring,
truncation or selection bias of the data.

Using a panel covering Swedish aid recipient countries between 1998-2016, three commonly used
models in aid allocation are examined; a multiple linear regression on a truncated data set, Heckman’s
two step model and the Tobit model. The models are estimated with a set of political and
altruistic variables that are frequently used as explanatory factors to aid allocation, with share of
Swedish aid as dependent variable.

With around 13 % of the total observations below threshold, the models yield similar parameter
estimations. The results from Heckman’s two step model and the multiple linear regression are
almost, but not exactly, the same. This can partly be explained by the information each model
has of the dependent variable, and partly by a small selection bias.

In general, the parameters have approximately the same impact on the dependent variable. However,
the estimations in the Tobit model are slightly different from the other models. Countries in
sub-Saharan Africa, the educational level and the expected lifespan in the recipient country have
a significant effect on the share of Swedish aid received according to the Tobit model, but not in
the other models. This is mainly explained by the different estimation methods in the models.}},
  author       = {{Ågren, Sandra}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Econometric Features of Models Used in Aid Allocation Studies}},
  year         = {{2019}},
}