Does Aid Contribute to Sustainable Development Goals? Empirical Evidence from a Donor Comparison
(Sprache: Englisch)
No Poverty, Zero Hunger, Good Health, Well-being and Quality Education - these are the first priorities of the Sustainable Development Goals (SDGs) that were launched jointly by all UN Member States on January 1, 2016. The agenda of this agreement contains...
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No Poverty, Zero Hunger, Good Health, Well-being and Quality Education - these are the first priorities of the Sustainable Development Goals (SDGs) that were launched jointly by all UN Member States on January 1, 2016. The agenda of this agreement contains 17 main goals with a total of 169 targets and is dedicated to improving global living conditions and to address issues of environmental and economical sustainability with a planning horizon through to 2030. Development assistance from economically advanced countries, also referred to as aid, is one of the major means to provide financing for countries with less developed economies that face severe social problems, and which often cannot handle these problems alone.Previous studies have shown, however, that aid is ineffective and recommend comprehensive restructuring of the common aid practices. Investigations that analyse the pattern of aid flows find, moreover, that granting aid to certain recipient countries cannot only be explained by altruistic motives. They show that several strategic or non-strategic reasons have a high explanatory power for individual donor aid allocation.
Against this background, the present study explores aid effectiveness of distinct bilateral donors. This is achieved by a large-scale panel data analysis applying per-capita economic growth, infant mortality and primary growth as indicators for measuring the contribution of aid to achieving the different SDGs.
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Text Sample:Chapter 5 A first approximation: Cross-Country Evidence
Taking together the findings of the existing literature that are presented in chapter 2 plus the observations of the previous section, this chapter now attempts to measure aid effectiveness based on a donor-related disaggregation. A cross-sectional analysis (in the following also termed cross-country analysis) forms the starting point for this purpose. As previously stated in section 2.1, early studies of the aid research literature already analyse the relationship between aid and growth based on cross-sectional data in the 1970s. Since then, it has remained an essential procedure in the research field, and has experienced increased application over the past years. Rajan and Subramanian (2008: 645-647), Chong et al. (2009: 66-70), Arndt et al. (2010:7-8, 2015A:9-10) as well as Minoiu and Reddy (2010: 31-35) among others adopt a detailed OLS estimation based on cross-country data before running dynamic panel data analyses. However, there are several reasons why a dynamic panel analysis should be the preferred approach - as outlined in the following chapter. Therefore, this preliminary analysis serves as a first approximation with the aim of providing a first impression of the relation between aid and the chosen final outcomes, distinguished by the different donors.
The analysis starts with an investigation of the impact on growth as the most common indicator for aid effectiveness. It then addresses the effects on the two social success indicators infant mortality and primary enrolment rate as measures for health and educational quality. While the main regressions observe averages over the full period 1960-2014 with an aid horizon of 1960-1990 and the observation period 1990-2014 of the indicator, a third section includes variations of observation periods with the purpose of determining quantitative changes of the aid effect after the Cold War and, by doing so, provides a first robustness test for
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the estimations of the main period.
5.1 The effect on growth
As section 2.1 indicates, and as Doucouliagos und Paldam (2009:441-445) discuss in more detail, results of previous aid effectiveness studies are highly sensitive to the methodological approach and the applied regression specification, particularly the choice of explanatory variables. Differences in empirical procedure are in fact one of the main reasons for divergent conclusions within the aid literature. Temple (2010: 4449) addresses this issue and states that a favourable approach is to build on existing work, in order to increase coherence and comparability of the empirical findings in the long run. The strategy of this study, therefore, is to apply specifications of existing studies that are considered well-elaborated and highly influential on recent research.
Additionally, the purpose in this context is to draw on those studies that find no positive effect of aggregated aid. The intention behind this choice is that insights, given that one finds a positive effect of certain donor countries while aggregated aid remains ineffective, are more valuable than they would be with total aid already having a significantly positive effect. Because of different causalities between aid and growth, and aid and social outcomes, different specifications are needed respectively. For the aid-growth analysis, regressions of this study take up the specification of Rajan and Subramanian (2008: 646). Several studies published in recent years, for instance both Clemens et al. (2012: 590-591) and Arndt et al. (2010: 6), point to the good elaboration and great influence of the study by Rajan and Subramanian (2008) and build on its specifications.
The original approach of Rajan and Subramanian (2008) includes analyses on the basis of both cross-section (650-657) and panel data (657-659) methodology over the period 1960-2000. This comprises variations of observation periods, estimators and the type of aid, e.g. economic a
5.1 The effect on growth
As section 2.1 indicates, and as Doucouliagos und Paldam (2009:441-445) discuss in more detail, results of previous aid effectiveness studies are highly sensitive to the methodological approach and the applied regression specification, particularly the choice of explanatory variables. Differences in empirical procedure are in fact one of the main reasons for divergent conclusions within the aid literature. Temple (2010: 4449) addresses this issue and states that a favourable approach is to build on existing work, in order to increase coherence and comparability of the empirical findings in the long run. The strategy of this study, therefore, is to apply specifications of existing studies that are considered well-elaborated and highly influential on recent research.
Additionally, the purpose in this context is to draw on those studies that find no positive effect of aggregated aid. The intention behind this choice is that insights, given that one finds a positive effect of certain donor countries while aggregated aid remains ineffective, are more valuable than they would be with total aid already having a significantly positive effect. Because of different causalities between aid and growth, and aid and social outcomes, different specifications are needed respectively. For the aid-growth analysis, regressions of this study take up the specification of Rajan and Subramanian (2008: 646). Several studies published in recent years, for instance both Clemens et al. (2012: 590-591) and Arndt et al. (2010: 6), point to the good elaboration and great influence of the study by Rajan and Subramanian (2008) and build on its specifications.
The original approach of Rajan and Subramanian (2008) includes analyses on the basis of both cross-section (650-657) and panel data (657-659) methodology over the period 1960-2000. This comprises variations of observation periods, estimators and the type of aid, e.g. economic a
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Bibliographische Angaben
- Autor: Paul Faust
- 2018, 96 Seiten, 21 Abbildungen, Masse: 19 x 27 cm, Kartoniert (TB), Englisch
- Verlag: Anchor Academic Publishing
- ISBN-10: 3960672160
- ISBN-13: 9783960672166
Sprache:
Englisch
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