Do Performance Measures of Donors' Aid Allocation Underperform?

Clist, Paul

doi:10.1111/twec.12165

Cited by 7 publications

(3 citation statements)

References 34 publications

(72 reference statements)

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“…We calculate both of these measures using recipient’s GDP/capita using constant dollars and using purchasing power parity (PPP). Given the results by Clist (2015), a general sense of which we will echo as well, we work with the donor‐year’s factor score across these

3 \times 2 \times 2 = 12

specifications for

y_{i, t}

. The appendix will show all results, some of which we will discuss in our robustness check section.…”

Section: Methodsmentioning

confidence: 98%

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Evaluating explanations for poverty selectivity in foreign aid

Heinrich

Kobayashi

2021

Kyklos

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Ending global poverty has been at the forefront of the development agenda since the 1970s, but many donors have failed to target their funds toward this goal. Activists have tackled this issue by appealing to donors’ humanitarian motives, but we know little about what explains donors’ decisions on how much to give to the poorest countries. This paper develops the donor motivation and foreign policy approaches and identify donors’ development motives and their budget sizes as potential determinants of poverty selectivity. We evaluate their explanatory power by assessing whether their relationships with selectivity are in the hypothesized directions and generalize beyond a particular dataset. Employing cross‐validation and Bayesian Model Averaging, we find few measures of donor motivations provide a generalizable and hypothesized explanation for poverty selectivity. In contrast, donor budget sizes exhibit a relationship that is both hypothesized and externally valid. Our study offers the first systematic analysis of aid selectivity and generates implications for recent approaches to improve the quality of foreign aid and the conventional approach to study foreign aid allocation and donor motives.

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3 \times 2 \times 2 = 12

specifications for

y_{i, t}

. The appendix will show all results, some of which we will discuss in our robustness check section.…”

Section: Methodsmentioning

confidence: 98%

“…It therefore follows that the greater the value of

y_{i, t}

, the more selective donor

i

’s aid allocation is. A study by Clist (2015) shows that selectivity rankings can be quite sensitive to choices for

a_{i, j, t}

and

ω_{j, t}

. Therefore, we want to use several ways to operationalize them and then work with a factor score.…”

Section: Methodsmentioning

confidence: 99%

Evaluating explanations for poverty selectivity in foreign aid

Heinrich

Kobayashi

2021

Kyklos

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“…For example, we rely on indirect measures of best practices. We acknowledge criticisms regarding the sensitivity of rankings as addressed by Clist (2015) and BenYishey and Wiebe (2009), and precisely because of this, we choose to focus our analysis on the differences among donor category groups rather than specific and individual donors.…”

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confidence: 99%

Grading foreign aid agencies: Best practices across traditional and emerging donors

Palagashvili

Williamson

2021

Review Development Economics

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Despite the rapid growth of non-Development Assistance Committee (DAC) emerging donors, these non-traditional donors are historically left out of the discussion on aid effectiveness. In this paper, we provide the first full evaluation of aid agency best practices across multiple agency categories.We rank and compare DAC donors, emerging non-DAC donors, and multilateral and UN agencies in the following five best practice categories: transparency, overhead costs, aid specialization, selective allocation, and effective delivery channels. Contrary to public impressions that emerging donors engage in worse practices, we find that non-DAC agencies rank similarly to DAC donors: Both groups are equally poor performers. Emerging donors engage in less aid fragmentation across countries and use fewer ineffective delivery channels. Traditional DAC donors, however, provide more transparent reporting. Overall, we find that multilateral agencies and UN donors outperform both DAC and non-DAC bilateral agencies. Collectively, our results suggest that most aid donors do not meet their own standards for best practices, and this finding is not unique to emerging donors. We highlight how our results reflect the broader political economy of aid allocation. | 655PALAGASHVILI And WILLIAMSOn | INTRODUCTIONForeign aid is one of the most researched and debated development topics. An important finding that emerged from this literature is that aid to developing countries has failed to achieve its expected results. 1 Consequently, the last decade has seen a growth in attempts to monitor foreign aid agencies to improve aid best practices and increase the effectiveness of aid. In general, aid best practices focus on the quality of delivery and effective allocation. The primary impetus for change and commitment to best aid practices reached a critical mass with the Paris Declaration in 2005, followed up by the Accra Agenda for Action in 2008 and the Busan Agreement in 2011. At each meeting, donors reaffirmed a pledge to the principles of "best aid practices," with a particular focus on achieving transparent and less fragmented aid delivery.Donor agencies pledged to adhere to better practices of aid-giving, and there exists a variety of methods to evaluate whether donors are engaging in these best practices. These donor evaluations typically include "traditional" donors, such as Development Assistance Committee (DAC), multilateral agencies, and UN agencies. In this paper, we create a new donor category for non-DAC donors, or emerging donors, and provide the first full evaluation and ranking of non-DAC, DAC, multilateral, and UN agencies.Non-DAC donors, such as China, Brazil, Saudi Arabia, Russia, and Turkey, operate outside the guidance of the DAC of OECD members and thus are not required to report aid allocations. This means that their aid practices have been difficult to assess due to insufficient data availability, and they tend to be left out of the discussion on aid effectiveness. 2 However, non-DAC aid is rapidly growing and transforming t...

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Evaluating Aid Agencies: Challenges, Comparisons, and Causes of Best Aid Practices

Palagashvili

2019

Lessons on Foreign Aid and Economic Development

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Do Performance Measures of Donors' Aid Allocation Underperform?

Cited by 7 publications

References 34 publications

Evaluating explanations for poverty selectivity in foreign aid

Evaluating explanations for poverty selectivity in foreign aid

Grading foreign aid agencies: Best practices across traditional and emerging donors

Evaluating Aid Agencies: Challenges, Comparisons, and Causes of Best Aid Practices

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