Receive Grants or Perish? The Survival Prospects of Ugandan Non-Governmental Organisations

This article was downloaded by: [Gazi University]On: 19 August 2014, At: 12:15Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

The Journal of Development StudiesPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/fjds20

Receive Grants or Perish? TheSurvival Prospects of Ugandan Non-Governmental OrganisationsRonelle Burger a & Trudy Owens ba School of Economics , University of Stellenbosch , South Africab School of Economics , University of Nottingham , Nottingham ,UKPublished online: 08 Feb 2013.

To cite this article: Ronelle Burger & Trudy Owens (2013) Receive Grants or Perish? The SurvivalProspects of Ugandan Non-Governmental Organisations, The Journal of Development Studies, 49:9,1284-1298, DOI: 10.1080/00220388.2012.754430

To link to this article: http://dx.doi.org/10.1080/00220388.2012.754430

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever orhowsoever caused arising directly or indirectly in connection with, in relation to or arisingout of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

http://www.tandfonline.com/loi/fjds20

http://www.tandfonline.com/action/showCitFormats?doi=10.1080/00220388.2012.754430

http://dx.doi.org/10.1080/00220388.2012.754430

http://www.tandfonline.com/page/terms-and-conditions

http://www.tandfonline.com/page/terms-and-conditions

Receive Grants or Perish? The Survival Prospectsof Ugandan Non-Governmental Organisations

RONELLE BURGER* & TRUDY OWENS***School of Economics, University of Stellenbosch, South Africa, **School of Economics, University of Nottingham,Nottingham, UK

Final version received October 2012

ABSTRACT This study examines survival patterns in a large, representative panel of Ugandan non-governmentalorganisations (NGOs) between 2002 and 2008. It finds no evidence that more effective or more altruistic NGOshave a greater likelihood of survival. The main determinant of survival appears to be access to grants, and NGOswithout grants struggle to survive. An investigation of the grant allocation mechanism suggests that effectivenessdoes not increase an NGO’s likelihood of receiving a grant. Grant allocation appears to be neither fair noreffective, but rather to be awarded on the basis of habit rather than merit: once a grant has been allocated there isa strong tendency for it to persist. The odds are stacked against small NGOs that have not previously receivedgrants. A picture emerges of two parallel NGO worlds: one where revenues are small, variable and hard to comeby and survival is not very likely, and the other where revenues are high, more stable and more accessible andsurvival is more likely. The study suggests it may be difficult for an NGO to move from the former to the latter.

Non-governmental organisations (NGOs) are acknowledged as being pivotal to poverty alleviation,especially in African countries where the governments’ capacity and revenue are often very limited(Werker & Ahmed, 2008; Anheier & Salamon, 2006; Hulme & Edwards, 1996). However, despitetheir prominent role in developing countries, little is known about how these organisations functionand survive.1 Amid widespread concern about the use of aid funds in developing countries andgrowing awareness of the prevalence of corruption and lack of transparency among NGOs,2 it isimperative to ask whether the current system for funding them is able to identify and ‘weed out’ theleast effective.

In this article we ask whether there is anything approaching a ‘market mechanism’ among AfricanNGOs, or whether survival is more or less random. To investigate patterns of survival, we use a uniquedata set consisting of a nationally representative panel of Ugandan NGOs. Previous research con-ducted by Fafchamps and Owens (2009) on the first wave of the data, collected in 2002, revealed aclear divide between NGOs that obtain grant funding and those that do not: the former are older, largerand more affluent. The research also found evidence of persistence in the pattern of grant allocation. In2008, through extensive tracking and repeated field visits, the authors and collaborators from MakerereUniversity surveyed the surviving NGOs originally sampled in 2002, paying particular attention to thereliable verification of non-survival from local community officers or ex-employees.3 This places us ina unique position to explore patterns and determinants of survival.

Correspondence address: Trudy Owens,School of Economics, University of Nottingham, University Park, Nottingham, NR72RD, UK. Email: [email protected] Online Appendix is available for this article which can be accessed via the online version of the journal available at http://dx.doi.org/10.1080/00220388.2012.754430

The Journal of Development Studies, 2013Vol. 49, No. 9, 1284–1298, http://dx.doi.org/10.1080/00220388.2012.754430

© 2013 Taylor & Francis

Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Our concern about survival and effective allocation has to do with the problems of asymmetricinformation specific to a developing country with traditional three-agent donor-funded projects: whereinstitutional donors pay for the project, NGOs act as intermediaries to execute the project, and the localcommunity is the beneficiary. In such a set-up there is usually little or no scope for communicationbetween the beneficiary community and the institutional donor. It is to be expected, then, that thelikelihood of direct information flow between these two parties will be proportional to the distancebetween the community and the donor. For instance, when donors are based in North America orEurope and have no local presence, they are physically removed from the site of NGO activities, andthe distances involved may make it prohibitively expensive for these donors to visit project sitesregularly to observe conditions, outputs and outcomes. In such cases, donors may be heavily reliant onsecond-hand information, often from the NGO itself. If the donor is unfamiliar with local circum-stances and culture and has no benchmark for cost comparisons, its interpretation of accounts andreports may be a further obstacle to assessing performance and detecting ineffectiveness or fraud. Dueto this information asymmetry, donors would be prompted to follow a second-best strategy inallocating grants and to base their funding decisions on productivity proxies; that is, a set of NGOcharacteristics that are expected to correlate with effectiveness.

To investigate the way these information problems affect survival, we examine the influence ofincome sources, perceived altruism and perceived effectiveness on the likelihood of survival. Thearticle proceeds as follows. We first outline the data used for this analysis. We then explore thedifferences between surviving and non-surviving NGOs by examining group means, and investigatethe determinants of survival using both ordinary probits and instrumental variable probits. Finding thatsurvival is largely dependent on receiving a grant, we provide a brief overview of the literatureregarding the determinants of grant allocation and supplement this additional analysis with our NGOdata. The conclusion summarises and interprets the empirical results and highlights the limitations ofthe research.

I. Data

The study used a representative two-wave panel survey of the Ugandan NGO sector conducted in2002 and 2008. The sampling frame for the 2002 survey was constructed via a mini census of theentire NGO population in Kampala and 14 districts.4

In 2002, 295 NGOs were surveyed. In the 2008 survey we returned to these 295 NGOs to see whatchanges had occurred in the intervening six years. The team initially started tracking NGOs during thesecond half of 2007 using telephone numbers from 2002, but this strategy had a fairly low successrate. In December 2007 a series of short field trips was more successful, although a number of opencases remained. These open cases were resolved during fieldwork trips for the survey from January toNovember 2008.

To avoid misclassification, the researchers were extremely conservative in declaring the ‘death’ ofan NGO. The guideline was that fieldworkers could only stop searching for an NGO after its demisewas confirmed by either the community development officer or a former member of staff. For eachNGO declared to be a non-survivor, field workers were required to capture a short description of thetime and reasons for the ‘death’.

The survey was conducted as two modules. The first used a questionnaire to collect information oneach NGO’s structure, finances and activities. The second consisted of a community focus groupinterview to discover how community members perceived each NGO.5 The aim was to compare, andpostulate links between, the two sets of findings: on the one hand, self-reported organisational features,such as the size of the NGO and the number of skilled workers it employed, and on the other,community perceptions of the NGO, such as how effective and responsive they considered theorganisation to be.

The questionnaire for the first module was extensive, consisting of 255 questions covering funding,expenditure, assets, ownership and governance.

The Survival Prospects of Ugandan NGOs 1285

Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

The second module comprised 268 community focus group interviews conducted in 2002.Communities were identified by asking the NGO surveyed to list a number of parishes where theyworked. In this way, parishes were matched to NGOs. In each community visited, six to ten focusgroup participants were recruited via a community leader. The community focus groups asked thegroup members for their opinions about poverty in their community, their community’s needs, andthose who helped the community meet those needs. It also asked more detailed questions about whatthey thought the particular NGO contributed.

The findings of the first module were matched to those of the community focus group module of2002 for 207 of 268 NGOs.6 There were cases where some NGOs were linked to more than onecommunity. To avoid problems with error terms, 21 duplicates were eliminated randomly, reducing thematched sample to 186 observations.7 The distribution of the sample was investigated due to concernsabout possible bias resulting from the loss of observations after matching. Encouragingly, the post-merger sample closely matched the distribution of the pre-merger sample for key continuous variablessuch as revenues and staff size.

How Do We Capture Effectiveness and Altruism?

We attempted to reflect organisational effectiveness by using a ‘perceived value added’ indicator thatwould be comparable across various NGO sectors and beneficiary communities. Drawing on thecontingent valuation approach, we present focus group participants with a hypothetical scenario toelicit a willingness-to-pay variable without the interference of constraints relating to the ability to pay.Focus group participants were asked to imagine that the NGO under assessment was facing bank-ruptcy. Then participants were shown a pile of 100 beans meant to represent a pot of money. Theparticipants were asked to decide how much of the money in the pot they would donate to save theNGO. The answer could range from zero to 100. This question allowed us to generate a measure ofeffectiveness incorporating both the quality and the quantity dimensions of the NGO’s efforts to servethe community.

The subjectivity of this measure could be seen as a drawback. We argue that such a communitydriven indicator is appropriate. It includes an assessment of whether the output that was created by theNGO was valued and appreciated by the community. Such concerns should be key if development andpoverty alleviation are acknowledged to be people-centred endeavours.

We acknowledge possible concerns. It could be argued that community perceptions may createdistortions by overvaluing NGOs that make more direct contributions to the community or that servethe agenda of the community. It is, for instance, conceivable that the community may be more awareof NGO contributions that are tangible and concrete (e.g. service delivery vs advocacy work) or maybe more willing to provide funding to NGOs that are known to regularly pay generous per diems tocommunity members. Additionally, one could be concerned that NGOs that are unpopular with thecommunity because they challenge reigning orthodoxies by, for instance, empowering females orrefusing to work via community elites may be punished via such a rating system. Lastly, there couldalso be concerns that perceptions are fickle, easy to change and not sufficiently anchored to be ofsubstance.

Our analysis with available proxies provides encouraging results, suggesting that communities areastute in judging the performance of NGOs and look beyond the surface. There is a negative, butinsignificant correlation between the perceived effectiveness measure and the NGO’s per diem rate.We also find that there is no significant difference in the average perceived effectiveness rating ofNGOs that do advocacy work and NGOs that promote the empowerment of women. While it is alwaysdifficult to verify that an indicator is accurately and reliably reflecting the variation it was designed tocapture, it is encouraging to see that the indicator is not distorted by such perspectives and prejudices.In addition, it is reassuring to find that a number of expected relationships with perceived effectivenessvariables hold: e.g. the indicator has a significant and positive relationship to the number of years thatthe manager has worked for the NGO, the existence of a basic infrastructure, and the manager having areligious title.

1286 R. Burger & T. Owens

Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Altruism was captured via a question on the perceived selfishness of the NGO. The focus group wasasked to agree or disagree with the statement that the NGO existed to serve the purposes of its ownstaff rather than to help the community. Answers were collected on a Likert scale, with one indicatingstrong disagreement with the statement, and five indicating strong agreement. Again, there may beconcerns about the validity of using a measure that is intermediated by community perceptions, whichcould be distorted by other influences.

However, the statistical relationships between the altruism variable and other variables in our dataset provide additional validation for our interpretation. There is a highly significant overlap betweenthe tendency to describe NGOs as responsive to the community’s needs and assessments of staffmembers as altruistic. Similarly, NGOs that have a structure in the community are rated as signifi-cantly less selfish than NGOs with no physical presence, where the community has to visit the officesof the NGO. NGOs that involved the community in their work by assessing their needs prior to aproject and asking for feedback after a project were also more likely to be assessed as being altruistic.Additionally, we find that NGOs in which the manager has a religious title, which target children ororphans, or which work in the education subsector are significantly more likely to be rated as altruistic,while organisations that listed fundraising as one of their main activities were less likely to bedescribed as altruistic by the community focus group. However, not all dimensions of the communityassessment overlapped: perceived competence and perceived effectiveness appear to be viewed asseparate dimensions because they did not have a significant relationship with the altruism variable.

To test the robustness of the relationship between survival and altruism, we will also includeresponsiveness,8 accessibility9 and community participation10 as alternative measures of an NGO’sorientation towards the community versus external stakeholders.

II. Which NGOs Survive?

Literature and Background

As a starting point for this analysis, we present a survey of the most important theories and findingsregarding NGO survival. Unfortunately, only a handful of large empirical studies have examined thisquestion, and researchers looking at the determinants of NGO survival still rely on generic theoriesborrowed from organisational studies. Resource dependency theory and the organisational ecologyapproach (both from the organisational studies literature) are the most widely cited theoretical frame-works in research on the survival of non-profit organisations.

Resource dependency theory, formulated by Pfeffer and Salancik (1978), highlights the importanceof acquiring and maintaining resources for ensuring the survival of organisations in an uncertainexternal environment. According to this theory, since resources often originate from outside theorganisation, access to such resources usually implies that those providing the resources have certainclaims over the organisation and that these claims need to be managed carefully. Although the theorydefines resources broadly to include networks as well as knowledge, in practice the theory has in mostcases been tested using revenue size as an approximation of the organisation’s resources and thus alsoas a measure of its control over the uncertain external environment. The significance of resources is arobust and widely cited finding in the study of non-profit survival (Hager, 2001; Fernandez, 2008).

Organisational ecology considers the organisational characteristics and environmental factors thataffect the birth, growth and survival of organisations. This literature has identified an organisation’ssize and the length of its existence as vital determinants of the likelihood of survival. Given therelationship between an organisation’s size and age, these effects are often difficult to disentangle(Lecy, 2010).

Stinchcombe (1965) observes that younger organisations tend to lack a strong network and reputa-tion, which creates a ‘liability of newness’. Stinchcombe (1965) and Hannan and Freeman (1989)suggest that younger organisations may find it more difficult to cope when faced with a crisis becausethey do not have established roles and procedures to deal with such situations, and Hager and


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Galaskiewicz (2002) point out that in younger organisations staff loyalty is not yet deeply entrenched,which could leave these organisations exposed to the whims and preferences of their workers. Studieson non-profit survival have confirmed that older organisations are more likely to survive (Selle &Øymyr, 1992; Bielefeld, 1994; Hager, Galaskiewicz, Bielefeld, & Pins, 1996; Twombly, 2003).

There is also some evidence on the ‘liability of smallness’. It has been suggested that smallorganisations may face an uphill battle because they find it more difficult to secure funding(Chambré & Fatt, 2002), cannot leverage economies of scale, and do not have strong, establishednetworks (Hager et al., 1996). Although empirical studies on non-profit survival have not been able todistinguish between these various explanations for the liability of smallness, they have provided strongsupport for the existence of this phenomenon (Bielefeld, 1994; Hager, 1999; Twombly, 2003).

In looking at the survival of NGOs, it is also important to consider the influence of mission andleadership, which are central concepts in the definition and description of NGOs. An NGO’s missionand drive are often intimately linked to charismatic leadership. Sooryamoorthy and Gangrade (2001)observe that when an enthusiastic individual with a vision launches an NGO, the organisation’smotivation and decision-making often become so intertwined with the leader’s personality andcharacter that the NGO is likely to collapse when the leader departs. Haveman (1993) also notesthat a change of leadership increases mortality for small organisations.

Empirical studies have established support for these arguments. Fernandez (2008) investigatedsurvival among 41 Spanish voluntary organisations in Madrid’s metropolitan area and found thatmission completion was an important factor in the dissolution of these organisations. This resonateswith the findings of Hager et al. (1996), where a fifth of the 47 Minneapolis-based non-profitorganisations that ceased operating between 1980 and 1994 reported that they had closed theirdoors because they had fulfilled their mission.

It is important to note that very little research has been done on NGO survival in developingcountries, and the work that does exist is piecemeal and based on case studies. As far as we know,there have been no previous studies of the survival of African NGOs. While the above survey of theliterature provides a useful starting point, we do not necessarily expect to see similar patterns emergein an African country where the funding and incentive structure is radically different from the set-up ina developed country. For instance, in Uganda unemployment is high and aid flow represents acomparably large proportion of gross domestic product (GDP) (Gupta, Powell, and Yang, 2005;IMF, 2008), so revenue may be a stronger pull factor for individuals starting an NGO and mayhave a more dominant influence on survival.

Descriptive Analysis

In this analysis, the focus is on the impact of information asymmetry in the NGO sector; therefore, thevariables of interest are perceived effectiveness, perceived altruism and access to grants. Based on theliterature surveyed in the previous section, we will also examine the age and the size of the NGO, aswell as the impact of leadership and mission.

The survival rate for NGOs in Uganda is 83 per cent. By 2008, 238 of the 286 baseline NGOs from2002 were still in existence and operational.11 As Table 1 shows, there were large and significantdifferences between the averages of the characteristics of the NGOs that survived up to 2008 and thosethat did not.

Generally, survivor NGOs appeared to be larger, more affluent, and older. Surviving NGOs weremore likely to have grant income, and had a higher degree of grant dependence than non-survivors.Seventy-two per cent of survivors and 46 per cent of non-survivors had received grants in the past.Grants constituted on average 50 per cent of survivors’ revenue but only 25 per cent of non-survivors’revenue. The differences between the averages of both these measures were significant.

Survivors were perceived as adding more value than non-survivors, but also as having more selfishstaff. However, these differences were small and not significant.


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Table 2. NGO survival probit

Variables: coefficient z-value Col.1 Col.2 Col.3 Col.4 Col.5 Col.6

NGO characteristicsNGO age 0.213 0.222 0.110 0.126 0.251 0.310

1.52 1.42 0.74 0.76 1.18 1.42Ln Salaried staff 0.035 0.034 0.036 0.045 0.312 0.038

0.49 0.44 0.49 0.57 0.36 0.43Education –degree 0.614** 0.919*** 0.562** 0.892*** 0.526* 0.708*

2.37 2.92 2.13 2.76 1.67 1.77Age 0.531 0.740 0.502 0.782 0.978* 0.712

1.08 1.30 1.05 1.42 1.71 1.21Length of service 0.068 0.069 0.086 0.081 −0.006 −0.137

0.41 0.39 0.51 0.46 −0.02 −0.50Other employment −0.027** 0.034 0.016 0.084 0.193 0.083

−0.13 0.13 0.07 0.33 0.07 0.28Religious title 0.678*** 0.841** 0.813*** 0.984*** 0.792*** 0.986***

2.54 2.36 3.03 2.64 2.50 2.17Relative lives abroad 0.419** 0.338 0.401* 0.310 0.260 0.283

2.07 1.54 1.94 1.40 0.95 0.98

Perceived altruism and effectivenessNGO regarded as selfish 0.077 0.084 −0.047

0.87 0.95 −0.41Perceived value added −0.225 −0.234 −0.013

−0.67 −0.71 −0.03

Sources of incomeReceived a grant in 2002 0.548** 0.481*

2.33 1.80

Proportion of revenue from grant 0.861** 0.684*2.44 1.62

Constant −2.281 −3.299 −2.392 −3.673* −3.974 −3.276−1.28 −1.59 −1.37 −1.80 −1.97 −1.38

Pseudo R-squared 0.113 0.144 0.135 0.161 0.179 0.172Observations 252 211 252 211 174 145

Notes: *Represents 10% level of significance; **5% level; ***1%.

Table 1. Test of equal means for NGO and manager characteristics in 2002, by survival

Categories VariablesAverage forsurvivors

Average fornon-survivors

P-valuefor t-test No. of obs.

Size Number of employees 37.27 33.58 0.69 286Revenue (in thousands ofUgandan shillings)

225,468 33,362 0.04 189

NGO age Age of NGO 10.59 6.46 0.03 286Manager characteristicsand commitment

Age of manager 41.72 39.65 0.15 269Years of education ofmanager

14.75 14.26 0.27 284

Source of income Ever received a grant 0.72 0.46 0.0003 286Proportion of incomefrom grant

0.50 0.25 0.004 194

Perceived altruism NGO staff seen as selfish 1.76 1.68 0.74 176Perceivedeffectiveness Perceived value added 0.64 0.54 0.15 172


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Regression Results

To examine how our three variables of interest – access to grants, perceived altruism and perceivedeffectiveness – influence the likelihood of survival, we estimated a model (see Table 2) with controlsfor organisational features that have been shown to be correlated with survival, including size, age, andthe manager’s vision and leadership (captured via the manager’s characteristics and commitment).

Table 2 reports the results from our probit estimations, which investigate predictors of survival in2008. We start with a baseline estimation that uses standard control variables for NGO characteristics,which are the years of the NGO’s existence and the size of the NGO (measured by full and part-timesalaried staff),12 and NGO manager characteristics, which are the manager’s education (nearly theentire sample is educated, so to refine the variable we create a dummy for whether the manager holds adegree), the manager’s age, the length of time the manager has been with the NGO by 2002, whetherthe manager had other employment in the same year, whether the manager has a religious title,13 andfinally, to control for connections, a variable for whether the manger has a relative living abroad. Wethen add our variables of interest sequentially, starting with our perceived altruism and perceivedeffectiveness variables measured from the focus group interviews with the community: whether thecommunity considers the NGO to be selfish, and how many beans the community would allocate tokeep the NGO in operation. Next we add our grant variables: whether the NGO has ever received agrant, and the proportion of revenue received from grants. Due to the loss in sample size when weinclude perceived altruism and perceived effectiveness we estimate the grant regressions with andwithout these variables. Our core conclusions remain unaltered.

Other than our survival variable, which has a value of one if the NGO existed in 2002 and 2008, allthe independent regressors are from the 2002 survey. All continuous variables are logged. As is oftenthe case, we encounter a trade-off between breadth and depth in our selection of funding variables,with the grant recipient dummy being a very blunt measure but which is available for almost all theNGOs in our sample. In contrast, the share of grants variable has a much finer grain but also a higherproportion of missing values and consequently a smaller sample.

According to the base specification in Column 1 of Table 2, having a degree matters, as does havinga relative living abroad and having a manager with a religious title. Having other employment –perhaps a sign of less commitment to the NGO in question – decreases the chances of the organisa-tion’s survival.

To test the hypothesis that NGOs are rewarded by the system, we include plausible indicators ofNGO motivation and performance: an altruism indicator and a measure of ‘perceived value added’, asdescribed in the data section above. The analysis shows that neither variable is significant. We also testthe significance of three other variables indicative of the community orientation of the NGO, namelyresponsiveness, accessibility and participation, which are all insignificant (not shown here). Thesefindings are consistent with an interpretation that more effective and more motivated NGOs are notmore likely to survive than others and that there is little evidence of a well-functioning feedbacksystem rewarding performance.14

In contrast, access to grants is strongly associated with NGO survival. An NGO that received a grantin 2002 and NGOs for whom grants represent a higher share of their revenue are more likely to havesurvived to 2008. The variable capturing connections – namely, a relative living abroad – remainssignificant when the grant recipient dummy is included, but becomes insignificant when including therevenue variable. Having a religious title and higher education remain significant after including thegrant variables, but the association between survival and having a relative living abroad, and the NGOmanager having other employment, does not appear to be robust.

We are concerned about potential endogeneity in the regressors due to the possibility of simultaneitybias affecting grants. It is possible that a similar range of factors could determine both the allocation ofgrants and survival. In recognition of this concern, we attempt to instrument for this effect by using arange of variables that are expected to be correlated to grants, but not to survival, i.e. that can thusserve as restrictions to help identify the exogenous influence of grants on survival.


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Table 3. NGO survival instrumental variable probit with perceived altruism and effectiveness

First stage: instrumentingincome

IV probit: determinants of NGOsurvival

Variables: coefficient z-value Grant receiptGrant as shareof revenue Grant receipt

Grant as share ofrevenue

NGO characteristicsNGO age 0.148*** 0.183*** −0.067 −0.354

4.08 3.80 −0.28 −0.70Ln salaried staff −0.023 0.017 0.065 −0.098

−1.11 0.65 0.68 −0.60

Manager characteristicsEducation – degree 0.164** 0.199* 0.567 0.138

2.00 1.93 1.49 0.21Age −0.073 0.055 1.100 0.772

−0.55 0.34 1.78* 0.84Length of service −0.024 −0.103* 0.040 0.291

−0.55 −1.85 0.19 0.66Other employment −0.098* −0.077 0.443 0.460

−1.68 −1.07 1.51 0.96Religious title −0.135* 0.051 1.555*** 1.096*

−1.76 0.51 2.96 1.68Relative lives abroad −0.018 −0.010 0.057 0.124

−0.33 −0.14 0.21 0.29

Perceived altruism and effectivenessNGO regarded as selfish 0.001 0.003 0.023 0.056

0.04 0.03 0.06 0.32Perceived value added −0.068 −0.018 −0.021 0.074

−0.86 −0.64 −0.20 0.13

Sources of IncomeReceived a grant 2.023**

2.19Proportion of revenue from grant # 0.732*

1.88

InstrumentsReceived seed money 0.230*** 0.161**

4.00 2.18Belongs to a network 0.104*

1.79Manager worked for other NGO inthe past

0.172***3.11

Evaluates how it fulfils communityneeds

0.143*1.79

Constant 0.593 −0.153 −5.418** −3.8891.20 −0.26 −2.23 −1.13

Centered R-squared 0.374 0.392Observations 211 145 211 145Joint F-test of instruments 10.46*** 3.68**Sargan test 2.985(0.23) 0.263(0.61)Wald test of exogeneity 3.40* (0.06) 4.26* (0.04)Amemiya-Lee-Newey 2.76 (0.25) 0.165 (0.68)

Source: Authors’ calculations based on 2002 and 2008 survey data.Notes: *Represents 10% level of significance; **5% level; ***1%. # based on the conditional likelihood ratio testproposed by Moreira (2009) and implemented in Stata using condivreg, to account for weak instruments in firststage.


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Building on the previous work of Fafchamps and Owens (2009), we use the social and professionalnetworks of the manager and formal signals of NGO credibility as instruments. As far as we are awarethere are no theoretical or analytical arguments to suggest that these factors should be expected to havea direct impact on survival, over and above the effect they have on survival via grants – aftercontrolling for our set of regressors. The theory section in Fafchamps and Owens (2009) demonstratedthat networks would predict the receipt of grants but not of other sources of income and this providessome preliminary theoretical support for the use of networks as instrument for this revenue stream. Theliterature indicates that networks may contribute towards the impact that organisational factors such assize and age have on survival, but the likely transmission mechanism for these effects is via theirimpact on resources. Additionally, because we include both size and age in our regressions, we are notconcerned about these relationships contaminating the instruments. Similarly, the inclusion of proxiesfor mission and leadership in the regression also reduces concerns about possible contamination viasuch channels.

Furthermore, it is worthwhile to note that in Uganda there is limited scope for the appointment ofmanagers as an avenue of endogeneity (i.e. recruiting managers to fit the profile of the NGO).Managers tend to be closely associated with the NGOs they manage, with a large proportion havingbeen with the NGO for as long as it has been in operation. Our analysis shows that 58 per cent ofmanagers have been with the NGO from the start and 71 per cent of managers have been with theNGO for at least 70 per cent of its life as an organisation. Anecdotes from the field support this: oftenan NGO will either stop its operations or migrate with a manager if he or she moves to a new location.

We experiment with four indicators representing the social and professional networks of themanager and the credibility signals of the NGO, namely: receiving a seed grant (an indicator of thestrength and effectiveness of the manager’s professional networks when he or she joined the NGO, butalso an early signal of external trust and credibility), whether the manager worked for any other NGOsprior to joining this NGO (professional networks), belonging to an NGO network (professionalnetworks), and whether the NGO evaluates if it fulfills the needs of the community it serves (signalof the NGO’s long-term commitment and credibility).

Determinants of whether an NGO received funding, and the level of that funding, do differ. In thecase of the receipt of grants (binary variable), we instrument using seed money, membership of anetwork, and whether the manager worked for another NGO in the past. Similarly, in the case of grantsas a share of revenue, we instrument using seed money and whether the NGO evaluates if it fulfills theneeds of the community.

We report an instrumental variable (IV) probit specification, but also estimate a linear probabilitymodel to retrieve the first stage instrumenting regressions. For completeness, we report the results ofboth the Sargan and Amemiya-Lee-Newey test of overidentifying restrictions.15

Columns1 and 2 in Table 3 report the instrumenting regressions (first stage) for receiving a grantand the proportion of revenue from grants respectively. Columns 3 and 4 in Table 3 are estimated withthe instrumented versions of the grant variables.

The instrumentation for grant receipt as a binary variable appears to be more successful andconvincing than that for grants as a share of revenue. F-tests indicate that weak instruments areunlikely to be a problem for the grant receipt IV regressions because they exceed the traditionalbenchmark of 10 by a healthy margin. However, while the F-test is still jointly significant for the IVfor grants as a share of revenue, it is much lower and suggests that weak instruments may be a problemin this case.16 Consequently, the p-value relating to the grant share variable in the core regression (i.e.Column 4) is estimated from a corrected likelihood ratio test proposed by Moreira (2009) for weakinstruments.17

The Wald test rejects the exogeneity of the grant variables, confirming that the concerns regardingendogeneity were justified and the instrumenting approach was required.

The Sargan and the Amemiya-Lee-Newey tests – designed to test overidentifying restrictions forcontinuous and binary dependent variables respectively – are both not rejected. The over-identifyingrestriction test shows that under the maintained assumption that any of our instruments is valid, we


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

cannot reject the hypothesis that all other IVs are valid as well. Although it is never possible to provethe validity of the IVs, this test offers support for our identifying assumption.

Table 3 reports the instrumented regression results for the two grant variables and confirms thatgrants remains correlated with survival.18 The coefficients are generally similar to those reported in theuninstrumented estimations and remain significant. The coefficients on grants are larger in theinstrumented regressions. Although we cannot rule out the endogeneity of IVs as an explanation,our analytical arguments and the diagnostics imply that this is unlikely. Alternative explanations forthe increased coefficients may be that grants were mismeasured in the initial specification or, in aheterogeneous effect framework, the impact of grants may be much higher for organisations whosereceipt of grants depended on the strength of their networks.

The robust significance of the manager having a religious title is interesting and could be interpretedas providing support to the stream of literature emphasising the importance of mission and visionaryleadership in NGOs.

Given that instruments are assumed to be exogeneous and that these claims cannot be conclusivelytested, we thus interpret this only as tentative evidence that access to grants is crucial for NGOsurvival. While the evidence from the regression analysis may only be considered tentative, it isreassuring that it is in line with anecdotes from the field. During our fieldwork we gathered informa-tion on the reasons why NGOs discontinued their work in the communities. In most cases, the demiseof an NGO was associated with events that cut it off from its funding source, such as the death orrelocation of the manager or a scandal that affected the legitimacy of the organisation. There was onlyone case where an NGO’s closure was directly associated with mission completion.

We investigate the reasons behind this association by examining whether grant revenue tends to behigher than community sources of income (including user fees, community donations and membershipfees) and less prone to extreme variation. The hypothesis appears to be valid. For the 2001 financialyear, the average revenue for NGOs with access to grants was 247 million Ugandan shillings, whilefor NGOs without access to grants it was 34 million. We captured revenue data for both the 2001 and2002 financial year and compare the absolute percentage change in income across the two periods,contrasting grant revenue with community income, and found that while the mean absolute changeacross the two periods is larger for grant income, the medians are very close, demonstrating theskewness of the variation in patterns of community income. The fluctuations of the community incomevariable have a lower spike around zero and a much longer tail to the right, reflecting the greaterlikelihood of extreme fluctuations in community income. For instance, we find that between 2000 and2001, 42 per cent of NGOs in our 2002 sample experienced a more than 50 per cent change in theircommunity revenue, while only 32 per cent had a change of that magnitude in their grant income.Similarly, revenue changes exceeding 100 per cent were more prevalent for community revenue (26%)than for grant income (16%).

The analysis shows that average grant income is significantly higher than community income and italso carries fewer risks. Therefore, it is plausible that grant income’s link to survival may work viasecuring greater financial stability. This is, however, exploratory analysis, and there are also otherexplanations for the relationship between grants and survival, which have not been tested here.

III. Which NGOs Attract Grant Funding?

The analysis in the previous section showed that revenue, particularly in the form of grants, had astrong association with survival. We found little evidence of a ‘market mechanism’ in the NGO sector,whereby more effective NGOs would be more likely to survive. In this section, to gain a betterunderstanding of the cycle of feedback and reward that influences survival via grants, we examine howgrants are allocated.

Martens (2002) argues that the essence of the grant allocation problem is an information problem,namely that ‘the people for whose benefit aid agencies work are not the same as those from whomtheir revenues are obtained’ (2002:14). The feedback between the user and the payer is complicated by


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

the geographic and political distance between the beneficiary communities and the donors who fundthe NGO projects. Beneficiaries experience and observe the NGO project first-hand, but have nocontrol over the payments to the NGO, and are therefore not able to use payment to encourage andreward NGO performance.

According to Martens (2002), donors often do not care whether grants achieve their intendedpurpose or not. They are plagued by the same ills that burden large public administrations. Becausethey pursue non-tangible and multi-dimensional goals, donors find it difficult to use incentives toencourage performance, and consequently, incentives are weak and effective accountability mechan-isms are often lacking. Martens (2002) maintains that excessive bureaucracy and procedures areintroduced by decision-makers in an attempt to maintain control and contain risks, and that thiscurbs discretion, hampers decision-making and limits responsiveness. He also explains how the desireto quantify, measure and control can divert the attention of aid organisations towards inputs andcontracts, and away from the outcomes that matter.

New institutionalism explains how these problems can be magnified and enhanced via NGOmimicry. According to the pioneers of this approach, Meyer and Rowan (1977), there is a set ofunwritten rules that NGOs need to follow if they want to gain legitimacy in the sector. This perceivedlegitimacy is crucial for survival, because NGOs can survive only if they manage to persuade externalactors that they deserve support (Hager, Galaskiewicz, & Larson, 2004). For NGOs that rely on donorfunding, these rules entail a bureaucratisation of development, which is usually associated with highlyvisible actions such as formal community participation processes and a considerable amount ofpaperwork, including feedback forms, reports, official registration and audited financial statements.

According to new institutionalism, these rules are supported and motivated by ‘rationalised myths’that link the rules to organisational effectiveness. However, these ‘myths’ frequently have no empiricalbasis and are in many cases socially and culturally constructed. The adoption and promotion of suchpractices happens partly via isomorphism, whereby new NGOs mimic the formal structure ofestablished NGOs to gain acceptance from the group.

The empirical work that follows will test these ideas. Our analysis suggests that there appears to be asignificant habitual component to grant allocation. Table A1 in the data appendix (available online)shows that 86 per cent of the NGOs with grants in 2002 also received grants in 2008, while only 46per cent of the NGOs without grants in 2002 had grants in 2008. Of the 229 surviving NGOs (withoutmissing values for either of these variables), 152 received grants in both periods. This is much higherthan the expected overlap of 136 NGOs under the assumption of independence. Similarly, the numberof NGOs not receiving grants in either of the periods is 28, which is again much higher than theoverlap of 12 NGOs anticipated under the assumption of independence.

The odds appear to be stacked against small organisations without grant income – out of a group of77 NGOs reporting that they had never received grants in 2002, 22 were no longer in operation by2008. Of the remaining 55 NGOs, 28 were still in operation but had still never received a grant, andonly 24 NGOs had received a grant by 2008. The lack of grants could not be attributed to a lack ofeffort or awareness of grant opportunities. A reasonable proportion of the 28 NGOs who had neverreceived a grant reported having submitted grant applications during the last 12 months (50% in 2002and 31% in 2008), and only eight of the 28 had not applied for a grant in either 2002 or 2008. Thisshould be seen against the backdrop of a high prevalence of grants in the sector: according to the 2008survey, 88 per cent of NGOs either currently had a grant or had received one in the past, and only 12per cent of NGOs had never received a grant previously.

We proceed to regression analysis to examine whether grants are allocated effectively by examiningthe partial correlations of grant allocation in 2008 with a variety of NGO characteristics measured in2002. Since little empirical work has been done on the determinants of grant allocation, the presentstudy largely builds on previous work by Fafchamps and Owens (2009). They found that managerialcharacteristics, including age of NGO and network membership, were significant predictors offunding; and that grant recipients are a select group of NGOs that have more educated and betterconnected managers and staff who are more skilled at writing grant applications. To investigatewhether a lack of grants may be merely a matter of insufficient capacity, effort and information,


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

we also add variables to capture the organisation’s size and the number of civil servants a managerknows.

Our regression results are summarised in Table A2 in the Online Appendix.19 The set of resultsshows that what matters for grant allocation is the size of the NGO, the education of the manager, andthe manager’s commitment to the NGO as measured by length of service and having other employ-ment. There is little evidence that simple and affordable external interventions such as joining an NGOumbrella or network will make a difference. The analysis provides further evidence that grant-givingmay have a strong habitual component: there is a positive and significant partial correlation betweenhaving received a grant in 2002 and the likelihood of receiving a grant in 2008. Significantly, ouraltruism and perceived effectiveness variables do not appear to impact upon the likelihood of receivinga grant in 2008, thus challenging claims that grants are allocated to more motivated and more effectiveNGOs. In line with the results regarding survival, we thus find no evidence of positive feedbackreinforcing and rewarding good behaviour amongst NGOs.

IV. Conclusions and Implications

This unique data set provides empirical support for existing theories and case study conclusionscontending that grants may often not be allocated effectively and that NGOs that serve the communitywell are not more likely to survive than others. The results suggest there may be two parallel worldsfor NGOs: one where revenues are small, variable and hard to come by and where the likelihood ofsurvival is relatively low, and one where revenues are high, more stable and more accessible andwhere survival is more likely.

Our data show that there does not appear to be anything approaching a ‘market mechanism’ in theNGO sector. NGOs that beneficiaries perceive to be altruistic or effective are not more likely tosurvive. We also find no significant association between these perceived altruism and effectivenessmeasures and the allocation of grants, which lends support to the case for greater transparency andmore effective feedback to guide the allocation of grants. If the systems governing funding andsurvival are not encouraging and rewarding effectiveness and altruism, this is a matter of concern,due to the growing importance of the NGO sector. This sector plays a crucial role in assistingvulnerable and poor individuals in developing countries, where service delivery capacity is oftenlacking and public funds are scarce.

Given the controversial nature of these conclusions, it would be important to test the robustness ofthese findings with different proxies for perceived effectiveness and altruism. Ideally, one would alsolike to examine these patterns in different institutional settings. Uganda is known to have high aidflows and may therefore not be viewed as a typical case. The lack of detailed and large panel data setsthat are representative of a country’s NGO sector remains a serious impediment to understanding theNGO sector and their funding mechanisms in more depth.

While this unique representative panel of NGOs provides insights into the funding frustrations ofNGOs, more empirical work on donor processes is required to better understand the institutionalenvironment and the incentives driving donor decisions in order to verify the expanding theoreticalliterature on the topic. Specifically, there is also scope for further work investigating how differentdonor types allocate grants to NGOs.

Acknowledgements

This work was supported by the British Academy [50401], Commonwealth Secretariat [ZACA-2006-116], the South African National Research Foundation [SFH2005082600083] and the University ofNottingham [NRF4322].We would like to thank Fred Matovu, Patrick Birungi and their team of enumerators for their diligentefforts in tracing the NGOs and administering the questionnaire. For useful comments we would liketo thank D. Bonbright, R. Burger, A. Dreher, M. Gugerty, O. Morrissey, H. Öhler, L. Salamon, W.


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Sokolowski and F. Teal. We are also grateful to participants of the following conferences and seminarswho gave us useful feedback on earlier drafts: the International Society for Third Sector Research,Stellenbosch; Centre for the Study of African Economies, University Oxford; and the Association forResearch of Nonprofit Organizations and Voluntary Action, Washington DC; and seminar presenta-tions at the University of Goettingen; University of Nottingham; and the Centre for Civil SocietyStudies at Johns Hopkins University.

Notes

1. This is presumably at least partly because appropriate data are lacking. Existing work on the survival of non-profitorganisations (e.g. Tuckman & Chang, 1991; Bielefield, 1994; Fernandez, 2008; Wollebaek, 2009) relates mostly todeveloped countries.

2. See Callamard (2006); McGann and Johnstone (2006); Burger and Owens (2010).3. For a full account of the original survey see Barr, Fafchamps, and Owens (2005).4. Since 1989, the NGO Registration Statute requires all NGOs in Uganda to register their organisation with the NGO

Registration Board in the Ministry of Internal Affairs (MIA). The initial intention was to draw the sample from this list, butit became evident that a number of NGOs in the register had registration certificates that had elapsed. We began by verifyingthe official register and found that only 15–30 per cent of the NGOs on the register were actually in operation. In some casesit was known that the NGO was still in operation but simply had not renewed its certification; in other cases the NGO wasknown to have ceased operation; but in other cases it was not clear that the NGO had ever begun operating. There was alsoconcern that many NGOs had changed their core functions and location without informing the Registration Board.

5. For a detailed discussion of the community focus group interviews, see Barr and Fafchamps (2006).6. In some cases, the NGO was not known to the focus group and therefore could not be matched back to the intended NGO. In

these cases, the focus group assessed an alternative NGO, which was often not part of the sample for the first module andsubsequently had to be dropped from the analysis.

7. Investigation of bias introduced by the loss of observations due to matching is available on request. The analysis of anumber of key observables such as income and expenditure shows that there is little evidence of such bias. This does not,however, exclude the possibility that there may be bias as a result of unobservable factors.

8. Responsiveness is measured on a five-point Likert scale as a consensus response from the community focus group todemonstrate their agreement with the statement that the NGO is always quick to respond when inhabitants of this parish orthe parish as a whole ask for help.

9. Accessibility is captured in three categories, i.e. (i) the NGO has an office in the community, (ii) the NGO does not have anoffice in the community, but it visits the community regularly; (iii) the NGO does not have an office in the community andcommunity members have to visit the NGO.

10. The community participation variable is constructed based on two variables, namely (i) Does the NGO ask the communityabout their needs before they initiate a project? (a binary variable compiled from three underlying questions) and (ii) Doesthe NGO ask the community for feedback after concluding a project? (a binary variable constructed from three questions tothe focus group).

11. Decisions had to be made for exceptional cases. Five NGOs that had become private enterprises were removed from thebaseline sample as being rare and special cases comparable neither to mortality nor to survival. Eight were classified asclosed: four that still existed in name but had stopped operating, and four whose leaders had moved and which had eitherceased to exist or undergone such radical transformation (e.g. geographical focus, activities and staff) that they could beregarded as entirely new NGOs.

12. Other measures of staff that included volunteer as well as salaried staff gave similar results.13. Reinikka and Svensson’s (2011) research on Ugandan not-for-profit health facilities finds that altruism (measured by

religion) has an effect on service delivery that matters quantitatively. We therefore include this variable in the specification.14. Although not shown in the table, the result remains when we include these variables in other specifications, and when they

enter these models individually.15. For robustness, we estimate both specifications using an instrumental variable linear regression which reports the same signs

and levels of significance.16. These test statistics are obtained from the 2SLS estimation, assuming a linear model. We are only interested in the first stage

results from this specification, which makes this approach valid.17. The Moreira p-value correction only exists for linear models. The values reported in Table 3 are thus based on linear

implementation of the regression.18. Not reported here, but available on request for our larger sample, we exclude our perceived altruism and effectiveness

variables. They remain insignificant. The coefficients of the funding variables do not change from those reported in Table 3.19. Columns 1 to 3 use probits. However, with such a specification there is reason to be concerned about selection bias, because

NGOs that did not survive are missing from our 2008 grant variable and the unobservable factors that are important forsurvival may also be important for grant allocation. We therefore also estimate a Heckman probit in columns 4 and 5. TableA1 [Online Appendix] shows that the hypothesis of independent equations cannot be rejected, thus the discussion below


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

concentrates on the first three models. The patterns of significance are reasonably stable, especially when considering thedrop in the sample size when including our altruism and perceived effectiveness variables.

References

Anheier, Helmut, & Salamon, Lester (2006). The nonprofit sector in comparative perspective. In Walter Powell and RichardSteinberg (Eds), The nonprofit sector: A research handbook. New Haven,CT: Yale University Press.

Barr, Abigail, & Fafchamps, Marcel (2006). A client community assessment of NGOs in Uganda. The Journal of DevelopmentStudies, 42 (4), 611–639.

Barr, Abigail, Fafchamps, Marcel, & Owens, Trudy (2005). The governance of non-governmental organizations in Uganda.World Development, 33 (4), 657–679.

Bielefeld, Wolfgang (1994). What affects nonprofit survival? Nonprofit Management and Leadership, 5 (1), 19–36.Burger, Ronelle, & Owens, Trudy (2010). Promoting transparency in the NGO sector: Examining the availability and reliability

of self-reported data. World Development, 38 (9), 1263–1277.Callamard, Agnès (2006). NGO accountability and the humanitarian accountability partnership: Towards a transformative

agenda. In Lisa Jordan and Peter van Tuijl (Eds), NGO accountability: Politics, principles and innovations. London:Earthscan.

Chambré, Susan M., & Fatt, Naomi (2002). Beyond the liability of newness: Nonprofit organizations in an emerging policydomain. Nonprofit and Voluntary Sector Quarterly, 31 (4), 502–524.

Fafchamps, Marcel, & Owens, Trudy (2009). The determinants of funding to African NGOs. World Bank Economic Review, 23(2), 295–321.

Fernandez, Juan J. (2008). Causes of dissolution among Spanish nonprofit associations. Nonprofit and Voluntary SectorQuarterly, 37 (1), 113–137.

Gupta, Sanjeev, Powell, Robert, & Yang, Yonzheng (2005). Macroeconomic challenges of scaling up aid to Africa. IMFWorking Paper WP/05/179.

Hager, Mark A. (1999). Explaining demise among nonprofit organizations. Dissertation Abstracts International, 60 (8), 3141.Hager, Mark A. (2001). Financial vulnerability among arts organizations: A test of the Tuckman-Chang measures. Nonprofit and

Voluntary Quarterly, 30 (2), 376–392.Hager, Mark A., & Galaskiewicz, Joseph (2002). Studying closure among nonprofit organizations using event structure analysis

and network methods. Paper presented at the Fourth Annual Health Care Organizations Conference, June 6–7, Berkeley,California.

Hager, Mark A., Galaskiewicz, Joseph, Bielefeld, Wolfgang, & Pins, Joel (1996). Tales from the grave: Organizations’ accountsof their own demise. American Behavioral Scientist, 39 (8), 975–994.

Hager, Mark A., Galaskiewicz, Joseph, & Larson, Jeff A. (2004). Structural embeddedness and the liability of newness amongnonprofit organizations. Public Management Review, 6 (2), 159–188.

Hannan, Michael T., & Freeman, John H. (1989). Organizational ecology. Cambridge, MA: Harvard University Press.Haveman, Heather A. (1993). Ghosts of managers past: Managerial succession and organizational mortality. The Academy of

Management Journal, 36 (4), 864–881.Hulme, David, & Edwards, Michael (1996). Introduction: NGO performance and accountability. In David Hulme and Michael

Edwards (Eds), Beyond the magic bullet: NGO performance and accountability in the post-Cold War world. West Hartford:Kumarian Press.

Lecy, Jesse (2010). Sector density, donor policy, and organizational demise: A population ecology of international nonprofits(Unpublished PhD dissertation). Social Science Maxwell School of Syracuse University.

Martens, Bertin (2002). Introduction. In Bertin Martens, Uwe Mummert, Peter Murell, and Paul Seabright (Eds), The institu-tional economics of foreign aid. Cambridge: Cambridge University Press.

McGann, James, & Johnstone, Mary (2006). The power shift and the NGO credibility crisis. The International Journal of Not-for-Profit Law, 8 (2), 65–77.

Meyer, John W., & Rowan, Brian (1977). Institutionalized organizations: Formal structure as myth and ceremony. AmericanJournal of Sociology, 83 (2), 340–363.

Moreria, Marcelo (2009). Tests with correct size when instruments can be arbitrarily weak. Journal of Econometrics, 152,131–140.

Pfeffer, Jeffrey, & Salancik, Gerald (1978). The external control of organizations: A resource dependence perspective. NewYork: Harper and Row.

Reinikka, Ritva & Svensson, Jakob (2011). The power of information in public services: Evidence from education in Uganda.Journal of Public Economics, 95 (7–8), 956–966.

Selle, Per, & Øymyr, Bjarne (1992). Explaining changes in the population of voluntary organizations: The roles of aggregate andindividual level data. Nonprofit and Voluntary Sector Quarterly, 21 (2), 147–179.

Sooryamoorthy, Radhamany, & Gangrade, Kesharichand D. (2001). NGOs in India: A cross-sectional study. London:Greenwood.

Stinchcombe, Arthur L. (1965). Social structure and organizations. In James G. March (Ed.), Handbook of organizations.Chicago, IL: Rand McNally.


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Tuckman, Howard P., & Chang, Cyril F. (1991). A methodology for measuring the financial vulnerability of charitable nonprofitorganizations. Nonprofit and Voluntary Sector Quarterly, 20 (4), 445–460.

Twombly, Eric C. (2003). What factors affect the entry and exit of nonprofit human service organizations in metropolitan areas?Nonprofit and Voluntary Sector Quarterly, 32 (2), 211–235.

Werker, Eric, & Ahmed, Faisal (2008). What do nongovermental organisations do? Journal of Economic Perspectives, 22 (2),73–92.

Wollebaek, Dag (2009). Survival in local voluntary associations. Nonprofit Management and Leadership, 19 (3), 267–284.


Dow

nloa

ded

by [

Gaz

i Uni

vers

ity]

at 1

2:15

19

Aug

ust 2

014

Documents

Receive Grants or Perish? The Survival Prospects of Ugandan Non-Governmental Organisations