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Money, mission or need: How do Ugandan NGOs choose activities? Amit Grover, Ronelle Burger, and Trudy Owens

Abstract Using a unique and representative panel survey of NGOs in Uganda this paper considers both the type of activities NGOs engage in and the motivations behind such choices. We find some evidence that suggest that NGOs may have entered the targeted sectors opportunistically in the hope to procure funding allocated to these activities – or perhaps ex post after having secured funding for the activity or project. While some concern may be warranted, the analysis also shows that there is much persistence in the sector, which is congruent with a deeper commitment to serving the community through this specific activity. Also, we find little evidence of grants being a major factor in the introduction of other services – the Global Fund appears to be a special case. Normally the decision to expand their portfolio of services is a function of the organisation’s age, indicating that it may be part of the organisational life cycle. It is furthermore encouraging to see evidence of responsiveness to community need in HIV/AIDS services. Our analysis shows that the choice of activities of the NGO is heavily influenced by the interests, priorities and experiences of NGO manager. This provides some evidence in support of the importance of mission on the choice of NGO activities and in turn the importance of the NGO manager’s experience and interests in setting priorities for the NGO. Determinants of participation in a sector appear to depend on the sector in question. Similarly we also find that the budget share of an activity is not determined by the same factors across sectors. In HIV/AIDS related services experience appear to matter, while professionalism and formal status is important in agricultural support services. Lastly, the analysis indicates that there may be a trade-off between expanding the portfolio of services and increasing the geographical coverage of the service.


1. Introduction This paper attempts to unravel the complex web of considerations, influences and stakeholder interests that determine the demand and supply of development projects in the NGO sector. We investigate the observed shifts in activities in the Ugandan NGO sector between 2002 and 2008 against the backdrop of the advent of number of large funding initiatives, in particular those of the Global Fund for AIDS, Tuberculosis and Malaria and the Bill and Melinda Gates Foundation. The Bill and Melinda Gates Foundation, which has a $38.1 billion endowment making it the largest private foundation in the world has the broad objective to enhance global development, which includes activities such as supporting farmers, providing finance to the poor, water and sanitation; improve global healthcare including HIV/AIDS. The foundation works in partnership with other NGOs. Around the time when our first round of surveys of Ugandan NGOs were being conducted, the Global Fund1’s was beginning to implement its multibillion dollar fight to combat AIDS, Tuberculosis and Malaria. The fund, borne out of a commitment of G8 leaders to greatly increase the resources around the world to fight the diseases, is distinct not only in the scale of its investment, in May 2009 $11.3 billion of grants had be signed and $7.8 billion had been disbursed, but also in its choice to act as purely a financial mechanism and assign responsibility of implementation to multi-sector partnerships consisting of government, civil society and private sector within specific countries. Reflecting their importance in controlling the spread of the disease in Uganda in the original proposals NGOs were given around a 30% share of the budget allocated2 to HIV/AIDS in both rounds of funding. In the first round, which commenced in June 2003, the approved maximum budget was $48,878,000 with $26,161,000 finally being disbursed. This was dedicated to a range of activities: education, counselling and testing activities as well as providing drugs and medical supplies and mitigation programs orphans and vulnerable children. In the third round, which started in 2005, a greater emphasis was put on antiretroviral drug treatment with $46,362,000 being distributed out of $82,586,000 request for funding. Although larger international NGOs were the primary recipients, eligibility for grants stretches from smaller NGO, that may asked to fulfil part of a grants objective, down to community based organisations, which raise awareness or support vulnerable groups. Therefore this funding is expected 1 2

All information is found on the Global Fund website: http://www.theglobalfund.org/en/ Sourced from the grant applications of the Ugandan CCM

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to impact all sizes of organisations in civil society. Anecdotally, many of the community development officers in the districts attributed the strong growth of NGOs between 2002 and 2008 to the impact of the Global Fund. Since 2002 there have been several large initiatives administered by different international donors to scale up the response to the AIDS epidemic in Uganda. The largest programme is PEPFAR which has $923 million committed to HIV control, followed by the Global Fund ($142.8 million), the World Bank MAPS ($47.5 million) and the sector wide approach to health (approx $9.75 million). Donors envisage NGOs as the front line of service provision in prevention, treatment as well as supporting vulnerable groups. More details of these programmes are provided in the appendix. In healthcare international donors finance the Ugandan health sector through multiple channels of project funding, sector funding and general budget support (Lake).

In 2001 total healthcare

expenditure was estimated at $423 million with NGOs making up a large source of finance providing over a third of health expenditure. NGO played a bigger role as financial backers of healthcare as opposed to as providers with 31% of total healthcare expenditure going through NGOs without medical facilities as opposed to 3% going through non profit organisations with medical facilities (National health accounts 2000-2001). In agriculture as part of their Poverty Eradication Action Plan (PEAP) the Ugandan Government developed the Plan for Modernization of Agriculture (PMA) in 2001 to eradicate poverty by supporting agricultural activities. The programme makes up approximately 10% of government expenditure (2003/2004) and allocating 496 billion Ugandan shillings or $2643 million from 2001-2004 (OPM 2005). Main activities include agricultural research, extension services, input and agricultural infrastructure provision. The programme adopts a multisectoral approach in its implementation working at the sub county and district level. Although, there has been considerable scepticism expressed by NGOs and parliamentarians about the degree to which the implementation is in fact multisectoral (OPM 2005).

3

Exchange rate used is January 2003 1867.7/$ source: Ministry of Finance Uganda

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This generous increase in funding targeted at specific activities provides a type of natural experiment to study how NGOs react to such influences. Specifically, we are interested to see to what extent NGOs can be swayed by grant money to adopt new activities. When confronted with an opportunity to expand its revenue base, does the NGO stay true to its mission and resist the temptation to tap into this new source of income? Or does the NGO behave more pragmatically, branching into the new stream of activities to procure more funding and thus ensure that the organisation survives and its community projects will continue? The paper explores this question by tracking and comparing NGO activities in 2002 and in 2008 to get a preliminary sense of how the escalation in available funding has affected the number of NGOs working in two of the targeted areas, namely HIV/AIDS support and prevention and agricultural extension services. The range of motivations that prompt NGOs to undertake HIV related services and farming activities are examined using an adapted utility maximisation framework. In recognition of the complex multistakeholder environment within which NGOs operate, this paper incorporates three possible motivations for undertaking projects: namely, alignment with NGO mission, meeting the needs of the community and revenue generation. Broadly, these three motivations correspond to the channels of influence for the three major stakeholders in NGO-driven development projects: NGO mission represents the preferences of NGOs, money represents an avenue whereby donors can assert their preferences (via conditionality and requirements) and beneficiary needs represent the preferences of the beneficiaries. The analysis uses a unique panel data set of Ugandan NGOs. In 2002, Barr, Fafchamps and Owens (2005) conducted the first round of a nationally representative survey of the Ugandan NGO sector. With the enormous growth in the sector – growing from 3,500 NGOs registered with the Ministry of Internal Affairs in 2002, to 7,000 by 2008 – we returned to not only trace and interview the original 300 NGOs, but doubled the sample size to take account of the rapid growth of the sector. In the second round, collected by Burger, Grover and Owens in 2008, 100% of the NGOs in the 2002 sample were tracked. 84% of the tracked NGOs had survived and 98% of the surviving NGOs were interviewed. Additionally, to capture the growth in the sector 255 new NGOs were added to the sample.

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The paper is organised as follows. Section 2 provides background to the paper. Section 3 outlines the empirical model. Section 4 describes the data, section 5 examines the descriptive statistics, section 6 discusses the regression results and section 7 concludes.

2. How do NGOs choose activities? Any model of NGO decision making is embedded within the dialogue on the objectives of managers and staff in this sector. For-profit firms have an incentive to maximise profit which serves to simultaneously explain their entry and survival in a sector, but there is no such unifying motive to explain NGO behaviour. Steinberg (2006) argues that in order to provide a theory of supply for non profit organisations they require an organisational objective to explain their decision to enter a sector. In the absence of profit maximisation a number of objectives exist to explain the presence of NGOs which include: an entrepreneurial objective to provide a collective good (Bilodeau and Slivinski 1997), an ideological belief to change the preference of others (James and Rose-Ackerman 1986 ), the desire to equalise the distribution of resources (Steinburg and Weisbrod 2005), as well as motivations often not considered in economics such as the desire for control, affiliation, and self expression (Steinberg 2006). For the purposes of this analysis, we can treat these objectives collectively under the umbrella, “mission”. NGO’s mission is central to their comparative advantage as service providers. This has been argued on many grounds – some more convincing than others. It has been proposed that in situations where the behaviour of service providers cannot be discerned NGOs may be preferred as providers as they are motivated primarily by mission and not money. Such arguments are usually supported by reference to the nondistribution constraint (cannot distribute profit/gains) and the donative labour hypothesis (NGO staff receive lower wages to ensure that staff that care about the mission self-select into the jobs). However Burger and Owens (forthcoming) have argued that the nondistribution constraint is simple to circumvent with creative accounting and inflated salaries and therefore unlikely to be a binding constraint. Furthermore, the donative labour hypothesis does not have a firm empirical base as it not clear that NGO wages are indeed lower than wages in the forprofit sector (e.g. Mocan and Tekin 2000 and Ruhm and Borkoski 2000). Additionally, this would not mean much unless unemployment is negligible and that is not a realistic assumption in any developing country. It is difficult to make an

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argument that NGOs are motivated exclusively or predominantly by mission and in this paper we try to steer clear of such generalisations. In this paper we diverge from the habit of assuming that mission is the central motivation of NGOs. In contrast to much of the theoretical literature on nonprofit organisations, we view mission as a prominent NGO motivation, but do not presume that it is the only or necessarily the most important motivation. Rose-Ackerman (1996) argues that mission may provide NGOs with a different advantage: catering to small groups of individuals with specific preferences or strong ideologies. She asserts that non profits are in a better position than public and private organisations to experiment and cater for tastes and groups at the margins of society. NGOs have a natural way to differentiate activities if donors value their ideology as well as the activities they undertake. This is particularly true when NGOs provide information or advocate a cause where service value is assessed by those who are providing it. Aldashev et al 2006 find evidence of such horizontal differentiation of activities in face of competition for donations. Steinberg (2006) describes how entrepreneurs go about turning their mission into work. They need to consider the necessary feasibility constraints such as the cost of entry, agency costs, regulation and funding their activities. He emphasise that procuring funding often entails tough decisions as most sources of funding has strings attached and the donor’s priorities do not always align with the NGO’s mission. James (1983) describes a model that takes a pragmatic view on the trade-off between mission and money. She argues that non-profit organisations often take on activities that derive no personal satisfaction in order to subsidise those that they do want to provide (for example, selling t-shits at the national opera). The trade-off between money and mission is well-documented in the literature on nonprofit organisations. NGO managers will face different restrictions in the type of services they provide depending on who is funding them. Larger grant agencies may give aid conditionally and have monitoring bodies in place to ensure funds are spent correctly. Commins argue that in extreme cases such donor arrangements can reduce NGOs to “ladles in the global soup kitchen” (2000: 70) – stripped of their initiative and unable to follow their own agenda or conscience, thus becoming mere tools to donors. A critical question then is how do mission interact with the need to raise revenue? Do the preferences of different funders and their power which NGOs survive subsequently determine the composition of activities within the sector? 6


Parallel to this question, we also examine how NGOs navigate the trade-off between their mission and community needs. Bilodeau and Slivinski (1997) find that NGO have a propensity to respond to unmet needs and to deliver services they feel are underprovided. However, it be acknowledged that an NGO’s mission is not necessarily aligned with the needs of the community. NGOs have their own interests and priorities and these can be odds with those of the communities they serve. In other instances the NGO’s paternalism may mean they only provides services which they view beneficiaries require rather than those beneficiaries want or need.

Particularism stemming from ideological beliefs

may also lead to services being duplicated in some regions or insufficient coverage of other regions and social groups (Steinburg 2006). Given that the objective of an NGO is often normative this apparent diversion from allocative efficiency may not be a significant outcome at least in eyes of the organisation. NGO often state their objective is to change the attitude of society, be it through religious conversion or raising awareness on political or socio-economic issues so the state of current preferences may not be an important factor when deciding which activities are worthwhile. Furthermore, objectives such as increasing equality in society or providing physical services may provide different grounds to evaluate the efficiency and relative successes of NGOs (Steinburg 2006). The next section sets up an economic model to examine the determinants of NGO activities and budget allocation decisions.

3. Constructing a model for choosing activities and allocating budget between activities How do we define an empirical model to describe how NGOs make decisions about which activities to undertake and what share of resources to allocate to each activity? We start by investigating optimal NGO expenditure over two activities within a generic utilisation maximisation problem. Expenditure over two activities, z and y, is subject to a budget and non zero constraint. max

,

,

,

(1) 0

Where x is the NGO’s total income

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The generic utility function specification will accommodate multiple modes of NGO behaviour, including the three-way trade-off between money, mission and need discussed in section 2. The interior solution to this problem gives rise to a Marshallian demand curve for each activity: ,

(2)

Where qj is the quantity of activity j demanded, which is a function of income and a vector of prices. This demand function can be expressed as an Engel curve in budget share form4. It is assumed that NGOs face different prices for carrying out activities and so a price variable is introduced to account for this. For the ith NGO the budget share in activity j is ∑

log

log

(3)

Where x is the income of the NGO, pij is the price of every activity and εij is the stochastic component. An activity can viewed to be an inferior, normal or luxury good if the elasticity of income, found by dividing β by the average budget share and adding one, is less than zero, in between zero and one, greater than one respectively. The budget share of activities may also be independent of income signifying NGO’s homothetic preferences. The stochastic term ε is used to allow for the heterogeneity in preferences of NGOs and their supporters. Additional explanatory variables are included to reduce endogeneity created by regressors being correlated with the error term. It is hypothesized that when zero expenditure is observed for an activity it is not just a corner solution to the maximisation problem when the propensity of demand is negative but an instance when an NGO abstains from a certain activity. Put another way the model for budget shares is separated into a 4

The almost ideal demand system would be a model of consumption, which adheres better with assumptions of convexity of utility function but without price data it is not possible to construct the price index.

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two stage decision process: first NGOs make a decision whether to undertake an activity, having decided to do so they decide how much of their budget to spend. Positive budget shares are only observed if the binary decision to engage in an activity is true. The equations can be extended by including a vector of taste variables, T for each NGO and their manager, which controls for heterogeneity in preferences. Finally, additional variables to account for barriers to activities B, which only affect the first decision, are used to ensure identification in the Heckman selection model. Formally the decision process for NGO activities is estimated as 0 1

0 The activity decision: α log

∑ β log

(4)

The budget share decision: log

log

(5)

Based on this framework, we conceptualise a two-stage empirical model: in the first stage the NGO makes a qualitative decision to participate in an activity and in the second stage they then decide how much resources to allocate to this activity. This two-stage process is estimated by a Heckman selection model. The model incorporates the motivations of the NGO’s manager and restrictions imposed by agents from outside the organisation. The preferences of donors and community stakeholders are viewed to be important external influences on the decision making process relating to activities. There are two major challenges associated with the implementation of this framework. Firstly, NGOs rarely charge the end user for services and even when user fees are present, they are usually heavily subsidised and often priced according to the beneficiary’s ability to pay. In the absence of prices, we thus need to find proxies for the costs of these services. However, these variables only need to provide

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a rough measure of the general price level faced by each NGO. These proxies are discussed in detail in the next section. Defining the boundaries between activities is a further problem: NGOs have less clearly defined boundaries between activities. NGO frequently use non-rival resources for multiple purposes; for instance they have workshops for sanitation and hygiene that also raise preventative health issues. However, in so far as activities compete for scarce resources such as budget and staff time, they can be separated. On an accounting level there are still issues relating to obtaining accurate estimates of the share of expenditure that each of the activities represent, but we tried to address that by asking respondents to estimate the budget proportion in the questionnaire. To consider the catalyst role of these large donor initiatives including the Global Fund and the Melinda and Bill Gates Foundation, we look at two activities that are targeted by these grant schemes, namely HIV/AIDS related services and farming activities. Within the group of activities targeted we opted for these two because they are likely to be more easily separable from other activities, given the highly specialised capital and human resource inputs they require. The next section describes the data we will use to estimate the empirical relationships.

4. Data For our analysis here we use two waves of a nationally representative sample of Ugandan NGOs. Details of the data and sampling procedure are outlined in Barr et al (2005). The 2002 survey covers 100 NGOs in Kampala and 200 in 14 randomly selected districts, for 2008 the numbers are 190 and 290 respectively. In the 2008 sample in line with growth in the sector the objective was to double the number of NGOs surveyed. Again a full account of the data and sampling procedure is detailed in Burger and Owens (2010). Ultimately the mentioned activities are subjective; this means that the accuracy of results depends upon the honesty and awareness respondents. Bias may exist if smaller NGOs try to list as many small activities as possible and bigger NGOs fail to list some important activities. Therefore enumerators were under strict instruction to interview senior members of NGOs, to find out as much about their

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activities and get the respondents to categorise activities for which the budget had been allocated. There is also a degree of subjectivity in classifying activities so the following criterion is used. Every activity is only allowed to be allocated to one category; if only the type of activity is mentioned this is used for categorisation. If an activity description is vague and only mentioned a target group, such as “support to children”, then this is introduced as a category in itself. When both the activity and the target group are mentioned the activity is classified by whether the target group changes the resources required; for instance “accommodation for orphans” is considered as “support for orphans”, whereas “IT training for women” is considered as education and training. For the two activities for which determinants are analysed, an HIV related service includes any budgeted activity that raises awareness, helps prevention and treats the disease. Farming activities includes support to farmers, extension services and providing inputs as well as private farming activities of the NGO. Presuming that respondents try to give accurate budget shares, there is still measurement error caused by rounding. Budget shares are mentioned to different degrees of accuracy, but 5% and 10% intervals for budget shares are common, therefore there could be substantial measurement error in smaller activities and heteroskedasticity in observations. Worse still there may be systematic error created if say larger shares are rounded up creating a bias in coefficients. These issues are not easily accounted for in Heckman selection models but possible solutions are discussed towards the end of the paper.

5. Descriptive analysis 5.1

Prevalence of activities

Figure 1 shows the prevalence of the top 20 NGO activities as cited in the 2008 survey. It is clear from the table that Ugandan NGOs engage in a diverse range of activities covering development, education, healthcare, social services and livelihoods. This is in line with what Salamon et al (1999)’s concluded based on their analysis of 32 surveys of developed and developing countries. They found that (based on staff allocation) education and social services appear to dominate NGO activities. The most commonly cited activity is education and training with over 43% of NGOs stating that they

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provide it in some form. Education and training activities range from providing vocational training courses, to primary and secondary education. Over 130 of the 476 NGOs interviewed in 2008 are involved in HIV/AIDS related services5. Most of the NGOs involved in HIV/AIDS related services say that they raise awareness or are involved in prevention of HIV/AIDS, with only 27 stating that they operate a health clinic. Both large and small NGOs are involved in this subsector, with 50% of the sample operating at a revenue under 47 million shillings in 2007 (approximately 26,000 US$)6. The sector’s involvement in sensitisation supports accounts (e.g. Parkhurst and Lush 2004) that NGOs in Uganda emphasise the importance of raising awareness to combat the epidemic in Uganda. Hence both small NGOS and even CBOs do receive funding for their involvement in HIV related services.

5

6

Data on activities is compiled from two sections of the questionnaire: firstly NGOs were asked to list their activities then assign budget shares allocated to each activity. The other source is a series of prompted responses to questions about whether the NGO engaged in particular activities. NGOs were not specifically asked whether they provided HIV related services but were asked if they raised awareness on HIV/AIDS. These observations are not included in the positive observations for HIV related services used in the analysis since they have not been allocated a separate budget share, so are assumed to be part of another activity. As prompted responses are likely to have a higher number of positive observations than mentioned responses they are treated separately in the description of activities. Differences between the two sections on activities give an indication of the extent of bias that may exist because respondents fail to mention activities. Using an exchange rate of 1800 Ugandan Shillings per US dollar

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FIGURE 1 : Prevalence of NGOs activities, 2000 Income generating activities for NGOs Conflict resolution Helping the poor and needy Arts, culture and sport Distribution of goods and services Water and sanitation Credit and finance Environment and conservation Employment promotion and… Support to orphans Curative healthcare Preventative healthcare Child services Counselling Raising awareness including… Advocacy and human rights Support to farmers and farming… Community development HIV/AIDS awareness and training Education and training 0

10

20

30

40

50

Alongside these services Ugandan NGOs also engage in activities that aid the development process such as supporting farmers (21.8%), providing credit (10.5%), sanitation (9.2%) and community development (27.5%). As is the case with caring services the world over, NGOs in Uganda are active in health, curative (15.1%) and preventative (13%), and social services, counselling (18%). They also help vulnerable social groups including: orphans (12%) and the poor and needy (8.6%). As is evident from table three this resonates with views of beneficiaries, which identifies supporting these social groups as a priority. Finally, the sample consists of a large number of niche activities that only a few NGOs engage in such as forestry (4%) and technical assistance (1.9%). When specifically asked about their role in raising awareness and advocacy the number of NGOs stating that they participated in these activities dramatically increases with over 90% of NGOs being involved in raising awareness, two thirds of which on HIV/AIDS, and 71% are involved in advocacy. As with Barr et al (2005) the vast majority of NGOs are involved in creating awareness. The results are evidence that the new legislation that allows that government to regulate and monitor the sector with a stronger hand has not dampened activism in the sector. This could be because Ugandan NGOs 13


tend to cooperate with government in their advocacy efforts: 45% of those organisations involved in advocacy use meetings with national government to raise issues and 84% use local government meetings. In comparison fewer NGOs use petitions or marches (around 10% each) to advocate their cause, whereas over 40% use public broadcasting to express their views. As reported by Barr et al (2005), the 2008 also shows little evidence of specialisation. In general the Ugandan NGO sector has a holistic approach to service delivery with the average NGO engaging in 4.2 activities. This trend is not limited to NGOs with larger revenue; excluding the top 50 NGOs with the highest revenue the average number of stays the same. This shows that irrespective of size, NGOs in Uganda want to provide a broad range of activities. Overall, activities are likely to be underreported given that we do not provide any categories and thus could not prompt respondents. Were we could triangulate we for instance found that only 0.2 percentage of NGOs cited disbursements of grants as one of their activities, but elsewhere in the questionnaire where they were prompted about such activities, more than 21% of NGO reported that they gave grants to other NGOs or CBOs. This may however be an extreme case as many NGOs may see subcontracting as a way of doing their work rather than an activity in itself. The underreporting of microfinance and water and sanitation activities may be a better indication of the overall trend. The percentage of NGOs involved in microfinance and the number that engage in water and sanitation increase from 9% to 13% and from 11% to 18% respectively when we incorporate questions were we specifically asked about these service categories. In terms of regional specialisation the average NGO has staff and volunteers working in 3.8 districts with 90% of the sample operating in fewer than eight districts, only five NGOs say they are present in every district. However the median number of districts is much lower at two. To an extent this supports the view that small to medium sized NGOs regionally focused at least in terms of the districts they work in. Regional specialisation seems probable since communities even within districts are very spread out and road access between regions is limited. To smaller organisations the costs of supporting NGOs further afield would be significantly higher that serving beneficiaries that are close by (Barr and Fafchamps 2006).

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5.2 Changes in the prevalence of activities, 2002 – 2008 In analysing the changes in the prevalence of activities between 2002 and 2008, the surveys provide two possible approaches, each with their potential pitfalls. Firstly, we can compare the information on activities listed in the 2002 survey with that of the 2008 survey. However, there was a considerable improvement in the quality of data collection in 2008. In the 2002 survey only 320 activities could be identified from the responses of NGOs with over 50% of NGOs not providing any information. This contrasts with over 2000 mentioned activities in the 2008 sample. Also, the comparison may be problematic because the 2008 question was phrased differently and did not appear in the same place in the questionnaire. The alternative is to use backward-looking questions that we had asked in 2008 survey about activities. However, recall error would be expected to be a significant issue here – especially given that the recall period of six years is considerable. Additionally there is a sampling issue at play here: we are comparing the 2002 and 2008 activities of the sample of NGOs that survived, thus excluding the 2002 NGO activities offered by NGOs that have since become extinct. Table 1 provides information on the changes in activities based on both methods. Both methods are likely to underreport activities in 2002 and thus to overestimate increase in activities since 2002. We have no evidence that underreporting will be unbiased. TABLE 1: Estimated changes in prevalence of activities, 2002 – 2008

Education and training HIV/AIDS awareness and training Community development Support to farmers and farming activities Advocacy and human rights Raising awareness including sensitisation Counselling Child services Preventative healthcare Curative healthcare

2008 43.9 28.2 27.5 21.8 19.1 18.9 18.1 15.8 15.1 13

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Estimates based on 2002 survey 2002 Change 44.9 -2% 9.6 194% 10.3 167% 22.8 -4% 7.4 158% 11 72% 9.6 89% 12.5 26% 16.2 -7% 18.4 -29%

Estimates based on recall using 2008 survey 2002 Change 36.3 21% 20.6 37% 20.2 36% 17.9 22% 16.6 15% 12.1 56% 16.1 12% 11.2 41% 4.9 206% 8.1 61%


Support to orphans Employment promotion and opportunities Environment and conservation Credit and finance Water and sanitation Distribution of goods and services Arts, culture and sport Helping the poor and needy Conflict resolution Income generating activities for NGOs

12 11.3 10.9 10.5 9.2 9 8.6 8 7.6 7.4

4.4 4.4 1.5 5.9 5.9 7.4 4.4 4.4 2.2 2.2

173% 157% 627% 78% 56% 22% 95% 82% 245% 236%

11.2 6.7 7.6 13.5 11.7 9.4 4.0 6.7 1.8 5.8

7% 68% 43% -22% -21% -4% 113% 19% 324% 27%

The two approaches give widely differing pictures of the changes in activities between 2002 and 2008. Spearman’s rank correlation coefficient is very low (0.08) and insignificant (0.76). This should not be surprising given the low cell sizes of some of these fields (especially towards the bottom of the list) and the recall method’s exclusion of 2002 NGOs that have not survived. While there is no way to compare the extent of the underestimation of 2002 activities and potential bias of the two approaches, the smaller variance and more plausible estimated levels lend some credence to the recall approach. There does however appear to be agreement amongst the two divergent measures on the direction of the trend in the one of our activities of interest, HIV/AIDS related services. The recall method estimates that there has been a 37% increase in the prevalence of the activity while a comparison between the 2002 and 2008 surveys estimates a much large increase of 194%. The two methods give divergent answers re the change in our other activity of interest, support to farmers. The recall approach estimates that the share of NGO that report that they support farmers have risen by 22%, while the comparison of the 2002 and 2008 surveys show a slight decrease (-4%). We also examine how organisational characteristics differ between those NGOs that introduce and discontinue activities.

NGOs can be placed into four mutually exclusive categories: they only

discontinued activities, they only introduced activities, their activity composition remained the same and they “streamlined” their activities by introducing some and discontinuing others. A comparative analysis of each group is conducted using revenue and staff numbers.

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TABLE 2: Added and discontinued activities vs. revenue and staff in 2008 Median of revenue ('000 Median of nr of Frequency Share Ugandan Shillings staff members No change in activities 199 42.9 64,000 12 Added activities 157 33.8 148,750 20 Discontinued activities 41 8.8 288,600 11 Streamlined activities (added and discontinued activities) 67 14.4 95,560 13 Total 464 100 103,000 14

Table 2 shows that it is more common for Ugandan NGOs to introduce activities than to discontinue them. Activities remained constant for 42.9% of the sample and were introduced by 33.8% of the sample. Smaller proportions of NGOs (8.8% and 14.4%, respectively) discontinued and streamlined services. Given the skewness of the distribution of revenue and staff, we focus our analysis on median values. In the four categories there are clear distinctions in median total revenues in 2007. NGO that keep the number of activities constant have the lowest median revenue (64,000,000 Ugandan Shillings). As expected NGO that introduce activities have significantly higher median revenue (148,750,000 Ugandan Shillings), which indicates that it is a habit for larger NGOs to expand their activities. Somewhat unexpected though, NGOs that discontinue activities have the highest median revenue (288,600,000 Ugandan Shillings). We use the nonparametric Kruskal–Wallis test to examine the hypothesis that these groups (samples) were generated by the same population. The test cannot reject the null of equal population medians at the 10% level (p>chi2 = 0.16). A different pattern emerges when examining the medians of total staff. NGOs that introduce activities have the most staff (20) followed by those that streamline them (13). NGOs who keep services constant have lower staff level (12) and those that discontinue them have the least staff (11). The Kruskal-Wallis test show that we can reject the null of equal population medians with confidence (p>chi2 = 0.0001). TABLE 3: Added and discontinued activities in 2008 vs. cited constraints in 2002 Constraint NGO lacked skilled staff

No change in activities 0.50

Added activities 0.45

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Discontinued activities 0.71

Streamlined activities 0.49

Total 0.50


NGO lacked equipment

0.80

0.75

0.62

0.62

0.73

NGO lacked vehicles

0.69

0.74

0.48

0.62

0.67

NGO lacked funds

0.95

0.96

0.81

0.92

0.94

We also consider cited constraints. There are however two patterns here that are at first glance counterintuitive, or at least at odds with initial expectations. NGOs which discontinue activities between 2002 and 2008 were less likely to see lacking equipment, vehicles or funds as a constraint in 2002, but more likely to described the lack of skilled staff as a constraint. The patterns for NGOs that expanded their list of activities are less clear, but there is some slight evidence that some of these NGOs may be motivated by resource shortages as those citing equipment and funding constraints are slightly higher than for the rest of the pack and lack of vehicles is considerably higher. However, ANOVA fails to reject the hypothesis of equal means (at the 10% level) only for the funding constraint (Prob > F = 0.073). All that we can thus (prudently) deduce from this table is that NGOs do not seem to discontinue activities mainly because of funding constraints. This makes sense: NGOs that discontinued activities had the highest median revenues, but the lowest median for staff numbers.

5.2

Community beneficiary needs

An important consideration in examining the frequency of activities within the NGO sector is how they relate to the needs of the communities they serve. Given the motivations and incentives in the sector we would expect beneficiary needs to be important. One can assume some inherent motivation to serve the community, and this would be strengthened by explicit external mechanisms such as community funding channels (user fees and member fees) and community participation processes (need assessment and community feedback). While there may be some alignment of priorities and interests between the NGO and the community, the literature has shown that it is naive to assume that preferences are perfectly or even well-aligned. Table 3 is constructed using beneficiary assessments from 2002 for villages in Uganda. The priorities of beneficiary communities are considered in aggregate, giving an impression of how their collective needs are reflected in the sector’s activities composition The average ranks measure the priority

18


beneficiaries give to each activity between 0 and 1, with 0 being the least important and 1 being the most. Communities were chosen at random from a list of parishes given by NGOs respondents. TABLE 4: Priority needs of community, 2002

Priority need Agriculture training Sanitation Healthcare Children's education Credit Water Adult education Roads Land Earning opportunities Security Market access Drainage Agricultural inputs Food/famine relief Orphan care Housing Agricultural water supply Grants Care of elderly

Cited by how many communities 263 263 252 246 241 235 225 221 179 59 55 23 18 17 11 11 8 6 5 2

Average rank when cited 0.93 0.92 0.69 0.63 0.57 0.66 0.39 0.45 0.39 0.5 0.46 0.61 0.53 0.5 0.54 0.53 0.37 0.59 0.86 0.4

There is wide agreement across communities that agricultural training is the most important issue (0.93) with only a 0.05 standard deviation from this point. Sanitation (0.92) and access to water (0.66), healthcare (0.69) and children’s education (0.63) are also priority issues but the standard deviation is larger around these values, suggesting some differences in opinion. Other activities such as market access, grants, orphan care and care for the elderly are raised by a fraction of communities as other important activities. This may be at least partly due to the lack of prompting. It is likely that if other groups had been asked about these activities they would have added it to their list. Comparing Table 3’s list of community needs with Figure 1 and Table 1’s information on services and activities offered by NGOs, we find a reasonably good matching. Services and activities provided by 19


NGOs correspond well with community needs. Support to farmers, water and sanitation, healthcare and education are important to beneficiaries and are services Ugandan NGOs frequently provide. But other NGO objectives such as advocacy, raising awareness and in particular HIV related services are not cited by benefiting communities but are still common activities. Caution needs to be taken interpreting the differences between NGO activities and community needs. There are many reasons why NGO activities may not match perfectly with the community needs reported. NGOs may contend that communities’ perceptions and beliefs about their needs may not always be accurate. Although such arguments could easily be a veil for paternalism, it has been shown that communities tend to systematically underestimate the importance of some services (such as for instance sanitation and clean water) because the utility of it is not directly observable. It is thus conceivable that in some cases NGOs may believe that communities needs a particular service or programme (e.g. better sanitation or higher vaccine coverage) even though the community may not rank it as a priority. Additionally, one should also bear in mind that in the case of HIV/AIDS there may be a degree of stigma associated with the topic so groups may not readily talk about it. It is also possible that beneficiaries include HIV related services with healthcare, although this definition is not strictly true since HIV related services includes sensitisation and awareness training. Lastly, due to the absence of fixed categories and the lack of prompting re NGO activities, it would not be advisable to compare the two lists too closely as the prevalence of some activities and needs may be underreported. The next section estimates the empirical model outlined in section 3.

6. Estimating the empirical models We approach the question regarding the motivation of being involved in specific activities from three angles: Firstly, we look at NGOs that have existed in 2002 and are still around in 2008 and examine how their 2002 characteristics can help to explain NGO activities and budget shares in 2008. Secondly, we investigate the correlates of the activities chosen by new NGOs. Lastly, we look at the factors associated with the introduction of new activities. We choose to look at these three samples separately because we argue that there be a significant amount of persistence in activities and the latter two questions allow us to concentrate on recent

20


movements in the sector. Recent shifts in activities could be attributable to the introduction of new activities by NGOs that have been around since 2002 or it could be due to new NGOs entering the sector. We model the processes separately as there is no ex ante reason to presume that the same dynamics would be at play across these two processes. Below we discuss how and why we selected variables to represent the relevant influences on the decision making process – as summarised in section 3’s framework. Revenue

Missing financial data is a further concern. In an attempt to minimise the impact of the

missing variables and the possible bias that a loss in sample would introduce, we use a revenue correlate with a low share of missing values. Here we use whether the NGO has ever received a grant in the past. One of the main concerns regarding an approach that would be too focussed on adapting itself to the available revenue streams would be fickleness and a lack of consistency. Consequently we want to examine persistence and commitment, i.e. how important is past activities in a sector as a predictor of current involvement. Barriers to making the decision to add services is included in the model as an indicator as an institutional response to curtail fickleness and ensure responsible, accountable and inclusive decision making. Examples of such mechanisms are requiring a vote of members or permission from the board to add new activities to the NGO’s portfolio. Community need To investigate the impact of community need on the selection of NGO activities, we include focus group variables capturing whether the community listed this activity as a need and how high this activity ranked among its needs. Mission The characteristics of the NGO and its leader are incorporated into the model to take account of personal preferences that may be associated with the NGO’s mission. The list includes whether the manager is Ugandan and his or her years of education. For farming support activities we also incorporate whether the manager is involved in farming and whether his or her father was a farmer.

21


Again the persistence of activities over time will provide some measure of the NGO’s commitment and dedication to this activity that will be useful in assessing the impact of mission on decision making re activities. Other controls The model also includes Kampala location, staff numbers (to represent size) and the years of existence. These factors also serves as proxies for the prices that the NGO face in the market: the Kampala dummy captures urban-rural differences in prices, staff numbers incorporates the influence of size and negotiating power on prices, while years of existence reflects the impact of experience and established relationships on prices. We also include a dummy showing whether accounts were audited externally in 2002 as an indicator of the professionalism and “formal status” of the NGO. The decision making processes re participating in an activity and allocating a budget share towards the activity are conceived as distinct. It is argued that the decision to pursue certain activities is made by largely by the NGO, taking account of the external circumstances and the likely implications of such a decision. While there is some fungibility with regards to allocated funding, it is expected that the NGO is more constrained in its decision re allocation of budget share. Consequently, we do not include the characteristics of the manager in this equation. Also we use different measures to capture community need in the two decision-making processes. When considering whether to participate or not, we represent community needs with a binary variable (i.e. is it listed by the community as a need?) but in the decision re budget share we use the depth of the community need (how highly this activity ranked among the community’s listed needs). The years of existence and the professionalism indicator (whether accounts were audited externally) were both included only in the budget share decision. These factors are expected to be relevant for the procurement of funding. Professional organisations with experience and established relationship may find it easier to access funds. Professionalism may also inhibit the fungibility of funds.

22


The grant recipient indicator indicates that an NGO may be exposed to the influence and preferences of donors. This is expected to influence the choice of activities. Institutional constraints on adding a new service is also only seen as factor in the choice of activities. 6.1

What motivates established NGOs to allocate resources to HIV/AIDS related services?

In the binary model used to describe the decision to provide HIV-related services three variables turn out to be significant at the 10% level: past activities in the health sector, community need and a Ugandan manager. As expected, the coefficients on the persistence variable and the community need variable are both positive. Having a Ugandan manager makes an NGO less likely to pursue HIV/AIDS related services. The years of existence variable is significant and positive indicating that experience and established relationship is associated with a higher budget share allocated to HIV/AIDS related services. Although the Kampala variable is not significant here, it is close to the 10% level of significance and it becomes significant if the specification is altered slightly. According to the results of the Heckman model, we cannot reject the hypothesis of independent equations. Therefore, these equations could also be estimated separately. Wald tests reject the null hypothesis of equal coefficients at the 1% level. Residuals do not appear to be normal suggesting that there may be room for improvement in the specifications of the model.  TABLE 5: Heckman selection model for determinants of HIV related services’ budget share (established NGOs) Budget share of HIV activities in 2008

Coef.

Constant Number of staff in 2002 Kampala-based Health activities in 2002 Ranking of health activities by community in 2002 Years of existence Accounts audited externally in 2002 HIV activities in 2008 Constant Number of staff in 2002 Kampala-based Health activities in 2002 23

P>|z|

66.75 -0.01 -25.64 -12.64 3.05 0.99 -11.06

Std. Err. 34.81 0.09 16.27 20.28 24.22 0.36 11.78

-1.24 -0.001 -0.50 1.35

1.01 0.003 0.46 0.31

0.22 0.72 0.28 0.00

0.06 0.95 0.12 0.53 0.90 0.01 0.35


Community cited health activities as a need in 2002 NGO has received grant by 2002 Constraints on decision-making Manager is Ugandan Manager's years of education

1.44 0.32 0.15 -1.62 -0.05

0.65 0.38 0.54 0.88 0.11

0.03 0.40 0.78 0.07 0.63

Lambda

-27.73

19.97

0.17

Nr observations Censored observations Uncensored observations Wald chi2(9): Prob > chi2

120 95 25 0.0004

 6.2

What motivates established NGOs to allocate resources to farming activities?

Four variables are significant at the 10% level in the equation representing the binary decision to provide farming activities: past activities in the farming sector, being a grant recipient, whether the manager is Ugandan and whether the manager is a farmer. As before, the influence of the persistence variable is positive (having been involved in the sector in the past increases the likelihood of current participation). The results show that this sector is not attractive for grant recipients and having received a grant in the past (and thus functioning is this realm, being eligible for grants and aware of such funding opportunities) makes an NGO less likely to provide agricultural support services. This variable is highly correlated with revenue so an alternative interpretation may be that NGOs with lower revenue may be more likely to enter the sector. In contrast to what we found with HIV/AIDS related services, we see that Ugandan managers are more likely to be involved in agricultural support services than managers from outside the country. Also, when the manager has a personal involvement in the sector as a farmer, the NGO is more likely to be involved in the sector. While the sign on community needs is positive, the coefficient is not significant. Thus it appears that the decision to provide agricultural support services is not a response to needs expressed by the community. The main determinant of the budget share allocation to agricultural support services is the professionalism indicator: organisations that have their accounts audited externally tend to have smaller budgets for agricultural support services.

24


TABLE 6: Heckman selection model for determinants of agricultural support services’ budget share (established NGOs) Coef. -91.01 -0.38

Std. Err. 179.65 0.30

P>|z| 0.61 0.20

-64.84

54.04

0.23

-3.25

20.04

0.87

152.51

174.44

0.38

1.96

1.62

0.23

-37.67

12.84

0.00

-6.06 -0.003 -1.05

. 0.01 0.76

. 0.57 0.17

1.46

0.41

0.00

0.56

0.40

0.16

NGO has received grant by 2002 Constraints on decision-making Manager is Ugandan Manager's years of education Manager's father was/is a farmer Manager is a farmer

-0.70

0.42

0.10

0.01

0.83

0.99

4.38 0.10 0.27

1.14 0.13 0.44

0.00 0.44 0.54

0.82

0.49

0.09

Lambda

8.26

21.80

0.71

Budget share of agricultural support in 2008 Constant Number of staff in 2002 Kampala-based Agricultural activities in 2002 Ranking of agricultural training by community in 2002 Years of existence Accounts audited externally in 2002 Farm support activities in 2008 Constant Number of staff in 2002 Kampala-based Agricultural activities in 2002 Community cited farm support activities as a need in 2002

73 52

Nr observations Censored observations Uncensored observations Wald chi2(9): Prob > chi2

21 0.0012

 Again the results show that the hypothesis of independence cannot be rejected. Wald tests on both reduced models of farming activities reject the null at the 1% level. The residuals do not appear to follow a normal distribution, suggesting it may be appropriate to consider nonparametric specifications. This is prioritised as a next step for this research.

25


6.3 What motivates NGOs to introduce new activities? We also undertake an analysis of the decision to undertake new activities. Focussing on the introduction of new activities should provide more scope for detecting opportunistic and strategic behaviour. However, Table 7 provides little evidence of such behaviour. Instead we see that older, more established and more professional NGOs introduce more services. Previous exposure to grants and the proportion of revenue represented by grants (not shown here) are not significant determinants of the number of services that were added to the NGO portfolio. Working in more districts has a negative activities, possibly suggesting that NGOs decide to either expand geographically within a smaller selection of services (specialisation) or serve a smaller set of communities via a number of services. TABLE 7: Tobit regression of the number of new activities introduced since 2002 by established NGOs Coef.

Constant Number of staff in 2002 Years of existence Years of existence squared Accounts audited externally in 2002 Constraints on decision-making NGO has received grant by 2002 NGO has a membership system Nr of districts where NGO worked in 2002 NGO has religious affiliation

-0.08 0.00 0.11 0.00 0.83 0.09 -0.56 -0.43 -0.08 -0.66

Robust Std. Err. 0.76 0.00 0.05 0.00 0.43 0.30 0.49 0.64 0.03 0.34

Sigma

1.86

0.19

Uncensored observations Left-censored observations

P>|t| 0.91 0.25 0.03 0.04 0.05 0.78 0.25 0.50 0.02 0.06

74 70

LR chi (x): Prob>F

0.049

Would this patterns be similar if isolate those services that experienced the increase in funding? Table 8 looks at the likelihood of introducing new activities relating to HIV/AIDS, health or agricultural support services. Here the proportion of revenue from grant is significant and positive, which will lend

26


some support to the view that the increased grant funding for these targeted area may have been a consideration for some. Conversely, NGOs with membership systems (and deeper roots in the community) were less likely to expand into these services. This variable was not significant in the previous regression model that considered all activities collectively. While professionalism still matters, we find that age does not. Given the complexity of interpreting these coefficients, none of these coefficients can present a convincing case for or against the main hypothesis on their own. However, viewed collectively, there appears to be some support for the anecdotal evidence suggesting that the promise of grant funding may have lured NGOs into these sectors. The results here are line with the Table 7: NGOs that work in more areas are less likely to expand their portfolio of activities. Also the table shows that NGOs that target the poor and NGOs with educated and committed managers (with no other employment) are more likely to introduce these activities. Although not shown here community needs re health and agriculture and past activities in this sector were not significant predictors of the introduction of activities in these sectors that have been targeted for additional funding.

TABLE 8: Probit for introduction of health activities, HIV/AIDS related activities or agricultural support services since 2002 by established NGOs Coef. Robust P>|z| std error Constant -2.04 0.96 0.03 Number of staff in 2002 -0.003 0.003 0.30 Years of existence 0.05 0.04 0.16 Years of existence squared 0.00 0.00 0.53 Accounts audited externally in 2002 1.21 0.64 0.06 Constraints on decision-making -0.23 0.46 0.62 NGO has received grant by 2002 -1.40 0.51 0.01 Grant as proportion of revenue 0.89 0.51 0.08 NGO has a membership system -0.64 0.39 0.10 Nr of districts where NGO worked in 2002 NGO has religious affiliation Target group is the poor Describes work as community development NGO manager involved with other NGO

27

-0.09 0.25 0.65 -0.38 0.25

0.05 0.32 0.33 0.40 0.34

0.07 0.43 0.05 0.34 0.47


NGO manager has other employment Manager's years of education Observations Pseudo R-squared Wald chi2(15): Prob > chi2

-0.76 0.16

0.34 0.09 109 0.27 0.056

0.03 0.06

6.4 What motivates new entrants to allocate resources to specific activities? To examine whether established NGOs and new entrants make decisions about which activities to pursue and how much resources to allocate to activities in the same way, we start by applying the model used to describe decision-making by established NGOs to new entrants. The comparison is problematic given that the original model was designed to consider the impact of persistence and these variables were often significant. We thus attempt a comparison but without two of the significant variables (age effect and the impact of prior involvement in the sector). Also, due to budget constraints we did not do community focus groups with the new sample of NGOs and therefore we do not have any indicator of community needs to include in the model. It is thus not surprising that we find that few patterns appear to be the same across established NGOs and new entrants. There are only two significant variables in the HIV/AIDS model of activity. The size variable (number of staff members) and having a Ugandan manager are significant in the determination of participation in HIV/AIDS activities for new entrants. However, this size variable was not significant in the decision-making of established NGOs and having a Ugandan manager was, but the coefficient sign was negative. Only one variable is significant for the farming support Heckman: having a Ugandan manager makes involvement in the farming support sector more likely. The latter was also significant in the decision-making model for established NGOs and had the same sign. We cannot reject the Wald test’s null hypothesis of equal coefficients at any reasonable level of confidence. Simultaneity bias may be a concern in this specification because we use 2008 variables as regressors in this model. However, most of the regressors can safely be assumed to be exogenous and there does not appear to be any obvious candidate variables prompting such concern. Misspecification is a greater concern and this model will need to be reconsidered and re-estimated. Tentatively, we find little evidence that established NGOs and new entrants make decisions regarding activities in the same way. More work is needed on the specification of models describing the decision-making of new entrants. 28


7. Conclusion We find some evidence that suggest that NGOs may have entered the targeted sectors opportunistically in the hope to procure funding allocated to these activities – or perhaps ex post after having secured funding for the activity or project. While some concern may be warranted, the analysis also shows that there is much persistence in the sector, which is congruent with a deeper commitment to serving the community through this specific activity. Also, we find little evidence of grants being a major factor in the introduction of other services – the Global Fund appears to be a special case. Normally the decision to expand their portfolio of services is a function of the organisation’s age, indicating that it may be part of the organisational life cycle. It is furthermore encouraging to see evidence of responsiveness to community need in HIV/AIDS services. Determinants of participation in a sector appear to depend on the sector in question. There are differences in the motivations in decision-making re NGO activities, both in the level and type of physical and human resources needed and the underlying motivations to carry out these activities. Interestingly, the decision and way NGOs engage in farm activities are highly influenced by manager’s personal decisions in particular motivations from the past have a causal impact on present service decisions. NGOs whose managers are farmers are more likely to be involved in providing agricultural support services. Also we find that Ugandan managers are more likely to venture into agricultural support services while foreign managers have a preference for HIV/AIDS related services. This supports the view that the mission of the NGO is heavily influenced by the interests, priorities and experiences of NGO manager. The results show that to adequately describe the decision-making mechanisms of NGOs re activities, we need a rich framework that takes account of the motivations of NGO managers and the priorities and interests of stakeholders. Similarly we also find that the budget share of an activity is not determined by the same factors across sectors. In HIV/AIDS related services experience appear to matter, while professionalism and formal status is important in agricultural support services. The analysis indicates that there may be a trade-off between expanding the portfolio of services and increasing the geographical coverage of the service. This may be attributable to distinct models of

29


specialisation: a NGO could either specialise within a service, delivering the same (presumably largely uncustomized service) to a large population of beneficiaries. The alternative model of specialisation would be to anchor the NGO within a specific set of communities and establish a strong relationship with these communities. Giving that the relative large cost of building a relationship with the community, travelling to the community and having a presence in the community, there may however also be a rationale to specialisation within a community and across services. The essence of this approach is that the value of the service to the community is dependent on its customisation to the preferences and needs of the community. The appropriateness of these two approaches will depend on the context and the community. It is for instance conceivable that specialisation across geographies are appropriate for certain services such as distributing wheel chairs (a core task for the NUDIPU which covers the entire country), while AIDS/HIV awareness training may be far more effective within a close and trusting relationship with the community There may be scope for extending this analysis with non-parametric estimators. Deaton (1998) identifies that the normality assumptions required for Heckman models in microeconometric analysis are incidental and can lead to large errors in model specification. Moreover heteroskedasticity, which is more than likely given the sources of measurement error in sample observations introduce further bias. Methods that generalise the Heckman two step procedure in a way that is distribution free (Newey, Powell and Walker 1990) and other semi parametric methods may provide ways to get more robust results.

References Aldashev, G. and Verdier, T. (2009), "The Goodwill Bazaar: NGO Competition and Giving Development", Journal of Development Economics, 1-16 Barr, A. and Fafchamps, M. (2006), "A client-community assessment of the NGO sector in Uganda", Journal of Development Studies, 42, 611-639 Barr, A. Fafchamps, M. and Owens, T. (2005), "The Governance of Non-Governmental Organizations in Uganda", World Development 33 No 4 , 657–679 Bilodeau, M. and Slivinski, A. (1997), "Rival Charities", The Journal of Public Economics 66, 449-467. 30


Burger, R. And Owens, T. Forthcoming. Promoting transparency in the NGO sector: Examining the availability and reliability of self-reported data. World Development.

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Macrae,J., Zwi, A. and Birungi, H. (1993) A healthy peace? Rehabilitation & development of the health sector in a post-conflict situation: The case of Uganda. London: London School of Hygiene and Tropical Medicine and Makerere University. Mocan, H. N. and Tekin, E. (2000.) “Nonprofit sector and part-time work: An analysis of employeremployee matched data of child care workers.” NBER Working Paper 7977. Moreira, M. (2001) “Tests with Correct Size when Instruments Can Be Arbitrarily Weak.” Working Paper 37. Berkeley: Center for Labor Economics, University of California. Morissey and Mc Gillivray (2000), "Policy Arena Aid Fungibility in Assessing Aid: Red Herring or True Concern", Journal of International Development 12, 413-428. Newhouse, J. (1970), "Towards a Theory of the Non Profit Sector", American Economic Review 60, 64-74 Newey, W.K., Powell, J.L. and Walker, J.M.. 1990. “Semiparametric Estimation of Selection Models: Some Empirical Results.” American Economic Review. May, 80:2, pp. 324–28. Owens, T. and Burger, R. (2009), "Receive aid or perish? Investigating survival prospects of African NGOs without grants", Mimeo. Pepall, L., Richards, D., Straub, J. And DeBartolo, M., 2006. Crowding Out and Competition in the Religious Marketplace. Mimeo. Parkhurst, J. and Lush, L. (2004), "The political environment of HIV: lessons from a comparison of Uganda and South Africa", Social Science & Medicine 59, 1913-1924. Rose-Ackerman, S. (1996), "Altruism, Nonprofits, and Economic Theory", Journal of Economic Literature 34, 701-728. Ruhm, C. J. and Borkoski, C. (2000), “Compensation in the Nonprofit Sector.” NBER Working Paper 7562. 32


Salamon L., Anheier H. and List R. (1996), The Emerging Nonprofit Sector: an Overview. Manchester: Manchester University Press. Salamon, L., Anheier, H., List, R., Toepler, S. and Sokolowski, S. (1999), Global Civil Society: Dimensions of the Nonprofit Sector, Baltimore: Johns Hopkins Centre for Civil Society Studies. Semboja, J. and Therkildsen, O. (1995), Service Provision under stress in East Africa: The state, NGOs and the People's organisations in Kenya, Tanzania, Uganda, Oxford: James Currey. Steinberg, R. (2006), "Economic Theories of the Non Profit Sector", In Powell, W. W. & Steinberg, R. The Non Profit Sector: A Research Handbook. New Haven: Yale University Press. Steinberg, R. and Weisbrod, B. (2005), "Non Profits with Distributional Objectives: Price discrimination and corner solutions", The Journal of Public Economics 89, 2205-2230. Veerbeek, M. (2008) A Guide to Modern Econometrics. New York: John Wiley and Sons.

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Appendix: Ugandan funding initiatives 2002 - 2008 Programme

Date

World Bank MAPs and other HIV projects

2001-2006

The Global Fund to Fight AIDS, Tuberculosis and Malaria

Round 1 2003

$26.2 Million Disbursed

Round 3 2005

$46.4 Million Disbursed

Round 7 2009

$70.2 Million Committed

The Unites States Presidents Emergency Plan for AIDS relief (PEPFAR)

FY 2004FY2008

$929.3 Million

Sector Wide Approach Health HIV prevention

2003-2007

7

Monies committed /disbursed $47.5 Million committed

$62.5 million $9.75 million

Implementation 1) Support the HIV control activities of the Uganda AIDS Commission 2) Support district activities in awareness prevention and treatment 3) Support civil society 1) Funds administered through a multisectoral 2) partnership: country coordination mechanism (CCM) 3) Principle recipient is the Ministry of Finance 4) NGOs and CBOs given approx 33% of resource allocation 1) National ownership of strategy 2) Multi sector approach including a large role for NGOs 3) Establish a network model to links link services communities and families 1) Bilateral donors finance ministry of health7

Table sourced from PEPFAR, MAPS and the Global Fund websites and 3rd round of Global Fund proposal documents

34

Money Mission or Need?: How Do Ugandan NGOs Choose Activities  

using a unique and representative panel survey of NGOs examine the activities NGOs engage in and the motivations behind these choices

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