The Governance of Nonprofit Organizations - SAGE Journals

The Governance of Nonprofit Organizations: Empirical Evidence From Nongovernmental Development Organizations in Spain Pablo de Andrés-Alonso Natalia Martín Cruz M. Elena Romero-Merino University of Valladolid

To verify the existence and relevance of control mechanisms that impede the expropriation of resources by the managers of nonprofits and that improve efficiency, we use a representative sample of Spanish nongovernmental development organizations (NGDOs). The authors study how the donors’ structure and board of trustees relates to organizational efficiency. Results show that the presence of an active institutional donor provides a control mechanism for these NGDOs, thus favoring the efficient allocation of resources, and that the structure of the board of trustees is irrelevant in this respect. Results are robust to alternative measures of technical and allocative efficiency. Keywords: nonprofit governance; board of trustees; nongovernmental development organizations; efficiency

Hansmann (1980) argued that “the non-distribution constraint,” the prohibition on distributing the benefits outside the organization that produces them, inspires confidence in consumers and donors by preventing internal agents’ opportunistic behaviors, such as reducing the quality of the products or expropriating resources. However, this constraint does not resolve other Note: We would like to express our gratitude to the three anonymous referees and V. Azofra, M. Espinilla, G. de la Fuente, M. García, J. W. Kuan, C. Mataix, P. T. Spiller, and A. Vernis for their helpful comments. Data collection for this research was possible thanks to the Federation of Spanish Nongovernmental Development Organizations, the Lealtad Foundation, the Spanish Agency for International Cooperation (AECI), the Protectorates of Spanish Foundations (Ministry of Education and Culture and Ministry of Social Affairs), and the Register of Public Utility Associations. Financial support by the Bank of Bilbao-Vizcaya-Argentaria Foundation is gratefully acknowledged. Any remaining errors are entirely our responsibility. Nonprofit and Voluntary Sector Quarterly, vol. 35, no. 4, December 2006 588-604 DOI: 10.1177/0899764006289765 © 2006 Association for Research on Nonprofit Organizations and Voluntary Action

588

Governance of Nonprofit Organizations

589

problems arising from the inability or impossibility of finding perfect agents who behave appropriately (Ben-Ner & Gui, 2003; Jensen, 1994). In fact, it is easy to speculate that the aspirations of the management team may differ from the general interest of the donor. Therefore, their decisions may also diverge from the initial objectives of the organization. Moreover, like those of all nonprofit organizations, managers and board members of nongovernmental development organizations (NGDOs) have a degree of autonomy that is unparalleled in the corporate world (Glaeser, 2003). Thus, although NGDOs are forbidden to distribute monetary dividends among the internal agents of the organization, managers can benefit from the nonprofit earnings through “perquisites,” such as the improvement of their working environment (Glaeser & Shleifer, 2001). The most recent academic work on nonprofit governance stresses that there are no effective external control mechanisms (Fisman & Hubbard, 2003; Glaeser, 2003; O’Regan & Oster, 2005), so that these organizations require internal governance mechanisms for their supervision. Therefore, in this article we focus on those mechanisms designed to monitor the NGDOs’ activities and to avoid the possible misappropriation of resources. Using the extensive literature on corporate governance as our starting point, we analyze the board of trustees as the major internal monitoring mechanism in nonprofits. The contractual literature suggests additional internal mechanisms that can complement the board’s tasks of control, such as large institutional public donors with the incentives and the necessary know-how to supervise the efficient allocation of its resources. Using a sample of Spanish NGDOs for the period 1995-2001, this article evaluates the role of boards of trustees and the oversight provided by large institutional donors. To begin our evaluation, we first examine the governance in nonprofits to propose verifiable hypotheses on the relation of governance and organizational performance. Next, we describe the design of the empirical research and then present our main results. Finally, we discuss our conclusions and the implications of the current study.

GOVERNANCE IN NONPROFIT ORGANIZATIONS During the past two decades, there has been much research on the mechanisms of corporate governance and their role in reducing agency problems between managers and shareholders in public companies (see the surveys of Hermalin & Weisbach, 2003; Larcker, Richardson, & Tuna, 2005). In most of these studies, scholars conclude that none of the external control mechanisms are as effective as the corporate control markets. The absence of external control mechanisms, or their limited success, makes clear the relevance of the internal controls. External mechanisms also exist in the nonprofit sector; however, their performance is no better than those of corporations. The United States Internal

590

Andrés-Alonso et al.

Revenue Service provides specific guidelines for the financial compensation of nonprofit executives. The intention is to ensure that the organization’s resources are used to achieve the stated mission; however, enforcing the regulations is difficult. Spanish regulations for the voluntary sector are less comprehensive (neither the Law of Foundations nor the Law of Association sets limits for the managerial compensations), so we cannot expect them to perform competently without being enforced in the courts. Because external control mechanisms are either lacking or ineffective, nonprofit organizations tend to return to self-governance. Internal control mechanisms, particularly those such as the board of trustees and large institutional donors, include those that ensure the appropriate behavior of participants in contractual relationships. BOARD OF TRUSTEES

In nonprofits, the equivalent of the corporate board of directors is the board of trustees. Its members are responsible for guiding the organization with care, skill, and integrity. Agency theory and contractual literature assert that there are features of the board (such as its size, composition, internal structure, and founders’ commitment) that help to guarantee the efficiency of the nonprofit organizations (Callen, Klein, & Tinkelman, 2003; Herman & Renz, 2000, 2004). In what follows, we examine these elements. Size. The empirical literature on for-profits notes that too many board members cause problems of communication, coordination, and decision making that lead to less efficient managerial monitoring (Eisemberg, Sundgren, & Wells, 1998; Yermack, 1996). These problems also occur in boards of trustees (Callen et al., 2003; O’Regan & Oster, 2005). Therefore, we propose: Hypothesis 1: An oversized board of trustees will be associated with negative NGDOs’ efficiency. Composition. We distinguish between two different elements in the composition of the board: the number of outsiders, that is, those members who do not participate in the functioning of the organization, and changes in the board. Although the presence of some insiders with specific knowledge about the functioning of the organization may be necessary for optimal strategic decision making (Baysinger & Hoskisson, 1990; Bhagat & Black, 1998), outsiders provide a level of independence essential for monitoring managerial activity, not only in for-profits (Baysinger & Butler, 1985; Rosenstein & Wyatt, 1990) but also in nonprofits as well (O’Regan & Oster, 2005). Thus, we propose: Hypothesis 2: A high presence of outsiders in the board of trustees will be positively related to the NGDO’s efficiency.


591

Rotation of board members. We assume that when some members leave the board, especially if they are insiders, the board loses some specific knowledge that is difficult to replace (Gispert, 1998; Rosenstein & Wyatt, 1990). The excessive rotation of trustees reveals a weakened board that usually results in ineffective monitoring (Brudney & Murray, 1998; Eldenburg, Hermalin, Weisbach, & Wosinska, 2004). We propose: Hypothesis 3: Increasing changes in the members of the board of trustees will be negatively related to the NGDO’s efficiency. Executive committees. The internal structure of the board can be modified by the use of executive committees and by the number of meetings of these committees per year. Even though philanthropic organizations are less complex than corporations, an executive committee is a simpler way to make outsized boards operative (Brudney & Murray, 1998; Houle, 1989). We propose: Hypothesis 4: Boards that delegate part of their functions on an executive committee will be associated with positive NGDO’s efficiency. Board meetings. Studies such as that by Brudney and Murray (1998) note that trustees who do not attend or participate in board meetings are an indication of governance problems. We propose: Hypothesis 5: The number of board meetings is positively related to the NGDO’s efficiency. Founders’ commitment. We examine the founders’ commitment as a signal of fidelity to the original organizational purposes and as the distinctive motivation for controlling managerial activity. We propose: Hypothesis 6: The founders’ presence in the board of trustees as a voting member is positively related to the NGDO’s efficiency. INSTITUTIONAL DONORS

The characteristics of boards that we describe above are related to the ownership and control structure of the firm. Such forms of ownership either hinder or favor the monitoring function of boards. Even though nonprofit organizations do not have legal owners, we can nevertheless identify some other constituencies, mainly large donors, that are significantly interested in the efficient use of the NGDO’s resources. In terms of motivating control, the donation structure of a nonprofit is analogous to the ownership structure of a for-profit firm.

592


The presence of active donors who provide the organization with large quantities of resources may favor the monitoring of manager behavior. In NGDOs, public institutional donors have enough power and access to information to become efficient monitors (Frumkin & Kim, 2001; Herman & Renz, 2000; O’Regan & Oster, 2002) because these donors usually demand detailed plans, financial budgets, and information on each project they finance (Frumkin & Kim, 2001). Therefore, we propose: Hypothesis 7: The presence of active donors in the NGDO, especially public institutional donors, will be positively related to the NGDO’s efficiency. METHOD SAMPLE

NGDOs channel public and private resources to projects in developing countries, thus complementing the work undertaken by governments and international organizations (Spanish Law on International Cooperation, 23/1998, Section 32). The importance of NGDOs is unquestionable: During the past 15 years, there has been an increase of 56% in the number of NGDOs operating in the Organization for Economic Cooperation and Development (OECD) countries, and a nearly 200% increase in the number of NGDOs in the developing countries. Beginning in the 1980s, in a cooperative effort among the OECD countries, a program was developed to cofund NGDOs’ projects, assuming there would be large growth globally in the amount of funds collected by NGDOs that could be used to help developing countries. In Spain, these organizations are among the most dynamic in the third sector, managing resources of more than €500 million per year. Almost 60% of those funds are public, coming from the national government, regional governments, or the European Union. The rest of the funding comes from small private donations. To test our hypotheses, we use a representative sample of NGDOs that comprises all the NGDOs registered in the Federation of Spanish NGDOs.1 To create a homogeneous group of organizations, the government required NGDOs to have a concrete legal form (foundations, associations or public utility associations). To qualify for tax exemptions, the NGDO can change its legal form of ”association” into that of a “public utility association.” This status also gives the authorities greater control over the organization and activities of the NGDO. VARIABLES

To collect the information on governance and performance from the 41 organizations, we studied the directories of the Federation of Spanish NGDOs


593

and part of the official data compiled in the public registers for the period 1995 to 2001 (Table 1). We use the first group of variables, the efficiency of these NGDOs, to evaluate their performance according to their compliance with their mission and objectives at a minimal cost. However, defining what efficiency means for a nonprofit is not easy. Nevertheless, by slightly changing the focus of nonprofit performance from the inside of the organization to the donors’ point of view, we are able to obtain a simple and reliable index. By following previous nonprofit studies (Callen & Falk, 1993; Frumkin & Keating, 2001; Sargeant & Kaehler, 1998) and some watchdog agencies, such as Better Business Bureau’s Wise Giving Alliance and the American Institute of Philanthropy (Trussel & Parsons, 2004), we found that the donors’ principal concern is the average portion of each contribution dedicated to the principal organization’s mission. Selecting the most commonly applied proxies for financial efficiency, we use the technical efficiency (EFFIC1) approach, which we define as the quotient of administrative expenses and total costs, and allocative efficiency (EFFIC2), measured by direct project expenses as a percentage of total donations. For the technical efficiency measure (EFFIC1), a low value indicates a good result. For the allocative efficiency measure (EFFIC2), a high value indicates a good result. On average, 87% of the donations received are used directly in projects, whereas the remaining 13% covers administrative costs, publications, training, and fund-raising (Table 2). The internal control mechanisms in this model—the second group of variables—represents, on one hand, the “best practices” of the board in terms of size (SIZE), composition (OUTS and ROTAT), internal structure (MINMEET and EXCOM), and commitment of its members (FUND). On the other hand, it represents the percentage of an active institutional donor in the finance of the NGDO (AECI, EU, and RG) (Table 2). Because of the disparity of the data, we include board size (SIZE) measured by the number of members in the model by using the logarithm expression (LSIZE). Therefore, the average board size, 13 trustees, cannot be taken as an accurate measure for the sample because of the disparity of the data (Table 2). For board composition, we include two concepts, members’ independence (OUTS) and their rotation (ROTAT), measured respectively by the proportion of outsiders on the board and the proportion of members who change each year compared to the total number of board members. To evaluate the independence of a trustee (OUTS), empirical studies distinguish between inside and outside members depending on how their work relates to that of the organization (Byrd & Hickman, 1992; Weisbach, 1988) and their pay as directors (Callen & Falk, 1993; Callen et al., 2003). Because no trustee of a Spanish NGDO is allowed to receive any kind of salary (except reimbursement for some specific expenditures related to their board responsibilities), we use only the information related to their work with the NGDOs.

594 AECI RG EU AGE LAGE EMPL LEMP REMUNa VOLUNTa FUN APU

Public active institutional donors

Legal condition

Employees

Age

FUND

LMEET

MINMEET

EXCOM

ROTAT

EFFIC1 EFFIC2 SIZE LSIZE OUTS

Founder in the board

Internal structure of the board

Composition of the board

Technical efficiency Allocative efficiency Size of the board

Abbreviation

Variables Definition Operating costs / total costs Costs of projects / total donations Number of members in the board of directors (SIZE) Logarithm of the number of trustees in the board Number of outsiders in the board / total number of trustees in the board Sum of new members entering the board and old members leaving the board in year t / total number of trustees in the board in year t-1 1: NGDO’s legal statutes establishes an executive committee; 0: NGDO does not establish any committee statutorily Minimum number of board meetings established in NGDO’s legal statutes Logarithm of the minimum number of board meetings statutorily established 1: NGDO’s founder is a member of the board; 0: NGDO’s founder is not a member of the board Total AECI donations / total donations Total regional governments donations / total donations Total European Union donations / total donations Yeari – year of foundation Logarithm of the age variable Number of employees Logarithm of the number of employees Number of remunerated employees Number of voluntary people in the NGDO 1: foundation; 0: the rest of legal forms 1: association or federation declared of public utility; 0: the rest of legal forms

Note: NGDO = nongovernmental development organization; AECI = Agency for International Cooperation. a. These two variables are not used to define the model but are included as descriptive features of the sample.

Control variables

Control mechanisms

Efficiency

Variables

Table 1.

Governance of Nonprofit Organizations Table 2.

EFFIC1 EFFIC2a SIZE LSIZE OUTS ROTATb MINMEET LMEET EXCOM FUND AECIc RG EU AGE LAGE EMPL LEMP REMUN VOLUNT FUN APU

595

Descriptive Statistics

M

SD

Minimum

Maximum

.0830 .8691 13.3306 2.4182 .9183 .1545 2.9669 .8726 .4008 .7149 .2612 .2091 .1149 14.7107 2.3675 529.9546 4.8231 164.9318 365.7479 .4132 .3099

.0582 .1507 8.4115 .5820 .1278 .2293 2.5440 .6385 .4911 .4524 .2363 .1712 .1821 16.2562 .7995 1,620.7344 1.4764 561.6518 1,512.8018 .4934 .4634

.0000 .1178 3.0000 1.0986 .3333 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 8.0000 2.0794 .0000 .0000 .0000 .0000

.3649 1.4754 45.0000 3.8067 1.0000 1.4000 12.0000 2.4849 1.0000 1.0000 1.0000 .7603 .7763 133.0000 4.8904 15,375.0000 9.6405 5,836.0000 1,529.0000 1.0000 1.0000

Note: EFFIC1 = technical efficiency; EFFIC2 = allocative efficiency; SIZE = size of the board; LSIZE = logarithm of number of trustees in the board; OUTS = number of outsiders in the board / total number of trustees in the board; ROTAT = sum of new members entering the board and old members leaving the board in year t / total number of trustees in the board in year t – 1; EXCOM = executive committee; NGDO = nongovernmental development organization; MINMEET = minimum number of board meetings; LMEET = logarithm of the minimum number of board meetings; FUND = founder in the board; AECI (Agency for International Cooperation) = total AECI donations / total donations; RG = total regional governments donations / total donations; EU: total European Union donations / total donations; AGE = yeari – year of foundation; LAGE = logarithm of the age variable; EMPL = number of employees; LEMP = LOGARITHM of the number of employees; REMUN = number of remunerated employees; VOLUNT = number of voluntary people in the NGDO; FUN = foundation; APU = association or public utility. a. The maximum value of EFFIC2 is 1.4754 because some NGDOs have more cost in projects than incomes. b. The maximum value of ROTAT can be more than a unit because of formula we use. There is the possibility of a complete change of the board followed by an enlargement. c. There are some NGDOs that are completely financed by AECI subventions, which is why the maximum proportion takes a value of 1.

Spanish NGDOs’ boards mainly comprise independent trustees; on average, more than 90% are outsiders (Table 2). For the variable ROTAT, we introduce the proportion of trustees that change each year as a concept directly related to the board independence (Eldenburg et al., 2004). In our sample, the average rotation is about the 15% (Table 2).

596


In the current study, we use the minimum number of board meetings established by the NGDO statutes (MINMEET). The average number for our sample is about 3 (Table 2), although the high dispersion of the data requires us to utilize its logarithm (LMEET). For committees, because of the idiosyncrasy of the sample, we studied only the existence of an executive committee (EXCOM) as statutorily recognized. We find that almost 60% of the Spanish NGDOs lack any kind of committee (Table 2). The last variable linked to the board is a dummy that indicates the presence of the founder in board meetings (FUND). Nearly 72% of a Spanish NGDO’s founders either attend meetings or continue their guidance through direct agents (Table 2). Finally, we evaluate the active role of institutional donors. As we note, the majority of funds comes from three public institutions: European Union (EU), the Spanish Agency for International Cooperation (AECI), or Spanish regional governments (RG). Approximately 59% of NGDOs’ funds are public, a percentage that highlights the role of national institutions. Indeed, the Spanish agency contributes 26% of the funds that the NGDOs of our sample handle. The rest of their funding comes from private individuals and firms (Table 2). We measure the weight of each institutional donor (EU, AECI, or RG) as a percentage of the total donations. We also include NGDOs’ age (AGE), size (EMPL), and legal status (FUN and APU) as control variables that may influence the level of organizational efficiency (Table 1). We control for the size and age of the NGDO. Both factors can be considered as a measure of reputation, legitimacy, and experience. Older and bigger NGDOs are supposed to be able to generate the synergies and knowledge that will improve their performance and efficiency (Marcuello & Salas, 2001). We measure the size of the NGDO by the number of voluntary and remunerated workers (EMPL), and its age by the number of years since the NGDO was created (AGE). We introduce both variables in logarithms to avoid distorting effects derived from their measurement and dispersion (LAGE and LEMP). Table 2 shows that the average age in our sample of NGDO is almost 15 years. The mean number of workers is 530, of whom 365 are voluntary (VOLUNT) and 165 salaried workers (REMUN). We also introduce the NGDOs’ legal status through a dummy control variable that distinguishes between a foundation (FUN) and an association (APU).2 The sample comprises 40% foundations and 30% public utility associations (Table 2). The remainder of the sample is associations (without public utility). EMPIRICAL MODEL

We formulate the empirical model by taking into account the behavioral processes described in the theoretical section above. For each NGDO, we collect


597

data for each of the variables described above. We estimate the following model: EFFICit = α + β1 LSIZEit + β2 OUTSit +β3 ROTATit + β4 EXCOMit + β5 LMEETit + β6 FUNDit + β7 AECIit + β8 RGit + β9 EUit + β10 LAGEit + β11 LEMPit + β12 FUNit + β13 APUit + µit where i represents the NGDO (from 1 to 41) and t the temporal period (from 1995 to 2001). EFFIC is the efficiency measure of each NGDO; LSIZE, OUTS, ROTAT, EXCOM, LMEET, and FUND are the variables related to the board characteristics; AECI, EU, and RG are the variables referring to the institutional donors; and LAGE, LEMP, FUN, and APU are the control variables. We estimate the model by using the econometric program TSP Version 4.3A for panel data. When we use information about the same organizations during the same period of time, each organization contributes multiple observations to the panel that are dependent on one another. In these cases, unobserved heterogeneity is always a potential problem (Petersen & Koput, 1991). Thus, to address these problems of unobserved heterogeneity, specific econometric programs for panel data such as TSP introduce additional firmspecific error terms that are either fixed over time for each firm (fixed-effects models), or that vary randomly over time for each firm (random-effects models; Sayrs, 1989). This technique allows us to consider the unobservable and constant heterogeneity, such as reputation, manager quality, operational procedures of the cooperation programs, and so on, and examine the response processes over time (Arellano, 2003). The econometric program TSP permits us to identify which effects—fixed or random—define each model. Initially, by using an F test in which the null hypothesis sustains the absence of any fixed or random effects on the variables, we can assess if the data follows a simple linear regression for the whole period that we estimate. Then, if the null hypothesis cannot be rejected, we can estimate the model by ordinary least squares. However, if the null hypothesis is rejected, we must then evaluate which effects best describe the model. We do this by using a Hausman test (based on a chisquare) in which the null hypothesis implies that the random effects define the model better than do the fixed effects. If this last test rejects the null hypothesis, we must use the fixed effects model. On the contrary, if it does not reject the null hypothesis, we must use the random effects model.

RESULTS Tables 3 and 4 show the results of the estimated model. In this model, we use technical efficiency and allocative efficiency as dependent variables. To obtain robust results, we first estimate a basic model (Model 1) by including

598


only those variables that are related to board characteristics (LSIZE, OUTS, LMEET, EXCOM, FUND and ROTAT) and institutional donors (AECI, EU, and RG). Next, we sequentially include each one of the control variables formerly described: size (Model 1 with LEMP), age (Model 1 with LAGE), and legal form (Model 1 with FUN-APU). Finally, we develop a complete model (Model 2) that contains the complete set of variables. When we examine the empirical results from the estimations of the models for the selected sample, we identify two essential findings. First, we see that the main internal mechanism of the nonprofit entities—the board of trustees—displays very different effects that depend on which measure of efficiency we use. Second, only a particular institutional public donor, the Spanish Agency for International Cooperation, maintains its effectiveness as a control mechanism for technical and allocative efficiency. When we examine the results related to the role of the board of trustees, we observe clear differences between the two measures we use for the NGDO’s efficiency. Although changes in board characteristics such as its size, independence, and activity have a significant consequence on allocative efficiency (Table 4), every effect disappears when we refer to technical efficiency (Table 3). As we predicted in Hypothesis 1, large boards (LSIZE) have a negative effect on the nonprofit’s efficiency when we measure efficiency by the percentage of funds spent directly on development projects (Table 4). We cannot make the same statement when referring to the technical efficiency. Oversized boards do not increase the administrative costs related to the total costs (Table 3). Hypothesis 2 is also verified for the allocative efficiency. We observe that trustees’ independence (OUTS) results in favorable nonprofit performance in terms of the proportion of resources spent on the NGDO’s projects (Table 4). Again, we cannot affirm that a board with a high number of outsiders results in a low percentage of administrative costs (Table 3). This result can be explained by the large cost of keeping the outsiders (vs. insiders) correctly informed about the activities of the NGDO. Regardless of which efficiency measures we use, we cannot verify either Hypothesis 3, which concerns the board member changes, or Hypothesis 4, which relates to the delegation of power on an executive committee. When we examine the number of meetings (LMEET), the relation is significant, although it is the opposite of what we expected. Thus, we cannot confirm Hypothesis 5. This effect may be related to the reactive role of the board, so that when efficiency decreases, the number of meetings increases. Finally, in Hypothesis 6, we outlined the commitment of the board members with the NGDO’s mission. However, we cannot confirm this hypothesis following the results of our model estimation (Tables 3 and 4). As we have noted, all the assertions we have been able to make can only be drawn from the allocative efficiency shown in Table 4. None of the characteristics of the board is significantly related to technical efficiency. In

Governance of Nonprofit Organizations Table 3. EFFIC1 (Technical Efficiency AECI EU RG LSIZE OUTS LMEET EXCOM FUND ROTAT LEMP LAGE FUN APU C N F test (p value) Hausman test (p value) R2

(1) Model 1 –.0391** –.0040 –.0105 –.0063 .0492 .0003 .0040 –.0161 –.0019

599

Results of the Model Estimation (EFFIC1) (2) Model 1 with LEMP

(3) Model 1 with LAGE

(4) Model 1 with FUN and APU

–.0385** –.0037 –.0104 –.0062 .0480 –.0002 .0036 –.0164 –.0019 .0014

–.0390** –.0032 –.0102 –.0067 .0478 .0001 .0039 –.0162 –.0019

–.0385** –.0022 –.0119 –.0040 .0393 .0010 .0022 –.0188 –.0005

.0013

(5) Model 2 –.0372** –.0028 –.0124 –.0028 .0386 .0007 .0017 –.0192 –.0004 .0025 –.0024 .0197 .0155* .0601

.0756**

.0702*

.0751**

.0184 .0144* .0689*

242

242

242

242

242

.0000

.0000

.0000

.0000

.0000

.5400

.6467

.2877

.1880

.2206

.5429

.5427

.5442

.5450

.5444

AECI (Agency for International Cooperation) = total AECI donations / total donations; EU: total European Union donations / total donations; RG = total regional governments donations / total donations; LSIZE = Logarithm of the number of trustees in the board; OUTS = Number of outsiders in the board / total number of trustees in the board; LMEET = logarithm of the minimum number of board meetings; NGDO = nongovernment development organization; EXCOM = NGDO’s legal statutes established an executive committee; FUN = foundation; ROTAT = sum of new members entering the board and old members leaving the board in year t / total number of trustees in the board in year t - 1; LEMP = logarithm of the number of employees; LAGE = logarithm of the age variable; FUN = legal condition; APU = association or public utility; C = constant term of the regression. In the regression, the Hausman test does not reject the hypothesis of no correlation between the individual effects and the independent variables, so that the most efficient estimation is the random effects one. * p < 0.10, ** p