Analysis of the Main Results

The results that arise from the Module of Voluntary Work included in the EAH 2010[1] enable the analysis of different features corresponding to voluntary actions, articulating them with diverse sociodemographic variables and the activity status of volunteers referring the labor market.

This set of data permits us to infer that 5.9 % of the population of the City of Buenos Aires did voluntary work in the month before the Survey took place. If we add the number of individuals that did voluntary work during the previous year but not the month before, we can estimate that approximately 7 % of the population of the City of Buenos Aires did voluntary work during the year 2010. This fact replicates trends that were identified both by the National Survey of Household Spending, 2005, which was carried out by the National Board of Statistics and Census (INDEC), and by a survey done in the City of Cordoba, Argentina in 2011 by the Center for the Study of State and Society (CEDES).

These percentages look very distant from the ones gathered in the VOICES! (2013) -TNS-Gallup survey (1997, 1998, 2000) . Due to the fact that TNS-Gallup is the company that provides annual information on the situation of volunteerism in Argentina, it is important to focus on some aspects already pointed out that differentiates both kinds of measurements and, at the same time, to build hypotheses that could be verified in future research.

A first aspect to consider is the fact that the Voluntary Work Module was part of the City Annual Household Survey. One of the main goals of this Survey is to detect the labor market status of the interviewees (employed/unemployed). A second aspect to take into account is the use of the expression “voluntary work” which can generate in the interviewee an image that bears a resemblance to an activity with a certain degree of organization, which is implicit in the notion of “work.” Finally, we should reflect on the heterogeneity of measurements: both surveys embrace two distinct populations since the survey TNS-Gallup is of national scope whereas the one taken as data source for this chapter is local.

The fact that the Voluntary Work Module is part of a survey that intends to capture living conditions and labor market insertion might have resulted in an underestimation of informal volunteering, that is to say, volunteering performed outside CSO or State-owned institutions.

Another issue to take into account is that the percentage of the population carrying out voluntary work could be smaller in the City of Buenos Aires compared to the estimates in the rest of the country. We can find some sort of evidence in a recent publication that reports on figures of volunteerism in Argentina during 2015 (Cilley, 2015). In this work, based on the VOICES!-TNS-Gallup survey,[2] we can spot two key elements: the survey asks about “voluntary chores” instead of “voluntary work,” the latter being the expression used by EAH. Additionally, the results show that volunteers in the city represent 14 % of the population, whereas in the Greater Buenos Aires the percentage is 19 % and reaches 28 % in the rest of the country, doubling the figures of Buenos Aires City.

Regarding that, it could be very useful to quote the caveats stated by Gilbertson and Wilson (2009) about the influence of some words in the questionnaire devoted to measure social participation and volunteering at local level.

Our comparison of questions measuring levels of participation in groups and organizations in the GHS (General Households Survey) and adapted in the South Yorkshire Survey, indicates how even small differences in the questioning methods and wording employed, influences the data collected and affects data comparability (...) A recent briefing produce by nfpSynergy[3] criticizes the Government's definitions of volunteering and civic participation employed in the Citizenship Survey and argues that they over estimate levels of volunteering. Whether their claims are well founded or not, debate around the boundaries of what constitutes volunteering raises questions about what is actually being measured and muddies the water when it comes to assessing how effective investment aimed at increasing levels of volunteering may be.

Reinforcing this idea Jonathan Baker, nfpSynergy’s researcher, said:

Government’s current Citizenship Survey over-estimates the number of volunteers in England and Wales—which may well mask a failure to increase levels of volunteering, despite the Government’s focus on, and high level of investment in, this area. Much of what the Citizenship Survey measures is not what most people would intuitively mean by volunteering. Tighter, more intuitive definitions are needed to uncover true volunteering levels; and to better plan and evaluate relevant Government strategy. Much good work is done in volunteering but, unless we can measure it properly, future investment could be misdirected.”[4]

To add to what has been pointed out, there is an element that arises from Cilley’s work that refers to the evolution of values reached by volunteerism through a temporal series that ranges from 1998 to 2015. Figures between the years of 2008 and 2015 show a certain lability, since the volunteer percentage at national level in 2008 reaches 19 %, in 2010 22 %, in 2012 goes down to 15 %, in 2013 it suffers another reduction to 13 % and in 2015 goes up again to 23 %. We believe that this lability is an indication of the difficulty in capturing this phenomenon in a consistent manner through a determined period of time when using instruments such as omnibus surveys. Although they are a useful tool with a positive cost-benefit outcome, they should be taken as a database not to rigorously measure volunteerism but to broadly illustrate the public on its importance.

The differences between the figures of the City of Buenos Aires compared to the rest of the country unfold the need to carry out a study on a national level using the Household Survey at a national scale in order to achieve a point of reference with better statistical precision.

Bearing in mind these clarifications, we continue with the introduction of data from EAH. An expansion of the sample calculated by the statistical office of the Buenos Aires city government, reached the number of 169,826 volunteers, almost 75 % (127,898) of them stated that they had carried out volunteer activities during the previous month (Fig. 9.1).

The average time devoted is 6.8 h per month, the result being a total of 871,770 h per month of work contributed by these volunteers. The total amount of hours that volunteers devote per month can be transformed into “full-time equivalent employees”, so that it can be estimated that civil society organizations in the City of Buenos Aires have an asset of voluntary effort equivalent to the full-time work of 5200 persons per month.

Of the total, 58.9 % perform voluntary work permanently and systematically, this percentage reflects the intensity of the commitment these social actors take on (Fig. 9.2).

In the Communes with a certain predominance of middle-class and upper middle- class households, we can observe a greater presence of stable volunteers. In the City of Buenos Aires, the relationship between social class and volunteerism does not show a clearly defined pattern although there is preliminary evidence that show a greater tendency to undertake activities that social actors perceive as “voluntary” in areas where there are reduced levels of poverty. Consequently, we could be in the presence of a phenomenon that shows a general degree of correlation with the economic status of interviewees and/or with the preconceived perceptions on the scope of the expression “voluntary work.’ ’ However, the hypothesis on the relationship between the relationship between social class and volunteerism has some degree of support in VOICES!-TNS-Gallup 2015 Volunteering Survey. As it can be deduced from this source, voluntary participation decreases in accordance with the drift from higher socioeconomic sectors to lower ones. We will elaborate on these aspects below.

Despite of the facts we have commented before, it has not been possible to establish a statistically solid correlation in between the total distribution of the volunteers in their respective Communes of residence and the levels of standard income that characterize them. That is to say, it is not possible to associate in an unequivocal manner a higher propensity to voluntary work to any socioeconomic strata.

However, it may not be concluded that the volunteers are distributed in a relatively equivalent way in the different Communes. Even though there is heterogeneity, there is also a slight relationship in between income levels and the density of the volunteers (number of volunteers per 1000 inhabitants). This tendency is particularly valid for the extremes of the standard income levels that exist per Commune. Thus, the higher density of volunteers in the two communes that have the highest income levels and inversely the communes that have lower income levels are also those with a lower proportion of volunteers. Thirty-one percent of the volunteers reside in the three Communes with the highest standard income level, a fact that

Fig. 9.1 Volunteers by length of observation window. Source: Buenos Aires Annual Survey (2010)










Last year


















Fig. 9.2 Volunteers by periodicity. Source: Buenos Aires Annual Household Survey (2010)

broadly indicates a certain link between the place of residence, in this case urban areas that are generally considered “middle class” (Lago, Mazzeo, Rivero, & Zino, 2012, p. 62) and the density of volunteers.

Almost two-thirds of volunteers are up to 50 years of age (Fig. 9.3). The majority of the volunteers are in the age group of 22-50 (51.6 %), this means that there is a higher proportion of volunteers in this age frame compared to the proportion that involves the total population (45.2 %). If we group the older age clusters (61 years old or more), we can verify that this segment of the population represents 22.1 % of volunteers since it represents 20.4 % of the whole city population. The difference between each percentage is small, that is why it cannot be said that there is a significant interest in volunteering in the group of senior citizens.

The mean of the distribution is 43.8 years and the median of the population who did the volunteering work is 42. The proximity between the mean and the median implies a kind of distribution not affected by outliers. In fact, three ranges (22-30, 31-40, and 41-50) have a similar proportion of volunteers and due to evidence it is plausible to consider a sort of quasi-normal distribution of frequency.

Almost two-thirds of volunteers are women (64.4 %), a similar number to the one obtained from other methodology implemented in 2005. In that case, a significant number of women, over 65 % was detected. This predominance was verified in all types of voluntary activities, particularly in health and social services. These numbers eloquently show the feminization (Serna, 2010) of the tasks they do (i.e., caring and feeding), as a persistent sign in the philanthropy field in Argentina (Gonzalez Bombal, Roitter, & Vivas, 2006).

The identification of the characteristics of the type of household where the person who does the volunteering activities resides shows one of the analytical potentialities that the Annual Household Survey (EAH) classification methodology provides. In this case, it allows connecting the voluntary work with the household positioning in the social structure and other demographic and socioeconomic characteristics. It can be observed that 51.2 % of the people that state they do volunteering work live in a “standard” household (Nuclear with full family core).

Data from EAH also help us compare the distribution of volunteers and nonvolunteers according to the type of household they belong to. If we compare both

Volunteersbyage. Source

Fig. 9.3 Volunteersbyage. Source: Buenos AiresAnnualHouseholdSurvey (2010) and Argentina National Population Survey (2010)

groups, we notice that standard family configurations (Nuclear with full family core) have a very high presence in the total number of volunteers (53.1 %). This presence is higher than the proportion of this kind of families among the whole population of nonvolunteers (45.4 %).

If we group together both nuclear with complete and incomplete family core, we discover that almost two-thirds of the volunteers (64.6 %) come from both categories, whereas these categories comport 56.1 % among nonvolunteers. On the contrary, Single Household category is less represented in the group of volunteers (22.6 %) than it is represented in the nonvolunteers universe (30.6 %). We could state that individuals that live alone are less inclined to participate in volunteer activities (Fig. 9.4).

It is important to point out that practically two-thirds (65.3 %) of the volunteers appear as employed in the labor market (Fig. 9.5). Also significant is the number of volunteers that are inactive (mainly nonworking students and retirees).

Among the employed who carry out voluntary work, the percentage of salaried employees is the highest followed by self-employed workers. In the same way, this pattern mimics the structure of the whole occupied population. The only element that stands out is that there is a higher proportion of self-employed workers performing as volunteers (25 %) when compared to the number of self-employed in the total population (19 %) (Fig. 9.6).

Volunteersbytypeofhousehold. Source

Fig. 9.4 Volunteersbytypeofhousehold. Source: Buenos Aires Annual Household Survey (2010)

Volunteers by activity status/activity condition. Source

Fig. 9.5 Volunteers by activity status/activity condition. Source: Buenos Aires Annual Household Survey (2010)

This data might qualify what was previously pointed out on the relationship between socioeconomic level and voluntary activities, since the category “Boss or employer” presents a similar percentage between volunteers (7.3 %) and the total population (7.7 %).

Of the total of the registered volunteering activities, taking into account both reference periods (the last month and the previous year), 28.4 % corresponds to those channeled through religious entities, followed in importance by those developed in Social Services (19.4 %) and Philanthropic Intermediaries (17.1 %) (Fig. 9.7).

In spite of the fact that in all Latin American countries religious organizations have a central role in gathering volunteers (Butcher, 2009; Landim & Scalon, 2000; Sandborn et al., 2006; Verduzco, 2003), this matter requires further study since religious institutions set in motion volunteerism that can be devoted to tasks that are outside the religious and sacramental activities per se, for example, education, health, or social services. The influence that religious entities, especially the Roman Catholic Church, has had on diverse social issues and its capacity to attract volunteers would require a more specific analysis which is beyond the scope of this chapter.

Volunteers by occupational category. Source

Fig. 9.6 Volunteers by occupational category. Source: Buenos Aires Annual Household Survey (2010)

  • [1] The figures in absolute values correspond to the sample expansion of the data from the population-based survey.
  • [2] TNS-VOICES is a local branch company associated to Win-Gallup International. See Accessed February 2, 2016.
  • [3] nfpSynergy is a UK research consultancy organization, devoted to the charity sector and not-for-profit issues. See Accessed February 2, 2016.
  • [4] See Accessed February 2, 2016.
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