Abstract
This chapter brings new data to bear on the long-standing question of whether apparent North–South disparities in rates of volunteering result from the widespread failure to take account of direct, as opposed to organization-based, volunteering in most official volunteering surveys. To do so, it first outlines some of the misconceptions, definitional obstacles, and methodological glitches that have afflicted efforts to measure volunteering cross-nationally in the past. It then outlines the considerable progress that has been made by international statistical authorities to remedy these problems. Finally, it brings new data to bear on the question of whether apparent North–South disparities in volunteer effort disappear once direct volunteering is brought into the picture. Ultimately, the conclusion that emerges is that when both organization-based and direct volunteering are taken into account, the total amount of volunteer work that becomes visible is massively increased and the absolute disparities in the amount of volunteer work between better-off and less-well-off countries narrows. But the relative disparities in volunteering rates remain stubbornly unmoved. The article suggests that this may have more to do with volunteering overperformance on the part of well-off country residents than any volunteering underperformance on the part of less-well-offcountry residents.
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Notes
- 1.
Regular surveys of formal volunteering carried out through organizations are currently conducted by the statistical offices of Australia, Canada, the United Kingdom, Switzerland, Norway, Germany, and the United States. A new Manual on the Measurement of Volunteer Work, developed by a technical experts group under the leadership of the Johns Hopkins Center for Civil Society Studies with support from United Nations Volunteers and issued by the International Labour Organization, calls on countries for the first time to measure direct as well as organization-based volunteering and provides a consensus approach for doing so. This Manual is available for adoption by countries and can be downloaded at: http://www.ilo.org/stat/Publications/WCMS_162119/lang—en/index.htm. A discussion of this new Manual is presented in the third section of this chapter.
- 2.
Following 2001, the questions about membership and volunteer work in voluntary organizations were replaced with one about active and inactive membership in voluntary organizations.
- 3.
For example, the question asking whether respondents helped a stranger or someone they didn’t know who needed help could be interpreted by respondents as entailing anything from providing hours of assistance to incidental acts, such as giving someone directions on the street. Likewise, questions about whether respondents volunteered time to an organization may entail compulsory community service required as a condition of graduation or mere attendance at events (such as religious services).
- 4.
The 2011 ILO Manual set the boundary for in-scope volunteer work at the household level, but the 19th ICLS Resolution extended this boundary to include also unpaid work done for related family members. See: 19th International Conference of Labour Statisticians, “Resolution I: Resolution concerning statistics of work, employment and labour underutilization,” October 2013.
- 5.
The internationally accepted minimum period of time in labor statistics is 1 hour during the reference period (i.e., 4 weeks).
- 6.
Ordinary participation in social gatherings or public events, e.g., concerts, festivals, celebrations, sporting games, religious ceremonies, demonstrations, etc., is excluded on the grounds that the main beneficiaries of such participation are the participants themselves. However, any activity that involves organizing, facilitating, or conducting such events produces benefits to others and is included if it meets other criteria specified in the definition.
- 7.
Other definitions of direct or “informal” volunteering do not provide such exclusion (c.f. Einolf, 2011). This exclusion makes conceptual sense, however, because it separates volunteering from other everyday activities that involve interpersonal interaction. Without such separation, virtually any interpersonal interaction can be considered volunteering, rendering the concept devoid of specific meaning.
- 8.
The economically active population is the population aged 15 or over that is not incarcerated or otherwise unable to work. Because volunteers typically work only part time, the full-time equivalent number of volunteers is likely much smaller than the number of people who do any volunteering, even though care has been taken to estimate the annual time a volunteer devotes to this activity over an entire year even when the reference period for the survey covers a shorter period. A complication of organization-based surveys is that a particular individual may volunteer for more than a single organization, thus potentially overstating the number of individuals volunteering. For an estimate of the number of physical persons volunteering, see Salamon et al. Table A2.
- 9.
Alternative data sources include opinion surveys, such as the Gallup World Giving Index, the International Social Survey Programme, or the Eurobarometer (for a review see Einolf, 2011). However, we believe that existing opinion surveys are far less reliable than TUS for the reasons explained earlier in this chapter.
- 10.
For further details about the methodological approaches and range of activities measured by TUSs see the United Nations Statistics Division website:http://unstats.un.org/unsd/methods/timeuse/tusresource.htm , and http://unstats.un.org/UNSD/demographic/sconcerns/tuse/default.aspx
- 11.
Annex A shows typical details of “Community services and help to other households” activities used in TUS methodology.
- 12.
Government of Pakistan, Statistics Division, Federal Bureau of Statistics, Time Use Survey 2007, Islamabad, 2009.
- 13.
Although a far greater number of countries conducted time use surveys, the results are either unavailable, inaccessible, or lacking sufficient detail. For further information on sources of data, see: OECD http://www.oecd.org/gender/data/OECD_1564_TUSupdatePortal.xls; Harmonised European Time Use Survey, https://www.h5.scb.se/tus/tus/Statistics.html; Government of Pakistan, Statistics Division, Federal Bureau of Statistics, Islamabad, 2009.
- 14.
For detailed country data and data assembly methodology see Salamon et al., 2004.
- 15.
We used a regression analysis to find our way to a good predictor of the aggregate size of the organization-based volunteer workforce measured as a share of the economically active population (EAP) in each country. We examined different regression models trying to find one that explains most of the cross-country variance on the dependent variable observed in the 43-country dataset. We found that the best results measured by the share of explained variance (R2 = 62 %) was the model with the entire nonprofit workforce share of EAP as the dependent variable, and per capita GDP (in USD) as the predictor variable. One important advantage of this approach was that per capita GDP data are available for virtually all countries in the world. We therefore proceeded in two steps. First, we estimated the size of the entire nonprofit workforce in the 139 countries in which CNP data were not available using the regression equation that emerged from our analysis of the 43 countries on which we have data. That model took the form of y = 0.02 + 0.0027x, where x is per capita GDP in US dollars and y is the nonprofit workforce as a share of the economically active population. In some instances, we applied downward adjustments if the predicted results seemed to run seriously counter to other available evidence. The result gave us an estimate of the nonprofit workforce share of EAP in each of these additional 139 countries. Then, as the second step, we computed the volunteer share of this nonprofit workforce in these same countries by applying the volunteer share of the nonprofit workforce estimated from the 43-country CNP data (41 %) to the aggregate nonprofit workforce in these 139 countries to yield the estimate of the organization-based volunteer share of EAP in each country, our ultimate dependent variable.
- 16.
We used a straightforward projection method based on the size of each country’s population 15 years of age or older. We calculate the total number of volunteer hours within the reference period of one year by multiplying the average number of minutes per person-day by 365 days, dividing minutes by 60 to convert to hours, multiplying the result by the size of the population 15 years of age or older in a given country to obtain the total number of volunteer-hours in that country in a year, and finally converting these volunteer hours to FTE volunteers by dividing by the number of hours per full-time job (1760 h). The base year for these estimations is 2005.
- 17.
The “normalization” procedure involved step-by-step removal of the outliers, starting from the highest and observing the effect of that removal on the skew value, a procedure also known as “top-coding.” When the positive skew value was reduced without becoming negative (which would produce underestimated results), we calculated the average based on the remaining observations. The “top-coded” value of average time was 13 min, which means that observations higher than this value did not affect this final step of our estimation procedure. Even with this process, we may have somewhat overestimated the actual amount of direct volunteering in the global South since the average of the actual direct volunteering values for countries in the South on which TUS data were available were well under the 6 min average we ultimately used for our estimations.
- 18.
As this figure shows “Volunteerland,” if there were such a place, would command the fourth largest workforce in the world, behind only China , India, and the U.S., but ahead of Indonesia, Brazil, Russia, and Japan. And this takes no account of the fact, noted earlier, that the actual number of people engaged in volunteer work is much larger than this due to the fact that most people volunteer for relatively brief periods of time so that the actual number of people represented by these 126 million FTE workers is really many times that. In fact, in earlier estimates we have put that figure at 971 million people (Salamon et al., 2011, p. 237).
- 19.
This grouping is based on World Bank data. The World Bank groups countries into five categories based on their per capita national income and OECD status. For the purpose of this analysis, we combined high-income OECD and high-income non-OECD countries into one “high-income” group.
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Annex A: Community Services and Help to Other Households in TUS
Annex A: Community Services and Help to Other Households in TUS
Pakistan
Community services and help to other households
Time used for:
610 | Community organized construction and repairs: buildings, roads, dams, wells, etc. |
615 | Cleaning of classrooms |
621 | Community organized work: cooking for collective celebrations, etc. |
622 | Cooking for School Nutrition Programs for Girls: Tawana Pakistan Project, etc. |
630 | Volunteering with or for an organization |
650 | Participation in meetings of local and informal groups/caste, tribes, professional associations, union, political and similar organizations |
660 | Involvement in civic and related responsibilities: voting, rallies, etc. |
671 | Caring for nonhousehold children |
672 | Caring for nonhousehold sick and disabled adults |
673 | Caring for nonhousehold elderly adults |
674 | Other informal help to other households |
680 | Travel related to community services |
688 | Waiting for community services and to help to other households |
690 | Community services not elsewhere classified |
Source: Government of Pakistan, Statistics Division, Federal Bureau of Statistics, Time Use Survey 2007, Islamabad, 2009
South Africa
Community services and help to other households
Time used for:
610 | Community organized construction and repairs: buildings, roads, dams, wells, etc. |
615 | Cleaning of classrooms |
620 | Community organized work: cooking for collective celebrations, etc. |
630 | Volunteering with or for an organization |
650 | Participation in meetings of local and informal groups/caste, tribes, professional associations, union, political and similar organizations |
660 | Involvement in civic and related responsibilities: voting, rallies, etc. |
671 | Caring for nonhousehold children mentioned spontaneously |
672 | Caring for nonhousehold children not mentioned spontaneously |
673 | Caring for nonhousehold adults |
674 | Other informal help to other households |
680 | Travel related to community services |
690 | Community services not elsewhere classified |
Source: Statistics South Africa, A Survey of Time Use: How South African Women and Men Spend their Time, Pretoria, 2001.
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Salamon, L.M., Haddock, M.A., Sokolowski, S.W. (2017). Closing the Gap? New Perspectives on Volunteering North and South. In: Butcher, J., Einolf, C. (eds) Perspectives on Volunteering. Nonprofit and Civil Society Studies. Springer, Cham. https://doi.org/10.1007/978-3-319-39899-0_2
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