Category Archives: data

Twenty Years of Generosity in the Netherlands

ERNOP 2017 presentation PaperOpen Science Framework

In the past two decades, philanthropy in the Netherlands has gained significant attention, from the general public, from policy makers, as well as from academics. Research on philanthropy in the Netherlands has documented a substantial increase in amounts donated to charitable causes since data on giving in the Netherlands have become available in the mid-1990s (Bekkers, Gouwenberg & Schuyt, 2017). What has remained unclear, however, is how philanthropy has developed in relation to the growth of the economy at large and the growth of consumer expenditure. For the first time, we bring together all the data on philanthropy available from eleven editions of the Giving in the Netherlands survey among households (n = 17,033), to answer the research question: how can trends in generosity in the Netherlands in the past 20 years be explained?

 

The Giving in the Netherlands Panel Survey

One of the strengths of the GINPS is the availability of data on prosocial values and attitudes towards charitable causes. In 2002, the Giving in the Netherlands survey among households was transformed from a cross-sectional to a longitudinal design (Bekkers, Boonstoppel & De Wit, 2017). The GIN Panel Survey has been used primarily to answer questions on the development of these values and attitudes in relation to changes in volunteering activities (Bekkers, 2012; Van Ingen & Bekkers, 2015; Bowman & Bekkers, 2009). Here we use the GINPS in a different way. First we describe trends in generosity, i.e. amounts donated as a proportion of income. Then we seek to explain these trends, focusing on prosocial values and attitudes towards charitable causes.

 

How generous are the Dutch?

Vis-à-vis the rich history of charity and philanthropy in the Netherlands (Van Leeuwen, 2012), the current state of giving is rather poor. On average, charitable donations per household in 2015 amounted to €180 per year or 0,4% of household income. The median gift is €50 (De Wit & Bekkers, 2017). In the past fifteen years, the trend in generosity is downward: the proportion of income has declined slowly but steadily since 1999 (Bekkers, De Wit & Wiepking, 2017). In 2015, giving as a proportion of income has declined by one-fifth of its peak in 1999 (see Figure 1).

GIV_CEX

Figure 1: Household giving as a proportion of consumer expenditure (Source: Bekkers, De Wit & Wiepking, 2017)

 

Why has generosity of households in the Netherlands declined?

The first explanation is declining religiosity. Because giving is encouraged by religious communities, the decline of church affiliation and practice has reduced charitable giving, as in the US (Wilhelm, Rooney & Tempel, 2007). The disappearance of religiosity from Dutch society has reduced charitable giving because the non-religious have become more numerous. The decline in religiosity explains about 40% of the decline in generosity we observe in the period 2001-2015. In Figure 2 we see a similar decline in generosity to religion (the red line) as to other organizations (the blue line).

REL_NREL

Figure 2: Household giving to religion (red) and to other causes (blue) as a proportion of household income (Source: Bekkers, De Wit & Wiepking, 2017)

 

We also find that those who are still religious have become much more generous. Figure 3 shows that the amounts donated by Protestants (the green line) have almost doubled in the past 20 years. The amounts donated by Catholics (the red line) have also doubled, but are much lower. The non-religious have not increased their giving at all in the past 20 years. However, the increasing generosity of the religious has not been able to turn the tide.

REL_DEN

Figure 3: Household giving by non-religious (blue), Catholics (red) and Protestants (green) in Euros (Source: Bekkers, De Wit & Wiepking, 2017)

The second explanation is that prosocial values have declined. Because generosity depends on empathic concern and moral values such as the principle of care (Bekkers & Ottoni-Wilhelm, 2016), the loss of such prosocial values has reduced generosity. Prosocial values have lost support, and the loss of prosociality explains about 15% of the decline in generosity. The loss of prosocial values itself, however, is closely connected to the disappearance of religion. About two thirds of the decline in empathic concern and three quarters of the decline in altruistic values is explained by the reduction of religiosity.

In addition, we see that prosocial values have also declined among the religious. Figure 4 shows that altruistic values have declined not only for the non-religious (blue), but also for Catholics (red) and Protestants (green).

REL_AV

Figure 4: Altruistic values among the non-religious (blue), Catholics (red) and Protestants (green) (Source: Giving in the Netherlands Panel Survey, 2002-2014).

Figure 5 shows a similar development for generalized social trust.

REL_TRUST

Figure 5: Generalized social trust among the non-religious (blue), Catholics (red) and Protestants (green)  (Source: Giving in the Netherlands Panel Survey, 2002-2016).

Speaking of trust: as donations to charitable causes rely on a foundation of charitable confidence, it may be argued that the decline of charitable confidence is responsible for the decline in generosity (O’Neill, 2009). However, we find that the decline in generosity is not strongly related to the decline in charitable confidence, once changes in religiosity and prosocial values are taken into account. This finding indicates that the decline in charitable confidence is a sign of a broader process of declining prosociality.

 

What do our findings imply?

What do these findings mean for theories and research on philanthropy and for the practice of fundraising?

First, our research clearly demonstrates the utility of including questions on prosocial values in surveys on philanthropy, as they have predictive power not only for generosity and changes therein over time, but also explain relations of religiosity with generosity.

Second, our findings illustrate the need to develop distinctive theories on generosity. Predictors of levels of giving measured in euros can be quite different from predictors of generosity as a proportion of income.

For the practice of fundraising, our research suggests that the strategies and propositions of charitable causes need modification. Traditionally, fundraising organizations have appealed to empathic concern for recipients and prosocial values such as duty. As these have become less prevalent, propositions appealing to social impact with modest returns on investment may prove more effective.

Also fundraising campaigns in the past have been targeted primarily at loyal donors. This strategy has proven effective and religious donors have shown resilience in their increasing financial commitment to charitable causes. But this is not a feasible long term strategy as the size of this group is getting smaller. A new strategy is required to commit new generations of donors.

 

 

References

Bekkers, R. (2012). Trust and Volunteering: Selection or Causation? Evidence from a Four Year Panel Study. Political Behavior, 32 (2): 225-247.

Bekkers, R., Boonstoppel, E. & De Wit, A. (2017). Giving in the Netherlands Panel Survey – User Manual, Version 2.6. Center for Philanthropic Studies, VU Amsterdam.

Bekkers, R. & Bowman, W. (2009). The Relationship Between Confidence in Charitable Organizations and Volunteering Revisited. Nonprofit and Voluntary Sector Quarterly, 38 (5): 884-897.

Bekkers, R., De Wit, A. & Wiepking, P. (2017). Jubileumspecial: Twintig jaar Geven in Nederland. In: Bekkers, R. Schuyt, T.N.M., & Gouwenberg, B.M. (Eds.). Geven in Nederland 2017: Giften, Sponsoring, Legaten en Vrijwilligerswerk. Amsterdam: Lenthe Publishers.

Bekkers, R. & Ottoni-Wilhelm, M. (2016). Principle of Care and Giving to Help People in Need. European Journal of Personality, 30(3): 240-257.

Bekkers, R., Schuyt, T.N.M., & Gouwenberg, B.M. (Eds.). Geven in Nederland 2017: Giften, Sponsoring, Legaten en Vrijwilligerswerk. Amsterdam: Lenthe Publishers.

De Wit, A. & Bekkers, R. (2017). Geven door huishoudens. In: Bekkers, R., Schuyt, T.N.M., & Gouwenberg, B.M. (Eds.). Geven in Nederland 2017: Giften, Sponsoring, Legaten en Vrijwilligerswerk. Amsterdam: Lenthe Publishers.

O’Neill, M. (2009). Public Confidence in Charitable Nonprofits. Nonprofit and Voluntary Sector Quarterly, 38: 237–269.

Van Ingen, E. & Bekkers, R. (2015). Trust Through Civic Engagement? Evidence From Five National Panel Studies. Political Psychology, 36 (3): 277-294.

Wilhelm, M.O., Rooney, P.M. and Tempel, E.R. (2007). Changes in religious giving reflect changes in involvement: age and cohort effects in religious giving, secular giving, and attendance. Journal for the Scientific Study of Religion, 46 (2): 217–32.

Van Leeuwen, M. (2012). Giving in early modern history: philanthropy in Amsterdam in the Golden Age. Continuity & Change, 27(2): 301-343.

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Filed under Center for Philanthropic Studies, data, household giving, Netherlands, survey research, trends

Introducing Mega-analysis

How to find truth in an ocean of correlations – with breakers, still waters, tidal waves, and undercurrents? In the old age of responsible research and publication, we would collect estimates reported in previous research, and compute a correlation across correlations. Those days are long gone.

In the age of rat race research and publication it became increasingly difficult to do a meta-analysis. It is a frustrating experience for anyone who has conducted one: endless searches on the Web of Science and Google Scholar to collect all published research, input the estimates in a database, find that a lot of fields are blank, email authors for zero-order correlations and other statistics they had failed to report in their publications and get very little response.

Meta-analysis is not only a frustrating experience, it is also a bad idea when results that authors do not like do not get published. A host of techniques have been developed to find and correct publication bias, but the problem that we do not know the results that do not get reported is not solved easily.

As we enter the age of open science,  we do not have to rely any longer on the far from perfect cooperation from colleagues who have moved to a different university, left academia, died, or think you’re trying to prove them wrong and destroy your career. We can simply download all the raw data and analyze them.

Enter mega-analysis: include all the data points relevant for a certain hypothesis, cluster them by original publication, date, country, or any potentially relevant property of the research design, and add the substantial predictors you find documented in the literature. The results reveal not only the underlying correlations between substantial variables, but also the differences between studies, periods, countries and design properties that affect these correlations.

The method itself is not new. In epidemiology, and Steinberg et al. (1997) labeled it ‘meta-analysis of individual patient data’. In human genetics, genome wide association studies (GWAS) by large international consortia are common examples of mega-analysis.

Mega-analysis includes the file-drawer of papers that never saw the light of day after they were put in. It also includes the universe of papers that have never been written because the results were unpublishable.

If meta-analysis gives you an estimate for the universe of published research, mega-analysis can be used to detect just how unique that universe is in the milky way. My prediction would be that correlations in published research are mostly further from zero than the same correlation in a mega-analysis.

Mega-analysis bears great promise for the social sciences. Samples for population surveys are large, which enables optimal learning from variations in sampling procedures, data collection mode, and questionnaire design. It is time for a Global Social Science Consortium that pools all of its data. As an illustration, I have started a project on the Open Science Framework that mega-analyzes generalized social trust. It is a public project: anyone can contribute. We have reached mark of 1 million observations.

The idea behind mega-analysis originated from two different projects. In the first project, Erik van Ingen and I analyzed the effects of volunteering on trust, to check if results from an analysis of the Giving in the Netherlands Panel Survey (Van Ingen & Bekkers, 2015) would replicate with data from other panel studies. We found essentially the same results in five panel studies, although subtle differences emerged in the quantative estimates. In the second project, with Arjen de Wit and colleagues from the Center for Philanthropic Studies at VU Amsterdam, we analyzed the effects of volunteering on well-being conducted as part of the EC-FP7 funded ITSSOIN study. We collected 845.733 survey responses from 154.970 different respondents in six panel studies, spanning 30 years (De Wit, Bekkers, Karamat Ali & Verkaik, 2015). We found that volunteering is associated with a 1% increase in well-being.

In these projects, the data from different studies were analyzed separately. I realized that we could learn much more if the data are pooled in one single analysis: a mega-analysis.

References

De Wit, A., Bekkers, R., Karamat Ali, D., & Verkaik, D. (2015). Welfare impacts of participation. Deliverable 3.3 of the project: “Impact of the Third Sector as Social Innovation” (ITSSOIN), European Commission – 7th Framework Programme, Brussels: European Commission, DG Research.

Van Ingen, E. & Bekkers, R. (2015). Trust Through Civic Engagement? Evidence From Five National Panel StudiesPolitical Psychology, 36 (3): 277-294.

Steinberg, K.K., Smith, S.J., Stroup, D.F., Olkin, I., Lee, N.C., Williamson, G.D. & Thacker, S.B. (1997). Comparison of Effect Estimates from a Meta-Analysis of Summary Data from Published Studies and from a Meta-Analysis Using Individual Patient Data for Ovarian Cancer Studies. American Journal of Epidemiology, 145: 917-925.

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Four Reasons Why We Are Converting to Open Science

The Center for Philanthropic Studies I am leading at VU Amsterdam is converting to Open Science.

Open Science offers four advantages to the scientific community, nonprofit organizations, and the public at large:

  1. Access: we make our work more easily accessible for everyone. Our research serves public goods, which are served best by open access.
  2. Efficiency: we make it easier for others to build on our work, which saves time.
  3. Quality: we enable others to check our work, find flaws and improve it.
  4. Innovation: ultimately, open science facilitates the production of knowledge.

What does the change mean in practice?

First, the source of funding for contract research we conduct will always be disclosed.

Second, data collection – interviews, surveys, experiments – will follow a prespecified protocol. This includes the number of observations forseen, the questions to be asked, measures to be included, hypotheses to be tested, and analyses to be conducted. New studies will be preferably be preregistered.

Third, data collected and the code used to conduct the analyses will be made public, through the Open Science Framework for instance. Obviously, personal or sensitive data will not be made public.

Fourth, results of research will preferably be published in open access mode. This does not mean that we will publish only in Open Access journals. Research reports and papers for academic will be made available online in working paper archives, as a ‘preprint’ version, or in other ways.

 

December 16, 2015 update:

A fifth reason, following directly from #1 and #2, is that open science reduces the costs of science for society.

See this previous post for links to our Giving in the Netherlands Panel Survey data and questionnaires.

 

July 8, 2017 update:

A public use file of the Giving in the Netherlands Panel Survey and the user manual are posted at the Open Science Framework.

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Giving in the Netherlands 2015: Summary of Principle Findings

This is a summary in English. Download this post in PDF here.

Prof. R.H.F.P. Bekkers, Ph.D., Prof. Th.N.M. Schuyt, Ph.D., & Gouwenberg, B.M. (Eds., 2015). Giving in the Netherlands: Donations, Bequests, Sponsoring and Volunteering. Amsterdam: Reed Business. ISBN 978 90 352 4818 2

I – Results for 2013

Total amount donated in 2013

In the Netherlands, about € 4.4 billion was donated to charitable causes in 2013.

The total figure is the sum of estimated contributions made in the course of the calendar year by households, bequests, foundations (both fundraising foundations and endowed foundations), businesses and lotteries. The amount is an underestimate because data on bequests and endowed foundations are known to be incomplete.

 In the Netherlands, approximately 0.7% of its Gross Domestic Product (GDP) is donated to charitable causes (€ 643 billion in 2013)

This low percentage seems to contradict the general impression that the Dutch are generous givers. By comparison: In the United States, the percentage of the GDP given to charitable causes in the period 1965-2013 fluctuated around 2% (Giving USA, 2014). However, the Dutch contribute to public, social and charitable causes primarily by paying taxes, while Americans do so to a far lesser extent, given the considerably lower tax burden in the United States. Furthermore, in contrast to ‘Giving In the Netherlands’, ‘Giving USA’ does seem to have a clear image of contributions from bequests and endowed foundations.

Sources of contributions in 2013

Households (money and goods)  € 1,944 million 45%
Bequests  € 265 million 6%
Foundations: Fundraising foundationsEndowed foundations € 106 million€ 184 million 2%4%
Corporations (gifts and sponsoring) € 1,363 million 31%
Lotteries € 494 million 11%
Total € 4,356 million 100%

The figures for households and corporations are estimates based on representative samples and generalized to the entire population (n = 1,505 and n = 1,164, respectively). The figures relating to bequests and foundations (fundraising and endowed foundations) are based on archival records. Since these available archival records are far from complete, we do not make generalizations to the entire sector for bequests and foundations, resulting in an underestimation being based only on information available to us.

Figures on bequests are taken from the Central Bureau of Fundraising (CBF), to which national fundraising foundations submit financial statements regarding their received contributions. 196 of 584 CBF-registered fundraising foundations reported bequests. Far from all fundraising foundations report their income to the CBF, churches and nonprofit organizations such as hospitals, museums and educational institutions for example do not. Therefore, the total amount donated through bequests is likely to be much higher than reported.

The figures on fundraising foundations are derived from the CBF as well. In total, 516 fundraising foundations contributed €3,097 million to good causes in 2013. The contributions of fundraising foundations as mentioned in the table above (€106 million) consists only of ‘income from investments’. The remaining income – such as fundraising among the Dutch population, and the commercial sector – are only included in figures from the respective chapters (households, corporations) in order to prevent double counting.

An issue for concern in our analysis on endowed foundations is the lack of complete data on grant making by this group of interest. It remains unknown how many endowed foundations there are, what they contribute as a group and what their combined assets are. There are 810 endowed foundation registered with a national data archive on philanthropy called ‘Kennisbank Filantropie’, through which they were asked to fill out an online questionnaire. The figures are based on the resulting sample of 141 endowed foundations that took the time and effort to report about their contributions. However, these foundations constitute only a small proportion of the total number of charitable endowed foundations in de Netherlands, since many foundations operate anonymously.

Six national permanent and semi-permanent gambling and lottery license holders support charitable causes with part of their proceeds. Since 2004, de BankGiroloterij N.V., de VriendenLoterij N.V. (formerly Sponsor Bingo Loterij) and De Nationale Postcode Loterij N.V. are classified under the N.V. Holding Nationale Goede Doelen Loterijen. The other three license holders are Stichting de Nationale Sporttotalisator (De Lotto), Sportech B.V. and Samenwerkende Non-profit Loterijen (SNL). Figures used in Giving In the Netherlands were derived from the annual reports of these license holders.

 

Recipient organizations in 2013

million € Percentage
Religion 977 22
International aid 578 13
Sports and recreation 554 13
Public/social benefit 547 13
Health 535 12
Environment, nature en animals 356 8
Other (not specified) 321 7
Culture 281 6
Education and research 208 5
Totala 4,356 100%

a All figures are rounded off. This may lead to a discrepancy between the sum of the sub-categories and the total amount displayed.

 In 2013, the Dutch donated by far the highest amount to religion (€806 million). Education and research remains the smallest sector in terms of charitable contributions (5%).

 

Sources and recipient organizations in 2013

The total amount donated by households, individuals (bequests), both fundraising and endowed foundations, businesses/corporations and lotteries to public or social causes is subdivided as follows:

House-holds a Bequests Foundations b Corpo-rations a Lotteries Total %
(€x million) FF EF Total
Religion 787 6 2 4 6 177 977 22
Health 213 83 24 23 48 155 36 535 12
International aid 304 61 15 16 31 67 115 577 13
Environment/nature/ animals 150 42 20 6 26 47 91 356 8
Education/ research 41 1 1 17 18 148 208 5
Culture 57 3 26 52 79 80 63 281 6
Sports/recreation 42 0 0 11 11 433 68 554 13
Public and social benefit 190 70 17 45 62 139 86 547 13
Other (not specified) 160 0 0 9 9 117 35 321 7
Total 1,944 265 106 184 290 1,363 494 4,356 100

a The figures on households and corporations are based on generalizations. That is: The total amount of contributions made by households and corporations in the Netherlands are derived from amounts reported in a sample of the respective groups. For bequests and foundations this is not the case, since the necessary information  needed to make these estimations is missing.

b FF = fundraising foundations; EF = endowed foundations

  •  Households give the highest amount to religious organizations.
  • Bequests primarily benefit health.
  • Fundraising foundations give from their own resources (investments), particularly to health and international aid.
  • Culture is an important sector for endowed foundations.
  • Sports and recreation is the favored sector of choice by businesses and corporations.
  • The lotteries supporting good causes give most of their money to international aid and environment, nature and animals.

 

 

Volunteer work in 2013/2014

In 2014, 37% of the population had performed unpaid volunteering activities for an organization in the preceding year.
  • Sports associations and religious organizations attract the highest amount of volunteers.
  • Volunteers spent an average of 18 hours per month on their volunteer work.
  • Most volunteers perform managerial tasks (26%), do chores (20%), do office work and administration (18%), give advice and training (17%) or offer transportation (14%).
  • There is an increased likelihood of finding volunteers among the elderly, parents, the religious, those who attend church regularly and the higher educated. People with a full time employment and those living in one of the three largest Dutch cities volunteer less often.

II – Trends 1995-2013

Total amounts donated, 1995-2013 (Million €)a

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013
2,279 2,164 3,426 3,614 4,925 4,379 4,562 4,708 4,255 4,356

a Due to applied corrections, figures differ slightly from previous editions of ‘Giving in the Netherlands’.

  • After a period with an upward trend starting in 2005, 2009 commenced a downward trend in total contributions to good causes. In 2013, we see total giving bounce back with a 2,3% increase compared to 2011.
  • It is important to note that trends should be interpreted with caution due to incomplete data on bequests and contributions of endowed foundations.

Giving as percentage of the Gross Domestic Product (GDP) 1995-2013a

 

Billion €
1995 1997 1999 2001 2003 2005 2007 2009 2011 2013
GDP 324 363 413 476 506 541 609 617 643 643
Total giving 2,3 2,2 3,4 3,6 4,9 4,4 4,6 4,7 4,3 4,4
Donations % GDP 0,7 0,6 0,8 0,8 1,0 0,8 0,8 0,8 0,7 0,7

a Due to applied corrections, figures differ slightly from previous editions of ‘Giving in the Netherlands’.

  • As a percentage of the Gross Domestic Product, donations have hovered around 0.8% since 1995. From 2003 onwards there is a downward trend.
  • Again, trends should be interpreted with caution because of incomplete data on bequests and contributions of endowed foundations.

Sources of contributions 1995-2013 (in millions of €) a,b

Million €
1995 1997 1999 2001 2003 2005 2007 2009 2011 2013
Households 1,419 1,121 1,414 1,788 1,899 1,854 1,945 1,938 1,829 1,944
Corporations 610 693 1,466 1,359 2,271 1,513 1,639 1,694 1,378 1,363
Lotteries -,- -,- -,- -,- 369 396 394 461 498 494
Foundations 163 214 329 237 196 431 339 387 294 290
Bequests 87 135 213 231 189 182 240 232 256 265
Total 2,279 2,163 3,422 3,615 4,924 4,376 4,557 4,712 4,255 4,356

a Due to applied corrections to the figures on households, corporations, lotteries, foundations and bequests, figures differ slightly from previous editions of ‘Giving in the Netherlands’.

b The figures on households and corporations are based on generalized numbers. That is: The total amount of contributions made by households and corporations in the Netherlands are derived from amounts reported in a sample of the respective groups. For bequests and foundations, this is not the case, since the necessary information  needed to make these estimations is missing.

Households

  • In 2013, Households donated a total of €1,944 million in money and goods. This amount exceeds that of 2011 (€1,829 million) with 6%. Adjusted for inflation, the value of gifts and goods donated by households has increased with 1,2% since 2011. Household giving represents 0.3% of GDP and 0,67% of household consumption expenditure in  2013

Bequests

  • The amount of income from bequests as reported by fundraising foundations in their financial statements has risen sharply since 1995.

Foundations

  • The figures are based on the sum of contributions from equity earnings of a non-representative group of endowed foundations (n=141) and the contributions from 448 fundraising foundations. It is difficult to make definitive statements about trends on contributions by foundations because the data concern only a small group of endowed foundations and the figures for the years 1995-2013 are calculated in different ways.

Corporations

  • The figures on contributions by corporations through sponsoring and gifts resemble those of 2011. According to our estimations, we see a slight decrease in sponsoring and a slight increase in making gifts, compared to 2011. In 2011, we reported a decline of contributions by corporations compared to 2009. In 2013 however, this decline seems to have halted. Contributions from corporations remain an important source of income for the different sectors.

 

Lotteries

  • Charitable contributions by lotteries have seen a strong increase in recent years. We do see a minor decline of contributions in 2013 compared to 2011, mainly caused by a decrease in contributions from the Lotto.

 

Recipient sectors 1995-2013

Trends in contributions to the different recipient sectors in terms of total amounts (in € million) and relative ranking (1-8)a,b

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013
Religion 587 (1) 511 (1) 490 (4) 750 (1) 938 (1) 772 (1) 1,001 (1) 892 (1) 806 (1) 977 (1)
Health 411 (2) 290 (4) 640 (1) 398 (4) 580 (4) 467 (5) 468 (5) 629 (3) 471 (5) 535 (5)
International aid 361 (3) 299 (3) 542 (3) 531 (3) 480 (6) 756 (2) 561 (4) 576 (4) 564 (3) 578 (2)
Environment/ nature/animals 204 (6) 183 (6) 309 (6) 251 (7) 309 (7) 356 (6) 376 (7) 438 (7) 378 (6) 356 (6)
Education/ research
58 (8) 83 (8) 232 (7) 125 (-) 301 (8) 277 (8) 295 (8) 285 (8) 150 (8) 208 (8)
Culture 83 (7) 87 (7) 165 (8) 335 (6) 610 (3) 326 (7) 386 (6) 453 (6) 293 (7) 281 (7)
Sports/recreation 246 (5) 410 (2) 579 (2) 686 (2) 930 (2) 686 (3) 687 (3) 715 (2) 702 (2) 554 (3)
Public and social benefit 283 (4) 257 (5) 422 (5) 373 (5) 554 (5) 519 (4) 572 (2) 469 (5) 538 (4) 547 (4)
Other (not specified) 46 (-) 44 (-) 47 (-) 158 (8) 223 (-) 220 (-) 216 (-) 251(-) 349 (-) 321 (-)
Total* 2,279 2,164 3,426 3,614 4,925 4,379 4,562 4,708 4,251 4,356

a Due to differences in rounding off, the total amounts can deviate slightly from the total amounts given in the previous table.

b Due to applied corrections to the figures on households, corporations, lotteries, foundations and bequests, figures differ slightly from previous editions of ‘Giving in the Netherlands’.

Ranking of recipient sectors, averaged over the period 1995 – 2013
1. Religion
2. Sports and recreation
3. International aid
4. Health
5. Public and social benefit
6. Environment, nature and animals
7. Culture
8. Education and research

Over the 18 year period, religion receives the highest contribution and education and research receive the lowest contributions.

Volunteer work 2002-2014

2002

2004

2006

2008

2010*

2012*

2014*

Volunteer work

46%

41%

42%

45%

41%

38%

37%

* Estimates include non-native Dutch citizens.

  • The declining trend in volunteering rates we reported in the previous ‘Giving in the Netherlands’ books seems to have persisted in 2014.
  • In the past two years, the average hours a volunteer spends volunteering per month decreased slightly, from 21 to 18 hours.
  • During the past years, volunteers seems to have specialized by dedicating themselves to a smaller number of tasks. The share of volunteers that is working on three or more tasks declined from about a half of all volunteers in 2002 to about a quarter of all volunteers in 2014.
  • The dynamics in volunteering seems to have worn off a little. In the past two years, less people started volunteering. Those that do start volunteering tend to spend significantly less time on volunteering than the loyal, continuous volunteers. There seems to be a positive relationship between continuous volunteering and experienced social pressure. Those who perceive stronger social pressure tend to be the more persistent volunteers and remain more loyal to the organization they volunteer for.

III – Highlights

Households/individuals
  • A total of 1,505 households were surveyed in the 2012 wave of the Giving in the Netherlands Panel Survey (GINPS). 1,320 of the respondents also participated in the GINPS 2010 wave.
  • The average amount donated in money and in kind by Dutch households in the calendar year 2013 was €204, virtually identical to that of 2011. In 2013, 88% of Dutch households gives to charitable organizations with an average of €232 over the entire calendar year. 47% gives in kind, with an average value of €113. While we see an increasing popularity of giving money and goods to charitable causes, the average amount these households contribute seems to decrease.
  • Households most often give to health (74%), followed by environment, nature and animals (44%) and international aid (41%). While less than a third of Dutch households (29%) give to religion, it receives the highest amount. Donations to religion represent 43% of the total amount donated by Dutch households. Organizations which provide international aid and health organizations receive 12% and 13% of the total amount of household gifts, respectively.
  • Although the traditional door-to-door collection remains the most popular way to donate money in the Netherlands, its popularity decreased. While in 2005 90% of households donated to a door-to-door collection, in 2013 this declined to 78%. Many other ways to donate also decreased in popularity since 2011. New forms of giving such as giving through text messaging or via the internet barely gained popularity during the past years.
  • Similar to the previous ‘Giving in the Netherlands’ edition, we find that giving behavior of Dutch households follows the 80/20 rule: 20% of the households is responsible for 80% of the total amount donated. There are large differences in giving behaviors between households. 12% percent of Dutch households does not donate to charitable causes and over a quarter of the households (26%) donated less than €25 in 2013. At the other end of the spectrum, one in every seventy (1,5%) Dutch give more than €2000. This group accounts for over a quarter (27%) of the total amount of charitable contributions in the Netherlands. A substantial proportion of these large donations comes from the wealthy Dutch.
  • Differences between households in giving behavior are associated with socioeconomic characteristics such as age (older people donate more), education (higher educated donate more), income and wealth (the more financial resources, the higher the donated amounts) and religion (religious Dutch, especially Protestants, donate more). Households seem to do more charitable giving as they hold more altruistic values and as the frequency with which they are asked for donations increases.
  • Although total charitable giving appears to be relatively stable across time, we find an interesting dynamic underlying the surface. Many households remain loyal donors to organizations operating in health, while the other sectors are comprised out of more incidental than loyal donors.
Giving by Corporations
  • In 2013, 70% of the corporations gave money by donating directly or sponsoring activities organized by nonprofit organizations. This percentage is similar to that of two years ago, when 71% of corporations donated directly or sponsored activities organized by nonprofit organizations. According to our estimations, the relative proportion of sponsoring decreased and the proportion of corporations giving increased, compared to 2011. However, we do not see a further decline as seen in 2011 compared to 2009. Corporations remain an important source for charitable contributions in the array of sectors.
  • Sports and recreation is the most popular sector for sponsoring and gift making among corporations. Simultaneously, we find that in absolute terms, sports and recreation received less money than previous years and the breadth of the support for this sector in our sample also decreased. The percentage of corporations that give to or sponsor activities in sports and recreation is lower than previous editions of ‘Giving in the Netherlands’
  • It seems that corporations do not utilize philanthropy strategically. A vast majority of the corporations does not have a specific giving policy, and only a small group of corporations communicates about their philanthropic activities to internal or external parties. Corporations that do utilize a charitable giving policy strategy operate more ‘strategically’: they communicate more often, but also tend to give higher amounts to charitable causes.
  • Corporations that sponsor and/or give mostly do so to a limited number of sectors.
  • Sponsoring and donating man hours remains an important way of giving by corporations in 2013 and seems to have steadily gained in popularity over the past years. Corporations thus explicitly aim to promote their employees’ active participation in societal projects.
  • Although corporations seem to be increasingly aware of the concept of corporate social responsibility (CSR), we do not see an increase in corporations engaging in CSR. Many corporations have initiated new CSR initiatives, but these do not seem to displace sponsoring or gift making.


Specials

 

The multiplier in the ‘Geefwet’ and giving to culture

Giving in the Netherlands 2015 contains one ‘special’. Since January 2012, gifts to cultural nonprofit organizations are 125% tax deductible, instead of the 100% deductibility of gifts to nonprofit organizations in other sectors. The Dutch government seeks to encourage donations to cultural nonprofits. In this chapter, we report on changes in the charity law (the ‘Geefwet’) and changes in giving to cultural nonprofit organizations.

  • Government cut backs on the cultural sector have necessitated a diversification of income sources for cultural nonprofit organizations.
  • It is too early to assess the effect of the tax law reform with sufficient accuracy.
  • Of all households, 11% gave to cultural nonprofit organizations, similar to 2011.
  • Wealthy Dutch households give more often (36%) to cultural nonprofit organizations than the average households do (11%), and also gives more (median gift of €100, compared to €8).
  • The proportion of wealthy households planning to give more to cultural nonprofit organizations the next year is lower than the proportion of wealthy households intending to give more.
  • The multiplier may be able to increase giving to cultural organizations. Among wealthy households that give to cultural nonprofit organizations, awareness of the multiplier is positively related to the intention to give more. About half of wealthy households do not know how the multiplier works. Raising awareness about the multiplier among donors could therefore increase the number and size of gifts to cultural nonprofit organizations.

 

References

Giving USA 2014. The annual report on philanthropy for the year 2013. Indianapolis: Indiana  University, Lilly Family School of Philanthropy.

Schuyt, Th.N.M. (Ed.), (2001). Geven in Nederland 2011: giften, legaten, sponsoring en vrijwilligerswerk. Houten/Diegem: Bohn Stafleu Van Loghum.

‘Giving in the Netherlands’ is published biennially by the Center for Philanthropic Studies at VU University Amsterdam.

Email: gin.fsw@vu.nl or visit www.giving.nl

[1] In contrast to donation behavior, volunteer work has been measured for the years 2013/2014. In June 2014, respondents were asked if they had performed volunteer work in the previous 12 months.

[2] Contrary to charitable contributions, volunteering was measure biyearly in years 2002, 2004, 2006, 1008, 2012 and 2014. In the month May of 2002, 2004, 2006, 2008, 2010, 2012 and 2014, respondents were asked whether they volunteered or performed unpaid work in the past 12 months.

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Filed under Center for Philanthropic Studies, data, foundations, household giving, philanthropy

Philanthropic Studies: Two Historical Examples

This post was published earlier in the newsletter of the European Research Network on Philanthropy

The 20th century has seen a tremendous growth of scientific enterprise. The increasing productivity of scientists has been accompanied by a proliferation of academic disciplines. While it is hard to determine an exact time and place of birth, the emergence of a separate field of research on philanthropy – Philanthropic Studies – took place largely in the 1980s in the United States of America (Katz, 1999). Looking back further in time, philanthropy American Style obviously has European roots. My favorite example to illustrate these origins – admittedly slightly patriotic – is the way the hallmark of capitalism was financed, documented by Russell Shorto in his book The Island at the Center of the World. Wall Street was built as a defense wall by the Dutch colonists against the Indians, the Swedes and the English, funded by private contributions of the citizens of New Amsterdam. The contributions were not altruistic in the sense that they benefited the poor or in the sense that they were motivated by concern for the welfare of all. Neither were these contributions totally voluntary. There was no system of taxes in place at the time, but Peter Stuyvesant went around the richest inhabitants of the city with his troops to collect contributions, in monetary or material form. I imagine the appeal to self-interest was occasionally illustrated by a show of guns when contributions were not made spontaneously.

Mannados

Today the study of philanthropy is spread over a large number of disciplines. It is not just sociologists, economists and psychologists who examine causes, consequences and correlates of philanthropy, but also scholars in public administration, political science, communication science, marketing, behavioral genetics, neurology, biology, and even psychopharmacology. Ten years ago, when Pamala Wiepking and I were writing a literature review of research on philanthropy, we gathered as many empirical research papers on philanthropy that we could find. We categorized the academic disciplines in which the research was published. The graph below displays the results of this categorization (for details, see our blog Understanding Philanthropy). The emergence of a separate field of philanthropic studies is visible, along with an increasing attention to philanthropy in economics.

After we had concluded our literature review, I detected a new classic. I would like to share this gem with you. It is an astonishing paper written by Pitirim Sorokin, a Russian sociologist who was exiled to the US in 1922. He founded the department of sociology at Harvard University in the 1930s. Before that, he conducted experiments at the University of Minnesota, and some of them examined generosity. The paper was published in German in 1928, in the Zeitschrift für Völkerpsychologie und Soziologie. It was not easy to obtain a copy of the paper. I managed to get one with the generous help of the staff at the University of Saskatchewan, where the complete works of Sorokin are archived; see http://library2.usask.ca/sorokin/. I have posted a pdf of the paper here: https://renebekkers.files.wordpress.com/2014/10/sorokin_28_full.pdf

Sorokin_28

Working with two colleagues, Sorokin asked students at the University of Minnesota how much money they were willing to donate to a fund for talented students, which would allow them to buy mathematical equipment (‘diagrams and a calculator’), and varied the severity of need and social distance to the students. The experiment showed that willingness to give declined the with the severity of need and with social distance. Students were willing to donate more for fellow students who were closer to them but needed less financial assistance.

Sorokin also gave the participants statements expressing egalitarian and justice concerns, to see whether the students acted in line with their attitudes. The attitudes were much more egalitarian than the responses in the hypothetical giving experiment. He was careful enough to note that the results of the experiment could not easily be generalized and needed replication in other samples, a critique repeated forcefully by Henrich et al. (2010). Sorokin saw his experiment as the beginning of a series of studies. However, the paper seems to have been forgotten entirely – Google Scholar mentions only 7 citations, extending to 1954. This is unfortunate. The experiment is truly groundbreaking both because of its methodology and its results. More than 8 decades later, economists are conducting experiments with dictator games that are very similar to the experiment Sorokin conducted. Perhaps this brief description brings his research back onto the stage.

References

Bekkers, R. & Wiepking, P. (2011). ‘A Literature Review of Empirical Studies of Philanthropy: Eight Mechanisms that Drive Charitable Giving’. Nonprofit and Voluntary Sector Quarterly, 40(5): 924-973.

Henrich, J., Heine, S.J., & Norenzayan, A. (2010). ‘The weirdest people in the world?’ Behavioral and Brain Sciences 33: 61–83.

Katz, S.N. (1999). ‘Where did the serious study of philanthropy come from, anyway?’ Nonprofit and Voluntary Sector Quarterly, 28: 74-82.

Sorokin, P. (1928). ‘Experimente Zur Soziologie’. Zeitschrift für Völkerpsychologie und Soziologie, 1(4): 1-10.

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Filed under altruism, data, Europe, experiments, helping, history, Netherlands, philanthropy

Why a high R Square is not necessarily better

Often I encounter academics thinking that a high proportion of explained variance is the ideal outcome of a statistical analysis. The idea is that in regression analyses a high R Square is better than a low R Square. In my view, the emphasis on a high R2 should be reduced. A high R2 should not be a goal in itself. The reason is that a higher R2 can easily be obtained by using procedures that actually lower the external validity of coefficients.

It is possible to increase the proportion of variance explained in regression analyses in several ways that do not in fact our ability to ‘understand’ the behavior we are seeking to ‘explain’ or ‘predict’. One way to increase the R2 is to remove anomalous observations, such as ‘outliers’ or people who say they ‘don’t know’ and treat them like the average respondent. Replacing missing data by mean scores or using multiple imputation procedures often increases the Rsquare. I have used this procedure in several papers myself, including some of my dissertation chapters.

But in fact outliers can be true values. I have seen quite a few of them that destroyed correlations and lowered R squares while being valid observations. E.g., a widower donating a large amount of money to a charity after the death of his wife. A rare case of exceptional behavior for very specific reasons that seldom occur. In larger samples these outliers may become more frequent, affecting the R2 less strongly.

Also ‘Don’t Know’ respondents are often systematically different from the average respondent. Treating them as average respondents eliminates some of the real variance that would otherwise be hard to predict.

Finally, it is often possible to increase the proportion of variance explained by including more variables. This is particularly problematic if variables that are the result of the dependent variable are included as predictors. For instance if network size is added to the prediction of volunteering the R Square will increase. But a larger network not only increases volunteering; it is also a result of volunteering. Especially if the network questions refer to the present (do you know…) while the volunteering questions refer to the past (in the past year, have you…) it is dubious to ‘predict’ volunteering in the past by a measure of current network size.

As a reviewer, I give authors reporting an R2 exceeding 40% a treatment of high-level scrutiny for dubious decisions in data handling and inclusion of variables.

As a rule, R Squares tend to be higher at higher levels of aggregation, e.g. when analyzing cross-situational tendencies in behavior rather than specific behaviors in specific contexts; or when analyzing time-series data or macro-level data about countries rather than individuals. Why people do the things they do is often just very hard to predict, especially if you try to predict behavior in a specific case.

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Filed under academic misconduct, data, methodology, regression analysis, survey research

Lunch Talk: “Generalized Trust Through Civic Engagement? Evidence from Five National Panel Studies”

Does civic engagement breed trust? According to a popular version of social capital theory, civic engagement should produce generalized trust among citizens. In a new paper accepted for publication in Political Psychology, Erik van Ingen (Tilburg University) and I put this theory to the test by examining the causal connection between civic engagement and generalized trust using multiple methods and multiple (prospective) panel datasets. We found participants to be more trusting. This was mostly likely caused by selection effects: the causal effects of civic engagement on trust were very small or non-significant. In the cases where small causal effects were found, they turned out not to last. We found no differences across types of organizations and only minor variations across countries.

At the PARIS colloquium of the Department of Sociology at VU University on November 12, 2013 (Room Z531, 13.00-14.00), I will not just be talking about this paper published in Political Behavior and about the new paper forthcoming in Political Psychology (here is the prepublication version). In addition to a substantive story about a research project there is also a story about the process of getting a paper accepted with a null-finding that goes against received wisdom. This story is quite informative about the publication factory that we are all in.

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Filed under data, psychology, survey research, trust, volunteering