Nonprofit organizational legitimacy and government grants under authoritarianism: evidence from Chinese foundations

Abstract

The literature on NGOs under authoritarian rule largely attributes NGOs’ receipt of government grants to their political connections. This article presents an alternative explanation by asking the question: Does nonprofit organizational legitimacy influence the receipt of government grants under authoritarianism? Applying logit regression to 2,021 Chinese foundations, this article proposes that passing the nonprofit evaluation, which is one of the major certification programs in the country’s nonprofit sector, is positively related to the probability of receiving government grants. Subsample analysis reveals that nonprofit evaluation is influential for the receipt of government grants primarily among foundations formally affiliated with government agencies. This article provides for the first time evidence that contemporary authoritarian regimes appreciate nonprofit organizational legitimacy, albeit still in a highly politicized manner.

Notes

1 See the International Center for Not-for-Profit Law at https://www.icnl.org/resources/civic-freedom-monitor/russia.

2 See the International Center for Not-for-Profit Law at https://www.icnl.org/resources/civic-freedom-monitor/egypt.

3 See China Statistical Yearbooks at http://www.stats.gov.cn/english/statisticaldata/annualdata.

4 See China Statistical Yearbooks.

5 For example, Adena et al. (2019) term the standard-setting by the BBB Wise Giving Alliance, Charity Navigator, and CBF-Keur as certification, while Bekkers (2003) and Hao and Neely (2019) call it accreditation.

6 In 2011, a young lady named Guo Meimei showed off her luxurious lifestyle on the Internet while claiming a business affiliation with the Red Cross Society of China. This scandal triggered public doubt regarding corruption and misconduct of Chinese NGOs.

7 See von Schnurbein and Fritz (2017) for a discussion on the two drivers––nature and nurture for nonprofit revenue diversification.

8 Accessible at https://github.com/ma-ji/RICF.

9 Accessible at http://doi.org/10.13140/RG.2.2.35141.55525.

10 Accessible at https://static-content.springer.com/esm/art%3A10.1007%2Fs41111-018-0094-2/MediaObjects/41111_2018_94_MOESM1_ESM.xlsx.

11 Prior studies usually assume that governmental and quasi-governmental NGOs are politically embedded in the same way and treated them as government-organized NGOs. Therefore, political connections are usually operationalized into a dichotomous variable. For example, a foundation is either politically embedded or not (Ni and Zhan 2017) or an NGO is either government-organized or not (Li, Lo, and Tang 2017). Models 6 and 8 indicate that combining governmental and quasi-governmental foundations may inaccurately estimate the relationship between nonprofit evaluation and government grants. This is because governmental connections alone can drive the nonprofit evaluation variable to be significant and positive (see the small p value for nonprofit evaluation in Model 8). In this case, the interpretation is that passing nonprofit evaluation increases the odds for politically connected foundations, including both governmental and quasi-governmental foundations, to receive government grants. However, Model 6 shows the nonprofit evaluation variable is not significant among quasi-governmental foundations. In sum, the distinction between governmental foundations and quasi-governmental foundations is of necessity and avoids the loss of interesting nuances.

12 See King and Zeng (2001) for a discussion on rare events.

13 For example, the coefficient for nonprofit evaluation in the penalized logit model for the full sample was 0.381 at p = 0.016, meaning passing the nonprofit evaluation may increase the odds of receiving government grants by 46.4%. Among governmental foundations, the coefficient for the same variable was 0.557 at p= 0.002, meaning the odds increase by 74.6%. In sum, only a small discrepancy exists between the results reported by standard logit models and penalized logit models.

Additional information

Funding

Beijing Yifang Foundation; Zhejiang Dunhe Foundation.