
This paper treats programs in which firms voluntarily agree to meet environmental standards as "green clubs": clubs, because they provide non-rival but excludable reputation benefits to participating firms; green, because they also generate environmental public goods. The model illuminates a central tension between the congestion externality familiar from conventional club theory and the free-riding externality familiar from the theory on private provision of public goods. We compare three common program sponsors--governments, industry, and environmental groups. We find that if monitoring of the club standard is perfect, a government constrained from regulating club size may prefer to leave sponsorship to industry if public-good benefits are sufficiently low, or to environmentalists if public-good benefits are sufficiently high. If monitoring is imperfect, an important question is whether consumers can infer that a club is too large for its standard to be credible. If they can, then the government may deliberately choose an imperfect monitoring mechanism as a way of regulating club size indirectly. If they cannot, then this reinforces the government's preference for delegating sponsorship.
jel: jel:D71, jel: jel:H41, jel: jel:Q58
jel: jel:D71, jel: jel:H41, jel: jel:Q58
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 47 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
