A BMS Session: Towards the Natural Environment Agency Theory (NEAT)

Title of Paper: Towards the Natural Environment Agency Theory (NEAT)

Amama Shaukat (Brunel University London)

Rajesh Tharyan (University of Exeter)

Grzegorz Trojanowski (University of Exeter)

Abstract

This paper develops the Natural Environment Agency Theory (NEAT). Viewing the firm as a nexus of contracts, we argue based on public property rights to clean air, water and land, that the firm (agent) has a contract with the society (principal) under which it implicitly agrees not to pollute or degrade these publicly owned natural environmental resources (commons) in the course of its operations. In turn, the society implicitly provides the business with a ‘license to operate'. If, however, the business violates this contract and imposes on the society negative externalities like air, water, or land pollution, which as per NEAT, we term the natural environmental agency costs (NEAC) then the society has the right to demand remedial action (i.e. demand business to internalise its NEAC) or in the worst case, society could revoke the firm’s license to operate.

We propose two mechanisms that potentially mitigates NEAC - bonding and monitoring. Bonding works via the firm’s (costly) environmental commitment actions, such as responsible environmental behaviour (environmental performance) as well the communication of this behaviour (environmental disclosures). Monitoring works via monitoring by outsiders such as media, analysts, etc. and by insiders such as institutional shareholders.

Based on NEAT we predict that environmental commitment (bonding), although potentially costly for the firm, reduces NEAC, resulting in improved stakeholder relations, and consequently improved financial performance and reduced risks. Monitoring in addition to facilitating stronger bonding, also has a direct impact on corporate financial performance (positive) and risk (negative). We test these predictions for US publicly listed firms employing a structural equation modelling (SEM) framework. Our results provide strong support for most of the NEAT-derived hypotheses.

Aims & Objectives