The behavioural aspect of green technology investments: a general positive model in the context of heterogeneous agents

TL;DR

This paper presents a behavioral model of green technology investments showing that considering behavioral factors significantly reduces expected adoption rates compared to normative models, highlighting the importance of behavioral insights in policy design.

Contribution

It introduces a simple, heterogeneous-agent model integrating behavioral responses to better predict green technology adoption rates.

Findings

Behavioral factors reduce adoption estimates from 81% to 20%.

Heterogeneous agent perspectives provide realistic macro adoption rates.

Policy effectiveness varies significantly when behavioral aspects are included.

Abstract

Studies report that firms do not invest in cost-effective green technologies. While economic barriers can explain parts of the gap, behavioural aspects cause further under-valuation. This could be partly due to systematic deviations of decision-making agents' perceptions from normative benchmarks, and partly due to their diversity. This paper combines available behavioural knowledge into a simple model of technology adoption. Firms are modelled as heterogeneous agents with different behavioural responses. To quantify the gap, the model simulates their investment decisions from different theoretical perspectives. While relevant parameters are uncertain at the micro-level, using distributed agent perspectives provides a realistic representation of the macro adoption rate. The model is calibrated using audit data for proposed investments in energy efficient electric motors. The inclusion of behavioural factors reduces significantly expected adoption rates: from 81% using a normative optimisation perspective, down to 20% using a behavioural perspective. The effectiveness of various policies is tested.