Policy Labels and Investment Decision-making

Much attention in recent years has turned to the potential of behavioural insights to improve the performance of government policy. One behavioural concept of interest is the effect of a cash transfer label on how the transfer is spent. The Winter Fuel Payment (WFP) is a labelled cash transfer to offset the costs of keeping older households warm in the winter. Previous research has shown that households spend a higher proportion of the WFP on energy expenditures due to its label (Beatty et al., 2011). If households interpret the WFP as money for their energy bills, it may reduce their willingness to undertake investments which help achieving the same goal, such as the adoption of renewable energy technologies. In this paper we show that the WFP has distortionary effects on the renewable technology market. Using the sharp eligibility criteria of the WFP in a Regression Discontinuity Design, this analysis finds a reduction in the propensity to install renewable energy technologies of around 2.7 percentage points due to the WFP. This is a considerable number. It implies that 62% of households (whose oldest member turns 60) would have invested in renewable energy but refrain to do so after receiving the WFP. This analysis suggests that the labelling effect spreads to products related to the labelled good. In this case, households use too much energy from sources which generate pollution and too little from relatively cleaner technologies.

Information Design

There are two ways of creating incentives for interacting agents to behave in a desired way. One is by providing appropriate payoff incentives, which is the subject of mechanism design. The other is by choosing the information that agents observe, which we refer to as information design. We consider a model of symmetric information where a designer chooses and announces the information structure about a payoff relevant state. The interacting agents observe the signal realizations and take actions which affect the welfare of both the designer and the agents. We characterize the general finite approach to deriving the optimal information structure for the designer - the one that maximizes the designer's ex ante expected utility subject to agents playing a Bayes Nash equilibrium. We then apply the general approach to a symmetric two state, two agent, and two actions environment in a parameterized underlying game and fully characterize the optimal information structure: it is never strictly optimal for the designer to use conditionally independent private signals; the optimal information structure may be a public signal or may consist of correlated private signals. Finally, we examine how changes in the underlying game affect the designer's maximum payoff. This exercise provides a joint mechanism/information design perspective.