Avoidance Policies – A New Conceptual Framework

This paper develops a general theoretical framework within which a heterogeneous group taxpayers confront a market that supplies a variety of schemes for reducing tax liability, and uses this framework to explore the impact of a wide range of anti-avoidance policies. Schemes differ in their legal effectiveness and hence in the risks to which they expose taxpayers - risks which go beyond the risk of audit considered in the conventional literature on evasion. Given the individual taxpayer’s circumstances, the prices charged for the schemes and the policy environment, the model predicts (i) whether or not any given taxpayer will acquire a scheme, and (ii) if they do so, which type of scheme they will acquire. The paper then analyses how these decisions, and hence the tax gap, are influenced by four generic types of policy: Disclosure – earlier information leading to faster closure of loopholes; Penalties – introduction of penalties for failed avoidance; Policy Design – fundamental policy changes that design out opportunities for avoidance; Product Register - the introduction of GAARs or mini-GAARs that give greater clarity about how different types of scheme will be treated. The paper shows that when considering the indirect/behavioural effects of policies on the tax gap it is important to recognise that these operate on two different margins. First policies will have deterrence effects – their impact on the quantum of taxpayers choosing to acquire different types schemes as distinct to acquiring no scheme at all. There will be a range of such deterrence effects reflecting the range of schemes available in the market. But secondly, since different schemes generate different tax gaps, policies will also have switching effects as they induce taxpayers who previously acquired one type of scheme to acquire another. The first three types of policy generate positive deterrence effects but differ in the switching effects they produce. The fourth type of policy produces mixed deterrence effects.

Can Early Intervention Policies Improve Well-being? Evidence from a randomized controlled trial

Many authors have proposed incorporating measures of well-being into evaluations of public policy. Yet few evaluations use experimental design or examine multiple aspects of well-being, thus the causal impact of public policies on well-being is largely unknown. In this paper we examine the effect of an intensive early intervention program on maternal well-being in a targeted disadvantaged community. Using a randomized controlled trial design we estimate and compare treatment effects on global well-being using measures of life satisfaction, experienced well-being using both the Day Reconstruction Method (DRM) and a measure of mood yesterday, and also a standardized measure of parenting stress. The intervention has no significant impact on negative measures of well-being, such as experienced negative affect as measured by the DRM and global measures of well-being such as life satisfaction or a global measure of parenting stress. Significant treatment effects are observed on experienced measures of positive affect using the DRM, and a measure of mood yesterday. The DRM treatment effects are primarily concentrated during times spent without the target child which may reflect the increased effort and burden associated with additional parental investment. Our findings suggest that a maternal-focused intervention may produce meaningful improvements in experienced well-being. Incorporating measures of experienced affect may thus alter cost-benefit calculations for public policies.

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.