We examine the effects of di¤erences in social capital on first and second best transfers to families with children, in an asym- metric information context where the number of births, and the future earning capacity of each child that is born, are random variables. The probability that a couple...

We examine the second-best family policy under the assumption that both the number, and the future earning capacities of the children born to a couple are random variables with probability distributions conditional on unobservable parental actions. Potential parents take their decisions without...

The relationship between government and parents is modelled as a principal-agent problem, with the former in the role of principal and the latter in the role of agents. We make three major points. The first is that, if the well-being of the child depends not only on luck, but also on parental...

The paper innovates on the existing optimal taxation literature by taking fertility as endogenous, and allowing for households to be di¤erentiated by ability to raise children, as well as wage rates. In a context where the government cannot observe personal abilities, fertility behaviour...

We analyse a model of income tax avoidance with heterogenous agents; we assume the presence of a comparison income e¤ect and of a psychic cost (disutility) of tax dodging. In this context, we show two sets of results. First, we study the policy preferences of the agents, and identify a...

Recent empirical work on intergenerational transfers has shown that: i) parents prefer to transfer resources to their children using bequests rather than inter vivos transfers (gifts), and ii) bequests tend to be divided equally, while gifts tend to be directed towards the less well-off...

Should a benevolent social planner subsidise family size? Typically, contributions assuming exogenous fertility yield an a¢rmative answer, while those assuming endogenous fertility do not reach de…nite conclusions. We re-examine the endogenous fertility model, and …nd that when...