Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the...

We consider the estimation of nonlinear models with mismeasured explanatory variables, when information on the marginal distribution of the true values of these variables is available. We derive a semi-parametric MLE that is shown to be consistent and asymptotically normally distributed. In a...

This paper examines the incentive effects caused by the interactions between unemployment insurance (UI) and sickness insurance (SI), two important components of Sweden's social insurance system. There are two main topics of interest: how the sickness report rate and the length of the subsequent...

This paper looks at a specific type of moral hazard that arises in the interplay between two large public insurance systems in Sweden, namely the sickness insurance (SI) and the unemployment insurance (UI). Moral hazard can arise from the benefit size structure as for some unemployed persons,...

This paper examines the incentive effects caused by the interactions between unemployment insurance (UI) and sickness insurance (SI), two important components of Sweden's social insurance system. There are two main topics of interest: how the sickness report rate and the length of the subsequent...

This paper evaluates two Swedish active labour market programmes for youth, namely youth practice and labour market training. A non-parametric matching approach is applied to estimate the average program effects. Moreover, the results obtained by matching are compared to results from standard...

In this paper, we use Bayesian nonparametric learning to estimate the skill of actively managed mutual funds and also to estimate the population distribution for this skill. A nonparametric hierarchical prior, where the hyperprior distribution is unknown and modeled with a Dirichlet process...

Consider an observed binary regressor D and an unobserved binary variable D*, both of which affect some other variable Y. This paper considers nonparametric identification and estimation of the effect of D on Y , conditioning on D* = 0. For example, suppose Y is a person's wage, the unobserved D...

How do people learn? We assess, in a distribution-free manner, subjects' learning and choice rules in dynamic two-armed bandit (probabilistic reversal learning) experiments. To aid in identification and estimation, we use auxiliary measures of subjects' beliefs, in the form of their...

Using recent results in the measurement error literature, we show that the official U.S. unemployment rates substantially underestimate the true levels of unemployment, due to misclassification errors in labor force status in Current Population Surveys. Our closed-form identification of the...