We consider optimal non-linear income tax problems when the social welfare function only depends on ranks as in Yaari (1987) and weights agree with the Lorenz quasi-ordering. Gini, S-Gini, and a class putting more emphasis on inequality in the upper part of the distribution belong to this set....

Credence goods markets – like for health care or repair services – with their informational asymmetries between sellers and customers are prone to fraudulent behavior of sellers and resulting market inefficiencies. We present the first model that considers both diagnostic uncertainty of...

How does uncertainty affect the costs of raising finance in the bond market and via bank loans? Empirically, this paper finds that heightened uncertainty is accompanied by an increase in corporate bond yields and a decrease in bank lending rates. This finding can be explained with a model that...

We develop a method for directly modeling cointegrated multivariate time series that are observed in mixed frequencies. We regard lower-frequency data as regularly (or irregularly) missing and treat them with higher-frequency data by adopting a state-space model. This utilizes the structure of...

This paper introduces a multivariate long-memory model with structural breaks. In the proposed framework, time series exhibit possibly fractional orders of integration which are allowed to be different in each subsample. The break date is endogenously determined using a procedure which minimises...

This paper considers a general model which allows for both deterministic and stochastic forms of seasonality, including fractional (stationary and nonstationary) orders of integration, and also incorporating endogenously determined structural breaks. Monte Carlo analysis shows that the suggested...

This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the...

For forecasting and economic analysis many variables are used in logarithms (logs). In time series analysis this transformation is often considered to stabilize the variance of a series. We investigate under which conditions taking logs is beneficial for forecasting. Forecasts based on the...

In this paper we specify a multi-factor long-memory process that enables us to estimate the fractional differencing parameters at each frequency separately, and adopt this framework to model quarterly prices in three European countries (France, Italy and the UK). The empirical results suggest...

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...