Publications

The recently published Household Finance and Consumption Survey has revealed large differences in wealth inequality between the countries of the Euro area. We find a strong negative correlation between wealth inequality and homeownership rates across countries. We use two decomposition methods to shed more light on this correlation. First, a Gini decomposition by homeownership status shows that the negative relationship is mostly driven by large between-group inequality across owners and renters. Second, to control for other observables, we conduct a detailed counterfactual decomposition of cross-country inequality differences. We confirm the major role for homeownership rates in accounting for the wealth inequality differences. Our analysis suggests that the cross-country variation is mostly driven by differences in the savings behavior of households in the bottom half of the wealth distribution and that those differences in savings are to a large extent channeled through housing wealth.

We derive a funding liquidity measure based on synthetic borrowing in the S&P 500 derivative markets. Our measure captures funding constraints of option liquidity providers and affects importantly the returns of leveraged managed portfolios. Hedge funds with negative exposure to changes in the funding liquidity earn high returns in normal times and low returns in crises periods when funding liquidity deteriorates. The results are not driven by the existing measures of funding or market liquidity. To an extent, our funding liquidity measure also affects leveraged closed-end mutual funds and asset classes where leveraged investors are marginal investors.

Privacy regulations can affect the willingness to collect personal health data that may be disclosed to insurers. Perfect privacy cannot always be guaranteed. Consequently, people may refrain from collecting personal health data. This paper provides a theoretical and experimental analysis of the importance of privacy regulations for information acquisition and disclosure behavior. We contrast three institutional settings in a simple game of persuasion: Disclosure Duty of collected data, Perfect Privacy and Imperfect Privacy. Under Perfect Privacy there exists a unique proper equilibrium with complete information acquisition. For Disclosure Duty no information acquisition is predicted. Imperfect Privacy can result in multiple equilibria. Our laboratory experiment confirms the qualitative differences on information acquisition for Perfect Privacy and Disclosure Duty. Behavior under Imperfect Privacy turns out to be very similar to Perfect Privacy: Imperfect Privacy does not stop people from collecting personal information. We discuss possible reasons for the observed behavior.

The asymptotic efficiency of indirect estimation methods, such as the efficient method of moments and indirect inference, depends on the choice of the auxiliary model, which is somehow ad hoc and based on an educated guess. We introduce an Akaike–type class of information criteria that helps the user in this choice among nested and non–nested auxiliary models. A Monte Carlo and an empirical illustration show the usefulness of the criteria.

Marriage has declined since 1960, with the drop being bigger for non-college educated individuals versus college educated ones. Divorce has increased, more so for the non-college educated. Additionally, positive assortative mating has risen. Income inequality among households has also widened. A unified model of marriage, divorce, educational attainment and married female labor-force participation is developed and estimated to fit the postwar U.S. data. Two underlying driving forces are considered: technological progress in the household sector and shifts in the wage structure. The analysis emphasizes the joint role that educational attainment, married female labor-force participation, and assortative mating play in determining income inequality.

European Monetary Union (EMU) member countries' forecasts are often combined to obtain the forecasts of the Euro area macroeconomic aggregate variables. The aggregation weights which are used to produce the aggregates are often considered as combination weights. This paper investigates whether using different combination weights instead of the usual aggregation weights can help to provide more accurate forecasts. In this context, we examine the performance of equal weights, the least squares estimators of the weights, the combination method recently proposed by Hyndman et al. (2011) and the weights suggested by shrinkage methods. We find that some variables like real GDP and GDP deflator can be forecasted more precisely by using flexible combination weights. Furthermore, combining only forecasts of the three largest European countries helps to improve the forecasting performance. The persistence of the individual data seems to play an important role for the relative performance of the combination.