05061 Abstracts Collection -- Foundations of Semistructured Data

From 06.02.05 to 11.02.05, the Dagstuhl Seminar 05061 ``Foundations of Semistructured Data\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Simple nonparametric inference for first-price auctions via bid spacings

In a classic model of the first-price auction, we propose a nonparametric estimator of the quantile function of bidders' valuations, based on weighted bid spacings. We derive the Bahadur-Kiefer expansion of this estimator with a pivotal influence function and an explicit uniform remainder rate. This expansion allows us to develop a simple algorithm for the associated uniform confidence bands that does not rely on bootstrap. Monte Carlo experiments show satisfactory statistical and computational performance of the estimator and the confidence bands. Estimation and inference for related functionals is also considered

HOW FAR CAN WE FORECAST? FORECAST CONTENT HORIZONS FOR SOME IMPORTANT MACROECONOMIC TIME SERIES

For stationary transformations of variables, there exists a maximum horizon beyond which forecasts can provide no more information about the variable than is present in the unconditional mean. Meteorological forecasts, typically excepting only experimental or exploratory situations, are not reported beyond this horizon; by contrast, little generally-accepted information about such maximum horizons is available for economic variables. In this paper we estimate such content horizons for a variety of economic variables, and compare these with the maximum horizons which we observe reported in a large sample of empirical economic forecasting studies. We find that there are many instances of published studies which provide forecasts exceeding, often by substantial margins, our estimates of the content horizon for the particular variable and frequency. We suggest some simple reporting practices for forecasts that could potentially bring greater transparency to the process of making the interpreting economic forecasts.