This paper discusses pooling versus model selection for now- and forecasting in the presence of model uncertainty with large, unbalanced datasets. Empirically, unbalanced data is pervasive in economics and typically due to different sampling frequencies and publication delays. Two model classes...

Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decision making under uncertainty. The probabilistic assessment about the set of possible trajectories that...

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model speci.cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coeØ cients, whereas...

We propose a classical approach to estimate factor-augmented vector autoregressive (FAVAR) models with time variation in the factor loadings, in the factor dynamics, and in the variance-covariance matrix of innovations. When the time-varying FAVAR is estimated using a large quarterly dataset of...

Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the regressors is large, distributed lag functions are typically...

This paper compares different ways to estimate the current state of the economy using factor models that can handle unbalanced datasets. Due to the different release lags of business cycle indicators, data unbalancedness often emerges at the end of multivariate samples, which is sometimes...

We study differences in the price paid for liquidity across banks using price data at the individual bank level. Unique to this paper, we also have data on individual banks' reserve requirements and actual reserve holdings, thus allowing us to gauge the extent to which a bank is short or long...

We use a unique and comprehensive data set on open-end real estate funds in Germany to study a liquidity crisis that hit this industry between 2005 and 2006. Since this industry is comparably unregulated our data set permits us to contrast competing explanations of liquidity crisis. We find that...

Open-end real estate funds are of particular importance in the German bank- dominated financial system. However, recently the German open-end fund industry came under severe distress which triggered a broad discussion of required regulatory interventions. This paper gives a detailed description...

Following Diamond (1997) and Fecht (2004) we use a model in which financial market access of households restrains the efficiency of the liquidity insurance that banks' deposit contracts provide to households that are subject to idiosyncratic liquidity shocks. But in contrast to these approaches...