The contribution of this paper is to offer a rationale for the observed seasonal pattern in house prices. We first document seasonality in house prices for the US and the UK using formal statistical tests and illustrate its quantitative importance. In the second part of the paper we employ a...

We provide an analysis that might help distinguish rationally justified movements in house prices from potentially non-rational movements, using a two-sector business cycle model, in which investment in housing is subject to collateral constraints. A large portion of the evolution of U.S. house...

Based on a stock-flow model of the housing market we estimate the relationship of house prices and explanatory macroeconomic variables in Germany using a regional panel dataset for 402 administrative districts. Using regional data exploits the variation across local housing markets and overcomes...

In this paper, we review the German practice of imputing the costs of owner-occupied housing by increasing the relative weight of actual rents in the CPI. As the structure of owner-occupied housing differs substantially from that of rental housing, this variant of the imputation method may cause...

In this paper we examine the sustainability of euro area public finances against the backdrop of population ageing. We critically assess the widely used projections of the Working Group on Ageing Populations (AWG) of the EU's Economic Policy Committee and argue that ageing costs may be higher...

The carry-over effect is the advance contribution of the old year to growth in the new year. Among practitioners the informative content of the carry-over effect for short-term forecasting is undisputed and is used routinely in economic forecasting. In this paper, the carry-over effect is...

Recently, several institutions have increased their forecast horizons, and many institutions rely on their past forecast errors to estimate measures of forecast uncertainty. This work addresses the question how the latter estimation can be accomplished if there are only very few errors available...

This paper compares two single-equation approaches from the recent nowcast literature: Mixed-data sampling (MIDAS) regressions and bridge equations. Both approach are used to nowcast a low-frequency variable such as quarterly GDP growth by higher-frequency business cycle indicators. Three...

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...

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...