This paper discusses the forecasting performance of alternative factor models based on a large panel of quarterly time series for the german economy. One model extracts factors by static principals components analysis, the other is based on dynamic principal components obtained using frequency...

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. To account for temporal instabilities in this relationship, this paper discusses an extension to MIDAS with time-varying parameters, which...

We explore the effects of chief executive officers' (CEOs') personal dominance - an idiosyncratic character trait strongly associated with a desire for influence and control - on two fundamental organizational design decisions: the CEO's span of control (1) and her delegation of responsibilities...

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 onexponential lag polynomials for the coe¢ cients, whereas...

This paper discusses pooling versus model selection for now- and forecasting in the pres-ence of model uncertainty with large, unbalanced datasets. Empirically, unbalanceddata is pervasive in economics and typically due to di¤erent sampling frequencies andpublication delays. Two model classes...

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 considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant...

In diesem Papier werden eine Reihe von Frühindikatoren für die Entwicklung der Ausrüstungs-, Wirtschaftsbau- und Wohnungsbauinvestitionen in Deutschland untersucht. Die Indikatoren werden auf Basis theoretischer Erwägungen oder wegen ihres technischen Zusammenhangs zur Investitionstätigkeit...