Showing 1 - 10 of 13
This paper addresses the relative importance of monetary indicators for forecasting inflation in the euro area in a Bayesian framework. Bayesian Model Averaging (BMA)based on predictive likelihoods provides a framework that allows for the estimation of inclusion probabilities of a particular...
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Distinguishing pure supply effects from other determinants of price and quantity in the market for loans is a notoriously difficult problem. Using German data, we employ Bayesian vector autoregressive models with sign restrictions on the impulse response functions in order to enquire the role of...
Persistent link: https://www.econbiz.de/10012991095
The paper analyses the performance of simple interest rate rules which feature a response to noisy observations of inflation, output and money growth. The analysis is based on a small empirical model of the hybrid New Keynesian type which has been estimated on euro area data by Stracca (2007)....
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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...
Persistent link: https://www.econbiz.de/10012991005
This paper considers factor forecasting with national versus factor forecasting withinternational data. We forecast German GDP based on a large set of about 500 time series, consisting of German data as well as data from Euro-area and G7 countries. For factor estimation, we consider standard...
Persistent link: https://www.econbiz.de/10012991056
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 coe¢ cients,...
Persistent link: https://www.econbiz.de/10012991063
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 di¤erent sampling frequencies and publication delays. Two model classes...
Persistent link: https://www.econbiz.de/10012991069