Time-varying Models for Macroeconomic Forecasts
This thesis consists of three studies focusing on ways to detect and model time variation among macroeconomic variables. In these three studies, errors with autoregressive moving averages (ARMA), model averaging, and stochastic volatility (SV) are used to investigate the uncertainty and the instability of macroeconomic dynamics. In particular, I expand upon both univariate (autoregressive; AR) and multivariate (vector autoregressive; VAR) time series models. ...[Show more]
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