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) processes. The linear VAR model is extendedto permit cointegration, a range of deterministic processes, equilibrium restrictions …
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All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct...
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with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that … correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the … hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the innite …
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A Bayesian model averaging procedure is presented that makes use of a finite mixture of many model structures within the class of vector autoregressive (VAR) processes. It is applied to two empirical issues. First, stability of the Great Ratios in U.S. macro-economic time series is investigated,...
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We develop a general framework for measuring biases in expectation formation. The method is based on the insight that biases can be inferred from the response of forecast errors to past news. Empirically, biases are measured by flexibly estimating the impulse response function of forecast...
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