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Titlebook: New Introduction to Multiple Time Series Analysis; Helmut Lütkepohl Textbook 2005 Springer-Verlag Berlin Heidelberg 2005 Analysis.Dynamic

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Estimation of Vector Autoregressive Processesrocess . All symbols have their usual meanings, that is, ν = (ν.,…, ν.)′ is a (. × 1) vector of intercept terms, the .. are (.) coefficient matrices and .. is white noise with nonsingular covariance matrix Σ.. In contrast to the assumptions of the previous chapter, the coefficients ν, ..,…, .., and
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VAR Order Selection and Checking the Model Adequacy . and we have discussed estimation of the parameters . In deriving the properties of the estimators, a number of assumptions were made. In practice, it will rarely be known with certainty whether the conditions hold that are required to derive the consistency and asymptotic normality of the estimat
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VAR Processes with Parameter Constraintshave their usual meanings. In the investment/income/consumption example considered throughout Chapter 3, we found that many of the coefficient estimates were not significantly different from zero. This observation may be interpreted in two ways. First, some of the coefficients may actually be zero a
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Estimation of Vector Error Correction Modelse of stationary processes. Therefore, in the first section, a simple special case model with no lagged differences and no deterministic terms is considered and different estimation methods for the parameters of the error correction term are treated. For this simple case, the asymptotic properties ca
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Specification of VECMsn rank are typically determined before further restrictions are imposed on the parameter matrices. Moreover, the specification of a VECM usually starts by determining a suitable lag length because, in choosing the lag order, the cointegration rank does not have to be known, whereas many procedures f
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Structural VARs and VECMsAR or VECM and, on the other hand, there are some obstacles in their interpretation. In particular, impulse responses are generally not unique and it is often not clear which set of impulse responses actually reflects the ongoings in a given system. Because the different sets of impulses can be comp
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