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Titlebook: Identification in Dynamic Shock-Error Models; Agustin Maravall,Klaus Neumann,Ulrich Steinhardt Book 1979 Springer-Verlag Berlin Heidelberg

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書(shū)目名稱(chēng)Identification in Dynamic Shock-Error Models
編輯Agustin Maravall,Klaus Neumann,Ulrich Steinhardt
視頻videohttp://file.papertrans.cn/461/460828/460828.mp4
叢書(shū)名稱(chēng)Lecture Notes in Economics and Mathematical Systems
圖書(shū)封面Titlebook: Identification in Dynamic Shock-Error Models;  Agustin Maravall,Klaus Neumann,Ulrich Steinhardt Book 1979 Springer-Verlag Berlin Heidelberg
描述Looking at a very simple example of an error-in-variables model, I was surprised at the effect that standard dynamic features (in the form of autocorre- 11 lation. in the variables) could have on the state of identification of the model. It became apparent that identification of error-in-variables models was less of a problem when some dynamic features were present, and that the cathegory of "pre- determined variables" was meaningless, since lagged endogenous and truly exogenous variables had very different identification properties. Also, for‘the models I was considering, both necessary and sufficient conditions for identification could be expressed as simple counting rules, trivial to compute. These results seemed somewhat striking in the context of traditional econometrics literature, and p- vided the original motivation for this monograph. The monograph, therefore, atempts to analyze econometric identification of models when the variables are measured with error and when dynamic features are present. In trying to generalize the examples I was considering, although the final results had very simple expressions, the process of formally proving them became cumbersome and lengthy (
出版日期Book 1979
關(guān)鍵詞Identifikationsverfahren; calculus; econometrics; economics; ?konometrie
版次1
doihttps://doi.org/10.1007/978-3-642-95339-2
isbn_softcover978-3-540-09112-7
isbn_ebook978-3-642-95339-2Series ISSN 0075-8442 Series E-ISSN 2196-9957
issn_series 0075-8442
copyrightSpringer-Verlag Berlin Heidelberg 1979
The information of publication is updating

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0075-8442 f autocorre- 11 lation. in the variables) could have on the state of identification of the model. It became apparent that identification of error-in-variables models was less of a problem when some dynamic features were present, and that the cathegory of "pre- determined variables" was meaningless,
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Autocorrelated Exogenous Variables, White Noise Shock,e to the presence of autocorrelation in the exogenous variables from the ones implied by the presence of autocorrelation in the shock, in this chapter we shall assume that the latter is a white-noise variable.
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Autocorrelated Shock: Autocorrelated Exogenous Variables. The General Model,e proceed to consider a general model where autocorrelation may or may not be present in the shock and in any number of exogenous variables. The analysis of this model brings together the results of all previous chapters.
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Summary,. The dynamics of the model are reflected, on the one hand, in the presence of distributed lags in the structural equation. On the other hand, possible autocorrelations between the exogenous variables and the shock are explained by autoregressive-moving average processes.
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Agustin Maravall,Klaus Neumann,Ulrich Steinhardtacellular senile plaques composed primarily of beta amyloid (Aβ) peptides and intracellular inclusions, termed neurofibrillary tangles, made up of primarily hyperphosphorylated tau protein (Braak and Braak, 1997a, b; Grundke-Iqbal et al., 1986; Selkoe, 2001). In addition, AD brains demonstrate signi
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