Study week on the econometric approach to development planning

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Monograph

Identifikator:: 1824422792

URN:: urn:nbn:de:zbw-retromon-217476

Document type:: Monograph

Title:: Study week on the econometric approach to development planning

Place of publication:: Amsterdam [u.a.]

Publisher:: North-Holland Publ. Co. [u.a.]

Year of publication:: 1965

Scope:: XLVII, 1259 S.; graph. Darst.

Digitisation:: 2022

Collection:: Economics Books

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Document type:: Monograph

Structure type:: Chapter

Title:: Dynamic structure and estimation in economy-wide econometric models / FranklinM. Fisher, Massachuetts Institute of Technology - Cambridge, Mass. - U.S.A.

Collection:: Economics Books

SEMAINE D’ ETUDE SUR LE ROLE DE L’ANALYSE ECONOMETRIQUE ETC, 403 observations generally available relative to the number of pre- determined variables, if all lagged endogenous variables are treated as predetermined. In addition, if lagged endogenous variables are so treated, then we have already seen that such treatment raises consider- able difficulties in the likely presence of serial correlation of the disturbances. On the other hand, economy-wide models are generally sufficiently closed to make their equations uniden- tifiable if only truly exogenous variables are treated as instru- ments. We shall discuss the problems raised by serial correlation in the next section which will be concerned with the question of how instrumental variables should be chosen in practice to avoid inconsistency. In the present section, we shall discuss the properties of the limited-information estimators ignoring these problems. Such a discussion is not rendered irrelevant by the practical difficulty of using all variables that are not current endogenous ones as instruments when the number of observations is relatively limited. This is so because given the variables which are to be treated as predetermined, treatment of all remaining variables as endogenous results in a situation in which every known limited-information estimator has its pre- cise counterpart (#2). Thus, for example, if only certain lagged endogenous and exogenous variables are to be used, replacing every other (save the normalized one) in a given equation by its value as computed from a multiple regression on the instru- ments and then regressing the normalized variable on the re- sulting variables provides the exact analogue of two-stage least squares. Of course. in such a situation, and especially where serial (3) It must be admitted, however, that if different predetermined va- riables are used in replacing each included endogenous variable (as suggested below), them it is not clear how limited-information maximum likelihood carries over to such cases. Fortunately, this will not matter for our purposes 61 Fisher - pag. 1g

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