Selling Latin America

Study week on the econometric approach to development planning

Bibliographic data

Monograph

Identifikator:: 101030657X

URN:: urn:nbn:de:zbw-retromon-41609

Document type:: Monograph

Author:: Aughinbaugh, William E.

Title:: Selling Latin America

Place of publication:: Boston

Publisher:: Small, Maynard & Company Publishers

Year of publication:: 1915

Scope:: 1 Online-Ressource (VI, 408 Seiten)

Digitisation:: 2018

Collection:: Economics Books

Usage license:: Get license information via the feedback formular.

Chapter

Document type:: Monograph

Structure type:: Chapter

Title:: XXII. The salesman and the customer

Collection:: Economics Books

SEMAINE D'ÉTUDE SUR LE ROLE DE L'ANALYSE ECONOMETRIQUE ETC. an criteria given and that it may be better to accept some incon- sistency by using endogenous variables with lower lags. Fi nally, after going only a few periods back, the chances are high in practice that adding an exogenous variable with a still higher lag adds a variable which is very highly correlated with the instruments already included and therefore adds little inde- pendent causal information (*). While the use of lagged exogenous variables is therefore highly desirable, it may not be of sufficient practical help to allow the search for instru mental variables to end. Whatever collection of current exogenous, lagged exogenous and (none, some, or all) lagged endogenous variables are used however, the multicollinearity difficulty just encountered tends to arise. Some method must be found for dealing with it. One set of interesting suggestions in this area has been provided by KLOEK and MENNES (°°). Essentially, they pro- pose using principal component analysis in various ways on the set of eligible instruments in order to secure orthogonal linear combinations. The endogenous variables are then replaced by their regressions on these linear combinations (possibly together with the eligible instruments actually ap- pearing in the equation to be estimated), and the dependent variable regressed on these surrogates and the instruments appearing in the equation. Variants of this proposal are alsc examined. This suggestion has the clear merit of avoiding multicol- linearity, as it is designed to do. However, it may eliminate such multicollinearity in an undesirable way. If multicollinear- ity is present in a regression equation, at least one of the variables therein is adding little causal information to that already contained in the other variables. In replacing a given endogenous variable with its regression on a set of instruments, Fa. (*) This is especially likely if the exogenous variables are principally ones such as population which are mainly trends. (*) Kroek and MEexNEs [17] 6] Fisher - pag. 47

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