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Download Aggregate Money Demand Functions: Empirical Applications in by Dennis L. Hoffman PDF

By Dennis L. Hoffman

ISBN-10: 9400918143

ISBN-13: 9789400918146

ISBN-10: 9401073082

ISBN-13: 9789401073080

The econometric effects of nonstationary info have huge ranging im­ plications for empirical learn in economics. particularly, those matters have implications for the examine of empirical kin resembling a funds call for func­ tion that hyperlinks macroeconomic aggregates: actual cash balances, genuine source of revenue and a nominal rate of interest. conventional financial idea predicts that those nonsta­ tionary sequence shape a cointegrating relation and for this reason, that the dynamics of a vector approach made out of those variables generates particular styles. Re­ cent econometric advancements designed to deal with nonstationarities have replaced the process empirical study within the sector, yet many basic demanding situations, for instance the difficulty of id, stay. This e-book represents the efforts undertaken by way of the authors lately so one can confirm the implications that nonstationarity has for the examine of mixture cash call for family members. we have now introduced jointly an empirical method that we discover valuable in undertaking empirical study. a number of the paintings was once undertaken through the authors' sabbatical classes and we want to recognize the beneficiant help of Arizona kingdom collage and Michigan kingdom collage respectively. Professor Hoffman needs to recognize the help of the Fulbright-Hays beginning that supported sabbattical learn in Europe and separate help of the Council of a hundred summer time learn application at Arizona kingdom University.

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Extra resources for Aggregate Money Demand Functions: Empirical Applications in Cointegrated Systems

Example text

Consider the identification of {3' on a row by row basis (cointegration vector by cointegration vector). The first row is denoted {3~ and let a priori homogeneous linear restrictions that apply to {3~ be represented by a p x m restriction matrix; ¢, so that {3i ¢ = 0 defines m homogeneous linear restrictions. Clearly, {3~ is identified only when the set of feasible transformation matrices, R, is sufficiently limited by ¢. Normalize by one element of {31 so that the first row of R is Rl = {I, Ri} and then {3~ is identified if and only if Ri = 0 for all feasible basis transformation matrices, R.

If economic theory delivers more information about the long-run relations than it does for the short-run relations, the preferred path to identification may be to first establish the identity of the {3 space. The conditions for identifying the cointegration space using simple linear restrictions on each vector of the space can be derived using an approach that dates from the work of the Cowles Commission. Consider the identification of {3' on a row by row basis (cointegration vector by cointegration vector).

If no additional information about the long-run is forthcoming, the (3 space will in general remain underidentified. As discussed above, restrictions on the space of feasible error correction parameters can sometimes be used to obtain identification. Suppose, for illustration, we knew nothing about the first cointegration vector. However, we had access to information that the (2,1) element is zero as above and, that no adjustments occur in investment as a result of "disequilibria" in the second vector.

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Aggregate Money Demand Functions: Empirical Applications in Cointegrated Systems by Dennis L. Hoffman

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