Demand-Supply Imbalance, Unexpected Imports and Unintended Inventory Accumulation

Caton, Christopher; Higgins, Charlotte

doi:10.2307/2526090

Cited by 11 publications

(4 citation statements)

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“…Both equations are ad hoc in the flexible accelerator tradition. The inventories equation for commodity exports also includes a role for rainfall in the rural sector and the domestic good inventories equation includes an imports disequilibrium effect in the tradition of the N I F model (Caton and Higgins, 1974).…”

Section: Estimation Resultsmentioning

confidence: 99%

An Overview of the Murphy Model*

Murphy

1988

Australian Economic Papers

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Section: Estimation Resultsmentioning

confidence: 99%

An Overview of the Murphy Model*

Murphy

1988

Australian Economic Papers

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“…(c) Non-farm irzveiitoriesthe non-farm inventory ( S N N ) equation was developed initially by Caton and Higgins (1974) and was based on inventory movements split into three components:…”

Section: Specific Exainplesmentioning

confidence: 99%

Macroeconometric Model Evaluation, With Special Reference to the Nif88 Model*

Simes

1988

Australian Economic Papers

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MACRO-ECONOMIC MODEL EVALUATION 31 through judicious modifications and use of constant adjustments. However, it is important for the wider acceptance of the worth of such a model that it be subjected to outside scrutiny in an unmodified form. BACKGROUNDMost econometric models are developed with two objectives in mind: for prediction under a range of shocks; and for policy prescription.Other objectives, such as use as a teaching tool or to discriminate between alternative theories, are usually of lesser interest in practice.While it may be desirable to place the evaluation process into an explicit decision theoretical framework. this has proved quite difficult, even in the single equation case.y Thus, a n essential part of the evaluation will centre around standard (frequentist) statistical properties of the model. More precisely, what statistical criteria can be used to determine whether a model is useful or even whether one model is better than another for a given task? A natural way to develop such tests would seem to rely on properties of dynamic simulations of the complete system (i.e. along the lines of various tests for individual equations which are based on either within sample properties or the predictive ability of the model). Unfortunately, as has been argued effectively by Pagan (1986) and Chong and Hendry (1986), dynamic simulations may be of limited use and indeed, at times, cloud the issues."' In particular, consider the linear model: which, given A ( L ) is invertible, has a final form:The residuals from the dynamic simulations are then: fit = ( A ( L ) ) -l u t . ( 3 )Under general conditions the fit are linear combinations of the u t . Thus, the dynamic simulation residuals in principle convey n o information that is not present in the errors of the structural equations. In addition, it is clear from equation (3) that the fitwill be serially correlated making the development of formal tests difficult.Accordingly, tests on dynamic residuals from the system will be at best difficult. Consequently, formal statistical evaluation in NIF88 relies heavily on the testing of 'See Efron (1986), and the subsequent comments, for a discussion of why Irequentist techniques continue to dominate practical work."These authors emphasise that dynamic simulations will have their uses. including facilitating an understanding of the long-run properties of the models. However, they argue that they are not useful for more formal statistical validation.

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“…A common experience when estimating import demand functions is that the estimated price elasticities are often statistically insignificant and usually quite small, see Adams et al [ [2]. These results have meant that there is not a great deal of statistical evidence, especially for Australia, to support the view that import quantities respond quickly and significantly to changes in relative prices.…”

Section: The Economic Record Marchmentioning

confidence: 99%