Business Economics and Public Policy Papers

Document Type

Working Paper

Date of this Version

8-11-2003

Publication Source

FRB International Finance Discussion Paper No.767

DOI

10.2139/ssrn.425003

Abstract

We study whether aggregation residuals in U.S. private investment in information technology (IT) exhibit a predictable pattern that is consistent with Hicks' composite-good theorem and that may be used for forecasting. To determine whether one can extract such a pattern, we apply the general-to-specific strategy developed by Krolzig and Hendry (2001). This strategy combines ordinary least squares with a computer-automated algorithm that selects a specification based on coefficients' statistical significance, residual properties, and parameter constancy. Then, we derive the testable implications from Hicks' theorem and evaluate them with econometric formulations; we find qualified support for these implications. Having obtained these formulations, we evaluate their ex-post predictive accuracy and compare it to that of an autoregressive model. The key finding is that ignoring movement in relative prices results in a loss of information for predicting aggregation residuals.

Keywords

aggregation errors, fisher aggregates, divisia aggregate, general-to-specific

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Date Posted: 27 November 2017