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IT investment and Hicks' composite-good theorem: the U.S. experience

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Author Info

  • Jaime Marquez
  • Shing-Yi Wang

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.

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File URL: http://www.federalreserve.gov/pubs/ifdp/2003/767/default.htm
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File URL: http://www.federalreserve.gov/pubs/ifdp/2003/767/ifdp767.pdf
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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 767.

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Date of creation: 2003
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Handle: RePEc:fip:fedgif:767

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Related research

Keywords: Information technology ; Econometric models ; Forecasting;

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  1. Krolzig, Hans-Martin & Hendry, David F., 2001. "Computer automation of general-to-specific model selection procedures," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 831-866, June.
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Cited by:
  1. Michael McMahon & Gabriel Sterne & Jamie Thompson, 2005. "The role of ICT in the global investment cycle," Bank of England working papers 257, Bank of England.

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