Data Uncertainty in General Equilibrium
AbstractIn this paper, using recent empirical results regarding the statistical properties of macroeconomic data revisions, we study the effects of data revisions in a general equilibrium framework. We find that the presence of data revisions, or data uncertainty, creates a precautionary motive and causes significant changes in the decisions of agents. We also find that the model with revisions captures some aspects of the business cycle dynamics of the US data better than the benchmark model with no revisions. Using our model we measure the cost of having data revisions to be about $33 billion, $5 billion of which can be recovered by eliminating the predictability of revisions. Comparing these numbers with the budgets of the major statistical agencies in the US, we conclude that any money spent on the improvement of data collection would be well worth it
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 131.
Date of creation: 11 Aug 2004
Date of revision:
Neoclassical growth model; productivity; forecasting; data uncertainty;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data
- E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-08-16 (All new papers)
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