Measuring Economic Growth with a Fully Identified Three-Signal Model
Bibliographic Data
| ID | 19317110 |
|---|---|
| Authors | Andrea Civelli (0000-0003-2643-503X, University of Arkansas [email protected]), Arya Gaduh (0000-0001-9234-2662, University of Arkansas, NBER [email protected]), Ahmed Sadek Yousuf (North South University [email protected]) |
| Year | 2024 |
| Pages | 1-30 |
| Publication date | 2024-08-22 |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Review of Economics and Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0034-6535 • E-ISSN: 1530-9142 |
| Publisher | MIT Press (PUBLISHER • US) |
| DOI | 10.1162/rest_a_01489 |
| OpenAlex | W4401872786 |
| Language | EN |
We augment Henderson et al. (2012)'s two-signal model of true GDP growth with a third signal to overcome its underidentification problem. The additional moment conditions from the third signal help fully identify all model parameters without ad-hoc calibrations of the GDP's signal-to-noise ratio. We characterize the necessary properties of the third signal. Using the model, we recover the optimal weight of official GDP in the composite true GDP growth estimates, which varies with the quality of the national statistics. The model improves on existing methodologies that use signals to measure true income
Data mining · Econometrics · Economics · Measure (data warehouse) · Moment (physics) · Noise (video) · Quality (philosophy) · SIGNAL (programming language) · Statistics · Artificial Intelligence · Computer Science · Economic Growth and Productivity · Economic theories and models · Mathematics · Monetary Policy and Economic Impact
| Highly cited | No |
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