arXiv 4 Dec 2020 · Econometrics · publishedInternational Journal of Forecasting (2024) · 5 citations (OpenAlex)
arXiv:2012.02601 · PDF · DOI · OpenAlex · Extracted main text
This paper presents a new way to account for downside and upside risks when producing density nowcasts of GDP growth. The approach relies on modelling location, scale and shape common factors in real-time macroeconomic data. While movements in the location generate shifts in the central part of the predictive density, the scale controls its dispersion (akin to general uncertainty) and the shape its asymmetry, or skewness (akin to downside and upside risks). The empirical application is centred on US GDP growth and the real-time data come from Fred-MD. The results show that there is more to real-time data than their levels or means: their dispersion and asymmetry provide valuable information for nowcasting economic activity. Scale and shape common factors (i) yield more reliable measures of uncertainty and (ii) improve precision when macroeconomic uncertainty is at its peak.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Delle Monache, D., A. De Polis, and I. Petrella (2023) Modeling and Forecasting Macroeconomic Downside Risk | 0.899 | 11 | 4 | 73% |
| 2 | Mariano, R. S. and Y. Murasawa (2003) A new coincident index of business cycles based on monthly and quarterly series | 0.874 | 5 | 2 | 100% |
| 3 | Creal, D., S. J. Koopman, and A. Lucas (2013) Generalized autoregressive score models with applications | 0.811 | 4 | 2 | 100% |
| 4 | Diebold, F. X., T. A. Gunther, and A. S. Tay (1998) Evaluating density forecasts with applications to financial risk management | 0.811 | 4 | 2 | 100% |
| 5 | Rossi, B. and T. Sekhposyan (2019) Alternative tests for correct specification of conditional predictive densities | 0.811 | 4 | 2 | 100% |
| 6 | Harvey, D., S. Leybourne, and P. Newbold (1997, June) (1997) Testing the equality of prediction mean squared errors | 0.737 | 3 | 2 | 100% |
| 7 | Antolín-Díaz, J., T. Drechsel, and I. Petrella (2024, January) (2024) Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails | 0.737 | 3 | 2 | 100% |
| 8 | Buccheri, G., G. Bormetti, F. Corsi, and F. Lillo (2023) Robust Recursive Filtering and Smoothing | 0.737 | 3 | 2 | 100% |
| 9 | Creal, D., B. Schwaab, S. J. Koopman, and A. Lucas (2014) Observation-driven mixed-measurement dynamic factor models with an application to credit risk | 0.737 | 3 | 2 | 100% |
| 10 | Ghysels, E., A. Sinko, and R. Valkanov (2007) Midas regressions: Further results and new directions | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 46 scored citations.