Yukang Jiang, Xueqin Wang, Zhixi Xiong, Haisheng Yang, Ting Tian
arXiv 31 Jul 2022 · Econometrics
arXiv:2209.05998 · PDF · DOI · OpenAlex · Extracted main text
The paper proposes a time-varying parameter global vector autoregressive (TVP-GVAR) framework for predicting and analysing developed region economic variables. We want to provide an easily accessible approach for the economy application settings, where a variety of machine learning models can be incorporated for out-of-sample prediction. The LASSO-type technique for numerically efficient model selection of mean squared errors (MSEs) is selected. We show the convincing in-sample performance of our proposed model in all economic variables and relatively high precision out-of-sample predictions with different-frequency economic inputs. Furthermore, the time-varying orthogonal impulse responses provide novel insights into the connectedness of economic variables at critical time points across developed regions. We also derive the corresponding asymptotic bands (the confidence intervals) for orthogonal impulse responses function under standard assumptions.
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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 | Hauzenberger, N. and M. Pfarrhofer (2021) Bayesian state-space modeling for analyzing heterogeneous network effects of us monetary policy | 0.644 | 2 | 2 | 100% |
| 2 | Lütkepohl, H (2005) New introduction to multiple time series analysis | 0.644 | 2 | 2 | 100% |
| 3 | Lütkepohl, H., A. Staszewska-Bystrova, and P. Winker (2020) Constructing joint confidence bands for impulse response functions of var models–a review | 0.644 | 2 | 2 | 100% |
| 4 | Sims, C. A (1980) Macroeconomics and reality | 0.644 | 2 | 2 | 100% |
| 5 | Frühwirth-Schnatter, S. and H. Wagner (2010) Stochastic model specification search for gaussian and partial non-gaussian state space models | 0.511 | 2 | 1 | 100% |
| 6 | Pesaran, M. H., T. Schuermann, and S. M. Weiner (2004) Modeling regional interdependencies using a global error-correcting macroeconometric model | 0.511 | 2 | 1 | 100% |
| 7 | Hochreiter, S. and J. Schmidhuber (1997, 11) (1997) Long Short-Term Memory | 0.405 | 1 | 1 | 100% |
| 8 | Ankargren, S., M. Unosson, and Y. Yang (2020) A flexible mixed-frequency vector autoregression with a steady-state prior | 0.405 | 1 | 1 | 100% |
| 9 | Breiman, L (2001) Random forests | 0.405 | 1 | 1 | 100% |
| 10 | Chung, J., C. Gulcehre, K. Cho, and Y. Bengio (2014) Empirical evaluation of gated recurrent neural networks on sequence modeling | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 18 scored citations.