Yunyun Wang, Tatsushi Oka, Dan Zhu
arXiv 9 Mar 2023 · Econometrics
arXiv:2303.04994 · PDF · DOI · OpenAlex · Extracted main text
Vector autoregression is an essential tool in empirical macroeconomics and finance for understanding the dynamic interdependencies among multivariate time series. In this study, we expand the scope of vector autoregression by incorporating a multivariate distributional regression framework and introducing a distributional impulse response function, providing a comprehensive view of dynamic heterogeneity. We propose a straightforward yet flexible estimation method and establish its asymptotic properties under weak dependence assumptions. Our empirical analysis examines the conditional joint distribution of GDP growth and financial conditions in the United States, with a focus on the global financial crisis. Our results show that tight financial conditions lead to a multimodal conditional joint distribution of GDP growth and financial conditions, and easing financial conditions significantly impacts long-term GDP growth, while improving the GDP growth during the global financial crisis has limited effects on financial conditions.
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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 | Adrian, T., N. Boyarchenko, and D. Giannone (2021) Multimodality in macrofinancial dynamics | 1.000 | 7 | 4 | 100% |
| 2 | Rossi, B. and T. Sekhposyan (2019) Alternative tests for correct specification of conditional predictive densities | 0.874 | 5 | 2 | 100% |
| 3 | van der Vaart, A. and J. Wellner (1996) Weak convergence and empirical processes: with applications to statistics | 0.874 | 5 | 2 | 100% |
| 4 | Sims, C. A (1980) Macroeconomics and Reality | 0.811 | 4 | 2 | 100% |
| 5 | Blanchard, O. J. and D. Quah (1989) The dynamic effects of aggregate demand and supply disturbances | 0.644 | 2 | 2 | 100% |
| 6 | Chavleishvili, S. and S. Manganelli (2019) Forecasting and stress testing with quantile vector autoregression | 0.644 | 2 | 2 | 100% |
| 7 | Chernozhukov, V., I. Fernández-Val, and B. Melly (2013) Inference on counterfactual distributions | 0.644 | 2 | 2 | 100% |
| 8 | Jordà, Ò (2005) Estimation and inference of impulse responses by local projections | 0.644 | 2 | 2 | 100% |
| 9 | Montes-Rojas, G (2019) Multivariate quantile impulse response functions | 0.644 | 2 | 2 | 100% |
| 10 | Plagborg-Mller, M. and C. K. Wolf (2021) Local projections and vars estimate the same impulse responses | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 52 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Inflation Target at Risk: A Time-varying Parameter Distributional Regression | 0.405 | 1 | 1 |
| 2 | Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials | 0.405 | 1 | 1 |