Nigar Hashimzade, Oleg Kirsanov, Tatiana Kirsanova, Junior Maih
arXiv 12 Feb 2024 · Econometrics · 2 citations (OpenAlex)
arXiv:2402.08051 · PDF · DOI · OpenAlex · Extracted main text
This paper presents a framework for empirical analysis of dynamic macroeconomic models using Bayesian filtering, with a specific focus on the state-space formulation of Dynamic Stochastic General Equilibrium (DSGE) models with multiple regimes. We outline the theoretical foundations of model estimation, provide the details of two families of powerful multiple-regime filters, IMM and GPB, and construct corresponding multiple-regime smoothers. A simulation exercise, based on a prototypical New Keynesian DSGE model, is used to demonstrate the computational robustness of the proposed filters and smoothers and evaluate their accuracy and speed for a selection of filters from each family. We show that the canonical IMM filter is faster and is no less, and often more, accurate than its competitors within IMM and GPB families, the latter including the commonly used Kim and Nelson (1999) filter. Using it with the matching smoother improves the precision in recovering unobserved variables by about 25 percent. Furthermore, applying it to the U.S. 1947-2023 macroeconomic time series, we successfully identify significant past policy shifts including those related to the post-Covid-19 period. Our results demonstrate the practical applicability and potential of the proposed routines in macroeconomic analysis.
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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 | Kim, C.-J (1994) Dynamic linear models with Markov-switching | 0.811 | 4 | 2 | 100% |
| 2 | Binning, A. and J. Maih (2015) Sigma point filters for dynamic nonlinear regime switching models | 0.644 | 2 | 2 | 100% |
| 3 | Blom, H. A. and Y. Bar-Shalom (1988) The interacting multiple model algorithm for systems with markovian switching coefficients | 0.644 | 2 | 2 | 100% |
| 4 | Chen, X., E. M. Leeper, and C. Leith (2022) Strategic Interactions in U.S. Monetary and Fiscal Policies | 0.644 | 2 | 2 | 100% |
| 5 | Maih, J (2015) Efficient perturbation methods for solving regime-switching DSGE models self | 0.644 | 2 | 2 | 100% |
| 6 | Fernandez-Villaverde, J., P. A. Guerron-Quintana, and J. Rubio-Ramirez (2015) Estimating Dynamic Equilibrium Models with Stochastic Volatility | 0.511 | 2 | 2 | 50% |
| 7 | Chen, X., T. Kirsanova, and C. Leith (2017) How Optimal is US Monetary Policy? | 0.511 | 2 | 1 | 100% |
| 8 | Bjornland, H. C., V. H. Larsen, and J. Maih (2018) Oil and macroeconomic (in)stability | 0.405 | 1 | 1 | 100% |
| 9 | Bar-Shalom, Y., X.-R. Li, and T. Kirubarajan (2001) Estimation with Applications To Tracking and Navigation | 0.405 | 1 | 1 | 100% |
| 10 | Bianchi, F (2012) Evolving monetary/fiscal policy mix in the united states | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 22 scored citations.