dsge: Dynamic Stochastic General Equilibrium Models
Specify, solve, and estimate dynamic stochastic general
equilibrium (DSGE) models by maximum likelihood and Bayesian methods.
Supports both linear models via an equation-based formula interface
and nonlinear models via string-based equations with perturbation up to
third order (Schmitt-Grohe and Uribe, 2004
<doi:10.1016/S0165-1889(03)00043-5>).
Solution uses the method of undetermined coefficients (Klein, 2000
<doi:10.1016/S0165-1889(99)00045-7>). Likelihood evaluated via the
Kalman filter or a bootstrap particle filter (Gordon et al., 1993).
Bayesian estimation uses adaptive Random-Walk Metropolis-Hastings or
Particle Marginal Metropolis-Hastings (Andrieu et al., 2010
<doi:10.1111/j.1467-9868.2009.00736.x>) with parallel chain support.
Additional tools include Bayes factor model comparison with
Kass-Raftery evidence scales, Ramsey optimal policy via linear-quadratic
regulator, nonlinear perfect foresight via stacked-time Newton
(Juillard et al., 1998), Kalman smoothing, historical shock decomposition, local
identification diagnostics, parameter sensitivity analysis,
occasionally binding constraints, impulse-response functions,
forecasting, and robust standard errors.
| Version: |
1.2.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
grDevices, graphics, stats, numDeriv |
| Suggests: |
coda, Matrix, R.matlab, readxl, testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-09-25 |
| DOI: |
10.32614/CRAN.package.dsge |
| Author: |
Mustapha Wasseja Mohammed [aut, cre] |
| Maintainer: |
Mustapha Wasseja Mohammed <muswaseja at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
dsge results |
Documentation:
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