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 first-order perturbation (linearization around deterministic steady state). Solution uses the method of undetermined coefficients (Klein, 2000 <doi:10.1016/S0165-1889(99)00045-7>). Likelihood evaluated via the Kalman filter. Bayesian estimation uses adaptive Random-Walk Metropolis-Hastings with prior specification. Additional tools include Kalman smoothing, historical shock decomposition, local identification diagnostics, parameter sensitivity analysis, second-order perturbation, occasionally binding constraints, impulse-response functions, forecasting, and robust standard errors.

Version:	1.0.0
Depends:	R (≥ 3.5.0)
Imports:	grDevices, graphics, stats, numDeriv
Suggests:	coda, testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-04-02
DOI:	10.32614/CRAN.package.dsge (may not be active yet)
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:

Reference manual:	dsge.html , dsge.pdf
Vignettes:	Introduction to the dsge Package (source, R code)

Downloads:

Package source:	dsge_1.0.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): dsge_1.0.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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