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dsge 1.0.0

Major release: complete DSGE estimation and analysis toolkit

Model-implied covariance reporting (v0.10.0)

• New model_covariance() for unconditional covariance and correlation matrices of model observables and controls.
• Supports ML fits, Bayesian fits, and raw solution objects.

Prediction and reporting tools (v0.10.0)

• New prediction_interval() for one-step-ahead prediction bands using Kalman filter innovation variance.
• New prediction_accuracy() for RMSE, MAE, and mean bias statistics.
• Enhanced fitted() method for ML-estimated models.

Robust standard errors (v0.10.0)

• New robust_vcov() for sandwich (Huber-White) variance-covariance estimation. Provides standard errors robust to model misspecification.

Bayesian diagnostics and model comparison (v0.10.0)

• New posterior_predictive() for posterior predictive checks with variance and autocorrelation statistics.
• New marginal_likelihood() via modified harmonic mean estimator for Bayesian model comparison.
• New geweke_test() for Geweke (1992) convergence diagnostic.
• New mcmc_diagnostics() for comprehensive MCMC health summary.

dsge 0.9.0

Occasionally binding constraints

• New simulate_occbin() for piecewise-linear simulation under inequality constraints (e.g., zero lower bound).
• New obc_constraint() helper for constraint specification.
• Shadow-shock algorithm with iterative regime detection.
• Plot method with constraint-binding period shading.

dsge 0.8.0

Second-order perturbation

• solve_dsge() now accepts order = 2 for second-order approximation of nonlinear models.
• New simulate_2nd_order() for pruned second-order simulation.
• New irf_2nd_order() for generalised impulse-response functions with asymmetric shock effects.
• Risk/precautionary corrections to the steady state (sigma-correction).

dsge 0.7.0

Perfect foresight / deterministic transition paths

• New perfect_foresight() for deterministic simulation of transition paths after temporary or permanent shocks.
• Supports both linear and linearized nonlinear models.
• Plot method with deviation-from-steady-state and level views.

dsge 0.6.0

Identification and sensitivity analysis

• New check_identification() for local identification diagnostics via Jacobian SVD of the autocovariance mapping.
• New parameter_sensitivity() for sensitivity of likelihood, IRFs, steady state, and policy matrices to parameter perturbations.
• New prior_posterior_update() for Bayesian informativeness diagnostics comparing posterior concentration to prior width.

dsge 0.5.0

Kalman smoother and shock decomposition

• New smooth_states() for Rauch-Tung-Striebel Kalman smoothing.
• New smooth_shocks() for extraction of smoothed structural shocks.
• New shock_decomposition() for historical decomposition of observed variables into individual shock contributions.
• Plot methods for smoothed states and shock decomposition.

dsge 0.4.0

Bayesian nonlinear DSGE estimation

• bayes_dsge() now accepts dsgenl_model objects for Bayesian estimation of nonlinear DSGE models via first-order perturbation.
• For each MCMC draw, the model’s steady state is re-solved and the system re-linearized at the candidate parameters, ensuring correct parameter- dependent dynamics.
• Failed steady-state solves, linearization failures, and Blanchard-Kahn violations are handled gracefully — proposals are rejected without crashing the sampler. Failure counts are reported in the output.
• Data is automatically centered around the parameter-specific steady state for nonlinear models.
• Posterior IRFs work for nonlinear models via the same irf() interface.

dsge 0.3.0

Bayesian estimation (linear)

• New bayes_dsge() function for Bayesian estimation of linear DSGE models via adaptive Random-Walk Metropolis-Hastings (RWMH).
• New prior() constructor for specifying prior distributions: normal, beta, gamma, uniform, and inv_gamma.
• Multiple chains with dispersed starting points from prior draws.
• Adaptive proposal covariance during warmup targeting ~25% acceptance rate.
• Parameter transformations (log, logit) with Jacobian corrections for constrained parameters.
• MCMC diagnostics: effective sample size (ESS), R-hat (split), MCSE, and acceptance rates.
• Posterior impulse-response functions via irf() with pointwise credible bands computed from posterior draws.

dsge 0.2.0

Nonlinear DSGE support

• New dsgenl_model() constructor for nonlinear DSGE models defined via string-based equations with VAR(+1) lead notation.
• steady_state() generic for computing the deterministic steady state via Newton-Raphson with damped line search.
• linearize() computes first-order Taylor expansion around steady state.
• solve_dsge() and estimate() now accept dsgenl_model objects.

dsge 0.1.0

Initial release.

• Formula-based linear model specification.
• Klein (2000) solution via method of undetermined coefficients.
• Maximum likelihood estimation via Kalman filter.
• Policy/transition matrix extraction with delta-method standard errors.
• Impulse-response functions, forecasting, stability diagnostics.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.