NEWS

dsge 1.0.0 (2026-04-02)

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

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.

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

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.

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.

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).

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.

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.

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.

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.

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.

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.

Initial release.