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.