Introduction | The Problem: Cross-Sectional Dependence | What is cross-sectional dependence? | Consequences of ignoring CSD | Testing for CSD: the pcd_test() function | The Model: Heterogeneous Panels with Common Factors | The general DGP | The CCE approach | Dynamic extension (DCCE) | Estimators | Mean Group (MG) | CCE Mean Group (CCE-MG) | Dynamic CCE (DCCE) | Verify that DCCE removes CSD | Regularized CCE (rCCE) | Long-Run Estimators: CS-DL, CS-ARDL, and PMG | CS-DL (Cross-Sectionally Augmented Distributed Lag) | CS-ARDL (Cross-Sectionally Augmented ARDL) | PMG (Pooled Mean Group) | Comparing All Estimators | The CD Test Suite | Bootstrap Inference | Worked Example: Ditzen (2018) Growth Regression | Step 1: Detect CSD in naive residuals | Step 2: Mean Group (no CSD correction) | Step 3: Dynamic CCE with 3 CSA lags (Ditzen 2018 Example 7.3) | Step 4: Summary table | Step 5: Unit-level heterogeneity | Auxiliary Diagnostics | Exponent of cross-sectional dependence | Information criterion for CSA lag selection | Rank condition | Panel unit root test: Pesaran CIPS | Slope heterogeneity: Swamy and Pesaran-Yamagata | Hausman test: MG vs pooled | broom compatibility | Confidence intervals | Visualising heterogeneity | Additional Estimators (v0.2.0+) | Augmented Mean Group (AMG) | Interactive Fixed Effects (IFE, Bai 2009) | Pooled CCE (CCEP) | Additional Diagnostics (v0.3.0+) | Panel Granger causality | IPS and LLC panel unit root tests | Pedroni cointegration test | Structural break test | Impulse Response Functions (v0.4.0) | The dcce_workflow() Pipeline | Quick-Start Guide | References

Overview | A Simple AR(1) Model | Simulate Data | Specify the Model | Solve at Known Parameters | Estimate the Model | Postestimation | Impulse-Response Functions | Forecasting | A Three-Equation New Keynesian Model | Model Specification | Simulate and Estimate | Nonlinear DSGE Models | A Simple RBC Model | Steady State | Solve and Inspect | IRFs | Bayesian Estimation | Specifying Priors | Running the Sampler | Posterior Diagnostics and IRFs | What This Package Currently Supports | Notes