Bayesian Methods for Economic Data Disaggregation
Run Bayesian disaggregation
Coherence score (prior → posterior alignment improvement)
Compute likelihood vector from a prior matrix via SVD (center-only, ro...
Interpretability score (structure preservation + plausibility)
Enable logging at a specific level
Log message with timestamp
Numerical stability (exponential penalty)
Adaptive posterior based on sector volatility
Dirichlet-conjugate posterior (analytical mean)
Multiplicative posterior (Hadamard product + renormalization)
Weighted-average posterior (convex combination)
Read CPI data from an Excel file
Read a weights matrix from an Excel file
Run grid search for parameter optimization (parallel PSOCK)
Save disaggregation results to disk
Spread a likelihood vector across time with a chosen temporal pattern
Composite stability score (numerical and temporal)
Temporal stability (smoothness over time)
Implements a novel Bayesian disaggregation framework that combines Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) dimension reduction of prior weight matrices with deterministic Bayesian updating rules. The method provides Markov Chain Monte Carlo (MCMC) free posterior estimation with built-in diagnostic metrics. While based on established PCA (Jolliffe, 2002) <doi:10.1007/b98835> and Bayesian principles (Gelman et al., 2013) <doi:10.1201/b16018>, the specific integration for economic disaggregation represents an original methodological contribution.