Bayesian Simultaneous Equation Models for Forecasting

Estimate and forecast Bayesian simultaneous equation models for macroeconomic time series. Provides tools to specify systems of behavioral equations and accounting identities, transform and manage time series, simulate from the posterior using a Metropolis-within-Gibbs sampler, and generate unconditional and conditional forecasts with user-defined priors and restrictions. Methods are described in Rathke A. and Sarferaz S. (forthcoming) "Bayesian Estimation of Simultaneous Equations Model".

KOMA - Large Macroeconomic Model

koma is an R package for Bayesian estimation of simultaneous equation models (SEMs) using Metropolis-within-Gibbs Markov Chain Monte Carlo (MCMC) methods.

Installation

Install the released version from CRAN:

install.packages("koma")

Or install the latest development version from GitHub:

pak::pak("TimothyMerlin/koma")

Documentation

• Getting started → Getting started with koma
• Equation syntax → Equation syntax reference
• Extended time series → Extended time series (ets)
• Parallelization → Executing koma in parallel
• Example: Klein model → Estimating Klein’s Model I
• Example: small macro model → Estimating small macro model for Switzerland
• Example: error correction → Error correction in a small open economy model
• Diagnostics → MCMC diagnostics for an estimated SEM
• HPD intervals → Highest probability density (HDR and HDI)

See the full documentation site for the complete function reference.

Contributing

Contributions are welcome! See CONTRIBUTING.md for the development setup and pull request process. Bug reports and feature requests are welcome via GitHub issues.