📦 Announcing valueprhr: Value-Price Analysis with Bayesian and Panel Data Methods

Package development
, , ,
1

Hello R Community,

I'm excited to announce the release of valueprhr, an R package now available on GitHub. This package is designed for researchers and analysts working in political economy, specifically focusing on the empirical relationship between labor values and market prices.

What does it do?
Drawing from classical and Marxian economic theory, valueprhr provides a comprehensive econometric toolkit to analyze the correspondence between direct prices (based on labor values) and prices of production across economic sectors over time. The core functions help you:

  • Quantify the relationship between value and price using Two-way Fixed Effects and Mundlak Correlated Random Effects models.
  • Validate predictive power through rigorous rolling-window and Leave-One-Sector-Out cross-validation.
  • Test for structural stability using Chow, CUSUM, MOSUM, and supF tests to detect regime shifts.
  • Implement Bayesian methods including sector-specific GLMs and hierarchical mixed-effects models with partial pooling.

At its core, the package addresses the transformation process —how closely market prices correspond to underlying labor values. It moves beyond simple correlation coefficients, offering tools to decompose variation into within-sector and between-sector components and to analyze multivariate dynamics using Partial Least Squares (PLS) and Panel VAR.

Specifically, the workflow relies on rigorous data construction: market price indices are constructed by temporally disaggregating the aggregate Consumer Price Index (CPI) for all items, utilizing the Input-Output matrix from the same period. This relies on the closed-form Bayesian solutions from the BayesianDisaggregation library, ensuring sectoral price movements remain statistically consistent with macroeconomic aggregates while preserving high-frequency dynamics.

Why is it useful?
Testing the labor theory of value has historically been limited by data availability and methodological inconsistencies. This package aims to make the process rigorous, transparent, and reproducible. It allows researchers to determine if price deviations are random or structurally determined by the organic composition of capital.

Getting Started:

The package includes comprehensive documentation on data preparation and model comparison. I hope valueprhr becomes a valuable tool in your heterodox economics or econometrics workflow.

I welcome any feedback, bug reports, or contributions on GitHub. What are your experiences or challenges with testing value-price deviations?

Best,

José Mauricio Gómez Julián