Estimation Methods for Markets in Equilibrium and Disequilibrium
Market fit coefficients
Equation classes
Model estimation
Market model formula
Log likelihood of a fitted market model
Marginal effects
Market side aggregation
Market force data descriptive statistics
Market model fit
Market model classes
Estimated market quantities
Market model simulation
Estimation of models for markets in equilibrium and disequilibrium
Short model and market descriptions
Model initialization
Model likelihoods and derivatives
Logger class
Number of coefficients
Number of observations
Plots the fitted model
Analysis of shortages
Prints a short description of the model
Single call estimation
Model and fit summaries
System classes
Variable name access
Variance-covariance matrix for a fitted market model
Provides estimation methods for markets in equilibrium and disequilibrium. Supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. Also provides post-estimation analysis tools, such as aggregation, marginal effect, and shortage calculations. See Karapanagiotis (2024) <doi:10.18637/jss.v108.i02> for an overview of the functionality and examples. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. Standard errors can be estimated by adjusting for heteroscedasticity or clustering. The equilibrium estimation constitutes a case of a system of linear, simultaneous equations. Instead, the disequilibrium models replace the market-clearing condition with a non-linear, short-side rule and allow for different specifications of price dynamics.
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