API Documentation

The majority of the package consists of classes, which compartmentalize different aspects of testing models of firm conduct.

There are some convenience functions as well.

Configuration Classes

Formulation(formula[, absorb, ...])	Configuration for designing matrices and absorbing fixed effects.
ModelFormulation([model_downstream, ...])	Configuration for designing matrices and absorbing fixed effects.

Data Manipulation Functions

There are also a number of convenience functions that can be used to compute markups, or manipulate other pyRVtest objects.

build_ownership(product_data, ...[, ...])	Build ownership matrices, \(O\).
build_markups(product_data, pyblp_results, ...)	This function computes markups for a large set of standard models.
construct_passthrough_matrix(pyblp_results, ...)	Construct the passthrough matrix using the formula from Villas-Boas (2007).
evaluate_first_order_conditions(index, ...)	Compute markups for some standard models including Bertrand, Cournot, monopoly, and perfect competition using the first order conditions corresponding to each model.
read_pickle(path)	Load a pickled object into memory.

Problem Class

Problem(cost_formulation, ...[, ...])

A firm conduct testing-type problem.

Once initialized, the following method solves the problem.

Problem.solve([demand_adjustment, ...])

Solve the problem.

Problem Results Class

Solved problems return the following results class.

ProblemResults

Results of running the firm conduct testing procedures.

The results can be pickled or converted into a dictionary.

ProblemResults.to_pickle(path)

Save these results as a pickle file.