Tutorial

This section uses a series of Jupyter Notebooks to explain how pyRVtest can be used to solve example problems, compute post-estimation outputs, and simulate problems.

• Testing Firm Conduct with Cereal Data
  • Overview
  • Load the main dataset
  • Estimate demand with PyBLP
  • Test firm conduct with pyRVtest
• Library of Models
  • Preliminaries and notation
  • Bertrand Competition: \(m=B\)
  • Monopoly (i.e., Perfect Collusion): \(m=M\)
  • Cournot Competition with Differentiated Products: \(m=C\)
  • Bertrand and Cournot with Profit Weights: \(m=PW(\lambda)\)
  • Non-profit Conduct: \(m=N(\lambda)\)
  • Marginal Cost Pricing (Perfect Competition / Zero Markup): \(m=PC\)
  • Rule of Thumb Models: \(m=R(\lambda)\)
  • Bertrand with Scaled Costs: \(m = SC(\lambda)\)
  • Constant Markup Models: \(m = CM(\eta)\)
  • Vertical Models with unobserved wholesale costs
  • Options to Test Other Models