Government Regulation, Deregulation, and Regulatory Behaviour

Governments may regulate for economic reasons or social reasons.

  • Economic regulation – Seeks to promote competition, regulate natural monopolies, and/or promote fair prices.  Economic regulation may come in the form of: anti-trust laws, cost of service regulation, rate of return regulation, or wage and price controls.
  • Social regulation – Seeks to facilitate product safety, worker protection, and/or environmental protection.  Social regulation may come in the form of product standards, employer safety laws, or pollution taxes/fines.

The economic impacts of regulating an industry can be quantified on a supply-demand curve, where price is on the y-axis and quantity of output is on the x-axis.  Commonly, economic regulation, such as a tax or output restriction, will exhibit a decrease in output and increase in price on this graph.  This inefficiency is called a deadweight economic loss.

Deregulation

Governments may deregulate industries because the market structure went from uncompetitive to competitive over time or the current regulation is keeping new firms from entering the market.

  • Short-term effects: Weaker firms go out of business, jobs are lost, less skilled workers struggle to maintain employment, and service quality temporarily weakens as the industry transitions.
  • Long-term effects: The market becomes more competitive, consumer prices drop,  more choices become available, production increases, and the deadweight loss experienced in the regulated period shrinks

Theories on Regulatory Behavior

  • Capture Hypothesis – theorizes that regulators will eventually become the captives of the industry interests that they regulate.  An argument behind this theory is that industry actors are more likely to invest in educating law makers and government bodies than the general population.  Therefore the general population, lacking expertise, is at a disadvantage when it comes to making regulatory proposals.
  • Share the Gains, Share the Pains Theory – asserts that regulators will find a compromise among consumers, law makers, and industry for designing regulations that are agreeable to all three of these groups.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.