examining the economic effect of various forms of pharmaceutical intellectual property by alex...
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Examining the Economic Effect of Various Forms of
Pharmaceutical Intellectual Property
By Alex McGuigan
Purpose/Goal
• Creating an economic simulation that can effectively replicate scenarios regarding intellectual property
• Finding the economic viability of our current pharmaceutical laws
• Looking for other solutions to our intellectual property situation
Scope
• Measuring pharmaceutical IP with economic data from 1980-2000
• Different IP laws– American IP: 20 year patent, heavy FDA
regulation, high legal, heavy healthcare reg• Test reforms to IP laws
– Other countries’ IP– No IP laws
Background• US IP laws are
highly contentious– Companies charge
high prices for drugs• Can take advantage
of inelastic demand• Price the poor in
Third World out of the market
– Third World nations ignore US IP laws
– Companies focus on new, high-tech drugs
• Much debate exists about the issue– Companies claim that
cost of creating drugs leads to prices
– Third World thinks they should be accessible to the poor
– Mostly rhetoric– Research is from a
business or sociological perspective
• Low economic input, almost no economic research
Research• Agent-Based
Modeling– Usually used for
ecological or sociological purposes
– Rarely from an economic perspective
• Sugarscape had a trade component
– More sociological than economic
• Axiomatic in nature
• Economic– Rarely from a
simulation perspective
– Usually uses real world data or axioms
– Research through analyzing existing data
– Agent based modeling can be very useful
Agents
• Vision– Sight– Evaluation of ideas– Profit estimations
• Metabolism– Efficiency – Management– No consumption of
sugar in location
• Sugar– Wealth– Capital
• Work to gain as much sugar as possible
Scapes (Locations)• Locations are ideas
– Locations produce a product if occupied
– Different IP laws for each
• No agents allowed• Agents from one
corporation• Any agents• Different lengths
– Locations have inherent supply/demand
– Shaped to measure different kinds of product markets and innovation
• Pyramid shape of ideas
• Linear shape
– Products will be clustered in nearby locations
– Inherent cost to occupy
– Initial cost to occupy
Corporations• Legal teams
– Conflicts between agents from different companies
• Decentralized control of agents– Control through
providing funding– Control through
firing
• Agents work for them– Hire agents from a
job market for sugar– Agents send portion
of profits back– Provide capital for
agents
• Work to gain most sugar possible– Incentive to
monopolize
Products
• Each product has a supply/demand market– Supply and demand
both have inherent values
– Supply also determined by output of product’s locations
–Prices and wages alter every turn• Based on supply
and demand–IP laws apply to
them to an extent
Lawsuit• Two agents attempt to occupy same
square, square has one company IP laws
• Legal teams match – legal score v. legal score
• Advantage to corporation that owned idea longer, advantage to holding similar ideas
Markets
• Inherent values– Real world data
• Use real world data to measure market ups and downs
–Limited economic estimation by agents and corporations• Imperfect• Based on vision
and estimation
Design
• Adapted MASON version of Sugarscape
• Test by using real-world data
• No randomness inside actual mechanics, account for market irrationality through vision and through using data from periods of irrationality
• Simplicity is the goal
Development
• Adapted MASON version was outdated– Also very large, much of
it extraneous– Hard to learn the ins and
outs of the program
• Implementing groups and markets required additional threading
• Optimization necessary, large cuts made
• Finding economic solutions was difficult– Trouble with mixed CS
and economic concepts
• Real world data presented challenges– Difficult to find a way to
influence agents while remaining decentralized and predetermined
– Hard to find and isolate proper economic data
Testing – Many trials of each
• Randomized– Randomized stats– Randomized
allocation product effectiveness
– Use real world data for agent placement, corporation roster
• Planned– Products will be
roughly placed together
– Products and ideas will be placed in specific layouts
– Use real world data to influence starting sizes, stats, layouts, etc.
Results
• Was not able to gain results for my specific instance
• Results became an economic model that can be applied to many situations, especially intellectual property
• Adapting to other types of intellectual property is merely a matter of changing IP laws in products and locations and using different real world data
Conclusion
• Agent Based Modeling can become a valuable tool for economics, if used in an innovative way
• Applying real world data is extremely difficult, continue working in spare time
• Enjoyed this project and plan on expanding it in the future to other areas of intellectual property and economics