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Maximum and minimum in economic models

Maximum and minimum in economic models. Calculus and Optimisation Maximum and minimum in economics. Maximum and minimum in economics. We now move to the 2 nd part of the course, which will focus on Calculus Calculus is the analysis of the properties of functions

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Maximum and minimum in economic models

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  1. Maximum and minimum in economic models Calculus and Optimisation Maximum and minimum in economics

  2. Maximum and minimum in economics • We now move to the 2nd part of the course, which will focus on Calculus • Calculus is the analysis of the properties of functions • We will be re-using the algebra concepts • The detail on the various methods will be covered in the coming weeks • This week, we look at an introduction to how the concept of maximum and minimum are used in economics.

  3. Maximum and minimum in economics Maximum: The concept of ‘utility’ Minimum: production decisions Calculus and optimisation tools

  4. Maximum: The concept of ‘utility’ • As was mentioned in the first few weeks, finding the best choice of a consumer means choosing the “best” outcome • In other words, the satisfaction of consumers • We also imagined a function f that gives satisfaction as a function of all the quantities of goods consumed

  5. Maximum: The concept of ‘utility’ satisfaction Maximum Calculus gives methods for finding this value. Why is it possible to build such a function? q Finding the “best choice” is effectively like trying to find the values of the quantities of goods for which function f has a maximum

  6. Maximum: The concept of ‘utility’ • Lets use a practical example: • Consumption of a single good • Chocolate cake for example • The function will be called the “utility” function • This is the traditional name in economics for the satisfaction of an agent.

  7. Maximum: The concept of ‘utility’ Extra U =1 Extra U = -2 Extra U =3 Extra U = 10 Extra U =5

  8. Maximum: The concept of ‘utility’ • Now of course, in reality, there is no function that can put a number on satisfaction • But agents are able to say when their satisfaction increases or falls. • This means that we can identify points where utility is maximum • Methods in calculus allow us to find the maximum, even if the function itself is not defined!

  9. Maximum and minimum in economics Maximum: The concept of ‘utility’ Minimum: production decisions Calculus and optimisation tools

  10. Imagine that the table gives the production costs of SciencesPo, given the size of the student population In order to plan for, the budget the director wants to have an idea of the cost per student of providing the lectures Lets work it out Minimum: production decisions

  11. Minimum: production decisions • What can we notice ? • Why is this the case • Additionally, the director would like to have an idea of the change in the costs per student when the student population increases

  12. Minimum: production decisions • Lets draw the cost per student • What can we observe? • Why is that the case ?

  13. Minimum: production decisions Minimum point of average production costs Cost per 10 students

  14. Maximum and minimum in economics Maximum: The concept of ‘utility’ Minimum: production decisions Calculus and optimisation tools

  15. Calculus and optimisation tools • For both cases, the maximum is the point where the function is neither increasing nor decreasing: • Utility no longer increases but is not yet falling. • Average costs are no longer falling but aren’t yet increasing. • This is basically how you find maxima and minima in calculus. • The methods may seem more ‘technical’, but the general stays the same

  16. Calculus and optimisation tools • First step: working on continuous functions • The examples we have seen are discrete • In other words, the functions are not smooth, so the tools of calculus cannot apply • Second step : Partial/total derivatives • Economics often uses functions of several variables, so we will have to take that into account when we look for the maximum

  17. Calculus and optimisation tools • Third step: constrained optimisation • Today’s example shows cases of “free optimisation” • We find a maximum/minimum regardless of anything else • But in real life, we often have constraints to take into account • Example: consumers have budgets they must respect • So we have to take the constraint into account when looking for the minimum

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