Lecture 2 : Economics and Optimization
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Lecture 2 : Economics and Optimization. AGEC 352 Spring 2012 – January 18 R. Keeney. Next Week. Go over some spreadsheet modeling on Monday Lab instructions on Monday We’ll use Blackboard Discussion Lab handout will be posted by 10 on Tuesday
Lecture 2 : Economics and Optimization
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Lecture 2: Economics and Optimization AGEC 352 Spring 2012 – January 18 R. Keeney
Next Week • Go over some spreadsheet modeling on Monday • Lab instructions on Monday • We’ll use Blackboard Discussion • Lab handout will be posted by 10 on Tuesday • Questions on discussion board must be answered before the 11:20 timeframe to get credit • Some DB questions will be volunteer, some not… • The only wrong answers are 1) no response and 2) I don’t know. Take your best guess at the simplest short explanation and we’ll work from there…
Review • Last Wednesday • 2 equations, 3 unknowns • Overcome this problem by making an assumption about the value of one of the unknowns • Assumption: Maximize Revenue • Doesn’t always work but it will for problems you see in this course • Today: Similar issue but the equations are more familiar
Functions • A function f(.) takes numerical input and evaluates to a single value • This is just a different notation • Y = aX + bZ … is no different than • f(X,Z) = aX + bZ • For some higher mathematics, the distinction may be more important • An implicit function like G(X,Y,Z)=0
Basic Calculus • y=f(x)= x2 -2x + 4 • This can be evaluated for any value of x • f(1) = 3 • f(2) = 4 • We might be concerned with how y changes when x is changed • When ∆X = 1, ∆Y = 1, starting from the point (1,3)
Marginal economics • In general, economic decision making focuses on changes in functions… • E.g. The change in revenue vs. the change in cost • If the revenue change is greater than cost, proceed
Issue • Why is the peak (maximum) of the profit graph not directly above the point where Marginal Revenue = Marginal Cost • Incomplete information used to generate the graph
Differentiation (Derivative) • Instead of the average change from x=1 to x=2 • Exact change from a tiny move away from the point x = 1 • We call this an instantaneous rate of change • Infinitesimal change in x leads to what change in y?
Power rule for derivatives (the only rule you need in 352) • Basic rule • Lower the exponent by 1 • Multiply the term by the original exponent • If f(x) = axb • Then f’(x) = bax(b-1) • E.g. • If f(x) = 6x3 • Then f’(x) = 18x2
Examples • f(x) = 5x3 + 3x2 + 9x – 18 • f(x) = 2x3 + 3y • f(x) = √x
Applied Calculus: Optimization • If we have an objective of maximizing profits • Knowing the instantaneous rate of change means we know for any choice • If profits are increasing • If profits are decreasing • If profits are neither increasing nor decreasing
Profit function Profits p
A Decision Maker’s Information • Objective is to maximize profits by sales of product represented by Q and sold at a price P that set by the producer • 1. Demand is linear • 2. P and Q are inversely related • 3. Consumers buy 10 units when P=0 • 4. Consumers buy 5 units when P=5
More information • **Demand must be Q = 10 – P • The producer has fixed costs of 5 • The constant marginal cost of producing Q is 3
More information • Cost of producing Q (labeled C) • **C = 5 + 3Q • So • 1) maximizing: profits • 2) choice: price level • 3) demand: Q = 10-P • 4) costs: C= 5+3Q • What next?
We need some economics and algebra • Definition of ‘Profit’? • How do we simplify this into something like the graph below?
Applied calculus • So, calculus will let us identify the exact price to charge to make profits as large as possible • Take a derivative of the profit function • Solve it for zero (i.e. a flat tangent) • That’s the price to charge given the function
Relating this back to what you have learned • We wrote a polynomial function for profits and took its derivative • Our rule: Profits are maximized when marginal profits are equal to zero • Profits = Revenue – Costs • 0 = Marginal Profits = MR – MC • Rewrite this and you have MR = MC
Next week • Monday and Wednesday • Lecture on spreadsheet modeling • Tuesday • Lab 10:30 – 11:20 (Lab Guide posted by 10) • Discussion board (details for login Monday) • Respond to questions I post about the assignment during lab time… • Ask any questions on that board you have about the lab work…