1. Econ 102 SY 2008 2009 Lecture 7 Profit Maximization and Supply August 21, 24 and 28, 2008

2. Econ 102 SY 2008 2009 Key concepts Production process Production function

3. Econ 102 SY 2008 2009 Outputs and inputs Production as the transformation of inputs into outputs Alternative production processes: One input, one output Several inputs, one output Several inputs, several outputs Several tiers of inputs, one output Substitution among inputs Transformation of one output to another

4. Econ 102 SY 2008 2009 L Q L1 Q1 Q2

5. Econ 102 SY 2008 2009 Q for local market Value AddedAggregate Intermediate Input K L x1 x2xn COL Xport

6. Econ 102 SY 2008 2009 Specification of technology Technology – how inputs are transformed into outputs. Net outputs – y i S – y i y Production plan - set of all technologically feasible net outputs, i.e. a negative y means it is a net input, while a positive y means it is a net output (y S ; – y y,– x y ); (y’ S ; – y y,– x y ) such that y’ S< y S Production possibilities set – set of all production plans

7. Econ 102 SY 2008 2009 Virgin Coconut Oil a b VCO1 C1 Copra C2

8. Econ 102 SY 2008 2009 Short run possibilities set Eventually technologically feasible set Immediately technologically feasible or short run production possibilities set - et of outputs, y i in the production possibilities set Y, constrained by some resource z - immediately technologically feasible :

9. Econ 102 SY 2008 2009 Production function Suppose the firm has one output and uses inputs x, then the production function is Efficient production plan: output y is efficient if there is no y’ > y that can be produced with input vector x, and y’ is not y. Transformation function: set of net output vector y. T(y)=0 if and only if y is efficient.

10. Econ 102 SY 2008 2009 Input requirement set Input requirement set – Set of inputs -x that can produce at least any y in Y. Isoquant: set of all inputs such that they produce the same level of output.

11. Econ 102 SY 2008 2009 L K a La Ka b Ya Yb c

12. Econ 102 SY 2008 2009 Examples of Convex Input requirement set

13. Econ 102 SY 2008 2009 Convex input requirement set

14. Econ 102 SY 2008 2009 Cobb Douglas Production Technology

15. Econ 102 SY 2008 2009 Leontief Production Technology

16. Econ 102 SY 2008 2009 Properties of Production Set Inaction. Zero production can be a production plan. 0  Y. Closedness. Given a sequence of production plans y i, i = 1; 2;… n; all plans are in Y and as y i  y, then the limit production plan y is also in Y. Guarantees that points on the boundary of Y are feasible. Closedness of Y implies that the input requirement set V (y) is a closed set for all y>=0. Free disposal or monotonicity. If y  Y, then y’  Y for all y’<y. Free disposal means commodities can be thrown away. A weaker requirement is that we only assume that the input requirement is monotonic: If x is in V (y) and x’ > x, then x’ is in V (y).

17. Econ 102 SY 2008 2009 Properties of Production Set Irreversibility. All production plans except the zero plan are irreversible. Convexity. Y is convex if whenever y and y’ are in Y, the weighted average ty + (1 - t) y’ is also in Y for any t with 0 <= t <= 1. With convexity of Y, and if all goods are divisible, two production plans y and y’ can be scaled downward and combined. Convexity rules out “start up costs" and other sorts of returns to scale.

18. Econ 102 SY 2008 2009 Properties of Production Set Strict Convexity. Y is strictly convex if y  Y and y’  Y, then ty +(1-t)y’  intY for all 0 < t < 1, where intY denotes the interior points of Y. Guarantees unique profit maximizing production plans. Implies input requirement set is convex. Convexity of input requirement set. If x and x’ are in V (y), then tx + (1 - t)x’ is in V (y) for all 0 <= t <= 1. Convexity of V (y) implies that, if x and x’ can each produce y, so can any weighted average of them.

19. Econ 102 SY 2008 2009 Propositions Convexity of production and input requirement sets. If production set Y is convex, then its associated input requirement set, V (y) is also convex. Quasi-concavity of prod function and convexity of input requirement set. Input requirement set V (y) is a convex set if and only if the production function f (x) is a quasi-concave function.

20. Econ 102 SY 2008 2009 Definitions: Concave and Quasi-concave functions Let X be a convex set. A function f : X  R is said to be concave on X if for any x, x’  X and any t with 0 = tf (x) + (1 -t)f(x’) The function f is said to be strictly concave on X if f(tx + (1 - t)x’) > tf (x) + (1 -t)f(x’) for all x, x’  X an 0 < t < 1. Let X be a convex set. A function f : X  R is said to be quasi-concave on X if the set{x  R : f(x) >= c} is convex for all real numbers c, for all real numbers c It is strictly quasi-concave on X if {x  R : f(x) >c} is convex for all real numbers c.

21. Econ 102 SY 2008 2009 x1x1 x2x2 x’ x f(x)=f(x’)=c t x + (1-t)x’ f(t x + (1-t)x’ )

22. Econ 102 SY 2008 2009 Returns to scale Suppose vector of inputs x which produces output y is proportionately scaled up or down, then there are three possibilities for output y. The technology may exhibit: (1) constant returns to scale; (2) decreasing returns to scale, and (3) increasing returns to scale.

23. Econ 102 SY 2008 2009 Definitions A production function f(x) is said to exhibit : constant returns to scale if f(tx) = tf (x) for all t >= 0. decreasing returns to scale if f(tx) 1. increasing returns to scale if f(tx) > tf (x) for all t > 1.

24. Econ 102 SY 2008 2009 x costs

25. Econ 102 SY 2008 2009 Returns to scale and homogeneity of production function CRTS implies production function is homogeneous of degree 1. Homogeneous production functions means: f(tx) = t k f(x). In general, a production technology which is homogeneous of degree k exhibits any of the returns to scale possibilities as follows: If k=1, then it is CRS. If k<1, then it is DRS. If k>1, then it is IRS.

26. Econ 102 SY 2008 2009 Global versus Local Returns to Scale Global if the returns to scale applies to all vectors in the input requirement set. Local if the type of returns to scale applies to a subset of the vectors in the input requirement set only; another type of RTS may apply to other subsets.

27. Econ 102 SY 2008 2009 Elasticity of Scale and local returns to scale It is defined as the percent increase in output due to a one percent increase in all inputs; evaluated at t=1. LOCAL RETURNS TO SCALE. A production function f(x) is said to exhibit locally increasing, constant, or decreasing returns to scale as e(x) is greater, equal, or less than 1.

28. Econ 102 SY 2008 2009 Marginal rate of technical substitution Suppose that technology is represented by a smooth production function. Suppose the firm is at producing y* = f(x* 1 ; x* 2 ). If the firm increases a small amount of input 1 and decreases some amount of input 2 to maintain a constant level of output. MRTS of the two inputs is defined to be the percent decrease in input 2 due to an increase of input 1.

29. Econ 102 SY 2008 2009 L K

31. MRTS of a Cobb Douglas Production Function

32. Econ 102 SY 2008 2009 Elasticity of substitution Defined as the percentage change of input ratio divided by the percentage change in MRTS. Measures the curvature of the isoquant.

33. Econ 102 SY 2008 2009

34. Profit Maximization Economic profit is defined to be the difference between the revenues the firm receives The revenues may be written as a function of the level of operations of some n actions, R(a 1,…, a n ), and costs as a function of these same n activity levels, C(a 1,…, a n ) Actions may be in term of employment level of inputs or output level of production expressed in value terms.

35. Econ 102 SY 2008 2009 Profit maximization Max  (p;w) = p’y-w’x such that {y,-x) is in Y Constrained or restricted or short run profit maximization Max  (p;z) = p’y-w’x such that {y,-x) is in Y(z) Suppose we have a production function f(x) where x is a vector of inputs then the profit function is:  (p,w) = py – w’x and its restricted or short run profit function  (p,w;z) = py – w’x.

36. Econ 102 SY 2008 2009 Conditions for profit maximum In vector notation Kuhn Tucker condition (which includes border solution): Y*

37. Econ 102 SY 2008 2009 Proposition Proposition. Suppose Y strictly convex. Then, for each given p, w  R L + the profit maximizing production {y*,-x*} is unique provide it exists.

38. Econ 102 SY 2008 2009 Iso-profit lines y=(  /p)+(w/p)x profit maximum when the slope of the iso-profit line equals the slope of the production function. Labor y Y=f (x) L*  =py-wL B

39. Econ 102 SY 2008 2009 End of Lecture 7 Profit Maximization and Supply