Teaching Managerial Economics

8/8/2019 Teaching Managerial Economics

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INTERDISCIPLINARY APPROACH TO TEACHING MANAGERIAL ECONOMICS

Samuel EnajeroDepartment of Social Sciences

University of Michigan-Dearborn4901 Evergreen RoadDearborn, MI 48128

[email protected]

ABSTRACT

Many economic topics can be presented either as a pure social science or asapplications in business. Linear programming, production costs and factor productivityare among topics presented differently in economics and business courses. Gaps exist,such that students who come across the same topics in economics and business coursesmay lack the information necessary to relate the concepts. This paper argues thatbusiness students would have more interest in economics and be better rounded inbusiness if the conceptual gaps were closed. Managerial economics, as offered in manybusiness departments, could be the bridge that links economic theories to their businessapplications.

JEL Classification: A23, A22, M21


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I - INTRODUCTION

Managerial economics, offered in many undergraduate and graduate programs

throughout the country, can be regarded as an important business course. It appears as a

required course in an undergraduate curriculum and as a foundation/core course in some

MBA programs. In some departments, managerial economics is the only upper level

economics course in both an undergraduate business degree and an MBA program. As

the name suggests, there is supposed to be abundance of business and management

content integrated with economics.

However, managerial economics is taught in many institutions as a pure social

science course. Some departments offer it as an alternative to intermediate

microeconomics. This is appropriate in a social science department offering BA or MA

programs with a concentration in economics. In this context, students learn economics

from a liberal arts or social science approach using algebra and graphs.

The fact that economics departments in some universities are in a college of arts

and sciences while in others, economics departments are in the school of business, lends

support to the need to separate the teaching contents of economics in these two different

schools. This is not an attempt to dichotomize economics as a social science and as a

business course (Dean & Dolan, 2001), but to draw up teaching contents tailored to suit

and benefit students in both schools.

The theories offered in economics, as a social science cannot be ignored. These

economic theories are applied in many spheres of life to derive efficiency (e.g., in

environmental economics, health economics, sport economics, labor economics, non-

renewable resource economics, urban economics, and business economics). A good


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portion of economic theories, nonetheless, may sound like novel ideas, if an upper level

economics course such as managerial economics, designed for business students, is

taught purely from a liberal arts perspective. Without injecting comparable business

content, students assume that economics is not a business course and their interest in

economics seems to diminish (Marburger, 2004; Anderson & Muraoka, 1990;

Gregorowicz & Hegji, 1998).

Little wonder that many business departments are struggling to retain economics

as a major (Gregorowicz & Hegji ,1998; Siegfried, 2007). One familiar hypothesis

suggests that majoring in economics is a reluctant choice for students more interested in a

business major (Kasper, 2008, pp. 457-472). Effectively, business students convey

their resentment indirectly by not majoring in a liberal arts discipline in a business

department. If economics were taught as a business course, perhaps, some students

would major in economics and minor in accounting, finance, management, marketing or

organizational behavioror vice versa.

On one hand, teaching managerial economics as a social science without

sufficient links to related business contents leaves conceptual gaps in the minds of

students. On the other hand, teaching managerial economics as a business course

divorced of theoretical framework as analyzed in social science departments would create

a shallow understanding of these business topics. In fact, the economic theories

underlying business are necessary for a thorough understanding of business courses.

Cements combined with sands, gravels or granites and rods are mixtures for

concrete that forms a building foundation. This mixture remains concrete with the power

of limestone in the cement, which is similar to granites or gravels. Analogically, in order


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to form a concrete foundation for a business curriculum, a course such as managerial

economics should be emphatically linked or overlapped with business courses.

Otherwise, except for students who apply mastery1 goal in learning (Baron &

Harackiewicz, 1997, 2001), business concepts will be fragmented in the minds of many

students even after graduation. Thus, the potential exists for some students to be

deprived of acquiring a well-rounded business education, with many questions still

unanswered during their career.

Among regular chapters in intermediate microeconomics repeated in a typical

managerial economics textbook are chapters on production costs, perfect competition,

monopoly, monopolistic competition, oligopoly, factor markets and game theory (Baye,

2006; Hirschey, 2006; Mansfield, 1993; Boyes, 2004; Samuelson & Mark, 2005; Allen,

et al, 2005). These topics covered in intermediate microeconomics appear and are taught

in the same form in managerial economics. Some texts have more business content than

others. Nonetheless, such business content is not enough to adequately equip the student

to link economics and business courses.

In teaching managerial economics, regardless of the textbook adopted, the

professor can inject business content into discussions to enable students appreciate the

importance of economics in business courses, such as accounting, finance, management

science, quantitative analysis, strategic management, operations management, and

organizational behavior. Interlinking these courses would give students the choice of

majoring in economics while spontaneously acquiring adequate business knowledge for

the real world.


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Furthermore, many professors of managerial economics may not have a business

background. These professors are academically or professionally qualified to teach in

business schools, as per AACSB (Gooding, Cobb & Scroggins, 2007). Since economics

PhDs are most likely to come from Arts and Sciences, they are inclined to approach the

teaching of managerial economics and other economics courses from a purely social

science perspective, irrespective of the department. Business students are left to figure

out by themselves the links between social science illustrations and business applications.

In many economics courses taught as social sciencesmanagerial economics,

industrial organization, antitrust and regulation, money and banking, and international

finance, just to name a fewthere are numerous areas where business content can be

injected during the course to the benefit of the students. These additions could stimulate

the imagination and experiences of the students, thereby providing students good reasons

to consider economics as a major in business schools.

For instance, are there similarities between isocosts, isoquants and production

possibility frontiers (PPF) as discussed in economics, and feasible regions in optimization

problems as explained in management science or quantitative analysis? Is the total cost

curve in economics the same as linear total cost in business? Does the degree of

operating leverage (DOL) as taught in managerial accounting or finance defy efficient

combinations of fixed and variable costs as derived in economics? These and many other

questions that leave gaps in the minds of the students could be answered by proper

teaching of managerial economics.

The next section of this paper discusses linear programming as presented in

economics and management science; section III analyzes a cost function in economics


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and its specific application (relevant range and DOL) in business; section IV illustrates

resource marginal productivity and performance evaluations as they relates to financial

markets; and section V concludes. Part A of each section contains presentations in a

typical economics course and Part B shows the business counterparts. Part C (and D

when necessary) integrates both parts. These are all managerial economics topics that

could be extended to enable students to gain deep appreciation for economics while

acquiring complementary business skills.

II LINEAR AND NON-LINEAR PROGRAMMING

A Economics Analysis

The objective of this topic is to demonstrate the use of optimization in economics.

Individuals maximize utility subject to market constraints. Society in general maximizes

outputs from limited or scarce resources. Firms maximize profits and revenues and also

minimize costs. All economic agents including the firm are faced with constraints.

A basic linear programming (LP) problem in economics is the cost minimization.

Along a production function, Q = f(K, L), there is technologically efficient combination

ofK(capital) andL (labor) that yields the optimal level of output, Q. A given output

level could be produced using more Kand lessL or less Kand moreL, taking into

account prices of the inputs, rand w. The optimal units ofKandL are derived from the

LP statement, minimize total cost, TC = rK + wL subject to Q = f (K, L). Here, the TC

equation is the objective function the LP tries to minimize given the Q function.

In economics, isoquants, meaning equal quantity and isocosts, equal cost, are used

to illustrate the technologically efficient combinations ofKandL in the objective and

constraint functions. Capital (K) is normally graphed as the production input on the


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vertical axis and labor (L) on the horizontal axis. The isoquants are generally convex to

the origin (since inputs are not perfect substitutes) and the isocosts are linear, intersecting

capital (K) axis and labor (L) axis.

Economic results are attained based on incremental or marginal analysis. Moving

along the isoquant changes the combinations ofKandL and this is dictated by the slope

of the isoquant. The slope of the isoquant is the marginal rate of technical substitution of

labor for capital (MRTSLK), which equals the marginal product of labor (MPL) divided by

the marginal product of capital (MPK):

MRTSLK = (MPL)/(MPK). (2.1)

Isoquants have four main properties: they are convex to the origin; isoquants further from

the origin denote larger level of outputs; they sloped downward; and isoquants never

intersect.

In addition to technological efficiency illustrated by the isoquant, market

constraint is illustrated by the isocost. The isocost line reflects all combinations ofKand

L the firm can employ in production for a given budget. The isocost line is depicted by

TC= wL + rK, where TC is the total costs, w equals price of labor (wage rate) and r

equals cost of capital (interest rate). The absolute value of the slope of the isocost line

equals the relative prices of the inputs, KandL, which is w/r. Efficiency (least costly

method of production) requires that firms employ the units of capital and labor where the

slopes of the isoquant and isocost lines are equal. That is where:

MRTSLK=(MPL)/(MPK) = w/r. (2.2)

Graphically, at the optimal point, the isoquant is tangent to the isocost. By cross

multiplication, the two right-hand terms become:


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(MPL)/w = (MPK)/r (2.3)

The producers least-cost input combination golden rule is for the manager operating in a

competitive input market to employ inputs such that the marginal product per dollar

spent is equal across all inputs applied. Isolating Kin objective function (TC = rk +

wL),

K = TC/r w/r(L) (2.4)

Figure 2.1 Isocost and Isoquant

As the scale of production expands, there will be a family of isocosts and isoquants as

indicated by the broken line and curve known as expansion path.

The dual version of cost minimization is revenue or profit maximization. A firm

producing two outputs,Xand Y, using KandL as inputs would maximize output, Q(X, Y)

= f(Kx, Lx,Ky,Ly) subject to TC = [r(Kx+Ky) + w(Lx+Ly)]. The profit statement would be

=pQ(X,Y) TC, that is, [pxQ(X)+p

yQ(Y)] (rK

x+ wL

x+ rK

y+ wL

y), wherep

xand p

y

equal the prices of the product, respectively.

The production possibilities (PPF) facing an entrepreneur are similar to that of an

economy. LP constraint maximization for the firm can be graphically depicted by the

TC/r

TC/w

K

L

isoquant

isocost


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PPFthe boundary between output attainable and unattainable using available resources

and technology. The PPF is bowed off from the origin due to the increasing opportunity

cost. This is illustrated in figure 2.2

Figure 2.2 Production Possibilities Frontier

The slope of the PPF is the marginal rate of transformation (MRT). As producers

in the economy transfers resources from the production of Y (a capital good for example)

to the production of X (consumption good), more units of Y would have to be sacrificed.

If equal units of resources are exchanged in the production of both goods, the PPF would

be linear. It is emphasized that an economy cannot produce outside the PPF, because

resources or inputs are fixed. The production possibility frontier is constrained by fixed

inputs and technology.

The most common method applied in illustrating optimization using linear or non-

linear programming is the use of the Lagrangian technique (See Appendix A for

illustration). In economics graduate departments, the student is assumed to have a

reasonable background in linear algebra to solve for optimal levels of unknown variables.

B Business Analysis

PPF

Y

X


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In business courses, such as management science, quantitative methods or

decision analysis, optimization using linear programming is approached differently.

Although the model is the same as in economics, the approach is prescriptive and the

analysis is more applied. The objective function and constraints containing the decision

variables are stated. It could be total profits for maximization or total costs for

minimization. As in part A, I will illustrate both minimization and maximization

problems, then compare parts A and B in part C.

Suppose a dietician in a home for the elderly is faced with the objective of

providing her residents with two meals, m1 and m2. Each meal should be rich in vitamin

C, iron and zinc. The prices of the meals and nutritional contents of vitamin C, iron and

zinc per hypothetical unit are provided in table 2.1.

Table 2.1 Prices and nutrients per lb for each meal

Meal (m1) Meal m2

Cost per meal $0.75 $1.00 Minimum daily needsVitamin C (units) 12 5 27

Iron 4 4 16Zinc 2 8 14

The problem facing the dietician is to determine what combination of the two

meals will satisfy the minimum daily needs and at the same time incur the least cost. The

linear programming would be:

Minimize C = 0.75m1 + m2 (objective function)

Subject to 12m1 + 5m2 >= 27 (vitamin C constraint)

4m1 + 4m2 >= 16 (iron constraint)

2m1 + 8m2 >= 14 (zinc constraint)

m1 and m2 > 0 (positive and whole meal requirement)


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Figure 2.3 below shows the graphical optimal solutions to the dieticians problem and the

exact points derived with simple algebraic manipulations of the LP equations.

Figure 2.3 The Feasible Region

There are four extreme pointsa, b, c and d. The area to the right of the extreme points

is the feasible region. Owing to the positive food requirements for both meals, only

points b and c are of importance to the dietician. The optimal solution to this simplified

minimization problem is at extreme point c where the dietitian would prepare 3 lb and 1

lb of meals 1 and 2, respectively, and spend $3.25 per day for both meals. A similar

illustration can be found in Chiang & Wainwright (2005).

In a management science course, LP might be a production maximization

problem. Mansfield (1993) has a good example of linear programming for a multiple-

product firm. Suppose XXX Auto Company can produce sedan and sport cars using four

facilities: sedan assembly plant, engine assembly plant, sheet metal stamping plant and

sport car assembly plant. Each sedan car that is produced per hour uses 4.5% of the

m1

6

3

5

2

1 42

m2

4

1

53 6

2m1+8m2=14. (zinc)

12m1+5m2=27vitamin C border

4m1+4m2=16

iron border

a

b, C =0.75(1)+1(3)=$3.75

c, C=0.75(3)+1(1)=$3.25

d0


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sedan assembly capacity and each sport car utilizes 4% of the sport car assembly plant.

Other percentage requirements per hour for engine and sheet metal stamping are

presented in table 2.2.

Table 2.2 Percentage of XXX Auto Company Fixed Capacity Needed per Hour

Plant Sedan Sport

Sedan assembly 4.5 0Sport car assembly 0 4

Engine assembly 2 3.33Sheet metal stamping 4 2

Contribution margin2 $400 $600

Let QSD and QSP be units of sedan and sport cars, respectively, produced per hour, and

equals total contribution margin per hour. The maximization problem would be:

Maximize = 400QSD + 600QSP

Subject to: .045 QSD


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Points ABCDE are the extreme points. The feasible region is defined by

0ABCDE. Maps of isoprofit lines can be drawn to determine sedan and sport car units

that generate the largest profits (per hour) for XXX Auto Company. Algebraically, the

feasible solutions for the extreme points are presented below on table 2.2. The optimal

point set that gives the maximum profit is at C, where XXX Auto Company produces

approximately 14 sedan and 22 sports cars per hour, assuming that there are customers

who are able and willing to buy these cars.

Table 2.3 Optimal Feasible Solutions

Points Sedan Sport Contribution Margins TotalA 0 25 400 600 $15,000

B 8.37 25 400 600 18,348

C 14.13 21.73 400 600 18,690

D 22.2 5.6 400 600 12,160E 22.2 0 400 600 8,880

6040

Qsport

60

20

20

40

Qsedan

Sedan car border

Sheet metal border

Engine border

Sport car borderB

A

E

D

C

0


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Linear programming problems with more than two decision variables are

cumbersome to solve using graphs and algebra. To avoid mathematical complications

that might usurp the students concentration, many business departments make use of

software packages made available by modern technology in teaching linear or nonlinear

programming. Excels Solver is readily available on every computer. In addition to

solving for optimal values, Excels Solver produces Answer, Sensitivity and Limits

Reports (Ragsdale, 2001). These reports are important for a manager in the day-to-day

allocation of business resources.

The first part of Answer Report provides the final values, which are the optimal

solutions to the LP (linear programming problem). The last part has formula, status and

slack columns. The formula columns have spreadsheet cell keys showing upper or lower

bounds (see Table A1 at the end). The status column indicates binding and nonbinding

constraints. Slacks are associated with the status column. Slacks are unutilized

resources. A binding constraint has zero slack and a nonbinding constraint has positive

slack. Thus, nonbinding constraints have unutilized resources.

Businesses are surrounded by uncertainty. Sensitivity analysis provides

information on how much the objective function coefficient could change without

affecting the optimal solution of the LP. This report contains allowable increase and

decrease of the objective and constraint coefficients (see Tables A2 and A3 at the end).

If prices change or the costs of production change, profits change as well. The sensitivity

Report becomes handy to the manager in times of volatile prices.

Another important information provided by Sensitivity Report in LP output is the

shadow price. The shadow price for a constraint shows how much the optimal


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solution would change with some changes in available resources (the bs in Appendix A).

Holding other variables constant, if the shadow price of a constraint is positive,

increasing the factor within the allowable increase would increase the optimal solution to

the LPs objective function and vice versa. A zero shadow price indicates that the

available resources have no further impact on the optimal solution. Thus, the shadow

price of a nonbinding constraint is always zero. Shadow price would be useful when the

organization is concerned with relevant cost or faced with divisional transfer pricing. Is

the shadow price related to the concept of opportunity cost as used in economics?

The Limits Report shows upper and lower limits. That is, it shows the largest and

smallest values each variable can take, while the values of all other variables are held

constant.

C Interdisciplinary Approach

Parts A and B of this section illustrate different approaches in economics and

business departments. The presentation of linear and nonlinear programming in

economics is shown in part A. The way linear programming is taught in courses such as

management science, quantitative analysis or operation management in a business

department is shown in part B. If the same group of students is enrolled in both courses,

most of them might not adequately relate the two approaches, even though both are linear

or nonlinear programming.

Take Figure 2.3 for example, reproduced here as Figure 2.3C. The dotted parts of

the borderlines depicting the constraints are removed and we have the solid-line parts

(points a, b, c and d) showing the feasible region.

Figure 2.3C Feasible Region, Isoquant and Isocost


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The student should understand the equivalent illustrations in parts A and B of this

section. First, while in economics, we have a smooth, well-behaved, decreasing,

differentiable and convex to the origin isoquant; the equivalence in management science

is a rugged and kinked feasible boundary line constructed by fixed input constraints.

Second, the optimal solution in management science is equivalent to the efficient

technological inputs combination as illustrated in economicsthat is, where the slope of

the isocost is tangent to the slope of the isoquant; this is mathematically expressed as in

equations (2.2) and (2.3)(dQ/dL)/(dQ/dK) = w/r; marginal rate of technical substitution

should equal ratio of input prices.

MRTSLK=(MPL)/(MPK) = w/r.

For the dietician, this ratio is 0.75, the price of meal 1 divided by the price of meal 2.

which is also equal to the slope of the objective function, , and the slope of the feasible

region at point of tangency in Figure 2.3C.

m1

6

3

5

2

1 42

m2

4

1

53 6

2m1+8m2=14.

12m1+5m2=27

vitamin C border

4m1+4m2=16

iron border

a

b, C =0.75(1)+1(3)=$3.75

c, C=0.75(3)+1(1)=$3.25

d0


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Third, while economics students would mistake the constraints for the isocost, the

isocost is different, as can be seen in Figure 2.3C. In fact, the LP constraints are

determinants of the feasible region (isoquant). Fourth, the properties of the isoquant

would be more memorable to the students using the constructs responsible for the shape.

For example, two of the properties say, isoquants further from the origin reflect greater

output and isoquants do not intersect. This could be explained by the fact that higher

feasible regions are constructed by higher and different levels of input constraints.

There are families of isoquants that are either linear for perfect substitutes or L-

shaped for perfect complements. The business counterparts and industries that display

such input characteristics and generate these types of feasible regions would be of interest

for economics and business researchers.

The same argument applies to a firms PPF and a maximization problem as shown

in Figure 2.4. Figure 2.4C reflects the feasible region, area 0ABCDE, for the XXX Auto

company problem. The dotted parts of Figure 2.4 depicting sedan, sport cars, sheet metal

and assembly constraints are removed. Instead of a concave, continuous and increasing

PPF as illustrated in economics (Figure 2.2), the solid line ABCDE becomes a kinked

PPF showing the possible combinations of sedan and sport cars XXX Auto Company can

produce with available inputs.

Figure 2.4C Maximization, Feasible Region/PPF


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If properly drawn to scale, the slope of the isoprofit line tangent to the optimal feasible

set should equal the ratio of the prices of the cars.

At point B, XXX Auto Company can produce approximately 8 sedans and 25

sport cars. At point C, the optimal feasible set, the company can produce approximately

14 sedans and 22 sport cars. At point D, it produces roughly 22 sport cars and 6 sedans.

If the company decides to produce at any points other than point C, the opportunity cost

of making such decision would be equal to the profits forgone. In this case, it would be

$342 at point B and $6,520 at point D (in net values).

The best learners as described in learning motivation literature are students who

link what they learned from one course to other courses. (Harackiewicz, Barron & Elliot,

1997, 2001; Ames & Archer, 1988; Hidi & Harachiewicz, 2000; Barron & Harackiewicz,

2001). The question remains whether the student can relate the materials as learned in

economics to what (s)he learned in management science. Integrating both parts as

6040

Qsport

60

20

20

40

Qsedan

(14.13, 21.73) = $18,680

(8.37, 25) = $18,348

(22.2, 5.6)= $12,160

BA

E

D

C

0


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described in part C in managerial economics would contribute to the students overall

comprehension of the topic. Knowing that the objective and constraint functions in LPs

are created from unit revenues and unit costs, efficiency which is the tenet of economics,

would be pursued, recognized and upheld in business analysis.

III COST FUNCTIONS, DOL AND THE RELEVANT RANGE

Production costs are common topics both in economics and business courses.

These costs are the same but are discussed differently. As in Section II above, Part A

illustrates the general approach used in teaching production costs in economics, and part

B shows how costs are explained in accounting. Parts C and D discuss the links.


The production function depends on fixed and variable inputs. Output (Q) is

expressed as a function of inputs or factors, such as capital, labor and materials. That is,

Q =f(K, L, M). Capital usually is the fixed input while labor and materials are the

variable inputs. Short-run and long-run periods are distinguished. A short run is a

production period when the amount of at least one production input is held fixed. In the

long run, all inputs can be changed.

Economic costs are comprised of explicit and implicit costs, which are the

opportunity costs; that is, the next best alternative use of these resources. Total costs

(TC) equal total fixed cost (TFC) plus total variable cost (TVC). In the short-run,

variable costs change with output but total fixed costs do not vary as output varies.

Average cost (AC) equals TC divided by quantity (Q) produced. Average variable cost

(AVC) is TVC divided by quantity (Q) produced. AFC is TFC divided by Q produced.


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Next, marginal cost (MC) is the change in cost associated with a one-unit change in

quantity (output) produced. MC = dTC/dQ, the first order derivative of total cost.

For the purpose of distinction between cost behaviors as illustrated in economics,

Figure 3.1 shows TC, TVC and TFC curves.

Figure 3.1 Costs Functions

The total cost function is monotonically increasing and continuously

differentiable. It has concave and convex segments. Economists are concerned with the

inflection points. How do costs behave with increases in output? Initially, MC falls with

an increase in output, and starts to rise again as output increases. The declining and

rising parts of the MC curve are caused by the shape of the TVC, which makes the ATC

and AVC curves convex. Thus, the ATC, AVC and MC are U-shaped. This also reflects

the properties of diminishing marginal returns.

TVC

TC

Output

TFC

Cost


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The long-run average total cost (LRAC) curve is the envelope of the short-run

average cost curves. Long-run involves plant expansion. Cost elasticities and economies

of scale in production levels are illustrated.

In undergraduate economics textbooks, graphs are often used to illustrate these

important properties of cost behaviors. In graduate courses differential calculus is

applied to describe and prove these properties.

B Business Analysis

Total cost (TC) is also comprised of fixed and variable costs. Business class

discussions are less mathematical and the graphical representations of these costs are

different from those displayed in part A of this section. Linear graphs rather than curves

suffice to convey TC, FC and VC as shown in Figure 3.2.

Figure 3.2

Here, costs are further decomposed into direct and indirect costs. Direct costs are

costs of labor and materials that can specifically be identified with an object. In this case,

the object is the output. Indirect costs are shared and also called overhead costs. Direct

Cost

TC

Output

TVC

TFC


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and indirect costs can be fixed or variable. Supervisory employees salaries, for

instance, are direct fixed costs; labor wages are direct and variable costs since they

change as the volume of activity changes. Electricity used to operate a plant is an

indirect variable cost, while machine depreciation is an indirect fixed cost.

In order for a business student to have a full understanding of this topic, we

cannot discuss variable cost without referring to product and period costs; that is

absorption (full) costing and variable costing, respectively. Variable costing assigns

variable manufacturing costs (direct labor, direct material and variable manufacturing

overhead) to the product. Absorption costing assigns full costs including fixed

manufacturing overhead to the product. Under variable costing, fixed manufacturing

overhead is a period cost while under absorption costing; fixed manufacturing overhead

is a product cost.

Table 3.1 Economics and Accounting Costs

Economics Classification

A - Fixed Costs (K) B - Variable Costs (L)Accounting Assignment Accounting Assignment

1.Machine (dep)* Indirect 1.Material Direct2.Buildings (dep) Indirect 2.Labor Direct

3.Cost of capital Indirect 3.Utilities Indirect**4.Plant Supervisor* Direct/indirect^ 4.Factory Supplies Indirect**

5.Plant Maintenance* Indirect 5.Sales Commission Indirect

6.Insurance Indirect 6.Delivery Charges Indirect7.Property Taxes Indirect 7.Labor Fringe3 Indirect**

8.Advertising Indirect9.Mngment Salaries Indirect

^Plant supervisors pay could be indirect if (s)he supervises more than one plant.*Fixed manufacturing overhead. **Variable manufacturing overhead.

Apparently, the definitions of fixed and variable costs are the same in economics

and accounting, but the conceptualizations are different. Fixed costs are costs that remain


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constant in total as volume changes. All items in column A qualify as fixed costs. For

instance, once a company makes a budget for advertising, it is unlikely to change much

during an operating period. Advertising qualifies as a fixed selling cost; sales

commission and delivery charges are variable selling costs. Cost of capital is the normal

profit that the firm planned to pay its investors, including bond, preferred and common

stocks holders. Plant maintenance covers maintenance contracts, janitors and guards. The

size of each of these items is different across industries, but the nature is similar whether

the firm is operating an airline, manufacturing autos, or is involved with health care,

education or food processing companies.

A course in economics groups these items in column A as fixed costs and

conceptualizes them as property, plant and equipment due to their constant behaviors as

volume changes. It classifies column B items as variable costs, and oftentimes, for

simplicity, identifies them as labor. A course such as managerial economics should not

follow suit. While a course in economic theory is more concerned with deriving the

efficiency benchmark, managerial economics should be more elaborate and specific

about the business equivalence of the economic classifications.

C Operating Income, Bankruptcy Protection and Shutdown

We can see the importance of integrating the economic illustration with real

accounting terms by analyzing different market scenarios. Business students would find

it more meaningful to incorporate a bankruptcy situation in the processes leading to

shutdown. Lets use ATC, AVC and MC curves as defined in part A of this section.


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Figure 3.3 ATC, AVC and MC

Assume this firm is operating in a competitive market. It maximizes economic

profits by producing where price (MR) equals MC. At price g, point a on Figure 3.3, the

neo-classical firm is making positive economic profit. Positive economic profit is a huge

accounting profit that is partly distributed to shareholders and partly kept as retained

earnings. Retained earnings, which is placed on the stockholders equity section of the

firms balance sheet, signals great performance and appears favorable on Wall Street.

The firms performance exceeds Wall Streets expectation.

If there is high competition and the price of the product drops to e, point b, this

firm makes zero economic profit but makes normal accounting profits that cover the cost

of capital. Investors and financial analysts could live with this level of profit. Below

point c, it pays the firm to shut down because total revenue is less than variable costs and

the firm is operating at a loss. If the firm shuts down at point c, it bears losses equal to its

fixed costs. Point c upward along the marginal cost (MC) is the short-run supply curve of

the neo-classical economic firm.

$

AVC

MC

ATC

q

a

c

b

f

e

0

g

d


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If revenues exceed variable costs, between points b and c, the firm is making

operating income and it may pay the firm to remain in business because it can afford all

variable costs and parts of its fixed costs. Due to competition and economic downturns, a

typical firm in many industries is more likely to find itself in this section of the graph.

Economic analyses assume that fixed costs must be paid in the short run

regardless of whether the firm continues operation or shuts down. The question is, which

of those fixed costs on Table 3.1, column A are unavoidable in the short run? Clearly,

the firm can avoid all items in column B if it stops operating. In order to answer this

question, it becomes relevant to consider the working capital of the firm.

Working capital equals current assets minus current liabilities. It measures

efficiency and the liquidity of the current operating cycle. Between points b and c, if

current assets exceed current liabilities, it indicates a company has enough cash flow to

cover its current obligations. On the other hand, if current assets are less than current

liabilities and the firm cannot pay its creditors, suppliers and employees (items in column

B, Table 3.2), the firm would be forced to file for Chapter 11. Therefore, the key to

survival between points b and c in Figure 3.3 would be proper working capital

management. Table 3.2 shows a simplified working capital of a firm.

Table 3.2 Working Capital

A - Current Assets B - Current LiabilitiesCash Accounts and Notes Payable

Accounts and Notes Receivable Interest Payable

Prepaid Expenses Accrued LiabilitiesMarketable Securities Accrued Salaries and Fringe

Inventories Other DebtsOther Liquid Assets


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All items on Table 3.1 would siphon cash in column A or increase all items in

column B, Table 3.2. Financial analysts often use current ratio, inventory turnover and

accounts receivable turnover ratios to assess the ability of the firm to pay current costs in

Table 3.1. In column A, Table 3.1, items numbered 1 and 2, depreciation expense, is not

a cash item; however, sometime in the past the firm borrowed to set up plants, properties

and equipment. Some of the borrowed principals are matured and reflect on column B,

Table 3.2. Item 3, column B on Table 3.1 also increases interest payable on Table 3.2.

Except for items 6 and 7, which may be prepaid, items 4 through 9 are fixed costs, which

the firm can avoid if it stops operating..

The only unavoidable fixed costs, if the firm shuts down, are the undepreciated

(carrying values) parts of items 1 and 2 of Table 3.1. Depending on the industry, these

items could be significant on the firms balance sheet. Thus, between points b and c of

figure 3.3, some firms would survive longer than others during bankruptcy protection,

depending on their working capital management.

The next question of concern to a managerial economics student is the essence of

separating these costs in Table 3.1 into indirect and direct costs. Direct costs are costs

that can be traced directly to the object, while indirect or overhead costs are allocated to

different objects. Also, some of the costs on Table 3.1, especially material, labor and

supervisory costs, raise the products intrinsic values; the quality of the product can

directly be traced to the material and labor used. Advertising, on the other hand, conveys

information to the consumer and may only reflect on the consumers perception of the

product. These costs are indirect, because they cannot directly be identified with the

product.


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Whether or not a firm commits more resources to such indirect costs depends on

the managements philosophy about a product. For instance, management that believes

that a product is 90% perception may commit more resources to indirect costs such as

advertising and gold-plated headquarters to create a brand and goodwill (nonproductive

assets) than to invest more in labor and materials.

D - The Relevant Range and Operating Leverage

Some curious students, however, might also be baffled by the curved TC and

TVC (Figure 3.1) learned in economics courses and the linear TC and TVC graphs

(Figure 3.2) learned in business courses. There is a large conceptual gap between this

region of costs as learned in economics and as learned in business courses. This gap

needs to be filled by appropriate illustrations in managerial economics.

The relevant range appears among the last chapters of some management

accounting texts (Hansen & Mowen, 2003, p. 671). The instructor might not get to that

chapter by the end of the course. However, relevant range is completely nonexistent in

most economics texts. Business analyses assume that there is a portion of the TC and

TVC where both costs and revenues are linear. It is the current operating range for which

the linear cost and revenue relationship are valid (Hansen & Mowen, 2003). See Figure

3.4.

Linearity properties of total revenue and total cost are among important

assumptions in cost-volume-profit (CVP) analysis where breakeven (BE) quantities are

derived. Other important terms within this range are contribution margin (CM), margin

of safety and operating leverage. Breakeven quantity is the level of production where

total revenue and total cost are equal and could also be derived by dividing TFC by unit


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CM. CM equals sales minus variable costs. Therefore, at breakeven (BE), point b on

figure 3.3, contribution margin (CM) equals total fixed costs (column A Table 3.1).

Margin of safety is the sales or revenue expected above the breakeven quantity.

Figure 3.4

Operating leverage is the relative combination of fixed and variable costs and the

use of fixed assets (costs) to generate revenue. In an operation where fixed costs (fixed

assets) can be substituted for variable costs (labor), a firm can raise its CM by investing

more in fixed assets and lowering variable costs. In this case, the firm uses fixed cost as

a lever to increase its contribution margin. As the firm invests in fixed costs, it also

acquires more risks. The degree of operating leverage (DOL) is a measure of this risk as

shown in equation 3.5 below. Table 3.3 illustrates CVP income statement.

Table 3.3 CVP Income Statement

ZZZ COMPANY

TVC

TC

Output

TFC

Cost

The Relevant Range


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PROFORMA CVP INCOME STATEMENTFOR THE MONTH ENDING MAR 31, 20XX

1000 sold Per unit 1100 sold 1100 sold 900 sold

Sales $600,000 $600 $660,000 $660,000 $540,000VC (400,000) (400) (440,000) (385,000)* (315,000)

CM 200,000 200 220,000 275,000 225,000FC (200,000) (200) (200,000) (235,000) (235,000)

Net Income 0 0 20,000 40,000 (10,000)

CM ratio 33.33% 33.33% 42%*FC are substituted for some VC; VC now $350 per unit DOL = 6.875%

DOL is sensitivity of profits to changes in output. It is an elasticity concept, that

is, dividing a percentage change in sales into a percentage change in profit. Given that Q

equals quantity sold, P equals price of the good, AVC equals unit variable cost, TFC is

total fixed costs and profit is = Q(P AVC) TFC,

DOL = (d/)/(dQ/Q) = {dQ(P AVC)/[Q(P AVC) TFC]}/dQ/Q (3.4)

Rearranging equation (3.4), DOL becomes:

{Q(P AVC)}/{Q(P AVC) TFC} (3.5)

The higher the TFC4 (items in column A, Table 3.1), the greater is the DOL for

the firm. Thus, if TFC denotes only costs associated with properties, plants and

equipment, excluding a host of other items that meet the definitions of fixed costs, the

risks facing the firm are understated.

A higher level of operating leverage magnifies profits in times of high sales and

magnifies losses during recession. For example, on Table 3.3, with 6.875 DOL, a drop in

sales by 200 units reduces profit from a positive $40,000 to a loss of $10,000. Higher

levels of fixed costs, therefore, could be linked to higher levels of risk.

Moreover, the application of operating leverage as analyzed in business courses

undermines technologically efficient combinations of capital and labor as discussed under


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isoquant and isocost (equations 2.2 and 2.3) in section II. While the level of production

is endogenously determined by the production function in economics analysis, modern

firms using operating leverage are bestowed, however, with the power to produce at any

level. The firm production point might not take into consideration scale diseconomies.

The firm applying operating leverage would therefore over-invest in assets.

CVP is a managerial economics topic as well as a management accounting topic.

Linearity assumption, the relevant range and operating leverage, therefore must be linked

and contrasted with the golden rule of inputs combination as discussed in economics if

the objective of a managerial economics course is to encourage business students to apply

mastery style of learning.

Note also that the variables used under the topics of isocosts and isoquants, which

are capital and labor (fixed and variable costs, respectively), are the same units used in

the construction of feasible regions in business courses such as quantitative analysis,

management science or operations management. The same variables are used in the

preparation of CVP income statements in an accounting course and operating leverage in

a finance course. Furthermore, these topics are heavily tested in professional business

examinations such as CPA, CIA and CMA. Students would improve their performance

on these exams if they understood the underlying theoretical basis.

IV MARGINAL PRODUCT AND PERFORMANCE EVALUATION


A firm incurs costs to produce. Production function is the other side of the coin to

the cost function. In the region where the marginal cost is increasing, the marginal

product curve is decreasing and vice versa. Thus, the short-run total product curve is a


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mirror image of the short-run total costs curve as shown in Figure 3.1 in Section III. The

law of diminishing marginal returns applies where the total cost curve is rising quickly

and the marginal product is decreasing.

Marginal analysis is a useful tool in economics, especially in resource

management and factor addition and reduction. The efficiency rule is to hire factors until

revenues brought in by a factor equals the cost of hiring the factor. That is, marginal

revenue product equals the factor price.

Let Q = output be a function of K (capital) and L (labor), Q = g(K,L); and

Revenue (R) be a function of output Q, R = f(Q). By the chain rule, we can find the

marginal revenue product of capital (MRPk) and marginal revenue product of labor

(MRPL) in equations (4.1) and (4.2) respectively, as:

dR/dK = (dR/dQ)(dQ/dK) (4.1)

dR/dL = (dR/dQ)(dQ/dL) (4.2)

From equations (4.1) and (4.2), (dR/dQ) is the marginal revenue (MR) and (dQ/dK) and

(dQ/dL) are the marginal physical product of capital (MPk) and the marginal physical

product of labor MPL, respectively.

Therefore, the marginal revenue product of capital (MRPk), which is of interest to

this section of the paper, equals MR x MPk. In adding capital, economic efficiency

requires that MRPk is set to equal the unit costs of acquisition of physical capital or factor

price (PF).

MRPk = PFk. (4.3)

B Business Analysis


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While economics is concerned with productivity of physical capital such as plants

and other assets, a course in finance would be concerned with the funds to acquire these

plants. Firms finance their assets with different combinations of sources of financing

known as capital structures. These are the selling of common stocks, preferred stocks,

bonds, the use of retained earnings, etc., generally classified into debt and equity. The

use of any of these sources of financing entails an opportunity cost of capital.

Thus, the heuristic approach in capital budgeting is for firms to invest in capital

projects until the rate of return from the project is equal to the cost of capital or an

ongoing interest rate. This efficiency rule is theoretically equivalent to the rule derived in

equation (4.3), part A - Economic Analysis, where dR/dK = MRPk= PFk.

The appropriate rate of return for any capital project, nonetheless, is controversial.

The desired or required rate of return (RRR) might be a good estimatethat is, the

minimum rate an investor would accept on a project of a comparable nature. Some call it

a hurdle rate. Determining these benchmark rates can be a breathtaking exercise. Others

believe that the cost of capital would be an appropriate threshold for the rate of return.

Combining different sources of financing, the cost of capital may not be readily

available. The after-tax cost of debt is the firms borrowing rate less applicable taxes.

The cost of preferred stocks is related to the dividends paid. The cost of equity financing

oftentimes is based on estimates. Theoretically, most commonly used for cost of equity

are the dividend growth model and CAPM (capital assets pricing model). The weighted

average of these three sources of financing (debts, preferred stocks and equity) is

generally known as the weighted average cost of capital (WACC). Whether CAPM is the


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appropriate measure of the cost of equity and WACC is the accurate measure of the

actual cost of capital remains a hot debate in finance literature.

C MRPk, Rate of Return and Performance Evaluation

Perhaps applying a marginal capital productivity rate set equal to the factor price

as in economics might give a better measure for the rate of return and the unit cost of

capital, respectively. The marginal revenue product of capital, (MRPk), is MR multiplied

by MPk. Assuming the firm is operating in a perfectly competitive industry, thus facing a

perfectly elastic demand curve, marginal revenue (MR) is equal to the price (P) of the

good the firm produces. The market price (P) is known. The price (P) multiplied by the

MPkwould give MRPk which could be compared to industrial rates to give an accurate

measure of the rate of return of acquired capital. The productivity rate (PR) could be

derived

(PRk) = (MRPk)/TR. (4.4)

= (P x MPk)/TR = (P x MPk)/(P x Q)

= MPk/Q or MPk/TPk (4.5)

Equation (4.5) is the percentage change in production and could be considered the

economic version of return on investment (ROI) or return on assets (ROA). The firm

would first equate its MRPk to the PF (actual acquisition cost) in order to select the

efficient levels of investment, and then determine the PR.

Suppose a given company can invest in units of capital. The cost of renting one

unit is $130.00 and the product sells for $5.00. Table 4.1 contains total product (TP),

marginal product (MP), marginal revenue product (MRP) and the productivity rate (PR)

of capital. With a unit cost of capital $130, efficiency requires that this company invest


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in 3 units of capital that yield 18% productivity. If the cost of acquisition drops to

$120.00, the firm gains by investing in 4 units of capital earning productivity rate of 13%.

Table 4.1 Total Product(TP) and Productivity Rate (PR)

Units of Capital TPk MPk MRPk PRk

1 88 88 440

2 124 36 180 29%

3 152 28 140 18%4 176 24 120 13%

5 198 22 110 11%

This efficiency rule could also be applied to determine the performance of human

capital such as CEOs or professional athletes to ascertain if the additional revenue they

generate (MRPk) as CEOs or pro-footballers is equivalent to their pay. Bonuses should

be compared to their productivity rate (PRk).

Therefore, Residual Income (RI), which is Income (Required Rate of Return x

Investment). Substituting the productivity rate (PRk) into RI equation for the rate of

return,

RI = Income (PRkx Investment) (4.6)

Residual income is usually compared with Return on Investment (ROI).

The Economic Value Added (EVA) equation, another important performance

measure in the literature, can also be altered by substituting (4.5) into the EVA equation:

EVA = ATOI [PRkx (total assets current liabilities)] (4.7)

where ATOI is After-Tax Operating Income.

The idea is to integrate economics concepts into a finance course. Teaching

managerial economics as in Part A, with regard to resource acquisitions, without

reference to Part B would leave many students unable to reconcile theoretical concepts in


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economics courses with finance courses. This would affect abstract analytical and

decision-making skills and graduates during their careers may generally rely on non-

economic factors in decision-making. Managerial economics would bridge the gap if

approached from interdisciplinary perspective.

VI CONCLUSION

Different methods of classroom presentation are illustrated. Linear programming,

production costs and marginal revenue product of capital are all economics topics, which

are also topics in management science or quantitative methods, accounting, and finance.

respectively. Part A of each section is a typical economics discussion. Part B is the

business school counterpart. Part C (and D when necessary) links and tries to integrate

the concepts in economics and business.

Economics forms the theoretical framework for many business courses. It is

shown that presenting these topics in a business department from a pure social science

perspective isolates economics theories from the other business courses. There are

conceptual gaps that dampen business students interest in economics and in turn deprive

the students from being well rounded in business.

It is argued that, if the classroom contents overlap, managerial economics offered

in many business departments could bridge the conceptual gaps between economics

taught as a social science in liberal arts settings, and operation management, accounting

and finance taught as business courses. Students would generate more interest in

economics as they can visualize conceptual connections in these courses. As economics

majors from business schools, students would develop more skills and be exposed to

more career choices.


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Tables

Table A1 Hypothetical Answer Report - Constraints

Cell Variable Cell Value Formula Status Slack

$C$7 X1 400 $C$7


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performance strategy is to outperform other students and earn higher grades.

Paradoxically, performance learners are found to score higher in examinations

than students who apply mastery style.

2. Contribution Margin is a term used in variable costing, which equals totalrevenue minus total variable costs. Gross Margin is the appropriate term

when absorption costing is used. Gross margin equals revenues minus cost of

goods sold. The latter includes beginning and ending finished goods

inventories and work-in-process inventories.

3. Labor fringe includes social security, life insurance, health insurance, pension,

training, vacation, sick leave, overtime and idle time. Some companies

classify these as indirect costs and others as direct. Many of these items are

expressed as a percentage of labor hours; therefore, they fit into variable costs.

Knowing which items in the firms financial statements are fixed, variable,

direct and indirect is important in making managerial decisions.

4. If executive compensations including bonuses, for example, are classified as

fixed costs, as shown in Table 3.1, the firms DOL increases as well as the

risks facing the firm.


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REFERENCES

Allen, W. Bruce, et al. 2005. Managerial Economics, Theory, Applications, and Cases.Sixth edition. New York: W.W. Norton & Company, Inc.

Ames, Carole and Jennifer Archer. 1988. Achievement Goals in the Classroom:Students Learning Strategies and Motivation Process. Journal of EducationalPsychology. Vol. 80, No. 3, 260-267.

Anderson, Roy C. and Dennis D. Muraoka. 1990. Survey of Managerial EconomicsTextbooks. Journal of Economic Education, Vol. 21, No. 1, 79-91.

Baye, Michael R. 2006. Managerial Economics and Business Strategy, 5th edition.Boston: McGraw-Hill.

Boyes, William. 2004. The New Managerial Economics. Boston, MA: Houghton.

Binger, Brian R. and Elizabeth Hoffman. 1998. Microeconomics with Calculus, 2ndedition. New York: Harper Collins Publishers.

Chiang, Alpha C and Wainwright. 2005. Fundamental Methods of MathematicalEconomics, 4th edition. New York: McGraw-Hill Book Company.

Dean, D.H. and Dolan, R.C. 2001. Liberal Arts or Business: Does the Location ofEconomics Department Alter the Major? Journal of Economic Education, Vol. 32, No.1, 18-35

Gooding, Carl, Richard Cobb and William Scroggins. 2007. The AACSB FacultyQualifications Standard: A Regional Universitys Metrics for Assessing AQ and PQ.Journal of Academic Administration in Higher Education. Vol. 3, Spring-Fall, 1-5.

Gregorowicz, P. and Hegji, C. 1998. Economics in the MBA Curriculum: SomePreliminary Survey Results.Journal of Economic Education, Vol. 29, No. 1, 81-87.

Hansen, Don R. and Maryanne M. Mowen. 2003. Management Accounting, 6th edition,Mason, Ohio: Southwestern Thomson Learning.

Harachiewicz, Judith M., et al. 2000. Short-term and Long-term Consequences ofAchievement Goals: Predicting Interest and Performance Over Time. Journal ofEducational Psychology, Vol. 92, No. 2, 316-330.

____________ 1997. Predictors and Consequences of Achievement Goals in theCollege Classroom: Maintaining Interest and Making the Grade. Journal of Personalityand Social Psychology, Vol. 73, No. 6, 1284-1295.


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Hidi, Suzanne and Judith M. Harachiewicz. 2000. Motivating the AcademicallyUnmotivated: A Critical Issue for the 21st Century. Review of Educational Research.Vol. 70, No.2, 151-179.

Hirschey, Mark. 2006. Managerial Economics, eleventh edition. Canada: Thomson,

Southwestern.

Kasper, H. et al. 2008. Sources of Economics Majors: More Biology, Less Business.Southern Economic Journal. Vol 75, No. 2, 457-472.

Mansfield, Edwin. 1993. Managerial Economics, Theory, Applications, and Cases,second edition. New York: W.W. Norton & Company, Inc.

Marburger, Daniel R. 2004. Making Managerial Economics Relevant to the MBA.Social Science Research Network, January, 1-22.

Ragsdale, Cliff T. 2001. Spreadsheet Modeling and Decision Analysis, 3

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edition.Cincinnati: Southwestern, Thomson Learning.

Samuelson, William and Stephen Marks. 2005. Managerial Economics, fifth edition.Somerset, NJ: John Wiley & Sons, Inc.

Siegfried, John J. 2007. Trends in Undergraduate Economics Degrees, 1991-2006.Journal of Economic Education, Vol 38, No. 3, 360-364.


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Appendix A

The objective function and the constraints are stated. The first and second

derivatives are taken, the former are set equal to zero (necessary conditions), and the

latter are compared to zero (sufficient conditions).

MAX (or MIN) c1X1 + c2 X2 + + cn Xn A2.1

Subject to: a11X1 + a12X2 + a1nXn


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A further breakdown is to carry out a comparative static analysis to check the

effect of any changes in the exogenous parameters, the coefficients and the constants, on

the optimal solutions. In some cases, the professor may extend the illustration to include

specific functions in the objective function. Cobb-Douglas or CES functions come to

mind. Envelope theorem and Kuhn-Tucker conditions (Binger & Hoffman, 1998; Chiang

& Wainwright, 2005) are other techniques the professor might apply in solving

optimization problems in a graduate economics course.

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Teaching Managerial Economics