Questions for Critical Thinking 3
Busi 620 Managerial Economics
Liberty University
Salvatore Chapter 6:
DQ2(a)
What are qualitative forecasts? Qualitative forecasts are methods used to enhance quantitative
forecasts when there is not enough available information to determine market changes, to assess
business opportunities in a future economic environment or to determine future demand for a
product that is in the planning stages.
What are the most important forms of qualitative forecasts? According to Salvatore (2015)
the most important forms of qualitative forecasts are surveys and opinion polls. Many
multinational companies also use foreign advisory committees.
2(b) What is their rationale and usefulness? The rationale for using qualitative methods is to
reduce the risk associated with developing new products, carrying inventory and making capital
expenditures. Surveys are useful to determine future consumer spending, to assess what other
industries are planning in terms of plant and equipment expenditures and to learn what other
companies are forecasting in relation to their sales and expected growth. Opinion polls, on the
other hand, are used to forecast sales based on internal and external information. These include
consumer opinions, the sales force, and an organization’s top management.
DQ3(a) What are time-series data? What are the possible sources of variation in time-series
data? Time-series data is a period of time arranged chronologically by days, weeks, months or
even years. The time-series data is then used in time-series analysis to forecast particular results
based on historical data from the same time-series. Using Black Friday for instance, every year
retailers draw consumers out to shop the day after Thanksgiving in hopes of huge revenues.
Forecasters use this historical information to forecast future revenues.
Sources of variation in time-series data include secular trends, cyclical fluctuations and
seasonal variations. There are often irregular or random influences that influence variations.
Secular trends usually show a long increase or decrease due to population growth, or even the
waning sales of a product that has been outmoded or technologically replaced.
Cyclical fluctuations are caused by the expansion and contraction of the economy. This happens
every few years and can be represented in one instance by the slowing down of new housing
starts.
Seasonal Variations are caused by fluctuations that occur regularly with the seasons year after
year. For example, consumers usually spend more in the winter due to the holidays and more
sales for housing construction are made during the spring and summer due to the weather.
Irregular or random influences are those that are unexpected. These include weather-related
events like tornadoes and wild-fires, wars and strikes.
These aspects of time-series data function together to give forecasters a bigger picture of factors
to work with.
(d) Why does time-series analysis deal primarily with trend and seasonal variations rather
than with cyclical and irregular or random variations? Trend and seasonal variations are
easier to predict and are more dependable than cyclical and irregular or random variations. A
trend occurs over a period of time in the form of a gradual increase or decrease. Seasonal
variations are data that happens around the same time every year. Time-series analysis typically
does not include cyclical fluctuations because they difficult to predict, and depending on the
product, may not even be affected by something like a slow-down in the economy. With regard
to irregular or random variables, it does not make good business sense to try to predict when and
where a disaster will strike, if at all.
(15) Explain why it is still useful to pursue forecasting even though it is often off the mark
by wide margins. The purpose of forecasting is to mitigate short-term risk, and to plan for long-
term growth. Firms using forecasting methods can determine whether product development is
needed to replace a downward trending product. Forecasting is also used to determine production
and inventory levels, and to help plan for capital expenditures. Without forecasting and planning
a firm is vulnerable to irregular or random variables and unable to survive cyclical variations.
Problem 7). The following table presents data on three leading indicators over a three-
month period. Construct the composite index (with each indicator assigned equal weight)
and the diffusion index. (The composite index is obtained by calculating the percentage change
for each series relative to the base month and then averaging these percentage changes. The
percentage change from the first to the second month is 10 for indicator A, 15 for indicator B,
and -10 for indicator C. Their simple average- since each indicator is given equal weight- is 5%.
Taking the first month as the base period with a composite index of 100, we obtain the composite
index of 105 for the second month. The diffusion index from month 1 to 2 is 66.7 (=2/3) because
two indicators move up and move down (see p. 239)).
Both the composite index and the diffusion index show an increase in economic activity for
month three and beyond.
Month
1
2
3
Leading
Indicator A
100
110
120
Leading Indicator B
200
230
240
Leading Indicator C
30
27
33
% Change from month 1 to Month 2
Leading Indicator ALeading Indicator BLeading Indicator C 110 -
(100/100)230- (200/200)27-(30/30)
10% 15%-10%
Composite Index from Month 1 to Month 3 - (100* .05) + 100 = 105
% change from Month 1 to Month 3
Leading Indicator ALeading Indicator BLeading Indicator B 120 -
(100/100)240 - (200/200)33 - (30/30)
20% 20%10%
Composite Index for Month 3 = (100 x 16.67) + 100 = 116.67
MonthComposite IndexDiffusion Index
1100
2 105 66.7
3 116.67 100
Appendix Problem 3). Forecast the data for 2000 again in Problem 1 with exponential
smoothing with w = 0.3 and w = 0.7. Is this a better forecast than the moving average?
Compare RMSEs for moving average and exponential forecasts to answer the above
question (see p. 237). Use 166.63, the mean of all 36 months as the initial forecast for Jan.
1998 for both exponential smoothing forecasts. *See attached Excel*
Appendix Problem 1). The following table reports the Consumer Price Index for the Los
Angeles area on a monthly basis from January 1998 to December 2000 (base year = 1982 –
1984). For 2000, use Excel to forecast the index for all of 2000 using a three- and six- month
average. Which provides a better forecast for 2000 using the data provided? You need to
calculate the moving average forecasts and RMSEs for year 2000, not the whole data
period.
Salvatore Chp 7
DQ3(a). How is the law of diminishing returns reflected in the shape of the total product
curve? The law of diminishing returns is the point at which the marginal product of the variable
input declines after a point. It is reflected in a downward arc as more inputs are used per unit of
time with fixed amounts of another input[Sal11]. At the point of diminishing returns, no matter
how many inputs of labor are added, the output of units produced will continue to decline.
(b) What is the relationship between diminishing returns and the stages of production? The
three stages of production are represented as the relationship between APL (Average Product of
Labor) and MPL (Marginal Product of Labor) curves. The first stage of production begins at the
origin or beginning to the point where the APL is at its maximum. The second stage of production
begins at the point where APL is at its maximum to where the MPL is zero. This is the only stage
where the ratio between input and output produces. The third stage of production represents
diminishing returns, where MPL is negative. At this point it is impossible for the producer to
increase output with less labor.
DQ11. Minimum wage legislation requires most firms to pay workers no less than the
legislated minimum wage per hour. Using marginal productivity theory, explain how a
change in the minimum wage affects the employment of unskilled labor. The marginal
productivity theory describes the relationship of labor input to productivity. The wages of labor
must be equal to the amount of expected output. If there was an increase of wages per unit of
labor, the amount of productivity would need to be increased, or the units of labor decreased to
keep the equilibrium. To make economic sense with a wage increase, labor would either be
expected to have more skill, or less of it would be used. McDonald’s is a good example of how
raising minimum wage affects unskilled labor. With several states adopting an increase in
minimum wage, and with talk about it at the federal level, the company has started replacing
labor with technology at their new stores. Dining-in customers use touch screens to place their
order, and pay for their meal using a self-pay station.
DQ13. Does the production function of Table 7-1 show constant, increasing, or decreasing
returns to scale if the firm increases the quantity of labor and capital used from (a) 2L and
2K to 4L and 4K? Returns to scale means the output either stays the same, increases or
decreases when input changes proportionally. In this case, the proportion of output is increasing
more than the proportion of labor. From 2L and 2K to 4L and 4K is a 100 percent increase of
both capital and labor. ΔQ/ΔL = Q2 – Q1 / L1 – L2. So, 40-18/ 4-2 = 22/2 or 11/1. This is 7 more
units of labor produced by 1 unit of labor at the origin of the table.
(b) 2L and 4K to 3L and 6K? On the table, this combination of labor and capital represents
decreasing returns to scale. ΔQ/ ΔL = 31 – 28 / 3 – 2 = 3/1. With the increase of labor units and
capital, the output is still producing, but at the same proportion as the origin. This means that the
returns to scale are decreasing. There are too many inputs of labor and capital for the outputs to
be produced economically.
Problem 4). Ms. Smith, the owner and manager of the Clear Duplicating Service located
near a major university, is contemplating keeping her shop open after 4pm and until
midnight. In order to do so, she would have to hire additional workers. She estimates that
the additional workers would generate the following total output (where each unit of
output refers to 100 pages duplicated). If the price of each unit of output is $10 and each
worker hired must be paid $40 per day, how many workers should Ms. Smith hire? Note:
Ms. Smith should hire workers as long as their marginal revenue product (MRP) exceeds
their marginal resource cost (MRC) and until MRP = MRC. MRP = MR * MP = P * MP = $10 *
MP (Use information in the problem to calculate MP). MRC = wages = $40
40 = 10 x 4 = 10 x 4 = 10 x 4 Ms. Smith should hire 5 workers.
Problem 10). John Wilson, the owner of a fast-food restaurant, estimated that he can sell
1,000 additional hamburgers per day by renting more automated equipment at a cost of
$100 per day. Alternatively, he estimated that he could sell an extra 1,200 hamburgers per
day by keeping the restaurant open for two more hours per day at a cost of $50 per hour.
Which of these two alternative ways of increasing output should Mr. Wilson use?
Problem 13). Indicate whether each of the following statements is true or false and give the
reason.
a). A firm should stop expanding output after reaching diminishing returns (see figure 7-4 –
on p. 280). This is a false statement. Figure 7-4 shows the point of diminishing returns beginning
in stage I. The producer should continue to operate as long as the marginal product (MP) of both
APL and MPL is positive but declining which would be Stage II. The point where both APL and
Workers
Hired
0
1
2
3
4
5
6
Total
Product
0
12
22
30
36
40
42
Marginal
Productiv
i y (MP)
0
12
10
8
6
4
2
Marginal
MarginaRevenue
l Productivity =
RevenueMRC (MR x
(MR) MP)
100
10 120
10 100
1080
1060
1040
1020
MPL are negative is when the producer should either stop producing. This is Stage III. A negative
MPL means that even if labor were free, production would be negative. The producer would have
to reduce labor.
(b) if large and small firms operate in the same industry, we must have constant returns to
scale. True. Whether a company is large or small, its output will increase in proportion to its
input. It does not matter whether a company is large or small unless the larger company is more
efficient and can drive the smaller company out of business.
