Deck 6: Demand Forecasting

Question 1

Regression analysis was used to estimate the following linear trend equation:
S_t = 10.5 + 0.25t
Use this equation to forecast the value of the dependent variable in time period 10.

A) 35.5
B) 13
C) 2.5
D) None of the above is correct.

Answer 1

13

Question 2

Regression analysis was used to estimate the following equation from quarterly data:
LnS_t = 2.5 + 0.01t
Use this equation to calculate the forecast value of the dependent variable (S_t) in time period 10.

A) 13.46
B) 12.49
C) 2.60
D) None of the above is correct.

Answer 2

13.46

Question 3

Regression analysis was used to estimate the following equation:
S_t = 10(1.02)^t
Use this equation to calculate the forecast value of the dependent variable in time period 4.

A) 40.80
B) 11.04
C) 10.82
D) None of the above is correct.

Answer 3

10.82

Question 4

Four different forecasting methods were applied to a set of time-series data. The root-mean-square error (RMSE) was calculated for each method. Which of the following four RMSE values would be associated with the forecasting method that fit the data set best?

A) 2.00
B) 1.96
C) 2.33
D) 6.21

Question 5

During the past eight years, the level of demand for a company's product has increased from 100 units per day to 137 units per day. What was the average annual compound growth rate over this period?

A) 37.00 percent
B) 4.63 percent
C) 4.01 percent
D) None of the above is correct.

Question 6

A firm currently has sales of 120 units per month. If the average growth rate of sales is 2 percent per month, approximately how many units will the firm be selling per month at the end of one year?

A) 152
B) 149
C) 144
D) None of the above is correct.

Question 7

The forecast level of sales for the month of May was 240 units. Actual sales in May turned out to be 200 units. Use an exponential smoothing coefficient of 0.80 to forecast sales for June.

A) 230
B) 220
C) 210
D) None of the above is correct.

Question 8

The forecast level of sales for the month of October was 140 units. Actual sales in October turned out to be 130 units. Use an exponential smoothing coefficient of 0.60 to forecast sales for November.

A) 146
B) 138
C) 134
D) None of the above is correct.

Question 9

The level of sales in May, June, July, and August were 84, 92, 83, and 89, respectively. What is the four-period moving average forecast of sales in September?

A) 90
B) 87
C) 85
D) None of the above is correct.

Question 10

The level of sales in May, June, July, and August were 84, 92, 83, and 89, respectively. What is the three-period moving average forecast of sales in September?

A) 88
B) 87
C) 85
D) None of the above is correct.

Question 11

Regression analysis was used to estimate the following seasonal forecasting equation:
S_t = 124 + 18D₁ - 46D₂ - 28D₃ + 2.5t
D₁ is a dummy variable that is equal to 1 in the first quarter and zero otherwise; D₂ is a dummy variable that is equal to 1 in the second quarter and zero otherwise; and D₃ is a dummy variable that is equal to 1 in the third quarter and zero otherwise. Forecast the level of sales in the second quarter of time period 10.

A) 195
B) 170
C) 103
D) None of the above is correct.

Question 12

Regression analysis was used to estimate the following seasonal forecasting equation:
S_t = 124 + 18D₁ - 46D₂ - 28D₃ + 2.5t
D₁ is a dummy variable that is equal to 1 in the first quarter and zero otherwise; D₂ is a dummy variable that is equal to 1 in the second quarter and zero otherwise; and D₃ is a dummy variable that is equal to 1 in the third quarter and zero otherwise. Forecast the level of sales in the fourth quarter of time period 10.

A) 149
B) 180
C) 205
D) None of the above is correct.

Question 13

Regression analysis was used to estimate the following linear trend equation:
S_t = -26 + 10t
The ratio-to-trend method was used to calculate 0.75, 0.95, 1.10, and 1.20, which are the seasonal adjustment factors for quarters 1, 2, 3, and 4, respectively.
Use this information to determine the forecast value for the third quarter of time period 7.

A) 105.6
B) 48.4
C) 45.1
D) None of the above is correct.

Question 14

Regression analysis was used to estimate the following linear trend equation:
S_t = -26 + 10t
The ratio-to-trend method was used to calculate 0.75, 0.95, 1.10, and 1.20, which are the seasonal adjustment factors for quarters 1, 2, 3, and 4, respectively.
Use this information to determine the forecast value for the first quarter of time period 9.

A) 87
B) 64
C) 48
D) None of the above is correct.

Question 15

Which of the following is a leading economic indicator?

A) Average prime interest rate charged by banks
B) Building permits for new private housing
C) Average duration of unemployment (inverted)
D) All of the above are leading economic indicators.

Question 16

Over a period of five years, a firm's sales increased from $1.2 million to $4.7 million. What is the firm's average annual linear rate of growth?

A) $7 million
B) $3.5 million
C) $700,000
D) None of the above is correct.

Question 17

Over a period of five years, a firm's sales increased from $1.2 million to $4.7 million. What is the firm's annual compounded growth rate?

A) 25.53 percent
B) 31.40 percent
C) 392.0 percent
D) None of the above is correct.

Question 18

Which of the following methods would be likely to perform the best for long-range forecasting?

A) Exponential smoothing
B) Econometric model
C) Moving average
D) Linear trend equation

Question 19

Regression analysis was used to estimate the following linear trend equation:
S_t = 10.5 + 0.25t
The current value of the variable to be forecast is 128. Use the information in the equation to forecast the value of the variable four time periods in the future.

A) 11.5
B) 129.0
C) 139.5
D) None of the above is correct.

Question 20

Regression analysis was used to estimate the following equation:
S_t = 10(1.20)^t
The current value of the variable to be forecast is 100. Use the information in the equation to calculate the forecast value of the variable in the next time period.

A) 12
B) 112
C) 120
D) None of the above is correct.

Question 21

A qualitative forecast

A) predicts the quality of a new product.
B) predicts the direction, but not the magnitude, of change in a variable.
C) is a forecast that is classified on a numerical scale from 1 (poor quality) to 10 (perfect quality).
D) is a forecast that is based on econometric methods.

Question 22

Which of the following is not a qualitative forecasting technique?

A) Surveys of consumer expenditure plans
B) Perspectives of foreign advisory councils
C) Consumer intention polling
D) Time-series analysis

Question 23

The first step in time-series analysis is to

A) perform preliminary regression calculations.
B) calculate a moving average.
C) plot the data on a graph.
D) identify relevant correlated variables.

Question 24

Forecasts are referred to as naive if they

A) are based only on past values of the variable.
B) are short-term forecasts.
C) are long-term forecasts.
D) generally, result in incorrect forecasts.

Question 25

Time-series analysis is based on the assumption that

A) random error terms are normally distributed.
B) there are dependable correlations between the variable to be forecast and other independent variables.
C) past patterns in the variable to be forecast will continue unchanged into the future.
D) the data do not exhibit a trend.

Question 26

Which of the following is not one of the four types of variation that is estimated in time-series analysis?

A) Predictable
B) Trend
C) Cyclical
D) Irregular

Question 27

The cyclical component of time-series data is usually estimated using

A) linear regression analysis.
B) moving averages.
C) exponential smoothing.
D) qualitative methods.

Question 28

In time-series analysis, which source of variation can be estimated by the ratio-to-trend method?

A) Cyclical
B) Trend
C) Seasonal
D) Irregular

Question 29

If regression analysis is used to estimate the linear relationship between the natural logarithm of the variable to be forecast and time, then the slope estimate is equal to

A) the linear trend.
B) the natural logarithm of the rate of growth.
C) the natural logarithm of one plus the rate of growth.
D) the natural logarithm of the square root of the rate of growth.

Question 30

The use of a smoothing technique is appropriate when

A) random behavior is the primary source of variation.
B) seasonality is present.
C) data exhibit a strong trend.
D) All of the above are correct.

Question 31

The greatest smoothing effect is obtained by using

A) a moving average based on a small number of periods.
B) exponential smoothing with a small weight value.
C) the root-mean-square error.
D) the barometric method.

Question 32

The root-mean-square error is a measure of

A) sample size.
B) moving average periods.
C) exponential smoothing.
D) forecast accuracy.

Question 33

Barometric methods are used to forecast

A) seasonal variation.
B) secular trend.
C) cyclical variation.
D) irregular variation.

Question 34

A leading indicator is a measure that usually

A) changes at the same time and in the same direction as the general economy.
B) responds to a change in the general economy after a time lag.
C) changes in the same direction as the general economy before the general economy changes.
D) has all of the properties listed above.

Question 35

If three of the leading indicators move up, two move down, and the remaining six are constant, then the diffusion index is

A) 3/6 = 50%
B) 3/11 = 27%
C) 5/11 = 45%
D) 6/11 = 55%

Question 36

A single-equation econometric model of the demand for a product is a ________ equation in which the quantity demanded of the product is an ________ variable.

A) structural, exogenous
B) structural, endogenous
C) definitional, exogenous
D) definitional, endogenous

Question 37

A reduced-form equation expresses

A) an exogenous variable as a function of endogenous variables.
B) an endogenous variable as a function of exogenous variables.
C) an exogenous variable as a function of both endogenous and exogenous variables.
D) an endogenous variable as a function of both exogenous and endogenous variables.

Question 38

Trend projection is an example of which kind of forecasting?

A) Qualitative
B) Time-series
C) Barometric
D) Econometric

Question 39

Turning points in the level of economic activity can be forecast by using

A) time-series analysis.
B) exponential smoothing.
C) barometric methods.
D) moving average.

Question 40

Econometric forecasts require

A) accurate estimates of the coefficients of structural equations.
B) forecasts of future values of exogenous variables.
C) appropriate theoretical models.
D) All of the above are required.

Question 41

The interdependence among sectors and industries in an economy are the basis for

A) input-output forecasting models.
B) naive forecasting models.
C) the use of smoothing techniques.
D) All of the above are correct.

Question 42

Input-output forecasting models employ

A) regression analysis to estimate the coefficients of predictive equations.
B) tables that describe interdependencies among sectors and industries in an economy.
C) a combination of moving average smoothing techniques.
D) None of the above is correct.

Question 43

When forecasting the GDP, unemployment rate is an example of a

A) Leading economic indicator
B) Lagging economic indicator
C) Coincident economic indicator
D) None of the above

Question 44

Which of the following is not one of the surveys used to forecast economic activity in general and in various sectors of the economy?

A) Surveys of business executives' plant and equipment expenditure plans
B) Surveys of plans for inventory changes and sales expectations
C) Surveys of consumers' expenditure plans
D) Surveys of firms' expectations of future expenses

Question 45

Which of the following best describes Delphi polling method?

A) Experts are polled one by one, others watch them while wait for their turn.
B) Experts are polled together; after discussion, they come up with a consensus.
C) Experts are polled separately; others' responses are provided but with identities hidden.
D) None of the above.

Question 46

All of the below are polling techniques used by firms to forecast sales except

A) executive polling.
B) middle-managers intentions polling.
C) sales force polling.
D) consumer intentions polling.

Question 47

Time-series analysis attempts to

A) understand the past patterns of data.
B) forecast future values.
C) optimize firms operations.
D) understand competitors' decisions.

Question 48

The fluctuations in the time-series data are due to

A) long-term trends.
B) business cycle trends.
C) seasonal trends.
D) all of the above.

Question 49

Every year, the first quarter sales are the highest, following a slump in the second and third quarter sales before coming back up in the fourth quarter. Such fluctuations are called

A) long-term fluctuations.
B) secular fluctuations.
C) business-cycle fluctuations.
D) seasonal fluctuations.

Question 50

Firm is predicting the sales to best predicted by the following constant percentage growth rate model:
S?=S?(1+g)?
If and the growth rate is computed to be 5%, what are the forecasted sales for the period 3?

A) 1.5
B) 1.74
C) 2.1
D) None of the above

Question 51

The last 6 years of sales are provided in the table below. Compute the 3-year moving average for 2019.
$$\begin{array} { | l | l | l | l | l | l | } \hline \text { Year } & 2014 & 2015 & 2016 & 2017 & 2018 \\\hline \text { Sales } & 8 & 10 & 11 & 10 & 12 \\\hline\end{array}$$

A) 10
B) 10.2
C) 11
D) 11.2

Question 52

The last 6 years of sales are provided in the table below. Compute the 5-year moving average for 2019.
$$\begin{array} { | l | l | l | l | l | l | } \hline \text { Year } & 2014 & 2015 & 2016 & 2017 & 2018 \\\hline \text { Sales } & 8 & 10 & 11 & 10 & 12 \\\hline\end{array}$$

A) 10
B) 10.2
C) 11
D) 11.2

Question 53

Furniture firm has decided to use exponential smoothing to forecast the next period's sales. If the forecasted sales for this period were 15,000, the actual sales of this period were 13,000 and the optimal weight was estimated to be 0.5, what are the projected sales of the next period?

A) 6,500
B) 7,500
C) 13,500
D) 14,000

Question 54

Furniture firm has decided to use exponential smoothing to forecast the next period's sales. If the forecasted sales for this period were 7,000, the actual sales of this period were 6,000 and the optimal weight was estimated to be 0.5, what are the projected sales of the next period?

A) 6,500
B) 7,500
C) 13,500
D) 14,000

Question 55

Four different forecasting methods were applied to a set of time-series data. The root-mean-square error (RMSE) was calculated for each method and is provided in the table below. Rank the four methods from the most accurate to the least accurate?
$$\begin{array} { | l | l | l | l | l | } \hline \text { Method } & \text { A } & \text { B } & \text { C } & \text { D } \\\hline \text { RMSE } & 1.00 & 0.98 & 0.95 & 1.01 \\\hline\end{array}$$

A) A, D, B, C
B) D, A, B, C
C) C, B, A, D
D) C, B, D, A

Question 56

Four different forecasting methods were applied to a set of time-series data. The root-mean-square error (RMSE) was calculated for each method and is provided in the table below. Rank the four methods from the most accurate to the least accurate?
$$\begin{array} { | l | l | l | l | l | } \hline \text { Method } & \text { A } & \text { B } & \text { C } & \text { D } \\\hline \text { RMSE } & 10.1 & 11.9 & 12.5 & 9.5 \\\hline\end{array}$$

A) A, D, B, C
B) D, A, B, C
C) C, B, A, D
D) C, B, D, A

Question 57

Cereal firm has estimated the demand for its product to be Q=15-1.5P+3Y-2ps+Pc, where P is the price of the good, Y is the consumer's income, P_S and P_C are prices of related goods. If P=3, Y=10, P_S=3 and P_C=3, what is the estimated demand for the firm's product?

A) 32.5
B) 35.5
C) 37.5
D) 40.5

Question 58

If two of the leading indicators move up, three move down, and the remaining five are constant, then the diffusion index is

A) 20 percent
B) 25 percent
C) 35.5 percent
D) 50 percent

Question 59

Regression analysis was used to estimate the following linear trend equation:
S_t = 10.5 + 0.25t
Use this equation to forecast the value of the dependent variable in time period 2.

A) 10.50
B) 11.00
C) 11.25
D) 22.00

Question 60

If five of the leading indicators move up, four move down, and the remaining one is constant, then the diffusion index is

A) 20 percent
B) 25 percent
C) 35.5 percent
D) 50 percent

Question 61

Forecasts of commodity demand may be based on macroeconomic forecasts.

Question 62

Barometric forecasting methods are most useful for long-term forecasts.

Question 63

The choice of a forecasting method should be based on an assessment of the costs and the benefits of each method in a specific application.

Question 64

Surveys and opinion polls are qualitative techniques.

Question 65

Qualitative forecasts based on surveys tend to perform particularly well during periods of unexpected international political upheaval.

Question 66

Time-series analysis generates forecasts by identifying cause-and-effect relationships between variables.

Question 67

Time-series data are observations on a variable at different points in time.

Question 68

The fundamental assumption of time-series analysis is that past patterns in time-series data will continue unchanged in the future.

Question 69

Time-series forecasting tends to be more accurate than "naive" forecasting.

Question 70

The long-run increase or decrease in time-series data is referred to as a cyclical fluctuation.

Question 71

A time series that displays regular seasonal variation is said to exhibit cyclical fluctuation.

Question 72

Irregular or random influences on time-series data give rise to the secular trend.

Question 73

Expansions and contractions in the general economy result in seasonal variation.

Question 74

Cyclical fluctuations in time-series data are generally forecast using qualitative techniques.

Question 75

The linear trend equation can be estimated by ordinary least-squares regression analysis.

Question 76

The constant percentage growth rate model cannot be estimated by ordinary least-squares regression analysis.

Question 77

Seasonal variation can be estimated by the use of dummy variables in linear regression analysis.

Question 78

Time-series analysis is particularly useful for forecasting turning points in time-series data.

Question 79

Naive forecasting methods include time-series analysis and smoothing methods.

Question 80

Smoothing techniques are most useful for time-series data that is primarily influenced by irregular variation.