Questions for Critical Thinking 3
Salvatore Chapter 6:
Discussion Questions: 2(a) and (b), 3(a) and (d), and 15.
2 (a) What qualitative forecasts? What are the most forms of qualitative forecasts? (b) What are the different types of Forecasting?
3 (a) What are time-series daa What are the possible soures of variation in time-series data? Why does time-series analysis deal primarily with trend and seasonal variations rather than with cyclical and irregular or random variations?
15 Explain why it is still useful to pursue forecasting even though it is often off the ark by wide margins.
Problems: 7 and appendix problems 1 and 3 (pp. 260–261).
7 The following table presents data on here leading indicators for a three-month period. Construct the coomposit index (with each indicator assigned equal weight) and the diffusion index.
Leading Indicator A
Leading Indicator B
Leading Indicator C
Appendix 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). Eliminating the dta for 2000, use Excell to forecast the index for all of 2000 usin a thre- and six-month averge. Which provides a etter forecast for 2000 using the data provided?
Appendix 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?
P7: 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 percent. 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).
Appendix problem 3: Compare RMSEs for moving average and exponential forecasts to answer “Is this a better forecast than the moving average?” (see also p. 237). Use 166.63, the mean of all 36 months, as the initial forecast for Jan. 1998 for both exponential smoothing forecasts.
Appendix problem 1: Delete “Eliminating the data for 2000.” You need to calculate the moving average forecasts and RMSEs for year 2000, not the whole data period.
Salvatore Chapter 7:
Discussion Questions: 3, 11, and 13.
3 (a) How is the law of diminishing returns reflected in the shape of the total product curve? (b) What is the relationship between diminishing returns and the stages of production?
11 Minimum wage legislation requires ost firms to pay workers no less than the legislated minimum wage per hour. Using tmarginal prouctivity theory, explain how a change in minimum wage affects the employment of unskilled labor.
13 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? (b) 2L and 4K to 3L and 6K?
Problems: 4, 10, and 13.
4 Ms. Smith, the owner and manager of the Clear Duplicating Service located near a major university, is contemplating keeping her shop open after 4 p.m. 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.