Durable Goods Sales & the Unemployment Rate
This is an excerpt from the paper...
This research examines the relationship between durable goods sales and the unemployment rate. During the past year in the United States, the unemployment rate has improved (Council of Economic Advisers, 1994, p. 12). Nevertheless, durable goods sales have yet to regain strength as had been anticipated (Council of Economic Advisers, 1994, pp. 1718, 2021). Managers of a major appliance chain are concerned about inventory levels. Understocking is undesirable because sales may be missed if products are not available when customers want to buy (Kotler, 1993, p. 543). Conversely, however, overstocking is equally undesirable because of the exposure to excess inventory expenses. A decision was made to analyze the macroeconomic aggregate data to determine the extent to which durable goods sales may be expected to change in relation to changes in the unemployment rate for persons 20 years old and older. The results of this analysis will provide the managers of the appliance chain with information that will improve the quality of their decisions related to inventory stocking level decisions. The principal statistical analysis procedure which will be used in assessing the relationship between changes in durable goods sales and changes in the unemployment rate is simple regression analysis (Summers, Peters, and Armstrong, 1993, p. 295). Data included in the analysis will be for the 19701993 time period on an annual basis. Additionally, however, both two
. . .
ion; thus, most projections relying on the moving average use only a fraction of the total available data.
The simple regression formula for the determination of a trend through the use of the moving average approach is the same as that for the determination of the arithmetic trendy = a + bx. The difference in the two approaches lies in the definition of b. In the arithmetic mean approach, b is the change in the variable value per time unit, which is determined for each prior time unit by comparing the value the dependent variable of one time unit with the value of the dependent variable in the immediately preceding time unit. In the equation, for the moving average approach, variable values for time periods are determined through the averaging of the predetermined number of time units. This, in this equation, b is still the change in the variable value per time unit; however, the determination involves the comparison of the average value the dependent variable of one time unit with the average value of the dependent variable in the immediately preceding time unit. In the moving average regression equation, y continues to be the estimated dependent variable value for the time period being projected, a continues to be the es
. . .
Some common words found in the essay are:
Peters Armstrong, Company SUMMARY, DESCRIPTION DATAThe, Unemployment Rate, RESULTS CONCLUSION, Economic Advisers, moving average, EMPIRICAL TESTS, durable sales, unemployment rate, , regression analysis, basic data, Charles Armstrong, simple regression, variable value, dependent variable, Kotler Philip, durable lagged period, lagged period, durable lagged, unemployment rate persons, changes unemployment rate, rate persons 20, simple regression analysis,
Approximate Word count = 1601
Approximate Pages = 6 (250 words per page)
More Essays on Durable Goods Sales & the Unemployment Rate
|