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LESSON: Business and Economic Forecasting Reference: Study Guide and Casebook for Managerial Economics By Edwin Masfield and Elizabeth Mansfield Although surveys are of considerable use, most major firms seem to base their forecasts in large part of the quantitative analysis of economic time series. The classical approach to business forecasting assumes that an economic time series can be decomposed into four components: 1. Trend 2. Seasonal variation 3. Cyclical variation 4. Irregular movements If the trend in the time series is linear, simple regression may be used to estimate an equation representing the trend. If it seems to be nonlinear, a quadratic equation may be estimated by multiple regression, or an exponential trend may be fitted. The seasonal variation in a particular time series is described by a figure for each month (the seasonal index) that shows the extent to which the month's value typically departs from what would be expected on the basis of trend and cyclical variations. Such seasonal indexes can be used to casonalize a time series, that is, to remove the seasonal element from the data. Many business and economic time series go up and down with the fluctuations of the economy as a whole. This cyclical variation, as well as the trend and seasonal variations, is reflected in many time series. It is customary to divide business fluctuations into four phases: 1. Trough 2. Expansion 3. Peak 4. Recession Variables go down before the peak and up before the trough are called leading series. Some important leading series are new orders for durable goods, average work week, building contracts, stock prices, certain wholesale prices, and claims for unemployment insurance. Economists sometimes use leading series, which are often called leading indicators, to forecast whether a turning point is about to occur. If a large number of leading indicators turn downward, this is viewed as a sign for a coming peak. If a large number turn upward, this is thought to signal an impending trough. Although these indicators are not very reliable, they are watched closely and are used to supplement other, more sophisticated forecasting techniques. The simplest kind of forecasting method is a straightforward extrapolation of a trend. To allow for a seasonal variation, such an extrapolation can be multiplied by the seasonal index (divided by 100) for the month to which the forecast applies. This entire procedure is simply a mechanical extrapolation of the time series into the future. For the past years, managerial economists have tended to base their forecasts less on simple extrapolations and more on equations (or systems of equations) showing the effects of various independent variables on the variable (or variables) one wants to forecast. These equations (or system of equations) are called ECONOMETRIC MODELS. Problem: The XYZ Corporation (USA setting), a hypothetical producer of landing gear, had the following monthly sales: SALES (Millions of Dollars) Month 2016 2017 2018 January February March CUT A W N April May June July August september October November December A. Is there evidence of seasonal variation in this firm's sales? B. How would you characterize this seasonal variation, if it exists? C. In 2019, the XYZ Corporation's sales increased from $7 million in April to $8 million in May. The seasonal index is 123.0 for May and 106.3 for April. Allowing the seasonal variation, do you think that sales increased from April to May? Why or Why not? Answer: A. Yes B. Sales tend to be high in summer and low in winter. The seasons are defined as spring (March, April, May), summer (June, July, August), autumn (September, October, November) and winter (December, January, February). C. Between April and May we would expect an increase of 123.0 106.3 - 1 100 or 15.7 percent. Thus this increase of 14.3 percent in 2019 is somewhat less than would be expected. Allowing for seasonal variation, sales did not increase between April and May in 2019. .The main functions of landing gear, undercarriage to the primary structure of the aircraft, are to enable the aircraft for a taxi, safe landing and takeoff, and to support the aircraft in the rest of the ground operation