Exam 6: Demand Forecasting

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.

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

In general, the greater the degree of irregular or random variation present in a time series, the more periods should be used to calculate a moving average forecast.

The table below shows the data on the four leading indicators for the four-month period. Construct a composite index with each indicator assigned an equal weight. Leading Indicators Month A 1 40 150 10 75 2 45 140 9 60 3 40 150 10 55 4 20 160 11 50

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

The last 6 years of sales are provided in the table below. Compute the 3-year moving average for 2019. Year 2014 2015 2016 2017 2018 Sales 8 10 11 10 12

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

The firm's market share over time estimated to be as shown in the table. Using the information, compute the three-period and the five-period moving average forecasts for the 7^th period. Period Firm's Market Share 1 30 2 29 3 24 4 26 5 26 6 29

You are a general manager and you are provided with the actual sales and the forecasts of three different forecasting techniques for the last 6 quarters. What measure can we use to decide which of the forecasting technique is best? Which of the following provides the most accurate forecasts? Quarter Actual Forecast A Forecast B Forecast C 1 43 42 42 44 2 46 45 45 45 3 45 46 44 48 4 46 48 46 46 5 47 48 48 45 6 46 47 46 44

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

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?

The diffusion index is a coincident indicator.

A firm has determined that its average level of sales (S_t) per week in thousands of dollars during a given year depends on the previous year's level of sales (S_t-1), the previous year's level of advertising (A_t-1) per month in thousands of dollars, and the current year's rate of annual industry growth (G_t) in percentage terms. The firm has also determined that the level of industry growth in the current period depends on the previous period's rate of industry growth (G_t-1) and on current period sales by the firm. During the current period, the firm's level of sales was $100,000, advertising was $40,000, and the rate of growth in the industry was 4 percent. The firm estimated the following two-equation econometric model: S_t = 4 + 0.40S_t-1 + 0.10A_t-1 + G_t and G_t = 1 + 0.5G_t-1 + 0.5S_t (i)Formulate a single-equation forecasting equation from this model. (ii)Forecast the level of sales in the next period.

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? Method A B C D RMSE 1.00 0.98 0.95 1.01

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

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.

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.

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?

The first step in time-series analysis is to

The table below shows the demand for Fidgets (they're like Widgets, only they're more active) over an eight-month period. Calculate a four-period moving average forecast for September. Also evaluate the quality of the four-period moving average forecasting model by calculating the root-mean-square error for the data set. Note: Round all intermediate calculations to two decimal places. Month Demand Jan 10 Feb 11 Mar 5 Apr 8 May 6 Jun 11 Jul 5 Aug 11