Managerial Economics ninth edition Thomas Maurice Chapter 7

Managerial Economics ninth edition Thomas Maurice Chapter 7 Demand Estimation & Forecasting Mc. Graw-Hill/Irwin Managerial Economics, 9 e Copyright © 2008 by the Mc. Graw-Hill Companies, Inc. All rights reserved.

Managerial Economics Direct Methods of Demand Estimation • Consumer interviews • Range from stopping shoppers to speak with them to administering detailed questionnaires • Potential problems § § § 2 Selection of a representative sample, which is a sample (usually random) having characteristics that accurately reflect the population as a whole Response bias, which is the difference between responses given by an individual to a hypothetical question and the action the individual takes when the situation actually occurs Inability of the respondent to answer accurately

Managerial Economics Direct Methods of Demand Estimation • Market studies & experiments • Market studies attempt to hold everything constant during the study except the price of the good • Lab experiments use volunteers to simulate actual buying conditions • Field experiments observe actual behavior of consumers 3

Managerial Economics Empirical Demand Functions • Demand equations derived from actual market data • Useful in making pricing & production decisions • In linear form, an empirical demand function can be specified as 4

Managerial Economics Empirical Demand Functions • In linear form • b = Q/ P • c = Q/ M • d = Q/ PR • Expected signs of coefficients • b is expected to be negative • c is positive for normal goods; negative for inferior goods • d is positive for substitutes; negative for complements 5

Managerial Economics Empirical Demand Functions • Estimated elasticities of demand are computed as 6

Managerial Economics Nonlinear Empirical Demand Specification • When demand is specified in log-linear form, the demand function can be written as 7

Managerial Economics Demand for a Price-Setter • To estimate demand function for a price-setting firm: • Step 1: Specify price-setting firm’s demand function • Step 2: Collect data for the variables in the firm’s demand function • Step 3: Estimate firm’s demand using ordinary least-squares regression (OLS) 8

Managerial Economics Time-Series Forecasts • A time-series model shows how a timeordered sequence of observations on a variable is generated • Simplest form is linear trend forecasting • Sales in each time period (Qt ) are assumed to be linearly related to time (t) 9

Managerial Economics Linear Trend Forecasting • If b > 0, sales are increasing over time • If b < 0, sales are decreasing over time • If b = 0, sales are constant over time 10

Managerial Economics A Linear Trend Forecast (Figure 7. 1) Q Estimated trend line 12 Sales 7 Time 11 2012 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 t

Managerial Economics Forecasting Sales for Terminator Pest Control (Figure 7. 2) 12

Managerial Economics Seasonal (or Cyclical) Variation • Can bias the estimation of parameters in linear trend forecasting • To account for such variation, dummy variables are added to the trend equation • Shift trend line up or down depending on the particular seasonal pattern • Significance of seasonal behavior determined by using t-test or p-value for the estimated coefficient on the dummy variable 13

Managerial Economics Sales with Seasonal Variation (Figure 7. 3) 2004 14 2005 2006 2007

Managerial Economics Dummy Variables • To account for N seasonal time periods • N – 1 dummy variables are added • Each dummy variable accounts for one seasonal time period • Takes value of 1 for observations that occur during the season assigned to that dummy variable • Takes value of 0 otherwise 15

Managerial Economics Effect of Seasonal Variation (Figure 7. 4) Qt Qt = a’ + bt Sales Qt = a + b t a’ c a t Time 16

Managerial Economics Some Final Warnings • The further into the future a forecast is made, the wider is the confidence interval or region of uncertainty • Model misspecification, either by excluding an important variable or by using an inappropriate functional form, reduces reliability of the forecast • Forecasts are incapable of predicting sharp changes that occur because of structural changes in the market 17