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Unformatted text preview: 1Slide #1 I. Qualitative (or Dummy) Independent Variables O bj1 0 O bj1 0 1 ? 2Slide #2 q This page was intentionally left blank 3Slide #3 q This page was intentionally left blank 4Slide #4 III. Introduction q A. New type of variable v 1. Past: used quantitative variables (numerically measurable); continuous v 2. Now: variables that take small number of values; discrete ü a) Gender ü b) Market size ü c) Region of country ü d) Marital status (married vs. not), etc 5Slide #5 Introduction (cont.) q B. Used as IV in this section q C. Used as DV later in course 6Slide #6 Introduction (cont.) q Institute of Management Accounts (IMA) publishes an annual Salary Guide v In Strategic Finance magazine ü [email protected] v Annual survey of members v “…based on a regression equation derived from survey results.” 7Slide #7 IMA Salary Guide (cont.) SALARY = 35,491 + 18393TOP + 8392SENIOR – 10615ENTRY +914YEARS +10975ADVDEGREE – 8684NODEGREE + 9195PROFCERT + 8417MALE v TOP=1 if top level mgmt, 0 if not v SENIOR=1 if senior level mgmt , 0 if not v ENTRY=1 if entry level , 0 if not v ADVDEGREE=1 if advanced degree , 0 if not v NODEGREE=1 if no degree , 0 if not 8Slide #8 IMA Salary Guide (cont.) q Average IMA member (1999) v Male v 14.5 years experience v Professional certification v Salary = $66,356 ü Figure obtained from substituting values into regression equation 9Slide #9 Are Wins Worth More in a Large Market? See regression output for dummy variables as IVs. (note) O bj1 0 2 10Slide #10 Introduction (cont.) q D. Example #1 v 1. Y = α + β X2 + μ v 2. Y: social program expenditures per state v 3. X2: state’s total revenue v 4. Suppose states’ legislatures controlled by Democrats spend more from same revenue than those controlled by Republicans v 5. How account for this in model? 11Slide #11 Introduction (cont.) q E. Example #2 v 1. Y = α + β X2 + μ v 2. Y: coach’s earnings v 3. X2: coach’s experience v 4. Suppose women earn less than men with equal experience (& other characteristics) v 5. How account for this in model? 12Slide #12 Introduction (cont.) q F. Example #3 v 1. Y = α + β X2 + μ v 2. Y: sales of swimsuits in Minnesota v 3. X2: Minnesota’s population v 4. Suppose sales peak in warm months v 5. How account for this in model? v 6. What’s the categorical variable? 13Slide #13 Introduction (cont.) q G. Example #4 v 1. Y = α + β X2 + μ v 2. Y: profits of NBA teams v 3. X2: wins v 4. Suppose teams in large markets make more profit on their wins than teams in other markets v 5. How account for this in model?...
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 Fall '11
 RichardHofler
 Econometrics, dummy variables

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