I. Binary (or Dummy) Independent Variables

III. Introduction
 A.


?
Slide #1

1. Past: used quantitative variables (numerically measurable); continuous  2. Now: variables that take small number of values; discrete
a) b)  c)  d)
 

New type of variable

Gender Market size Region of country Marital status (married vs. not), etc

Slide #2

Introduction (cont.)
 B.  C.

Introduction (cont.)
 Institute

Used as IV in this section Used as DV later in course

of Management Accountants (IMA) publishes an annual Salary Guide
In Strategic Finance magazine  sfmag@imanet.org  Annual survey of members  “…based on a regression equation derived from survey results.”


Slide #3

Slide #4

IMA Salary Guide (cont.)
SALARY = 35,491 + 18393TOP + 8392SENIOR – 10615ENTRY +914YEARS +10975ADVDEGREE – 8684NODEGREE + 9195PROFCERT + 8417MALE
       

IMA Salary Guide (cont.)
 Average


IMA member (1999)

TOP=1 if top level mgmt, 0 if not SENIOR=1 if senior level mgmt , 0 if not ENTRY=1 if entry level , 0 if not ADVDEGREE=1 if advanced degree , 0 if not NODEGREE=1 if no degree , 0 if not PROFCERT=1 if hold professional certification , 0 if not MALE=1 if male , 0 if not YEARS=years of experience
Slide #5

Male  14.5 years experience  Professional certification  Salary = $66,356  Figure obtained from substituting values into regression equation
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1

Are Wins Worth More in a Large Market?


Introduction (cont.)
D. Example #1
   

 

1. Y =  + X2 +  2. Y: social program expenditures per state 3. X2: state’s total revenue 4. Suppose legislatures controlled by Democrats spend more from same revenue than those controlled by Republicans 5. How account for this in model? 6. What’s the categorical variable?

See regression output for dummy variables as IVs. (note)
Slide #7 Slide #8