If you are downloading this SHAZAM code for use on your own computer, select "File", then "Save As...", and save on your own diskette (a:) or your own hard drive (c:\) using the same filename e143sh10.sha.

IMPORTANT: you must then use an editor (like TED) to delete all of the HTML code from the top and the bottom of the file, leaving only the SHAZAM code. The line which reads "* SHAZAM code (e143sh10.sha) downloaded from UCLA Econ 143 (CAMERON) WebSite" should be the first line of your edited program file. Save the edited program as mgr.sha

* SHAZAM code downloaded from UCLA Econ 143 (CAMERON) WebSite: 
* HTML file called e143sh10.htm, and should have 
*  been downloaded as mgr.sha

* CONTENTS OF NETWORK FILE n:mgr.sha

* Suppose you have a sample of mid-level managers who have been surveyed
* concerning the number of hours per week they spend on work-related activities,
* either in the office or at home.  (These data are fictional.)  The dependent
* variable is HOURS (per week, averaged over a three-month period) and the 
* explanatory variables you are considering are:
*    FEMALE=1 if female; 0 if male
*    SPOUSE=1 if married or equivalent; 0 otherwise
*    SWORK=1 if spouse full-time employed; 0 otherwise
*    CHILDREN=1 if has children; 0 otherwise
*    CYOUNG=number of children under the age of 6
*    CMED=number of children between 6 and 18 years
*    CADULT=number of children over age 18
sample 1 60
read(mgr.dat) hours female spouse swork children cyoung cmed cadult
stat

* next see how manager hours depends on gender
pause
ols hours female

* next see how manager hours depends on parenthood
pause
ols hours children

* next see how manager hours depends on gender controlling for parenthood
pause
ols hours female children

* next try some interaction terms and practice interpreting them
pause

* generate some interesting interaction terms:
genr spousef=spouse*female
genr cf=children*female
genr cyf=cyoung*female
genr cmf=cmed*female
genr caf=cadult*female

* you should be able to address the following questions based on the
* regression to be done next:
*  Among childless single managers, do males or females put in more hours?
*  What is the effect of having a spouse for males?
*  Is the effect of having a spouse different for females than males?
*  Are hours greater or less if the spouse works, given there is a spouse?
*  What is the effect on male hours of parenthood in general (this could
*  be interpreted as the "fixed cost" of parenthood)?
*  For females, what is the "fixed cost" of parenthood in terms of decreased
*   work hours?
pause
*  Can you have CHILDREN=1 but CYOUNG, CMED, and CADULT all equal to zero?
*  What are the "marginal costs" of each different type of child for males?
*  What are the "marginal costs" of each different type of child for females?
*  What age group of child has the greatest per-child negative effect on
*    male hours?
*  What age group of child has the greatest per-child positive effect on
*    male hours?  Why, do you think?
*  Do children of any age have a significantly different effect on female
*    hours than on male hours?  How would you test this, rigorously?
*  Do young children impact female hours more than male hours?
*  Do adult children impact female hours differently than male hours?
pause 

* try a model with variables and interaction terms:
ols hours female spouse spousef swork children cyoung cmed cadult &
  cf cyf cmf caf / auxrsqr