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The data are available in the any of the three files MOM.dat , MOM.doc , and MOM.wks .

  1. Provide scatter plots among the dependent variable (Natural logarithm of hours) against each of the explanatory variables Natural logarithm of real wages, Age, Number of children, and Health. (Label these Figures 1 to 4.)
  2. Present a table of the summary statistics for all of the variables in this data set (except ID and Year ).
  3. Provide a histogram of each of the following variables: Natural logarithm of hours, Natural logarithm of real wages, Age, and Number of children. (Label these Figures 5 to 8).
  4. Estimate Equation (1) using (1) OLS (sometimes called a “pooled model”), (2) a “between” model (where the observations in the regression are the averages over the 10 years of each variable for each individual, (3) a fixed effects model, (4) a MLE random effects model and (5) a GLS random effects model. Present the results of your estimations in a single table and offer an interpretation for each parameter you estimate. Use Table 1 as shown below as a template for the table to present your results.
Hours and wages: summary of linear panel model estimations (dependent variable is the natural logarithm of total hours worked in a year; the observations consist of 532 adult males over the 10 year period 1978-1987).
(1) Pooled (2) Between (3) Fixed Effects (4) MLE Random Effects (5) GLS Random Effects
Natural logarithm of real wages
( ) ( ) ( ) ( ) ( )
Age
( ) ( ) ( ) ( ) ( )
Age 2
( ) ( ) ( ) ( ) ( )
Number of children
( ) ( ) ( ) ( ) ( )
Health indicator
( ) ( ) ( ) ( ) ( )
Intercept
( ) ( ) ( ) ( ) ( )
R 2
σ μ
σ ε
Sample size

The Effectiveness of Advertising Bans on Smoking. Anti-smoking activists often push for a total ban on cigarette advertisements. Indeed, one of the basic assumptions of the groups pushing the 1996 proposed settlement with the tobacco companies is that the amount of tobacco consumed is positively affected by the amount of tobacco advertising. There are two mechanisms that might underlie such a relationship. The first mechanism suggests that the advertising increases the amount of cigarettes smoked by current smokers. Many economists doubt that the tobacco advertising increases the consumption of current smokers, arguing that the total consumption of cigarettes is unresponsive to advertisement. Instead, they argue that advertising is an effort by cigarette companies to affect the brand of cigarettes that current smokers consume. The second mechanism suggests that advertising is an effort by cigarette companies to induce non-smokers (especially children) to try cigarettes. The main reason that cigarette companies want non-smokers to try smoking, so the argument goes, is that some percentage of non-smokers who try cigarettes will become addicted and will form the future demand for cigarettes.

The effect of a total ban on advertising would be completely different if cigarette companies advertise with the hope of increasing the number of people addicted to cigarettes. In particular, the ban should have a small or negligible effect on current cigarette demand. Instead, the cigarette companies would face a steadily decreasing demand for their product. Such a decrease in demand would reduce future profits for these companies. If future profits fell enough, some of the companies might be forced out of business. Clearly, it is this result that anti-smoking activists have in mind with their proposals to ban cigarette advertisements.

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Source:  OpenStax, Econometrics for honors students. OpenStax CNX. Jul 20, 2010 Download for free at http://cnx.org/content/col11208/1.2
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