differences in the raw data, but the result for smoking cessation is still only borderline significant. Comparable results are obtained in columns 7-8 with an indicator for college graduation as a measure of education.

Table 5 presents results using an alternative instrument: rather than only the risk of being drafted, I have created an instrument that also includes the risk of being killed in Vietnam. The intuition behind this alternative instrument is that what might have caused individuals to enroll in college to avoid the draft is not so much the risk of being drafted, but the risk of being drafted and killed. I calculate the risk of being killed in action as the ratio between the number of soldiers killed in action in a year and the level of troops engaged in Vietnam during that year.<sup>26</sup> Then, for each year, I multiply the yearly induction rate with the probability to be killed in action.<sup>27</sup> Figure 8 compares the two risk measures used as instrument, the risk of induction and the risk of induction multiplied by the risk of being killed in action. Although these measures peak for the same birth cohort, the slope is steeper when the probability of being killed in action is also considered. As reported in table 5, when the risk of induction multiplied by the risk of being killed in action is used as an instrument (see columns 3 to 8, when actual Vietnam veteran status is controlled for), the results are qualitatively very similar to the results with the induction risk (see table 4) as instrument. However, the results are here always significant, even for the smoking cessation regressions. If anything, the point estimates of the coefficients are slightly higher than the ordinary least square results and the first instrumental variable strategy, especially in the case of smoking cessation. It is especially important to establish the significance of the positive effect of college education on the decision to stop smoking, because, as argued in section 3, this is the more appropriate margin to study the relationship between education and smoking, since that decision is taken after schooling is completed. Interestingly, this is also a margin where the actual Vietnam veteran status has no effect, as indicated by the results in the even columns in tables 3 to 5.

On the other hand, actual Vietnam veteran status has an important impact of the probability of being a current smoker, even after controlling for age, income, education, race, and gender. The inclusion of this variable in the instrumental variable regressions

> 26 The casualty data are taken from the website <u>http://www.vietnamwall.org/casualty.html</u> (accessed on May 11, 2004) and derived from the Combat Area Casualty File of 11/93 and the Adjutant General’s Center (TAGCEN) file of 1981, available from the National Archives. For the years 1961-1965, the number of killed in action (1864) has been evenly spread over the five years, as no yearly details were available. The level of U.S. troops engaged in Vietnam for each year is taken from the website <u>http://www.25thaviation.org/id430.htm</u> (accessed on May 11, 2004).

> 27 The final measure of the risk to be induced and killed for each birth cohort is calculated as the previous measure of the risk of induction. I average the yearly number of inductions in Vietnam multiplied by the probability of being killed in action over the years when a particular birth cohort was aged 19-22, and divide this number by the size of the birth cohort.

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