suggests that most of the identifi cation comes from cross- regional variation in young men’s wage growth and in changes in our instrumental variable.
30
Likewise, Figures 2a– 2d indicate that movements in young men’s employment rates and in our instrumental variable are more strongly correlated when the data is grouped
at least by region Figures 2a–2c than when it is not Figure 2d. Together, Figures 1 and 2 suggest that identifi cation of the impact of wages on young men’s employment
originates mainly from cross- regional variation in young men’s employment move- ments, wage growth, and exposure to rising oil prices. Graphical analysis of other
outcomes also suggests a predominant identifi cation role for cross- regional variation in young men’s wage growth and in changes in our instrumental variable.
IV. Results
Table 1 presents OLS and 2SLS results from Equation 2 estimated on the sample of young men using our basic group defi nition, in which group fi xed effects
aer
are defi ned by the interaction of four age categories, seven education levels, and eight regions. Four outcomes are considered: being employed, being enrolled in
school, being neither enrolled in school nor employed, and being both enrolled in school and employed. For each outcome, separate regressions are run based on various
percentiles used for imputing wages of nonemployed men.
For all estimators and percentiles considered, increased real wages unambiguously raise young men’s employment rate and reduce their probability of being neither en-
rolled in school nor employed. The 2SLS estimator suggests that a ten- point increase in log after- tax real wages 0.10 raises young men’s employment rate by 3.5 to 4.7
percentage points.
31
Since roughly 59 percent of young men were employed in 2001, these numbers imply wage elasticities of labor market participation that range from
0.59 0.350.59 to 0.80 0.470.59.
32
In addition, 2SLS parameter estimates show that a ten- point increase in log after- tax real wages lowers young men’s likelihood of be-
ing neither in school nor employed by 1.4 to 1.9 percentage point and reduces young men’s school enrollment rate by 2.6 to 3.5 percentage points, from a baseline 2001
school enrollment rate of 52 percent. Contrary to OLS results, 2SLS estimates do not support the hypothesis that increased wages induce male students to start combining
30. Cross- regional variation in changes in our instrumental variable is driven by cross- regional variation in young men’s employment shares in the oil industry during the 1997–2000 period.
31. In contrast, minimum wage parameter estimates indicate that a ten- point increase in log real minimum wages is associated with a drop in employment rates of roughly one percentage point Appendix Table A1.
Results not shown indicate that income from social assistance potentially available to nonemployed single males is uncorrelated with employment rates.
32. Comparing these numbers with those of Gustman and Steinmeier 1981 is difficult since they report no wage parameter estimates or wage elasticities. Using SIPP US data from May 1983 to April 1986, Kimmel
and Kniesner 1998 find an employment elasticity of 0.65 for a sample that includes both young and older single men. Using more recent data on samples of individuals aged 18–59, Bargain, Orsini, and Peichl 2012
compute labor supply elasticities for 17 European countries and the United States. For single men, they find that wage elasticities at the extensive margin range from 0.04 to 0.62 with a cross- country mean of 0.23.
Because we focus on young single men aged 17–24 rather than 18–59, we expect to find—and we do find—somewhat larger wage elasticities than those reported in Bargain, Orsini, and Peichl 2012.
Panel A: Age-education-region-year Cells
Panel C: Age-region-year Cells Panel B: Education-region-year Cells
Panel D: Age-education-year Cells dm_employed
= 0.000
+ 0.740
dm_oil dm_employed = –0.000 + 0.915 dm_oil [0.000] [0.191]
[0.001] [0.280]
dm_employed = 0.000 + 0.983 dm_oil dm_employed = –0.000 + 0.444 dm_oil
[0.000] [0.207] [0.000] [0.453]
–. 4
–. 2
.2 .4
–.1 –.05
.05 .1
.15 –.
4 –.
2 .2
0. 4
–.1 –.05
.05 .1
.15
–. 4
–. 2
.2 0.
4
–.1 –.05
.05 .1
.15 –.
4 –.
2 .2
0. 4
–.1 –.05
.05 .1
.15
Figure 2 Young Men’s Employment Rates and Oil Prices
Notes: Deviations over time of young men’s employment rates from group- specifi c means on the Y- axis are plotted against oil prices demeaned on the X- axis. A linear fi t is plotted and the resulting equation is
shown under each panel. Standard errors from these weighted regressions are clustered at the group level and are between brackets.
p 0.001; p 0.01; p 0.05; † p 0.10.
school and work: Estimates of 
1
, which are positive with OLS, become negative and imprecisely measured under 2SLS.
In sum, our main fi nding is that following improved wage offers, young men gen- erally increase their labor market participation though two channels: a a reduction
in school enrollment and; b the re- entry into the labor market of some individu- als who were neither in school nor employed. Estimates from 2SLS provide no evi-
dence—at least in the aggregate—that young men start combining school and work in greater numbers in response to increased wages.
These qualitative patterns hold when we restrict our attention to young men with a high school diploma, a trades certifi cate or diploma, or more education henceforth,
young men with a high school diploma or more education Table 2. For this subsam- ple, the 2SLS estimator indicates that a ten- point increase in log after- tax real wages
raises labor market participation by between 2.7 and 3.4 percentage points, reduces school enrollment by between 3.3 and 4.1 percentage points, and lowers the likelihood
of being neither in school nor employed by between 0.9 and 1.1 percentage point.
A different story emerges for young men with no high school diploma. For this subsample, there is virtually no evidence that increased wages lead to a drop in
school enrollment. Only OLS parameter estimates based on the 15th percentile are negative and statistically signifi cant at conventional levels in school enrollment
equations Table 3. In response to improved wage offers, less- educated young men appear to increase their labor market participation by making transitions from be-
ing neither in school nor employed into employment and by combining school and work in greater numbers. Parameter estimates from 2SLS indicate that a ten- point
increase in log after- tax real wages boosts labor market participation by between 5.3 and 8.7 percentage points, from a baseline employment rate of about 50 percent.
These numbers imply a substantial wage elasticity of labor market participation for less- educated young men that varies between 1.07 and 1.75.
33,34
A ten- point increase in log after- tax real wages also lowers the likelihood of being neither
in school nor employed by between 2.3 and 3.7 percentage while increasing the proportion of individuals who combine school and work by between 2.5 and 4.0
percentage points.
V. Robustness Checks
