Altonji, Joseph G., Lisa B. Kahn, and Jamin D. Speer. 2016. “Cashier or Consultant? Entry Labor Market Conditions, Field of Study, and Career Success.” Journal of Labor Economics, 34(S1).
Arellano-Bover, Jaime. 2020. “Career Consequences of Firm Heterogeneity for Young Workers: First Job and Firm Size.” Working Paper.
Carillo-Tudela, Carlos, Hermann Gartner, and Leo Kaas. 2021. “Recruitment Policies, Job Filling Rates and Matching Efficiency.” Working Paper.
- Dependent variable is the fraction of students in the birth cohort, parental income quintile cell at the university who earn in the top 1% of the income distribution for their birth cohort in 2014. Plots show coefficients on the interaction between birth cohort fixed effects and an indicator for the university losing access to at least one prestigious firm recruiting on campus between 2007 and 2009. Figure A.6b is the same as Figure 6, and shows results from a regression that includes CZ-university tier-birth cohort fixed effects and university fixed effects. Figure A.6a is the same, but instead includes state-university tier-birth cohort fixed effects and university fixed effects. See Figure 6 and text for details of the regression specification and included covariates.
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- Figure 4: Dropped Target Campuses in 2009, by University Characteristics Ivy Plus Univ. Elite Univ. Tier 2 Univ. Tier 3-5 Univ. Firm-Univ. Distance ≤ 50 50 < Firm-Univ. Distance ≤ 200 Firm-Univ. Distance > 200 Fract. Parents in Top Quintile Fract. Parents in Top 1% Ln(Students in Cohort) Fraction Female Public Univ.
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- Figure 5: Campuses Added Back After Being Dropped in 2009 Ivy Plus Univ.
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- Figure 6: Effect of Losing Access to Prestigious Firms During the Recession: Within CZ-University Tier-Cohort Estimates -.02 -.015 -.01 -.005 0 .005 Top 1% Income for Cohort in 2014 1980 1982 1984 1986 1988 1990 Notes: Dashed lines show 95% confidence intervals. Standard errors are clustered at the university level.
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- Figure A.4: Dropped Target Campuses in 2009, by University Characteristics, Treating Missing Recruiting as Dropped Ivy Plus Univ. Elite Univ. Tier 2 Univ. Tier 3-5 Univ. Firm-Univ. Distance ≤ 50 50 < Firm-Univ. Distance ≤ 200 Firm-Univ. Distance > 200 Fract. Parents in Top Quintile Fract. Parents in Top 1% Ln(Students in Cohort) Fraction Female Public Univ.
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- Firm Stops Recruiting in 2009 -.1 0 .1 .2 .3 Notes: Plot shows coefficients on university characteristics, when the dependent variable is an indicator for whether the firm was not recruiting on campus in 2009 (recruiting was either coded as zero or missing), but had recruited in 2007. The sample includes all firm-university pairs for which Recruit = 1 in 2007. See text and notes to Figure 4 for details.
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- Firm-Univ. Distance ≤ 50 50 < Firm-Univ. Distance ≤ 200 Firm-Univ. Distance > 200 Ln(Students in Cohort) Dropped in '09, Added in '10 or '11 -.3 -.2 -.1 0 .1 .2 (a) Added Back 2010 or 2011 Ivy Plus Univ.
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- Firm-Univ. Distance ≤ 50 50 < Firm-Univ. Distance ≤ 200 Firm-Univ. Distance > 200 Ln(Students in Cohort) Dropped in '09, Added in '10 or '11 -.4 -.2 0 .2 (a) Added Back 2010 or 2011 Ivy Plus Univ.
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- Firm-Univ. Distance ≤ 50 50 < Firm-Univ. Distance ≤ 200 Firm-Univ. Distance > 200 Ln(Students in Cohort) Dropped in '09, Added in '10-'13 -.4 -.2 0 .2 (b) Added Back 2010-2013 Notes: Plot shows coefficients on university characteristics, when the dependent variable is an indicator for whether the firm was recruiting on campus in 2010 or 2011 (A.5a), or 2010 or 2011 or 2012 or 2013 (A.5b), after not recruiting on campus in 2009, but recruiting in 2007. The sample includes all firm-university pairs for which Recruit = 1 in 2007 and Recruit = 0 in 2009. This differs from Figure 5 because Return is set to missing here if Recruit is missing. Standard errors are clustered at the university level. See text and Figure 5 for details.
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Forsythe, Eliza, and Russell Weinstein. 2021. “Recruiting Intensity, Hires, and Vacancies: Evidence from Firm-Level Data.” IZA Discussion Paper, No. 14138.
- Forsythe, Eliza. 2020. “Why Don’t Firms Hire Young Workers During Recessions?” Working Paper.
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Hershbein, Brad, and Lisa B. Kahn. 2018. “Do Recessions Accelerate Routine Biased Technological Change? Evidence from Vacancy Postings.” American Economic Review, 108(7).
Kahn, Lisa B. 2010. “The Long-Term Labor Market Consequences of Graduating from College in a Bad Economy.” Labour Economics, 17(2).
Liu, Kai, Kjell G. Salvanes, and Erik O. Sorensen. 2016. “Good Skills in Bad Times: Cyclical Skill Mismatch and the Long-Term Effects of Graduating in a Recession.” European Economic Review, 84.
Lochner, Benjamin, Christian Merkl, Heiko Stüber, and Nicole Gürtzgen. 2021. “Recruiting intensity and hiring practices: Cross-sectional and time-series evidence.” Labour Economics, 68.
Modestino, Alicia Sasser, Daniel Shoag, and Joshua Ballance. 2020. “Upskilling: Do Employers Demand Greater Skill When Workers are Plentiful?” Review of Economics and Statistics, 102(4).
- Observations are weighted by the number of students in the birth cohort at the university. All regressions include only universities that have data for each cohort. Plots show coefficients on interaction between birth cohort fixed effects, university tier, and an indicator for the local area experiencing a severe recession from 2007 to 2009. All effects in the regressions are relative to non-Ivy Plus Tier 1 universities. Plots (A.1a) and (A.1b) present coefficients from the same regression, which includes CZ-birth cohort fixed effects and university fixed effects. The indicator for severe recession in this regression is one if the CZ experienced an above-median increase in the unemployment rate from 2007 to 2009. The regression includes only commuting zones that have a non-Ivy Plus Tier 1 university. See text for details.
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Oreopolous, Philip, Till von Wachter, and Andrew Heisz. 2012. “The Short- and Long-Term Career Effects of Graduating in a Recession.” American Economic Journal: Applied Economics, 4(1).
Oyer, Paul. 2006. “Initial Labor Market Conditions and Long-Term Outcomes for Economists.” Journal of Economic Perspectives, 20(3).
- Recruit 2000 2002 2004 2006 2008 2010 2012 (d) 106 Tier 3-5 Universities (Selective) Mean Recruit2007 = .029 Notes: Dashed lines show 95% confidence intervals. Plots show regressions similar to those described in Figure 2, but with a separate regression for each tier of university selectivity. In Panel (a) standard errors are clustered at the firm level because there are only 12 universities, whereas in the other panels standard errors are clustered at the firm and university level. See text and Figure 2 for details.
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- Recruit 2000 2002 2004 2006 2008 2010 2012 Notes: Dependent variable is an indicator for whether firm f recruits at university j in year t. Plot shows coefficients on year indicator variables, from a regression with firm-university pair fixed effects. Dashed lines show 95% confidence intervals, and standard errors are clustered at the firm and university level. The regression includes only firm-university pairs with data in 2007, 2009, and 2013, and only firms that recruit on at least one campus in the data throughout the sample period, and universities that attract at least one firm in the data throughout the sample period. See text for details.
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- Recruit 2000 2002 2004 2006 2008 2010 2012 Notes: Dependent variable is an indicator for whether firm f recruits at university j in year t. Plot shows coefficients on year indicator variables, from a regression with firm-university pair fixed effects. Dashed lines show 95% confidence intervals, and standard errors are clustered at the firm and university level. The regression includes only firm-university pairs with data in 2007, and only firms that recruit on at least one campus in the data throughout the sample period, and universities that attract at least one firm in the data throughout the sample period. See text for details. Figure 3: Changes in Recruiting Over Time, within Firm-University Pairs, by University Selectivity -.3 -.2 -.1 0 .1 ∆
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- Standard errors are clustered at the firm and university level. We exclude universities for which the reporting of mobility report card variables is for multiple universities in a university system. We use covariate values corresponding to the 2007 cohort. See text for details.
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- Table A.5: Changes in Recruiting Over Time, within Firm-University Pairs Setting Recruit to Zero for Nonarchived Pages Recruit 2000-0.022** (0.008) 2001-0.026*** (0.008) 2002-0.024*** (0.008) 2003-0.025*** (0.007) 2004-0.025*** (0.007) 2005-0.017*** (0.005) 2006-0.015** (0.006) 2008-0.016** (0.006) 2009-0.019** (0.008) 2010-0.015* (0.008) 2011-0.014* (0.008) 2012-0.013** (0.006) 2013-0.006 (0.006) University Tier All Balance 2007 Observations 229,317 R-squared 0.386 Mean, Recruit2007 0.044 Notes: *** p-value ≤ .01, ** p-value ≤ .05, * p-value ≤ .1. This table shows results similar to those in Appendix Table A.4, but using a version of Recruit set to zero instead of missing if the recruiting page is nonarchived for reasons other than being blocked to robots or nonworking links. See Appendix Table A.4 and text for details.
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Weinstein, Russell. 2018. “Employer Screening Costs, Recruiting Strategies, and Labor Market Outcomes: An Equilibrium Analysis of On-Campus Recruiting.” Labour Economics, 55.
Weinstein, Russell. 2020. “Local labor markets and human capital investments.” Journal of Human Resources. Weinstein, Russell. Forthcoming. “Firm Decisions and Variation Across Universities in Access to High-Wage Jobs: Evidence from Employer Recruiting.” Journal of Labor Economics.
Yagan, Danny. 2019. “Employment Hysteresis from the Great Recession.” Journal of Political Economy, 127(5).