Konstantin Görgen, Melanie Schienle
arXiv 18 Sep 2019 · Statistics — Applications · 3 citations (OpenAlex)
arXiv:1909.08299 · PDF · DOI · OpenAlex · Extracted main text
We use official data for all 16 federal German states to study the causal effect of a flat 1000 Euro state-dependent university tuition fee on the enrollment behavior of students during the years 2006-2014. In particular, we show how the variation in the introduction scheme across states and times can be exploited to identify the federal average causal effect of tuition fees by controlling for a large amount of potentially influencing attributes for state heterogeneity. We suggest a stability post-double selection methodology to robustly determine the causal effect across types in the transparently modeled unknown response components. The proposed stability resampling scheme in the two LASSO selection steps efficiently mitigates the risk of model underspecification and thus biased effects when the tuition fee policy decision also depends on relevant variables for the state enrollment rates. Correct inference for the full cross-section state population in the sample requires adequate design -- rather than sampling-based standard errors. With the data-driven model selection and explicit control for spatial cross-effects we detect that tuition fees induce substantial migration effects where the mobility occurs both from fee but also from non-fee states suggesting also a general movement for quality. Overall, we find a significant negative impact of up to 4.5 percentage points of fees on student enrollment. This is in contrast to plain one-step LASSO or previous empirical studies with full fixed effects linear panel regressions which generally underestimate the size and get an only insignificant effect.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Abadie, A., S. Athey, G. W. Imbens, and J. M. Wooldridge (2020) Sampling-based vs | 0.961 | 9 | 5 | 89% |
| 2 | Mitze, T., C. Burgard, and B. Alecke (2015) The tuition fee 'shock': Analysing the response of first-year students to a spatially discontinuous policy change in Germany | 0.928 | 5 | 3 | 80% |
| 3 | Belloni, A., V. Chernozhukov, and C. Hansen (2014) a): High-Dimensional Methods and Inference on Structural and Treatment Effects | 0.874 | 5 | 2 | 100% |
| 4 | MacKinnon, J. G. and H. White (1985) Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties | 0.843 | 5 | 4 | 60% |
| 5 | Bruckmeier, K. and B. U. Wigger (2014) The effects of tuition fees on transition from high school to university in Germany | 0.811 | 4 | 2 | 100% |
| 6 | Meinshausen, N. and P. Bühlmann (2010) Stability selection | 0.811 | 4 | 2 | 100% |
| 7 | Belloni, A., V. Chernozhukov, and C. Hansen (2014) b): Inference on treatment effects after selection among high-dimensional controls | 0.737 | 3 | 2 | 100% |
| 8 | Dwenger, N., J. Storck, and K. Wrohlich (2012) Do tuition fees affect the mobility of university applicants? Evidence from a natural experiment | 0.585 | 3 | 1 | 100% |
| 9 | Baier, T. and M. Helbig (2011) War all die Aufregung umsonst? Über die Auswirkung der Einführung von Studiengebühren auf die Studienbereitschaft in Deutschland | 0.511 | 2 | 1 | 100% |
| 10 | Kane, T. J (1994) College Entry by Blacks since 1970 : The Role of College Costs , Family Background , and the Returns to Education | 0.511 | 2 | 1 | 100% |
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