The DOI matches its Crossref record; 49 of the 58 references it cites were found in a registry or an index; none of the 24 sources its claims cite is checked for support yet.
The short- and long-run impacts of secondary school absences
Open accessAbstract
Abstract We provide novel evidence on the causal impacts of student absences in middle and high school on state test scores, course grades, and educational attainment using a rich administrative dataset that tracks the date and class period of each absence. We use two similar but distinct identification strategies that address potential endogeneity due to time-varying student-level shocks by exploiting within-student, between-subject variation in class-specific absences. We also leverage information on the timing of absences to show that absences that occur after the annual window for state standardized testing do not affect test scores, providing a further check of our identification strategy. Both approaches yield similar results. We find that absences in middle and high school harm contemporaneous student achievement and longer-term educational attainment: On average, missing 10 classes reduces math or English Language Arts test scores by 3–4% of a standard deviation and course grades by 17–18% of a standard deviation. 10 total absences across all subjects in 9th grade reduce both the probability of on-time graduation and ever enrolling in college by 2%. Learning loss due to school absences can have profound economic and social consequences.
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68 Own result · 32 Own interpretation · 19 Not checked yet · 13 No basis given · 11 Own method
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“The effects of absences are approximately linear and similar in magnitude across student and school subgroups.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
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In the paper
“We find that absences in the spring semester are far more detrimental than those in the fall semester.”
- Also stated in: § 1 Introduction · hedged
“In contrast, absences in the fall semester appear to matter very little, if at all.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
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- Also stated in: § 1 Introduction · hedged
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In the paper
“Our results show that on average, missing 10 math classes in the spring semester reduces math scores on state standardized tests by 7% of a standard deviation”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
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In the paper
“Similarly, having 10 absences in the spring semester reduces course grades by 19% of a standard deviation.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
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In the paper
“Second, these between-subject differences are relatively stable over time.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.3 Identifying Assumptions
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In the paper
“Both the white-black and white-Hispanic attendance gaps increase significantly over the course of the school year, with the white-black gap more than tripling and the white-Hispanic gap more than doubling, as shown in Figure 2.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
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In the paper
“This level of granularity allows us to show that absences that occur after the annual window for state standardized testing do not appear to affect test scores”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
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In the paper
“First, all point estimates are remarkably robust across a variety of models that account for the potential sources of endogeneity: nonrandom classroom assignments; unobserved school, classroom, or neighborhood shocks; unobserved student and family background characteristics; and time-varying student-level shocks.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
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In the paper
“There is a clear increase in the average number of absences in both subjects in the spring semester.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 2.3 Absence Data
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In the paper
“Within-student standard deviations of absences are relatively large compared with the overall standard deviation, indicating that more than half the variation in absences occurs within, as opposed to between, students.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 2.3 Absence Data
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In the paper
“Panel B of Table 4 and Appendix Table A2 show nearly identical results in high school math and in ELA courses, respectively.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
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“Most of the coefficients are insignificant other than when comparing math with science, suggesting that students' preferences do not change systematically as they progress.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.3 Identifying Assumptions
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In the paper
“First, between-subject differences tend to be small in magnitude and statistically indistinguishable from zero.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.3 Identifying Assumptions
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In the paper
“For example, as Column 2 shows, having 10 spring absences reduces student achievement by 9.5% of a standard deviation, a slightly bigger estimate than the coefficient from our preferred model in Table 4 (7.0%).”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.2 Stacked Regressions
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In the paper
“The effect of fallsemester absences is negative and marginally significant but small in magnitude, suggesting that having 10 absences lowers test scores by about 1% of a standard deviation.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
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In the paper
“there is considerable withinstudent-year variation in subject-specific absences: While highly correlated (with a .85correlation coefficient), they are not perfectly correlated, as two-thirds of student-year observations have a different number of math and ELA absences.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.3 Identifying Assumptions
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In the paper
“The two plots are nearly identical, suggesting that math and ELA absences differ for reasons unrelated to math ability or preferences (which are loosely captured by lagged math performance).”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.3 Identifying Assumptions
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In the paper
“The coefficients shrink a bit but are still closely aligned with those in Table 4: Having 10 spring absences reduces students' math test scores by about 6% of a standard deviation.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.2 Stacked Regressions
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In the paper
“The estimate reported in Column 6 controls for ELA absences, though Appendix Table A4 shows that this result is robust to using absences in other classes, including physical education.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
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In the paper
“The point estimate in the preferred proxy-variable model of Column 6 is 7% of a standard deviation and is strongly statistically significant.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
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In the paper
“The results are very similar to those in Table 4.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.2 Stacked Regressions
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In the paper
“Depending on the model specification, the effect of having 10 fall-semester absences ranges from 1 to 3% of a standard deviation and is statistically indistinguishable from zero in the preferred proxy-variable model of Column 6.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
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In the paper
“Indeed, this is exactly what we see, as the point estimate in Column 5 is twice as large as that in Column 4 and is not driven by selection on unobservables: The Oster bound is nearly identical to the point estimate.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 5.2 Long-Term Outcomes
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In the paper
“On average, a student has 1.7 absences that only last for one day and 0.7 absence spells that last for two days.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“The effects are similar for boys and girls and for students from different racial and ethnic backgrounds, though the harm for black students is larger than for other groups, and the effect for white students is imprecisely estimated.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.4 Nonlinearity and Heterogeneity
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In the paper
“Figure 8 plots fitted regression lines from the linear, quadratic, and nonparametric models, which approximately overlap with each other, though the nonparametric estimates are fairly noisy for higher absence counts, as there are relatively few students in those bins.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.4 Nonlinearity and Heterogeneity
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In the paper
“Columns 2 and 3 show that these absolute effects are smaller for college enrollment but remain statistically significant and in percentage terms are similarly sized effects, given the lower base rate of college enrollment.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 5.2 Long-Term Outcomes
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In the paper
“Still, the effects of absences are fairly similar in magnitude, especially when comparing across multi-way spells of different lengths.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“The effect of a stand-alone absence is bigger than the marginal effect of an absence that is part of a longer absence spell; this finding is consistent with the notion of fixed costs to catching up following any absences and/or economies of scale in making up missed work.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“Finally, we see an insignificant and close-to-zero coefficient estimate for week 21-22 absences, which is reassuring because those absences almost certainly occurred after the test was taken.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“Because absences later in the year are more detrimental to course grades and exam scores”
§ The Short-and Long-Run Impacts of Secondary School Absences > 6 Conclusion
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In the paper
“The effect of absences on four-year college enrollments is not only smaller but also likely due to selection on unobservables, as even a modest (60%) amount of selection on unobservables is enough to explain away the point estimate of -0.02.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 5.2 Long-Term Outcomes
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In the paper
“The modal absence is a one-off event (i.e., part of a one-day spell).Most absences are part of one-or two-day spells.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“Estimated coefficients for absences in weeks 1-14 and 15-16 are both around -0.05 and are statistically significant though slightly smaller than the baseline estimate that restricts the effects of all spring-semester absences to be the same.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“We do not see any systematic differences between more-and less-advantaged schools; absences seem similarly harmful across school types.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.4 Nonlinearity and Heterogeneity
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In the paper
“Harm does vary somewhat across schools, but it does not vary systematically by student demographic or socioeconomic background.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.4 Nonlinearity and Heterogeneity
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In the paper
“The coefficient estimates for absences in weeks 17-18 and 19-20 are almost twice as large, suggesting that absences during the testing window are more harmful than those that occur earlier in the spring semester.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“In sum, all absences are harmful, while the marginal cost of absences that are part of a longer absence spell is smaller.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
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In the paper
“More than 75% of the estimates are negative, and most are within one standard deviation of the baseline point estimate.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.4 Nonlinearity and Heterogeneity
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In the paper
“Patterns are similar when using other school years.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 6 Conclusion
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In the paper
“This assumption is plausible, as the primary mechanism through which absences harm achievement is via lost instructional time.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.2 Exploiting Subject-Specific Absence Data
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In the paper
“Lastly, the studied district has a large and diverse student body, providing the power and variation necessary to conduct the analysis.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 2.1 Administrative Data
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In the paper
“Because attendance is an intermediate output of the education production function as well as an input, it might be affected by the same shocks that affect test scores and other educational outcomes.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.1 Value-Added Model
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What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The lagged scores and classroom and tract-by-year fixed effects included in X eliminate many of the threats to validity articulated above, but concerns about idiosyncratic student-level shocks to both A and y remain.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.2 Exploiting Subject-Specific Absence Data
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: Absences in one subject do not affect achievement in another subject, conditional on other factors and the student-year shock.
- The authors state this as an assumption: Within-student differences in absences between math and ELA are conditionally random, so absences in one subject serve as a good proxy for the student-year shock.
None of the sources cited for this claim have been checked yet.
In the paper
“Moreover, the harm attributable to absences is fairly similar across all levels of schooling: Comparable estimates from North Carolina showed similar effects of absences in grades 4 and 5.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Once again, the results are robust, suggesting that relatively stable unobserved student and family characteristics are not biasing the simple lagged-score estimates reported in Column 1.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“This effect is economically significant, as it is roughly equivalent to replacing an average teacher with one from the 20th percentile of the effectiveness distribution (Herrmann and Rockoff, 2012).”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
What the sources say
- Not checked yetcites Herrmann and Rockoff, 2012
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“This too is plausible in the current setting, given the strong correlation between subject-specific absences in a given year and the underlying process through which an idiosyncratic shock would affect attendance.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.2 Exploiting Subject-Specific Absence Data
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“As shown in Equation 3, using student-byyear fixed effects, we control for time-varying student-specific shocks and directly attribute the difference between students' math and ELA performance to their subject-specific absences.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.2 Stacked Regressions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“To our knowledge, this is the first credible evidence that absences harm achievement in both middle and high schools, and this finding suggests that absences are a serious concern at every level of K-12 schooling.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Existing evidence comes almost exclusively from primary school settings and considers absenteeism using full-day absences.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
In the paper
“We have no reason to believe there would be any systematic bias or error in this traditional way of marking attendance (Whitney and Liu, 2017).”
§ The Short-and Long-Run Impacts of Secondary School Absences > 2.3 Absence Data
What the sources say
- Not checked yetcites Whitney and Liu, 2017
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The concern is that idiosyncratic (timevarying) shocks jointly affect current achievement and attendance but are not adequately controlled for by lagged test scores or student or school fixed effects.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.1 Value-Added Model
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“An exception is a study by Gottfried and Kirksey (2017), who similarly found that spring, but not fall, absences are associated with end-of-year elementary school test scores in a small urban district in California.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
What the sources say
- Not checked yetcites Gottfried and Kirksey (2017)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Gershenson et al. (2017) found the effects of annual primary school absences to be approximately linear”
§ The Short-and Long-Run Impacts of Secondary School Absences > 3.1 Value-Added Model
What the sources say
- Not checked yetcites Gershenson et al. (2017) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This weighted average of the fall and spring impacts uncovered in Table 4 is misleading, as it overstates the importance of fall absences and understates the importance of spring absences.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These results suggest that middle and high school absences are harmful for both contemporaneous academic achievement and long-run educational attainment.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Absences in later grades are fundamentally different from those in earlier grades, as older students have more agency over their school attendance habits”
§ The Short-and Long-Run Impacts of Secondary School Absences > 1 Introduction
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“This effect size is similar to that estimated using similar methods for 4th-and 5th-graders in North Carolina (Gershenson et al., 2017).”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
What the sources say
- Not checked yetcites Gershenson et al., 2017 source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Once again, the Oster bounds suggest that there is a causal effect on college enrollment, though sorting seems to play a bigger role here than in the high school graduation analysis.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 5.2 Long-Term Outcomes
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“As discussed in Section 2, we can only impute testing windows, as the exact timing of testing is unknown and may vary across students within a school.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
In the paper
“These results further confirm that lost instructional time induced by absences harms student performance and that the baseline estimate is not biased by selection (Herrmann and Rockoff, 2012).”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.3 Timing of Absences
What the sources say
- Not checked yetcites Herrmann and Rockoff, 2012
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, the results in Table 7 provide additional evidence that middle and high school student absences harm achievement, that this relationship is causal, that absences later in the year are more harmful than those earlier in the year, and that a likely mechanism is simply lost instructional time.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 5.1 Course Grades
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These are economically significant effects on par with the impacts of other popular interventions.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 6 Conclusion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The similarity between the three models suggests that the effect of absences is approximately linear and that there is no nonlinearity in achievement at the threshold of chronic absenteeism (though chronically absent students certainly perform significantly worse than students with just one or two absences).”
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.4 Nonlinearity and Heterogeneity
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: The effects of absences are linear, with no diminishing or increasing costs and no discrete effect at the chronic absenteeism threshold.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Again, this is to be expected because math absences and ELA absences are highly correlated.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 5.2 Long-Term Outcomes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In sum, the results of Table 8 reaffirm a causal interpretation of the main finding that absences harm achievement and provide arguably novel evidence that 9th-and 10th-grade absences have a causal effect on subsequent educational attainment, which motivates the potential value of absence-related interventions in high school.”
§ The Short-and Long-Run Impacts of Secondary School Absences > 5.2 Long-Term Outcomes
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is unlikely that all absences are discretionary”
§ The Short-and Long-Run Impacts of Secondary School Absences > 6 Conclusion
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it appears that late-year absences are simply harder to make up, either because there is less time to do so or because students are busier and encountering more difficult material later in the year”
§ The Short-and Long-Run Impacts of Secondary School Absences > 6 Conclusion
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Grades in the district are based on academic performance and cannot be based on nonacademic factors such as absences.
The authors state this as an assumption.
Absences in one subject do not affect achievement in another subject, conditional on other factors and the student-year shock.
“second, that any spillover effects of absences in one subject on academic mastery in another are relatively trivial.”
“Conditional on math absences, X, and the year-specific student shock, ELA absences do not affect math achievement.”
The authors state this as an assumption.
Within-student differences in absences between math and ELA are conditionally random, so absences in one subject serve as a good proxy for the student-year shock.
“first, that in a given school year, within-student differences in absences in math and English language arts (ELA) are conditionally random”
“A -j needs to be a good proxy in the sense that conditional on A -j , A j is no longer correlated with the idiosyncratic shock (v it in Equation 2).”
The authors state this as an assumption.
Within-student differences in absences between subjects are conditionally random and not due to year-specific subject preferences.
“both the proxy plug-in and stacked student-year fixed-effects strategies assume that such differences are conditionally random (e.g., because of the timing of a dentist appointment or leaving school early due to illness) and not the result of a year-specific preference for one subject over the other.”
The authors state this as an assumption.
Non-math absences do not directly affect math performance, ruling out cross-subject spillover effects.
“the redundancy assumption made by the proxy plug-in solution, which is that non-math (e.g., ELA) absences do not directly affect math performance.”
The authors state this as an assumption.
The effects of absences are linear, with no diminishing or increasing costs and no discrete effect at the chronic absenteeism threshold.
“The main results presented in Section 4.1 assume that the effects of absences are linear -that is, that there are neither diminishing nor increasing costs to student absences, nor is there a discrete effect of crossing the threshold for being considered chronically absent, which in this district is defined as missing at least 10% of total school days (accruing about 18 absences).”
The authors state this as an assumption.
The harm of absences is the same across all student and school types.
“The models estimated to this point also assume that the harm of absences is the same across all student and school types.”
The paper relies on this without support.
Grades in the district are based on academic performance and cannot be based on nonacademic factors such as absences.
“Grades in the district are explicitly based on academic performance and are not allowed to be based on nonacademic factors such as absences.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Both correlational and quasi-experimental studies find that student absences have negative effects on several academic and longer-run economic outcomes (5–7).”
From Higher chronic absenteeism threatens academic recovery from the COVID-19 pandemic (2024) · cites this paper as [5]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“More generally, consistent school attendance is an educationally consequential behavior.”
From Higher chronic absenteeism threatens academic recovery from the COVID-19 pandemic (2024) · cites this paper as [5]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ The Short-and Long-Run Impacts of Secondary School Absences > Figures and Tables
“Ever Enrolled in College Ever Enrolled in 4-Year”
§ The Short-and Long-Run Impacts of Secondary School Absences > Figures and Tables
“Outcome Averages 0.504 0.493 0.481 0.580 0.311”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ The Short-and Long-Run Impacts of Secondary School Absences > 4.1 Main Results
“Panel A presents estimates for six slightly different model specifications using the sample of middle school students (grades 6-8).”
§ The Short-and Long-Run Impacts of Secondary School Absences > Figures and Tables
“Note: Observations are at the student-semester-subject level and include the full analytic sample with nonmissing values.Data include 7th-to 11th-graders from the school years 2002-2003 to 2012-2013 at the student-classroom level.”
Citations
Cites
(2001) · RePEc: Research Papers in Economics · Cited by 27,577
Specification Tests in Econometrics
Hausman, J. A. (1978) · Econometrica · doi:10.2307/1913827 · Cited by 18,820
Unobservable Selection and Coefficient Stability: Theory and Evidence
Oster, E. (2019) · Journal of Business & Economic Statistics · doi:10.1080/07350015.2016.1227711 · Cited by 5,367
Selection on observed and unobserved variables: Assessing the effectiveness of Catholic schools
Altonji, J. G., Elder, T. E., & Taber, C. R. (2005) · Journal of Political Economy · doi:10.1086/426036 · Cited by 3,706
Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood
Chetty, R., Friedman, J. N., & Rockoff, J. E. (2014) · American Economic Review · doi:10.1257/aer.104.9.2633 · Cited by 1,717
Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates
Chetty, R., Friedman, J. N., & Rockoff, J. E. (2014) · American Economic Review · doi:10.1257/aer.104.9.2593 · Cited by 1,241
(2011) · Issue Lab (Candid) · Cited by 1,167
Projecting the Potential Impact of COVID-19 School Closures on Academic Achievement
Kuhfeld, M., Soland, J., Tarasawa, B., Johnson, A., Ruzek, E., & Liu, J. (2020) · Educational Researcher · doi:10.3102/0013189x20965918 · Cited by 997
Self-citationLOEBER, R., & FARRINGTON, D. P. (2000) · Development and Psychopathology · doi:10.1017/s0954579400004107 · Cited by 926
The impact of COVID-19 on student experiences and expectations: Evidence from a survey
Aucejo, E. M., French, J., Araya, M. P. U., & Zafar, B. (2020) · Journal of Public Economics · doi:10.1016/j.jpubeco.2020.104271 · Cited by 896
Research works printed but not linked: 2
- Dundar, 2016, The National Student Clearinghouse as an integral part of the national postsecondary data infrastructure, National Student Clearinghouse Research Center, 20, 1
- Gottfried, Michael A. and E. Hutt, Addressing Absenteeism, Harvard Education Press, 2019.
Cited by
Sorted by citations
Higher chronic absenteeism threatens academic recovery from the COVID-19 pandemic
Dee, T. S. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2312249121 · Cited by 110
“Both correlational and quasi-experimental studies find that student absences have negative effects on several academic and longer-run economic outcomes (5,6).”
Molnár, G., & Hermann, Z. (2022) · Learning and Instruction · doi:10.1016/j.learninstruc.2022.101706 · Cited by 73
School absenteeism and academic achievement: Does the timing of the absence matter?
Keppens, G. (2023) · Learning and Instruction · doi:10.1016/j.learninstruc.2023.101769 · Cited by 56
The Long-Term Effects of Student Absence: Evidence from Sweden
Cattan, S., Kamhöfer, D. A., Karlsson, M., & Nilsson, T. (2023) · The Economic Journal · doi:10.1093/ej/ueac078 · Cited by 44
Blanden, J., Doepke, M., & Stuhler, J. (2022) · National Bureau of Economic Research · doi:10.3386/w29979 · Cited by 72
Metadata
- Authors
- Liu, J., Lee, M., & Gershenson, S.
- Affiliations
- University of Maryland, College Park (US)
- Brown University (US)
- American University (US)
- Corresponding author
- Liu, Jing
- Venue
- Journal of Public Economics
- Publisher
- Elsevier BV
- Published
- 2021-07
- Volume
- 199
- Pages
- 104441
- ISSN
- 0047-2727 (ISSN-L)
- OpenAlex
- W2972629176
- Semantic Scholar
- 1565bc898d49f78abe44a5b35d24ec9dc5743a4c
- Cited by
- 143
- References
- 58
- Citations by year
- 2026: 29 · 2025: 20 · 2024: 41 · 2023: 25 · 2022: 19 · 2021: 6
- FWCI
- 18.87
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Journal of Public Economics (publishedVersion)
- SSRN Electronic Journal (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Econstor (Econstor) (submittedVersion)
- Funders
- Institute of Education Sciences
- Spencer Foundation
- Topics
- Social Sciences › Education › Youth Substance Use and School Attendance
- Social Sciences › Education › School Choice and Performance
- Social Sciences › Education › Educational Outcomes and Influences
- Keywords
- school absenteeism, course grades, educational attainment, high school graduation, college enrollment, learning loss, junior high school, high schools, endogeneity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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