Replication of Goolsbee, Lovenheim, and Slemrod’s “Playing with Fire: Cigarettes, Taxes, and Competition from the Internet” ( <i>American Economic Journal: Economic Policy</i> , 2010)
Bibliographic record
Abstract
This study replicates the empirical findings of Goolsbee, Lovenheim and Slemrod, henceforth GLS, and performs a variety of robustness checks. Using taxable cigarette consumption, real cigarette excise tax rates, wholesale cigarette prices, per capita income, and other state-level data for the period 1980–2005, GLS report that rising Internet penetration in the presence of cigarette taxes has a significant causal effect on the elasticity of demand for taxable cigarettes. I am able to exactly replicate GLS’s findings, and explore their robustness in three ways. First, I examine sensitivity to the removal of outlier cohorts of states from the data. Second, I use population-unweighted state-year observations in place of GLS’s population-weighted state-year observations. Third, I probe the robustness of GLS’s key interaction term (real state cigarette taxes * Internet penetration) by (i) adding Internet penetration interaction terms to all main effects in the model and (ii) performing an orthogonalization procedure (Balli and Sørensen, 2013) to purge from GLS’s estimate of the key interaction term any spurious correlation that might exist between Internet penetration and the included variables, which would then be loaded on to the interaction between Internet penetration and cigarette taxes. GLS’s results were robust to all but the orthogonalization procedure. This raises the possibility that the effect identified by GLS is an artifact of spurious correlation between Internet penetration and cigarette taxes over time. In sum, GLS’s data may have insufficient power to identify the stand-alone effect of Internet penetration on cigarette tax-sales elasticities in a fully-interacted model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".