Bonus vetus OLS: A simple approach of addressing the ’border puzzle’and other gravity equation issues. ms: Notre Dame
Bibliographic record
Abstract
Motivated to solve the “border puzzle ” of Canadian-U.S. trade, theoretical foundations for the gravity equation of international trade were refined recently to emphasize the importance of the endogeneity of multilateral price (resistance) terms, cf., Anderson and van Wincoop (2003). While regionspecific fixed effects can also generate consistent estimates of gravity-equation coefficients, cf., Feenstra (2004), Anderson and van Wincoop argue that proper computation of general equilibrium comparative statics requires custom estimation of the entire nonlinear system of trade flow and price equations. We show in this paper that these multilateral price terms are critical, but nonlinear estimation is not. Virtually identical results can be obtained using “good old ” ordinary least squares – bonus vetus OLS. The key is using a first-order log-linear Taylor-series expansion to approximate the multilateral price terms. Among several findings, we note just three. First, the approximation allows us to solve for a simple log-linear gravity equation revealing a fundamental theoretical relationship among bilateral trade flows, regional and world incomes, and bilateral, multilateral, and world trade costs. Second, we provide econometric and simulation results supporting that virtually identical coefficient estimates and comparative statics can be obtained much more easily by estimating a reduced-form gravity equation including theoreticallymotivated exogenous bilateral, multilateral, and world resistance terms. Third, we show that our methodology generalizes to other settings as well, working just as effectively to explain world trade flows.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".