The Feldstein‐Horioka puzzle in an ARIMA framework
Bibliographic record
Abstract
Purpose To test the Feldstein‐Horioka hypothesis that the investment‐to‐output ratio moves one‐for‐one with the saving‐to‐output ratio, suggesting international capital mobility. Design/methodology/approach The paper uses the econometric framework developed by Fisher and Seater, interpreting the Feldstein‐Horioka hypothesis as a long‐run phenomenon, and paying particular attention to the integration properties of the data, since meaningful tests critically depend on these properties. The paper also investigates the power of the long‐horizon regression tests, using the inverse power function of Andrews. Findings The paper tests the Feldstein‐Horioka hypothesis for 15 European countries, as well as for the USA and Japan, using annual data for the period from 1960 to 2002. Evidence is found against the Feldstein and Horioka hypothesis of low international capital mobility. Originality/value Although the findings are in contrast to those of Feldstein and Horioka, they are consistent with neoclassical growth theory according to which there is no reason to expect a relation between saving and investment if there are no barriers to capital movements.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".