The Term Structure of Interest Rates in a Pure Exchange Economy where Investors Have Heterogeneous Recursive Preferences
Bibliographic record
Abstract
This paper presents an equilibrium model of the term structure of interest rates when investors have heterogeneous recursive preferences. We consider a pure exchange economy with two classes of investors who have different relative risk aversions and different elasticities of intertemporal substitution. The RRA and the EIS can be varied independently for each investor. We use the model to examine the effects that the heterogeneity in preferences of investors has on their portfolio-consumption choices as well as on the instantaneous interest rate and bond yield. We find that the heterogeneity only in the RRA affects the cross-sectional as well as intertemporal variations of the consumption rate, the portfolio allocations for each investor and the instantaneous interest rate. However, the heterogeneity only in the EIS matters only for the intertemporal variations of these processes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".