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The functionality allows the user to enter a value of `eti` that is either a scalar (i.e., constant over income) or a dictionary with keys `knot_points` and `etc_values`, which each contain corresponding lists of income values and the ETI at those values. E.g., using the estimate of the ETI over the income distribution from [Gruber and Saez (2002)](http://piketty.pse.ens.fr/files/GruberSaez2002.pdf), this would look like:\r\n\r\n```python\r\neti_dict = {\r\n \"eti_values\": [0.18, 0.106, 0.567, 1.0],\r\n \"knot_points\": [30000, 75000, 250000, 10000000]\r\n}\r\n```\r\n\r\nWhere the last value is provided to help find just a gradual increase in the ETI after $250,000. Using a linear spline, the results look like:\r\n![linear_spline](https://github.com/PSLmodels/InverseOptimalTax/assets/10715924/918108e0-2bdd-47f9-b373-ac77e1626739)\r\n\r\nThe sharp changes in the ETI in this interpolated function are probably not realistic and introduce odd kinds in the implied social welfare weights. \r\n\r\nHowever, with so few datapoints, a cubic spline has its own problems (going off to values that are unrealistically high):\r\n![cubic_spline](https://github.com/PSLmodels/InverseOptimalTax/assets/10715924/40cd20ff-9a73-4537-b2d6-973d4ff19edd)\r\n\r\nI believe the solution is to find more data points on the ETI on different parts of the income distribution that can be used to inform a cubic spline. This should allow for some smoothness in the ETI spline, but without a steep slope in some values beyond those in the literature.\r\n\r\ncc @john-p-ryan \r\n\r\n\r\n\r\n", - "created_at": "2023-10-27T02:46:36Z", - "updated_at": "2023-11-27T15:15:46Z", - "closed_at": "2023-11-27T15:15:46Z", - "merged_at": "2023-11-27T15:15:46Z", - "merge_commit_sha": "7cb3657268877cec5cc7e092c6f58f0965e55089", + "body": "This PR adds a new notebook to produce the plots use in a presentation at the National Tax Association Annual Meetings in 2023.", + "created_at": "2024-01-31T19:39:43Z", + "updated_at": "2024-02-03T21:30:03Z", + "closed_at": "2024-02-03T21:30:00Z", + "merged_at": "2024-02-03T21:30:00Z", + "merge_commit_sha": "d0127007ee7b60a64c76dda3f425c0cfdcb93a6e", "assignee": null, "assignees": [], "requested_reviewers": [], @@ -1373,15 +1373,15 @@ "labels": [], "milestone": null, "draft": false, - "commits_url": "https://api.github.com/repos/PSLmodels/InverseOptimalTax/pulls/23/commits", - "review_comments_url": "https://api.github.com/repos/PSLmodels/InverseOptimalTax/pulls/23/comments", + "commits_url": "https://api.github.com/repos/PSLmodels/InverseOptimalTax/pulls/25/commits", + "review_comments_url": "https://api.github.com/repos/PSLmodels/InverseOptimalTax/pulls/25/comments", "review_comment_url": "https://api.github.com/repos/PSLmodels/InverseOptimalTax/pulls/comments{/number}", - 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