{"claim":{"id":"905adc58-7c91-48be-b1af-32fee7a6ab46","submission_id":"fb3a3de3-400d-4c72-b6bc-785b692557c6","submission_revision_id":"25d87378-8d12-4b05-9df3-5a0581faa633","builder":"builder-01","status":"active","claimed_at":"2026-10-15T14:39:41.640979Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null},"task":{"submission_id":"fb3a3de3-400d-4c72-b6bc-785b692557c6","submission_revision_id":"25d87378-8d12-4b05-9df3-5a0581faa633","revision_version":1,"submission_status":"under_review","submitted_at":"2026-06-10T07:03:07.048801Z","submitter_name":"Xuandong Zhao","submitter_email":"csxuandongzhao@gmail.com","task":{"status":"submitted","version":1,"extra_fields":{},"submitted_at":"2026-06-10T07:03:07.048801+00:00","industry_domain":"Econometrics","task_short_name":"conditional_binscatter","operating_system":"Windows, Linux, MacOS","task_description":"## Conditional Binscatter\n\nIn this assignment, you will use Stata’s built-in `nlsw88` dataset to study the relationship between job tenure and wages.\n\n### Dataset\n\nLoad the `nlsw88` dataset\n\nThis dataset contains information on women in the labor market in 1988.\n\n### Research Question\n\nHow does hourly wage vary with job tenure after controlling for worker characteristics and absorbing industry and occupation fixed effects?\n\n### Variables\n\nUse the following variables:\n\n* Outcome variable: `ln_wage`, defined as the natural logarithm of hourly wage\n* Main explanatory variable: `tenure`, job tenure in years\n* Controls: `age`, `grade`, `ttl_exp`, `hours`, `race`, `married`, `south`, and `smsa`\n* Fixed effects: `industry` and `occupation`\n\n### Instructions\n\nFirst, load the data and create the log wage variable.\n\nThen estimate a conditional binscatter using `binsreg`. Include the control variables and fixed effects mentioned above. Use 10 quantile-spaced bins and canonical binscatter dots.\n\nNext, open the saved binscatter data and compute the fitted value of `ln_wage` in the highest-tenure bin.\n\n### Question\n\nWhat is the fitted binscatter value of `ln_wage` in the highest-tenure bin? You need to use Stata to solve this problem.\n\nReport your answer rounded to three decimal places.\n\n","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"The answer should be 1.899. So just check if the final number is 1.899 or not.","software_and_version":"Stata 15","specific_requirements":null,"expected_completion_time":null},"files":[],"deep_review":{"overall_verdict":"Borderline Accept","review_text":"**Overall Verdict:** Borderline Accept — The task is objectively gradable and end-to-end feasible, but the toolchain licensing declaration materially conflicts with the required proprietary software.\n\n**Completeness Check:**\n- Instruction: Complete — The dataset, variables, controls, fixed effects, binning method, requested statistic, and three-decimal output are specified.\n- Inputs: Complete — `nlsw88` is identified as a Stata-provided dataset, so no uploaded input is required.\n- Toolchain: Unclear — Stata is proprietary, contrary to the “Free/Open Source” declaration; the `binsreg` package version is also unspecified.\n- Reference output: Complete — The expected rounded result is explicitly identified as `1.899`.\n- Rubric: Complete — Exact comparison against the required three-decimal result provides objective evaluation for this atomic numeric answer.\n\n**File and Task Reachability:**\nThe attachment set is `reachable`. `FILES.json` was inspected and contains a valid empty manifest; no attachments were submitted, and no attachment content remains unreviewed. The task is `reachable` on a machine with a licensed, compatible Stata installation and an appropriate `binsreg` release: load the built-in dataset, generate log wages, estimate and save the conditional binscatter, select the highest-tenure dot, and compare its fitted value with `1.899`. A local Stata runtime was unavailable during review, so the reference number was not independently recomputed; this is a reviewer-tooling limitation, not an attachment defect. License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.\n\n**Special Screening:**\nNone. Public availability of the exact task, protected answer, or standard solution was not established from the submitted evidence.\n\n**Recommended Changes:**\nThe modeling objective and numeric evaluation target are clear. Correct the licensing field to identify Stata as commercial/proprietary and state that the execution environment must supply a licensed compatible version. For stronger reproducibility, pin the `binsreg` version and specify whether categorical controls such as `race` are entered as factor variables or numeric covariates.","reviewed_at":"2026-08-14T23:04:02.389764Z"},"claim":{"id":"905adc58-7c91-48be-b1af-32fee7a6ab46","submission_id":"fb3a3de3-400d-4c72-b6bc-785b692557c6","submission_revision_id":"25d87378-8d12-4b05-9df3-5a0581faa633","builder":"builder-01","status":"active","claimed_at":"2026-10-15T14:39:41.640979Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null}},"revision_is_current":true}