1{2 "record_id": "53a228745dc9a32b1002f59f1be59cdca85e461e",3 "eligible": false,4 "exclusion_reason": "Data are not an empirical sample: the paper states (Section 2.1, p. 3) that 'the report obtained 3,000 simulated valid data points by adding random noise'; the provenance of any underlying real listings is not documented. Conference proceeding (student paper). Flag for human review: Tables 4-5 (pp. 7-8) do print OLS coefficients with SE and p-values on log price per m2 (10,000 yuan/m2) for school district (0.273, SE 0.011), sea view (0.452, 0.032), subway (-0.014, 0.018), elevator (0.052, 0.029), renovation (0.033, 0.022), age-band dummies, south orientation (0.009, 0.010) and area in m2 (0.001, SE printed as 0), plus district dummies, but they are estimated on simulated data.",5 "study": {6 "title": "Variance analysis and linear regression: Exploring the impact of location factors on the average logarithmic price of pre-owned housing in Shenzhen",7 "year": 2024,8 "doi": "10.54254/2753-8818/39/20240598",9 "country": "China",10 "region_city": "Shenzhen (10 central administrative districts)",11 "sample_start": null,12 "sample_end": null,13 "property_type": "condo_apartment",14 "price_type": "listing",15 "data_source": "3,000 simulated data points (random noise added), nominally based on second-hand housing data from real estate companies in Shenzhen",16 "document_type": "conference",17 "estimators": ["OLS"],18 "spatial_method": "none (district dummies)",19 "time_fe": false,20 "location_fe": true,21 "se_type": "OLS",22 "n_obs_total": 3000,23 "ai_methods": [],24 "notes": "Theoretical and Natural Science, Proceedings of the 2nd International Conference on Mathematical Physics and Computational Simulation. Dependent variable: log of price per m2 in 10,000 yuan/m2. Model A adj. R2 0.63, Model B (district x school interactions) adj. R2 0.643, residual df 2979/2970."25 },26 "models": [],27 "coefficients": []28}29