{
 "record_id": "53a228745dc9a32b1002f59f1be59cdca85e461e",
 "eligible": false,
 "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.",
 "study": {
  "title": "Variance analysis and linear regression: Exploring the impact of location factors on the average logarithmic price of pre-owned housing in Shenzhen",
  "year": 2024,
  "doi": "10.54254/2753-8818/39/20240598",
  "country": "China",
  "region_city": "Shenzhen (10 central administrative districts)",
  "sample_start": null,
  "sample_end": null,
  "property_type": "condo_apartment",
  "price_type": "listing",
  "data_source": "3,000 simulated data points (random noise added), nominally based on second-hand housing data from real estate companies in Shenzhen",
  "document_type": "conference",
  "estimators": ["OLS"],
  "spatial_method": "none (district dummies)",
  "time_fe": false,
  "location_fe": true,
  "se_type": "OLS",
  "n_obs_total": 3000,
  "ai_methods": [],
  "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."
 },
 "models": [],
 "coefficients": []
}