About this Dataset

Meta-Dataset For Property Values And Water Quality

We conduct a comprehensive literature review and meta-analysis of studies that examine the effects of water quality on waterfront and non-waterfront housing values. We identify 36 studies that yield 665 observations. The rows of the dataset include each observation from the hedonic studies and the columns include the variables we created from each study (e.g., year of publication, type of publication, water quality measure, location, waterbody type, elasticities).
Organization: U.S. Environmental Protection Agency
Last updated: 2023-10-10T18:52:36.026470
Tags: benefit-transfer, hedonic, lake, meta-analysis, property-value, water-clarity

Tables

Meta-dataset For Property Values And Water Quality

@usgov.epa_gov_meta_for_property_values_and_water_quality_bfc08.meta_dataset_for_property_values_and_water_quality

169.7 kB
665 rows
114 columns

CREATE TABLE meta_dataset_for_property_values_and_water_quality (
  "obsid" BIGINT,
  "studyid" BIGINT,
  "studyname" VARCHAR,
  "studygroup" VARCHAR,
  "specid" BIGINT,
  "specname" VARCHAR,
  "estid" BIGINT,
  "estname" VARCHAR,
  "pubyear" BIGINT,
  "pubtype" VARCHAR,
  "table" VARCHAR,
  "depvar_desc" VARCHAR,
  "depvar_assessed" BIGINT,
  "funcform" VARCHAR,
  "logtype" VARCHAR,
  "wqintrx" VARCHAR,
  "distgradient" VARCHAR,
  "distbuf" BIGINT,
  "distbuf_infer" BIGINT,
  "spatial_fe" VARCHAR,
  "spatial_lag" BIGINT,
  "spatial_auto" BIGINT,
  "sampsize" BIGINT,
  "sample_firstyr" DOUBLE,
  "sample_lastyr" DOUBLE,
  "geog" VARCHAR,
  "state" VARCHAR,
  "sampextent" VARCHAR,
  "hometypes" VARCHAR,
  "avgprice" DOUBLE,
  "avgprice_unit" VARCHAR,
  "census_yr" BIGINT,
  "census_geog" VARCHAR,
  "census_geog_name" VARCHAR,
  "census_fips" VARCHAR,
  "census_inc" DOUBLE,
  "census_totpop" DOUBLE,
  "census_popcol" DOUBLE,
  "census_blk" DOUBLE,
  "census_hisp" DOUBLE,
  "census_tothh" DOUBLE,
  "census_totarea" DOUBLE,
  "northeast" BIGINT,
  "midwest" BIGINT,
  "south" BIGINT,
  "west" BIGINT,
  "waterbody" VARCHAR,
  "wbsize" DOUBLE,
  "wbsizeorig" DOUBLE,
  "wbsize_units" VARCHAR,
  "wbnum" VARCHAR,
  "wbtype" VARCHAR,
  "wqvar" VARCHAR,
  "avgwqvar" DOUBLE,
  "wqvar_units" VARCHAR,
  "wqvar_infer" BIGINT,
  "avgwqrorig" DOUBLE,
  "avgwqrorig_units" VARCHAR,
  "wqvar_type" VARCHAR,
  "num_wqvars" BIGINT,
  "other_wqvars" BIGINT,
  "avghmin" DOUBLE,
  "avgcmax" DOUBLE,
  "avgprctchangepop" DOUBLE,
  "avgdist" DOUBLE,
  "avgdistorig" DOUBLE,
  "avgdistunits" VARCHAR,
  "avgwfdummy" DOUBLE,
  "avgtime" DOUBLE,
  "avgclearlow" DOUBLE,
  "wqdesc_var1" VARCHAR,
  "wqintx_var1" VARCHAR,
  "wqcoef_var1" DOUBLE,
  "wqcoef_se_var1" DOUBLE,
  "wqcoef_t_var1" DOUBLE,
  "wqcoef_sl_var1" DOUBLE,
  "wqcoef_desc_var1" VARCHAR,
  "wqdesc_var2" VARCHAR,
  "wqintx_var2" VARCHAR,
  "wqcoef_var2" DOUBLE,
  "wqcoef_se_var2" DOUBLE,
  "wqcoef_t_var2" DOUBLE,
  "wqcoef_sl_var2" DOUBLE,
  "wqcoef_desc_var2" VARCHAR,
  "wqdesc_var3" VARCHAR,
  "wqintx_var3" VARCHAR,
  "wqcoef_var3" DOUBLE,
  "wqcoef_se_var3" DOUBLE,
  "wqcoef_t_var3" DOUBLE,
  "wqcoef_sl_var3" DOUBLE,
  "wqcoef_desc_var3" VARCHAR,
  "wqdesc_var4" VARCHAR,
  "wqintx_var4" VARCHAR,
  "wqcoef_var4" DOUBLE,
  "wqcoef_se_var4" DOUBLE,
  "wqcoef_t_var4" DOUBLE,
  "wqcoef_sl_var4" DOUBLE,
  "wqcoef_desc_var4" VARCHAR,
  "wqdesc_var5" VARCHAR,
  "wqintx_var5" VARCHAR
);