Open Access

Property Values, Water Quality, and Benefit Transfer: A Nationwide Meta-analysis

Dennis Guignet, Matthew T. Heberling, Michael Papenfus and Olivia Griot

Article Figures & Data

  • Table 1

    Mean Elasticity Estimates of the Three Most Frequently Examined Water Quality Measures

    Water Quality MeasureUnweighted Mean (1)Cluster-Weighted Mean (2)Variance-Adjusted Cluster-Weighted Mean (3)RES Cluster-Adjusted Weighted Mean (4)nStudiesClusters (Kd)
    Chlorophyll a (mg/L)
    Waterfront0.737*
    [−0.044, 1.517]
    0.324*
    [−0.036, 0.684]
    −0.023***
    [−0.028, −0.019]
    −0.026***
    [−0.031, −0.021]
    1833
    Nonwaterfront within 500 m0.005
    [−0.201, 0.211]
    0.01
    [−0.085, 0.105]
    0.008***
    [0.005, 0.010]
    0.009***
    [0.006, 0.012]
    1833
    Fecal Coliform (count per 100 mL)
    Waterfront−0.018***
    [−0.026, −0.011]
    −0.037
    [−0.088, 0.014]
    −0.028
    [−0.079, 0.023]
    −1.3E-4***
    [−1.8E-4, −0.7E-4]
    3644
    Nonwaterfront within 500 m−0.020*** [−0.034, −0.006]−0.058* [−0.127, 0.010]−0.061*
    [−0.129, 0.008]
    −0.052**
    [−0.096, −0.008]
    2033
    Water Clarity (Secchi disk depth, m)
    Waterfront0.158
    [−6.099, 6.416]
    0.206
    [−16.575, 16.987]
    0.191
    [−16.590, 16.972]
    0.109***
    [0.099, 0.118]
    1771866
    Nonwaterfront within 500 m0.028***
    [0.020, 0.036]
    0.042***
    [0.025, 0.059]
    0.041***
    [0.024, 0.058]
    0.026***
    [0.017, 0.034]
    83619
    • Note: Confidence intervals at the 95% level are displayed in brackets. Only elasticity estimates pertaining to the three most commonly examined water quality measures in the hedonic literature are presented, but the full suite of mean elasticity estimates are presented in Appendix B.2. We present the respective units for each water quality measure in parentheses just as a reference but emphasize that the elasticity estimates are unit-less. RES, random effect size.

    • * p < 0.1;

    • ** p < 0.05;

    • *** p < 0.01;

  • Table 2

    Descriptive Statistics of Observations Pertaining to Water Clarity

    VariableMeanStd. Dev.Min.Max.
    Dependent Variable
    Elasticity0.11670.2543−0.64781.7198
    Study Area/Commodity Variable
    Waterfronta0.68080.467101
    Mean clarity (Secchi disk depth, m)2.341.970.386.45
    Lake or reservoira0.56150.497201
    Estuarya0.43850.497201
    Waterbody sizeb (sq. km)6.88465.31560.000220.8858
    Median income (thousands, 2017$)59.07814.14437.86591.174
    College degree (% population)0.13660.04140.07680.2734
    Population density (households/sq. km)49.9158.381.41227.96
    Mean house price (thousands, nominal $)211.314131.34131.287675.364
    Northeasta0.28850.453901
    Midwesta0.19230.394901
    Southa0.48460.500701
    Westa0.03460.183201
    Methodological Variable
    Elasticity variance1,228.15918,704.529.03E-06301,448.5
    Unpublisheda0.15000.357801
    Not in situ measurea0.61150.488301
    Other water quality variablesa0.21920.414501
    Assessed valuesa0.05380.226101
    Study time period (years)10.273.82324
    Time trend (0=1994 to 20=2014)8.596.17020
    No spatial methodsa0.38080.486501
    Double-loga0.43080.496101
    Linear-loga0.30770.462401
    Lineara0.03850.192701
    Log-lineara0.22310.417101
    • Note: Unweighted descriptive statistics are presented for n = 260 elasticity estimates in the meta-dataset per-taining to water clarity. Estimates are based on 18 primary hedonic studies, corresponding to 66 study-housing market clusters.

    • a Independent variables that are dummy variables.

    • b Size of the waterbody (or waterbodies) examined in the primary studies was only available for n = 79 of the 260 observations in the meta-dataset pertaining to water clarity. If multiple waterbodies were examined in the primary study hedonic regression models, the average waterbody size is reported.

  • Table 3

    Variance-Adjusted Cluster-Weighted Least Squares Meta-regression Results

    Variable(1)(2)(3)(4)(5)(6)
    Waterfronta0.1457***
    (0.046)
    0.0170
    (0.023)
    −0.0677
    (0.052)
    0.1010**
    (0.039)
    −0.1126 (0.086)0.1251***
    (0.042)
    Midwesta−0.1056
    (0.087)
    −0.1488*
    (0.082)
    −0.2059 (0.132)−0.2561***
    (0.096)
    −0.3156***
    (0.116)
    Southa−0.2248***
    (0.076)
    −0.2797***
    (0.084)
    −0.3209*
    (0.171)
    −0.2889***
    (0.108)
    −0.3945***
    (0.131)
    Westa−0.1803
    (0.120)
    −0.1803
    (0.121)
    −0.1747
    (0.147)
    −0.3745**
    (0.180)
    −0.3772**
    (0.174)
    Estuarya−0.0401**
    (0.016)
    −0.1223***
    (0.039)
    Waterfront × estuary0.1274**
    (0.055)
    0.1721*
    (0.088)
    Mean clarity0.0375
    (0.030)
    0.0799**
    (0.035)
    Waterfront × mean clarity−0.0684**
    (0.029)
    −0.1061**
    (0.050)
    Elasticity variance8.97E-07***
    (1.52E-07)
    6.26E-07**
    (2.56E-07)
    6.26E-07**
    (2.57E-07)
    5.10E-07
    (3.30E-07)
    6.02E-07**
    (2.56E-07)
    5.02E-07
    (3.65E-07)
    Time trend0.0183***
    (0.006)
    0.0223***
    (0.006)
    Linear-loga0.1973
    (0.161)
    0.1987
    (0.159)
    Lineara0.2198**
    (0.086)
    0.1159
    (0.083)
    Log-lineara−0.0020
    (0.008)
    −0.0059
    (0.008)
    Constant0.0414*
    (0.021)
    0.2474***
    (0.077)
    0.3320***
    (0.090)
    0.3092*
    (0.182)
    0.1681
    (0.122)
    0.0493
    (0.180)
    Observations260260260260260260
    Adjusted R-squared0.0800.1480.1480.1560.1700.176
    • Note: The dependent variable is the home price elasticity with respect to water clarity (Secchi disk depth). Clustered-robust standard errors are in parentheses and are clustered according to the K = 66 study-housing market combinations. Weighted least squares regressions are estimated using the “regress” routine in Stata 16 and defining analytical weights equal to the variance-adjusted cluster weights (see equation [3]).

    • a Independent variables that are dummy variables.

    • * p < 0.1;

    • ** p < 0.05;

    • *** p < 0.01;

  • Table 4

    RES Cluster-Adjusted Weighted Least Squares Meta-regression Results

    Variable(1)(2)(3)(4)(5)(6)
    Waterfronta0.0828***
    (0.018)
    0.0374*
    (0.022)
    −0.0356
    (0.050)
    0.0715*
    (0.036)
    0.0080
    (0.044)
    0.0829**
    (0.031)
    Midwesta−0.0204
    (0.040)
    −0.0462
    (0.036)
    −0.0475
    (0.048)
    −0.1565***
    (0.032)
    −0.1476***
    (0.039)
    Southa−0.0833***
    (0.031)
    −0.1451***
    (0.043)
    −0.1096
    (0.081)
    −0.2600***
    (0.037)
    −0.2495***
    (0.044)
    Westa−0.0607
    (0.097)
    −0.0607
    (0.098)
    −0.0595
    (0.107)
    −0.3200***
    (0.111)
    −0.4216***
    (0.077)
    Estuarya−0.0181
    (0.020)
    −0.0534***
    (0.020)
    Waterfront × estuary0.1019*
    (0.055)
    0.0582
    (0.050)
    Mean clarity0.0247
    (0.037)
    0.0601***
    (0.022)
    Waterfront × mean clarity−0.0332
    (0.032)
    −0.0317
    (0.024)
    Elasticity variance2.22E-05
    (2.18E-05)
    2.05E-05
    (2.04E-05)
    2.01E-05
    (2.01E-05)
    2.01E-05
    (2.01E-05)
    1.91E-05
    (1.93E-05)
    1.86E-05
    (1.89E-05)
    Time trend0.0121***
    (0.002)
    0.0158***
    (0.002)
    Linear-loga−0.0371
    (0.040)
    −0.0953*
    (0.049)
    Lineara0.0807
    (0.091)
    0.0493
    (0.052)
    Log-lineara−0.0023
    (0.005)
    −0.0001
    (0.005)
    Constant0.0257
    (0.016)
    0.1025***
    (0.031)
    0.1755***
    (0.055)
    0.1086
    (0.098)
    0.1577***
    (0.034)
    0.0034
    (0.063)
    Observations260260260260260260
    Adjusted R-squared0.1010.1460.1590.1480.2010.222
    • Note: The dependent variable is the home price elasticity with respect to water clarity (Secchi disk depth). Clustered-robust standard errors are in parentheses and are clustered according to the K = 66 study-housing market combinations. Weighted least squares regressions are estimated using the “regress” routine in Stata 16 and defining the analytical weights equal to the random effect size (RES) cluster-adjusted weights (see Section 2).

    • a Independent variables that are dummy variables.

    • * p < 0.1;

    • ** p < 0.05;

    • *** p < 0.01;

  • Table 5

    Out-of-Sample Transfer Error: Median Absolute Value of the Percent Difference in Predicted Elasticities

    Weighing SchemeWeighted MeanWLS 1WLS 2WLS 3WLS 4WLS 5WLS 6
    Comparison with Synthetic Observations for Excluded Cluster (n=85)
    Variance-adjusted cluster (%)92.590.587.0108.193.9119.0104.2
    RES cluster-adjusted (%)76.076.382.789.489.490.778.9
    Comparison with Excluded Cluster Observations (n=260)
    Variance-adjusted cluster (%)130.5127.589.8100.599.9120.3121.4
    RES cluster-adjusted (%)82.783.483.189.590.493.787.2
    • Note: The out-of-sample transfer error is calculated by iteratively leaving out sets of observations pertaining to each of the K = 66 clusters, estimating the model with the remaining clusters ’ observations, and calculating the predicted elasticities and resulting transfer error for the synthetic observation or the actual observations corresponding to the excluded cluster. RES, random effect size; WLS, weighted least squares.