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;