Table 3: Summary statistics and variable descriptions Variable Mean Standard deviation N Description Per capita CO$_{2}$ 3.82 4.73 232 Carbon dioxide emissions, industrial, in metric tons per capita Deforestation 0.68 1.28 223 Annual deforestation, average percentage change, 1990-1995 Energy depletion 3.13 7.43 223 In percent of GDP, equal to the product of unit resource rents and the physical quantities of fossil fuel energy extracted Rural water access 51.20 27.42 137 Access to clean water, percentage of rural population, 1990-1996 Urban water access 76.28 21.76 140 Access to clean water, percentage of urban population, 1990-1996 GATT/WTO membership 0.78 0.41 232 Member country of GATT/WTO: 1 if member, 0 otherwise Real GDP per capita 7.30 7.47 232 Real (1990) gross domestic product per capita, in thousands of dollars Polity 3.17 6.85 232 Index, ranging from-10 (strongly autocratic) to 10 (strongly democratic) Area per capita 51.6 89.56 232 Land area divided by population Note: Same data used by Millimet and Tchernis (2009). We thank Prof. Millimet for sharing the data with us. Original source is Environmental in- dicators and country-level controls are from Frankel and Rose (2005), whereas GATT/WTO membership data are from Rose (2004). N = number of observations. For further details, see the aforementioned papers. for each outcome subsample. More specifically, for each outcome, we model the probability of a country being a GATT/WTO member ( D = 1 if member, D = 0 otherwise) by a standard Probit model and consider two different specifications: For each of these specifications, we test the null hypothesis Spec1: X includes real per capita GDP, land area per capita, and polity. Spec2: X is defined as in Spec1 but adds pairwise interaction terms between each covariate. against H$_{1}$ , which is simply the negation of H$_{0}$ . Table 4 reports the testing results for each specification, together with normalized IPW estimator for the ATE based on (4.3). We also consider the normalized IPW estimator for the ATT , where w treat 1 ,i = D$_{i}$ , w treat 0 ,i = (1 − D$_{i}$ ) q ( X$_{i}$, ˆ θ$_{n}$ ) / ( 1 − q ( X$_{i}$, ˆ θ$_{n}$ )) , and ¯ w treat d,n is the sample mean of w treat d,i , d = { 0 , 1 } . The associated standard errors and p -values are in parenthesis and brackets, respectively. Following Millimet and Tchernis (2009), we trim observations with estimated propensity score outside the interval [0 . 05 , 0 . 95] to avoid denominators arbitrarily close to zero. Bootstrapped p -values for our proposed specification tests are based on 100,000 bootstrap draws $^{7}$. At the 5% level we find that, based on the CvM$_{n}$ test statistic (2.8), Spec1 is rejected for per capita CO$_{2}$, deforestation and energy depletion, but is not rejected for rural and urban 7 Note that the variables in Spec1 and Spec2 are all functions of the same three covariates: real per capita GDP, land area per capita, and polity. As so, Spec1 and Spec2 have the same information content with respect to the reliability of Assumption 2.1. 27 ̂ ATT$_{n}$ = 1 n n ∑ i $_{=1}$( w treat 1 ,i ¯ w treat 1 ,n − w treat 0 ,i ¯ w treat 0 ,n ) Y$_{i}$, (5.1) H$_{0}$ : ∃ θ$_{0}$ ∈ Θ : E [ D − Φ ( X $^{′}$θ$_{0}$ ) | Φ ( X $^{′}$θ$_{0}$ )] = 0 a.s.,