accesses to clean water. The evidence of propensity score misspecification is weaker when using the KS$_{n}$ test statistic (2.9). Spec2 , on the other hand, is not rejected for any outcome at the usual significance levels, using either CvM$_{n}$ or KS$_{n}$ test statistic. Thus, our tests suggests that Spec2 should be preferred when analyzing per capita CO$_{2}$, deforestation and energy depletion, whereas for urban and rural water access, our tests do not favor either specification. Table 4: Effect of GATT/WTO membership on environmental quality Note: Spec 1 and Spec 2 are different specifications of the propensity score. ̂ ATE$_{n}$ and ̂ ATT$_{n}$ are the estimators for ATE and ATT in (4.3) and (5.1), respectively, but with observations with estimated propensity score outside [0 . 05 , 0 . 95] trimmed. Standard errors are in parenthesis, and p -values in brackets. “ CvM$_{n}$ ” and “ KS$_{n}$ ” respectively stand for the bootstrapped p -values of our proposed Cram´er-von Mises and Kolmogorov-Smirnov tests based on 100,000 bootstrap draws. See the main text for further details. Per capita CO$_{2}$ Deforestation Energy Depletion Rural water access Urban water access Spec 1 Spec 2 Spec 1 Spec 2 Spec 1 Spec 2 Spec 1 Spec 2 Spec 1 Spec 2 ̂ ATE$_{n}$ -1.29 -1.00 0.26 0.34 -3.35 -3.39 3.07 2.89 -5.21 -4.62 (0.58) (0.49) (0.20) (0.21) (1.35) (1.38) (4.84) (4.79) (3.75) (3.72) [0 . 025] [0 . 039] [0 . 203] [0 . 105] [0 . 013] [0 . 014] [0 . 526] [0 . 547] [0 . 165] [0 . 213] ̂ ATT$_{n}$ -0.81 -0.56 0.14 0.22 -2.16 -1.62 1.74 1.33 1.74 -3.34 (0.68) (0.59) (0.20) (0.21) (1.30) (1.34) (5.02) (4.98) (4.19) (4.16) [0 . 234] [0 . 338] [0 . 500] [0 . 287] [0 . 097] [0 . 228] [0 . 730] [0 . 790] [0 . 679] [0 . 422] CvM$_{n}$ 0.01 0.28 0.01 0.45 0.01 0.35 0.53 0.26 0.49 0.23 KS$_{n}$ 0.12 0.24 0.17 0.57 0.12 0.43 0.70 0.52 0.63 0.28 Next we comment on the consequences of propensity score misspecification. For per capita CO$_{2}$ , our results suggest that the overall effect of GATT/WTO membership on emissions is negative and statistically significant at the 5% level under both propensity score specifications. On the other hand, we find the effect of GATT/WTO membership on per capita CO$_{2}$ is not statistically significant among the treated sub-population using either specification. In terms of point estimates, however, there are important differences. For example, the AT E point estimate under Spec1 (misspecified propensity score) is 30% higher (in absolute terms) than under Spec2 . Note that the 0 . 3 difference in AT E represents roughly 8% of the overall per capita CO$_{2}$ emissions. When we analyze the effect of GATT/WTO on deforestation and energy depletion, our re- sults again highlight the consequences of propensity score misspecifications. We find that the AT E point estimate for the effect of GATT/WTO membership on deforestation is 30% larger under Spec2 than under Spec1 , and the AT T point estimate for the effect of GATT/WTO membership on energy depletion is 25% smaller under Spec2 than under Spec1 . Such large differences are economically significant, as the 0.08 difference in AT Es on deforestation repre- sents nearly 12% of the mean annual deforestation, and the 0.46 difference in AT T s on energy 28