Climate change, geography and trade agreements: A perspective of Asian bilateral trade

PLOS One | https://doi.org/10.1371/journal.pone.0320363 April 25, 2025 12 / 23 PLOS One Trade agreement, climate change and geography The authors [39] also documented their findings, the geographic structure of Ricard- ian into the general equilibrium, and the proposed simple structural equations for bilateral trade, which are relevant to absolute and comparative advantages and geographical barriers for trade. However, they did not cover the geographic aspect as we did. The marginal export level and the marginal probability of emissions are found significant and positive concerning physical distance. Similarly, the marginal export level and the marginal export probability of physical distance have a positive impact, which is less than domestic geography. Variables such as access to an ocean and a common border have a significant and strong impact on bilateral exports and their probability among the Asian countries. For instance, Central Asia, West Asia, and South Asia, excluding Sri Lanka, the Maldives, China, and Russia, have more common borders and access to an ocean. The study concluded that all geographic factors and the GDP are complementary to one another in determining the export level and its probability between trading partner countries under both dimensions. Table 4. Simultaneous Effects of Geographical Factors on Asian’s Bilateral Exports. Location Exporting Countries Importing Countries Estimation GDP Interaction Geographical Interaction GDP Interaction Geographical Interaction (1) (2) (3) (4) (5) (6) (7) (8) Dependent Variable: Exportijt

CO2 5.281** 4.033*** 4.372*** 2.755*** -0.348 0.858 1.554** 0.494 * (2.437) (0.695) (1.276) (0.316) (1.132) (0.626) (0.638) (0.276) Physical-distance 0.969 * 0.794*** 4.498*** 3.024*** 0.102 0.539*** 1.333** 0.519 * (0.512) (0.0879) (1.342) (0.332) (0.230) (0.0744) (0.650) (0.288) Lndistance -0.254*** -0.120*** -0.265*** -0.125*** -0.394*** -0.193*** -0.472*** -0.201*** (0.062) (0.016) (0.051) (0.016) (0.057) (0.016) (0.053) (0.016) Access to Ocean 1.168*** 0.641*** 1.218*** 0.658*** 1.769*** 1.447*** 2.346*** 1.460*** (0.310) (0.033) (0.231) (0.033) (0.421) (0.032) (0.364) (0.032) Common Border 0.425 0.634*** 0.437** 0.619*** 0.175 0.607*** 0.397*** 0.573*** (0.275) (0.040) (0.195) (0.039) (0.168) (0.039) (0.141) (0.039) LnGDP 2.659** 2.062*** 0.215*** 0.089*** 0.147 0.951*** 0.586*** 0.340*** (1.246) (0.327) (0.043) (0.014) (0.608) (0.294) (0.087) (0.013) Lntariff -0.050*** -0.032*** -0.052*** -0.033*** -0.025*** -0.018*** -0.031*** -0.017*** (0.016) (0.002) (0.011) (0.002) (0.005) (0.002) (0.005) (0.002) Lnpopulation -0.202*** -0.086*** -0.223*** -0.095*** 0.044** 0.056*** 0.056*** 0.039*** (0.044) (0.010) (0.038) (0.010) (0.021) (0.009) (0.017) (0.009) CO2 * GDP -0.183** -0.146*** 0.025 -0.030 (0.089) (0.026) (0.043) (0.024) PhyDist*GDP -0.018 -0.016*** -0.002 -0.020*** (0.013) (0.003) (0.008) (0.002) CO2 * PhyDist -0.325*** -0.217*** -0.105** -0.041 * (0.102) (0.026) (0.053) (0.023) Lambda 1.314** 1.377*** 0.755** 1.292***

(0.603) (0.430) (0.380) (0.323) Constant -63.360 * -59.750*** -46.940*** -39.170*** 6.944 -26.900*** -20.560** -16.190*** (35.420) (8.544) (17.380) (3.905) (16.390) (7.590) (9.317) (3.410) Observations 44436 44436 44436 44436 44436 44436 44436 44436 Note: the term ***, ** and * denote that significance level at 1%, 5% and 10% respectively. Ln indicates logarithm for variables. https://doi.org/10.1371/journal.pone.0320363.t004