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 14 / 23 PLOS One Trade agreement, climate change and geography importer countries. The remoteness in exporter countries seems with higher magnitudes that cause a reduction in the export level and probability than importer countries. More interestingly, the effect of a trade agreement is also investigated on bilateral exports along with the non-linear and simultaneous effect of economic GDP. The outcomes are reported in Table 6. A trade agreement has a remarkable impact on bilateral exports between the trading partners. More specifically, trade agreements provide trading partners with ben- efits in the form of nominal (i.e., tariff) or quantity (i.e., imposing quantity restrictions). The outcomes reveal that a 1% increase in PTA upsurges bilateral exports by 11.4% in the case of domestic geographic countries. On the contrary, 14% of bilateral exports are increased due to a 1% change in trade agreements for the partner geographic countries (importers). This suggests that trade agreements between the trading partners reduce the tariff or enhance export quantity. Consequently, bilateral exports have increased over time. However, trade agreements are diverse in nature, which can have a substantial impact on bilateral exports due to different trade mechanisms. Furthermore, trade agreements are considered based on a geographic-oriented environment where production and consumption have contrarily Table 6. Structural Gravity Model. Exporting Countries Importing Countries (1) (2) (3) (4) (5) (6)

VARIABLES Dependent Variable: Exportsijt CO2 -0.355 0.376** 0.327*** 0.167 0.352*** 0.069** (0.245) (0.151) (0.054) (0.119) (0.046) (0.030) Physical-distance 0.145 0.330*** 0.428*** 0.186 0.379*** 0.249*** (0.201) (0.121) (0.010) (0.143) (0.050) (0.007) Lndistance -0.891*** – – -1.239*** – – (0.176) – – (0.168) – – Access to Ocean 0.751*** – 0.622 3.006*** 1.553*** 1.308*** (0.044) – (0.386) (0.039) (0.282) (0.032) Common border 2.627*** 0.117 0.742*** 1.497*** 0.704*** 0.854*** (0.401) (0.201) (0.035) (0.283) (0.166) (0.034) LnGDP -0.107 – – 0.572*** – – (0.094) – – (0.192) – – Lntariff -0.124 -0.214*** -0.189*** -0.340*** -0.328*** -0.257*** (0.076) (0.056) (0.011) (0.071) (0.053) (0.011) Lnpopulation -0.097 -0.122*** -0.089*** 0.314*** 0.104*** 0.122*** (0.511) (0.030) (0.009) (0.077) (0.027) (0.008) Remoteness – -3.875 -6.335*** – 0.002*** 0.001*** – (3.875) (1.970) – (0.030) (1.120) Lambda – 0.242 – – 0.740*** – – (0.381) – – (0.275) – – – – – – – Constant 24.970*** -8.564 -8.226 -3.486 1.294 -8.327*** (8.947) (13.700) (6.104) (2.728) (1.941) (0.398) Observations 44436 44436 44436 44436 44436 44436 R-squared 0.145 0.104 – 0.449 – – Number of exporter – 46 46 – 46 46 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.t006