Replication files for GVCs and the Endogenous Geography of RTAs
Description
We compare the observed RTAs to the probability threshold optimizing the joint prediction of signed and unsigned agreements, and derive a counterfactual RTA geography by signing predicted but unsigned agreements. To assess the trade and welfare consequences of signing unsigned agreements in General Equilibrium, we follow Anderson, Larch & Yotov (2018) and use a General Equilibrium Poisson Pseudo Maximum Likelihood (GEPPML) method to solve the system of equations associated with the model. We proceed by estimating a probability model using data over the 1990-2014 period; the fiveyear lag for covariates implies that we will consider agreements that were signed between country pairs over the 1995-2014 period, adding to the usual controls for the indirect involvement of the country pair in the fragmentation of value chains. We evaluate model goodness-of-fit by considering the probability cut-off that provides the best percentage of correctly-predicted events (a countrypair being, or not, members at a given date of an RTA: RTA=1 and RTA=0).: the optimal cut-off probability maximizes the percentages of true positives and true negatives. We focus on the mis-classified RTAs that are classified as FP from the probabilistic model are be used in a structural gravity system to evaluate the welfare changes associated with alternative sets of trade agreements
Files
Steps to reproduce
Read the details of the methodlogy here: http://www.lionel-fontagne.eu/uploads/9/8/3/3/98330770/fs_regionalism_dec_2020.pdf