1. The Political Economy of Discrimination: Modelling the Spread of Preferential Trade Agreements Mark S. Manger Assistant Professor McGill University mark.manger@mcgill.ca

3. What explains the geographic variation in the spread of PTAs? Research Question

4. Milner (1997), Chase (2003, 2005): Multinational firms seek greater economies of scale through PTAs. Problem: Suggest no PTAs in Asia Pacific Chase (2005): PTAs to facilitate regional production sharing. Problem: Predicts PTAs with China, not ASEAN Mansfield, Milner, Rosendorff (2002): Democratic Countries are more likely to sign PTAs. Problem: Everybody’s doing it now. Current Knowledge: Bottom-up Explanations

5. Grieco (1997): Capabilities shift hypothesis; disadvantaged countries will shun PTAs with rising powers. Problem: Opposite of what we observe. Mansfield and Reinhardt (2003): Growing WTO membership creates friction; more PTAs induce states to likewise sign agreements. Problem: Leaves geographic pattern of PTAs unexplained. Current Knowledge: Top-down Explanations

6. Baldwin’s (1996) predicts regional spread of PTAs. Countries join agreements because they fear trade diversion. Problems: trade diversion is not evident complex network of PTAs does not conform to expectations. Countries rarely join existing PTAs. Current Knowledge: Domino theory of regionalism

7. Countries will sign PTAs when their neighbours are doing so. Baldwin hypothesis: trade diversion leads countries to join existing PTAs with neighbours Existing PTA not open to expansion or unattractive: Excluded countries form alternative PTAs with other proximate countries Competition for export markets or FDI: Developing countries sign PTAs when their neighbours are gaining preferential access to major markets Spatially Dependent PTAs

8. First-cut at only modelling geographic proximity Undirected dyad-year framework with binary dependent variable DV: All reciprocal PTAs 1960-2004, not counting partial scope agreements Estimators: Familiar logit with cubic splines; Bayesian MCMC W= row-standardized spatial weight matrix of the dependent variable at t-1 divided by distance Model

9. Economic model: GDP per capita for i and j GDP per capita j Difference in GDP Distance between i and j Bilateral trade Political economy variables: Spatial weights in Wy Trade dependence i on j Trade dependence j on i Controls: Alliance Democracy i and j Multilateral trade round underway New dispute with 3rd party Dispute loss with 3rd party Hegemony PTA density and PTA density squared Number of WTO members Trade partner PTA coverage i Trade partner PTA coverage j Variables

11. Space is not just geography: explore similarity measures like GDP/cap, export profiles, trade links. Develop appropriate spatial lag estimator for binary DV panel data Computational challenges: R is sloooow Future research avenues