1. Interdependence of Preferential Economic Policies across Subjects Peter Egger* & Georg Wamser * ETH Zürich, CEPR Workshop on PTAs and the WTO: A New Era WTO, November 04, 2010

2. Motivation Many Economic Integration Agreements affect services; directly or indirectly: Some Goods Trade Agreements (customs unions; free trade areas; single market programme) Specific Service Trade Agreements under auspices of WTO (economic integration agreements; GATS commitments) Bilateral Investment Treaties Bilateral Tax Treaties Currency Unions including Pegs

3. A Snapshot of EIAs for 2005 Type of agreement% of pairs GTA11.60 STA11.62 DTT20.54 BIT6.27 CUP2.73 Altogether, there are 124 countries and 7,873 pairs.

4. A Snapshot of EIAs for 2005 Countries with/and GTASTABITDTTCUP None GTA STA5.5 BIT1.91.6 DTT6.04.45.3 CUP0.9 0.41.4 None 3.85.50.510.11.266.5

5. What’s Behind That Simple Table Reality is a jungle of EIAs (Spaghetti Bowl in 5-dimensional space): 2 5 =32 combinations possible The following ones are most frequent: AgreementsFrequency (All Years?2005) GTAGTA STASTA BITBIT DTTDTT CUPCUP # of pairs% of all EIAs 000005,23866.53 0010080010.16 010004295.45 100003003.81 001102573.26

6. Questions Determinants of each type of EIA (economic fundamentals)? How is membership correlated given fundamentals? What are consequences of EIAs and their combination? Which outcomes are affected?

7. This project Step 1 – Endogenous selection into EIAs: Estimate probability of a country to select itself into individual agreements and combinations thereof (multiple treatment selection) Step 2 – Estimate treatment effects from endogenous selection into agreements and their combinations on:  Goods trade  Services trade  FDI

8. Some data Outcomes (bilateral): Trade in goods Trade in services Stocks of foreign direct investment Sample: 124 countries (124  123 pairs) 16 years (1990-2005)

9. Goods Trade Inside and Outside Countries with/and GTASTABITDTTCUP None else GTA STA 4.75 98.2 BIT 5.94 100 6.22 100 DTT 5.67 99.4 6.17 99.3 5.57 98.8 CUP 5.80 98.8 7.20 98.3 5.72 100 6.42 99.6 None else 1.28 89.0 -.087 89.5 4.81 96.4 4.12 98.2 1.25 97.2 -.377 71.6 Means: log exports (top) and % of exports>0 (bottom).

10. Service Trade Inside and Outside Countries with/and GTASTABITDTTCUP None else GTA STA 5.93 17.3 BIT 4.33 32.0 4.72 26.7 DTT 5.73 20.9 5.90 24.3 4.09 23.9 CUP 6.10 36.5 6.10 49.0 3.41 29.4 5.48 33.2 None else 3.11 0.52 0000 4.14 10.6 4.42 9.5 2.34 4.4 2.26 0.97 Means: log exports (top) and % of exports>0 (bottom).

11. FDI Stocks Inside and Outside Countries with/and GTASTABITDTTCUP None else GTA STA 5.67 39.1 BIT 4.13 46.2 5.01 32.3 DTT 5.97 43.9 5.95 47.4 4.30 40.2 CUP 6.56 51.0 6.56 68.5 3.82 36.97 5.62 51.24 None else 2.39 7.4.620 1.8 4.55 33.7 4.46 27.3 3.61 11.9 2.09 3.5 Means: log FDI (top) and % of FDI>0 (bottom).

12. Summary Statistics for Outcome OutcomeMeanStd.Dev.Pairs Goods trade (US$).7514.12 98,899 P(goods trade>0).779.415127,019 Service trade (US$)4.002.343,548 P(service trade>0).083.169120,964 FDI stocks (US$)3.763.5310,538 P(FDI stocks>0).083.276126,859 Values are expressed in logs.

13. Correlation Coefficients for Outcome Outcome (binary)(G)(S)(F) Goods trade (G)1.00-- Service trade (S)0.141.00- FDI stocks (F)0.100.161.00 Outcome (logs)(G)(S)(F) Goods trade (G)1.00-- Service trade (S)0.841.00- FDI stocks (F)0.810.781.00

14. Multivariate Probit Regressions

16. Correlation of Disturbances Countries with/and GTASTADTTBITCUP GTA STA.460 DTT.092.025 BIT-.064-.095.478 CUP.031.079.024.003

17. Outline of work for the summer Estimation of treatment effects on outcome by propensity score matching: For goods trade, services trade, FDI stocks each: Propensity of positive outcome (ext. margin) Log level (int. margin) Using propensity score matching for multiple treatments (and estimated propensities from multivariate probit)

18. Estimating ATTs 32 EIA combinations (treatments) possible More than an economist can digest and more than the econometrician can estimate: Of the 32 ATTs, 10 are based on more than 1,000 units both in the treatment and control group Next table focuses on the ATTs of the most frequent combinations of “pills taken”

19. Average Treatment Effects on the Treated (ATTs) TreatmentControlsG-tradeS-tradeFDI GTAGTA STASTA DTTDTT BITBIT CUPCUP GTAGTA STASTA DTTDTT BITBIT CUPCUP PLogP P 0010000000.0612.22.0571.71.1611.570 0100000000.090.226-.003---.016-1.24 1000000000.1311.80.000-.061.037.970 0011000000.0362.90.1881.10.2361.67 1100000000.1862.67.0045.26.1571.60 Significance: ~ 15%; ~ 10%; ~ 5%; ~ 1%; ~ insignificant.

20. Foregone Trade and FDI Suppose every pair would use all modes corresponds to Average Treatment Effect (ATE) of “11110” relative to “00000” World effects (for average/randomly drawn pair) of MarginG-tradeS-tradeFDI Extensive.120.474.269 Intensive4.441.462.53

21. Conclusions Estimated effects pertain to long run Short run (conditional on initial state) is also accessible In general: standard errors larger for intensive margin than for extensive margin (less observations). Int.marg. effects relatively large but –Estimates pertain mainly to DC-with-LDC. –Have large standard errors.

22. Conclusions Clearly: more is better for both ext. and int. margin of outcome Ext.-margin of S-trade and FDI depend more on BIT and DTT than on GTA and STA Policy makers who want to stimulate a mix of G-trade, S-trade, and FDI will have to pursue a mix of GTA-STA and BIT-DTT