Theoretical and empirical background

To investigate the effects of foreign policy (herein OCP) on bilateral trade flows, we implement an empirical tool commonly used in the international trade literature:

the structural gravity model. Equation 1 shows the economic intuition derived from Newton’s law with the positive and proportional effect of economic size of trading partners (Y_i, E_j) on bilateral trade (X_ij) and the reverse effect of trade costs (τ_ij).

Indeed, based on the Armington hypotheses about specialization, identical constant elasticity substitution (σ) and the theoretical-consistent background developed by Anderson and van Wincoop (2003), we formulate the following theoretical gravity equation: We estimate a structural gravity model (Head and Mayer, 2014) by taking into account multilateral resistance (Anderson and van Wincoop, 2003) through fixed

25For more details about how the data were derived, see the appendix of Head etal. (2010):

http://strategy.sauder.ubc.ca/head/Papers/erosion.pdf.

26http://minilien.fr/a0sgsa

27http://en.wikipedia.org/wiki/Dates_of_establishment_of_diplomatic_relations_

with_the_People’s_Republic_of_China#cite_note-1and complemented with Mackerras (2001), Taylor (2010), Shinn and Eisenman (2012).

effects²⁸ (country-year and country-pair). This method captures other trade costs across other export and import markets through relative price effects (Pi, Pj). The exclusion of these terms leads to an omission bias with more unobserved trade bar-riers. To the extent that it is very difficult to have price indices for each country of the sample, fixed effects through country-year and country-pair allow for this mul-tilateral resistance to be taken into account even if some variables will be removed according to the fixed effects used (Equations 2-3). We also improve our regressions with a Huber-White estimator to avoid any heteroscedasticity issue and thus to have robust standard errors clustered by country-pair.

Our empirical gravity equations have the following forms:

lnX_ijt =β₀+β₁U N vote_ijt+γ_it+γ_jt+γ_ij +n_t+_ijt (4.2) lnX_ijt=β₀+β₁Diplomacy China_ijt+γ_it+γ_jt+γ_ij +n_t+_ijt (4.3) whereX_ijt is the bilateral export flows betweeni (origin country) andj (destina-tion country) at yeart. Following Baldwin and Taglioni (2006) and Head and Mayer (2014) we include country-year fixed effects (γ_i(j)t), country-pair fixed effects (γ_ij) and time dummies (n_t). _ijt is a random error term satisfying typical assumptions.

OCP is broken into two components: the vote of China’s recognition by the UN in 1971 (U N vote_ijt) and the presence of diplomatic ties between outside countries and China (Diplomacy China_ijt).

We specify the following dummy variables. U N vote_ijt (Table 9) is decomposed according to the nature of the vote (Yes, No, Abstention). U N vote Y es_ijt equals 1 for relationships between countries having voted “Yes” and China for each year since

28The tetrad method (Head et al., 2010) can be used, but this approach is sensitive to the reference countries chosen (Head and Mayer, 2014).

China’s recognition by the UN in 1971, and 0 otherwise. U N vote N o_ijt equals 1 for relationships between countries having voted “No” and China for each year since China’s recognition by the UN in 1971, and 0 otherwise. U N vote Abs_ijtequals 1 for relationships between countries that abstained and China for each year since China’s recognition by the UN in 1971, and 0 otherwise. Diplomacy China_ijt (Table 10) is equal to 1 for relationships between countries and China depending on whether there are diplomatic ties with China, and 0 otherwise. The same specifications are made for the Taiwanese bilateral trade flows concerning these two variables of interest.

We then disaggregate our second variable of interest (Diplomacy China_ijt) across developed (OECD)²⁹ and developing countries (ex-colonies)³⁰ to search for evidence of heterogeneity of diplomatic ties on trade flows according to trading partners of China and Taiwan.

Alternatively, we employ PPML with country-pair fixed effects³¹ (Equations 4-5) to resolve any omission bias with the presence of zero flows in our sample. The log-linear form is unable to handle zero trade flows because the logarithm of zero is undefined, in this respect, PPML is the empirical method most often employed because of its robustness (Santos Silva and Tenreyro, 2006, 2011 ; Gomez Herrera, 2013 ; Fally, 2015). We also correct for any potential endogeneity of political factors with panel data estimation techniques and country-pair fixed effects, as advocated by Baier and Bergstrand (2007).

The following equations are thus estimated, where α_i(j)t captures time-varying monadic variables such as GDP and population of trading partners:

29Europe (EU), North-America, South-America, Asia, Middle-East, Oceania.

30sub-Saharan-Africa (SSA), North-Africa, Asia, South-America

31Country-year fixed effects is a method “computationally burdensome and even impossible to apply in the case of large datasets that include many countries and years. [...] We therefore adopt another solution that consists of capturing these terms (multilateral resistance) with bilateral fixed effects.” (Lavall´ee and Lochard, 2015)

Xijt=β0+β1lnαi(j)t+β2U N voteijt+γij +µt+ijt (4.4) Xijt =β0 +β1lnα_i(j)t+β2Diplomacy Chinaijt+γij +µt+ijt (4.5) We also want to provide evidence of economic diplomacy effects on bilateral trade flows over a specific time period. In other words, we capture the post effects of our variables of interest and then break down all 5 years: 5, 10 and 15 years after the vote on China’s recognition in 1971 and the establishment of diplomatic ties with China. For instance, t5 U N vote Y es_ijt equals 1 for relationships between countries having voted “Yes” and China for the 5 first years since China’s recognition by the UN in 1971, and 0 otherwise. t5 Diplomacy China_ijt equals 1 for relationships between countries having diplomatic ties with China for the 5 first years after the implementation of this diplomatic agreement, and 0 otherwise, etc. This instructive approach allows us to determine whether the effects of these components of the OCP on trade flows vary over time.

4.5 Results

The average effects of these channels (U N vote_ijt, Diplomacy China_ijt) are there-after presented for the two-way trade flows of China and Taiwan. We provide findings for the first component of the OCP over the entire period since the UN vote in 1971 and for the second over the period since the establishment of diplomatic ties. We focus on PPML fixed-effect specifications to avoid misinterpreting the estimated co-efficients by taking zero trade flows into account and to correct heteroscedasticity (Section 4.3).