Another potential source of bias in our results could lie in the importance of cross country investments in the form of _Foreign Direct Investments_ . In table 8, we investigate the robustness of our findings to the inclusion of FDI links using UNCTAD’s data. We find that accounting for cross-country investments only reinforces the specific role of trade in intermediate inputs in the increase of GDP comovement within the country-pairs included in our sample. However, because the coverage of such data is limited, it is important to keep in mind that the sample is different than in previous analysis – see table 1 for an overview of data coverage for each country pair. Over and beyond the role of Global Value Chains, our results highlight the negative but insignificant relationship between Foreign Direct Investments with GDP comovement.

**Table. 8.** The impact of financial integration: Foreign Direct Investment

|||corr|GDP<sup>_HP_</sup>|||corr|GDP<sup>_BK_</sup>|||corr|∆GDP||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|ln(_TP_)|**0.121**<sup>_∗∗_</sup><br>|**0.161**<sup>_∗∗_</sup><br>|||0.095<br>|**0.133**<sup>_∗∗_</sup><br>|||_−_0.001<br>|0.053<br>|||
||(0.060)|(0.068)|||(0.061)|(0.068)|||(0.059)|(0.065)|||
|ln(_TPI_+_K_)|||**0.179**<sup>_∗∗∗_</sup>|**0.198**<sup>_∗∗∗_</sup>|||**0.169**<sup>_∗∗∗_</sup>|**0.183**<sup>_∗∗∗_</sup>|||0.078|**0.108**<sup>_∗_</sup>|
||||(0.059)|(0.068)|||(0.060)|(0.068)|||(0.058)|(0.065)|
|ln(_TPf inal_)|||_−_0.108<sup>_∗∗_</sup>|_−_0.079|||_−_0.128<sup>_∗∗_</sup>|_−_0.094<sup>_∗_</sup>|||_−_0.111<sup>_∗∗_</sup>|_−_0.077|
||||(0.050)|(0.054)|||(0.051)|(0.054)|||(0.049)|(0.051)|
|ln(_FI_)||_−_0.021||_−_0.021||_−_0.020||_−_0.020||_−_0.021||_−_0.022|
|||(0.017)||(0.017)||(0.017)||(0.017)||(0.017)||(0.017)|
|_thirdEX_|**0.868**<sup>_∗∗_</sup><br>(0.401)|**1.293**<sup>_∗∗∗_</sup><br>(0.430)|**0.910**<sup>_∗∗_</sup><br>(0.400)|**1.259**<sup>_∗∗∗_</sup><br>(0.432)|**0.883**<sup>_∗∗_</sup><br>(0.408)|**1.311**<sup>_∗∗∗_</sup><br>(0.432)|**0.930**<sup>_∗∗_</sup><br>(0.406)|**1.276**<sup>_∗∗∗_</sup><br>(0.434)|**1.505**<sup>_∗∗∗_</sup><br>(0.396)|**1.800**<sup>_∗∗∗_</sup><br>(0.413)|**1.529**<sup>_∗∗∗_</sup><br>(0.395)|**1.758**<sup>_∗∗∗_</sup><br>(0.415)|
|_thirdIM_|0.246|0.353|0.282|0.372|0.073|0.204|0.109|0.219|_−_0.160|_−_0.104|_−_0.144|_−_0.106|
||(0.475)|(0.503)|(0.472)|(0.501)|(0.483)|(0.506)|(0.478)|(0.503)|(0.469)|(0.483)|(0.466)|(0.481)|
|CP FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|TW FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|_N_<br>|1,062|928|1,062|928|1,062|928|1,062|928|1,062|928|1,062|928|
|R<sup>2</sup>|0.472|0.480|0.480|0.485|0.467|0.479|0.478|0.485|0.501|0.515|0.508|0.519|

_Notes: ∗_ p _<_ 0.1; _∗∗_ p _<_ 0.05; _∗∗∗_ p _<_ 0.01. In parenthesis: std. deviation.

# **3.6 Other GVC measures**

Recent advances in data collection and theoretical decomposition of trade flows have shown the various ways of measuring GVC participation.<sup>22</sup> In this paper, we use Borin and Mancini (2019), which proposes a new toolkit for value-added accounting of trade flows at aggregate, bilateral and sectoral level. As in Koopman et al. (2014), trade flows are decomposed into the components described in figure 5.

22In particular, see Bems et al. (2011) and Johnson (2018) 19