12.10.2013 Views

PDF, GB, 56 p., 1,3 Mo - Femise

PDF, GB, 56 p., 1,3 Mo - Femise

PDF, GB, 56 p., 1,3 Mo - Femise

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

Ceteris paribus, if the share of intermediates in production is high eg. 80% than<br />

this may be harder to achieve, as it requires more use of domestic intermediates<br />

comprising domestic value added. Hence we would expect a positive correlation<br />

between ROO restrictiveness and the share of intermediates to output. However,<br />

it is important to not that this is only relevant for those industries in which the<br />

value added rule is applied, hence in the regressions we also include an interaction<br />

terms between this variable, and the proportion of 6-digit industries with the more<br />

aggregate industry class for which the VA rule is applied.<br />

7. Share of intermediate imports out of total imports; Here we divide imports of each<br />

industry into intermediate and final goods (on the basis of the BEC classification,<br />

and then reaggregate up to the ISIC classification). If intermediate imports are<br />

high (and if they are then used in the same sector as the final goods exports) than<br />

once again, it may be difficult to meet the value added criterion. Hence high<br />

intermediate imports may be associated with a more restrictive ROO, and we<br />

would expect a positive coefficient. However this may not be the case if the<br />

intermediates are then used in other sectors. Once again principally applies to<br />

those industries where the VA criterion is used and therefore in the regressions we<br />

have interacted this term with our CA variable as in (5) above.<br />

4.3 Results<br />

For these regressions we have estimated the ROO and ROO+TD coefficients using<br />

the gravity model described earlier – however in this case our estimations are crosssection<br />

regression, and are undertaken for each year of the sample. In this case then<br />

the ROO and ROO+TD coefficients provide an estimate for any given year of the<br />

extent to which trade is lower between countries both of which have a free trade<br />

agreement with the EU, but which do not have the possibility of diagonal cumulation<br />

between themselves. We then take the estimated ROO and ROO+TD coefficients<br />

from these first stage regressions, as our dependent variables, and consider the role of<br />

the explanatory variables discussed above.<br />

Table 5 below, summarises the expected sign on the coefficients on the basis of the<br />

preceding discussion:<br />

Table 5: 2nd Stage variables and the expected coefficient sign<br />

Variable Expected coefficient<br />

EU tariff +<br />

Partner tariff + or -<br />

Exp / output +<br />

Exports to EU / total exports +<br />

Intermediates / output +<br />

Share of intermediate imports + or -<br />

Type of ROO na

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!