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^
^
S
L, across
=
Σ
λ
j
(l
j
– m
L
)
2
j=1
n
Following the notation of Francois, Jansen, and Peters (2012), λ
j
is the sector j share
of total employment,
î
j
is the per cent change in sector j employment, and m
∧
L
is total
per cent change in employment across all sectors. Since we do not model changes
in total employment levels here, and employ a long-run closure where overall labour
participation and employment levels are determined by factors outside the model,
m
∧
= 0. This means out index reduces to the following:
^
S
L, across
=
Σ
λ
j
(l
j
)
2
j=1
n
The index S
L, across
gives us a measure of variation of employment across sectors and thus
a measure of the actual number of workers that change jobs by moving across sectors.
In essence, an index value of 0.5 means, that roughly 5 workers out of 1,000 have
moved across sectors. The index provides a useful indicator for the adjustments taking
place in labour markets following trade liberalisation.
17
Table 38 Displacement of less and more skilled labour in the EU and US, total
effects (in per cent), 2027 benchmark, 20 per cent direct spill-overs
Less skilled
More skilled
Less ambitious
Ambitious
Less ambitious
Ambitious
EU
0.33
0.65
0.28
0.55
US
0.21
0.48
0.21
0.46
Source: CGE calculations.
17 The index is a lower bound on labour displacement, as it is likely to underestimate the actual amount of job churning that
occurs. Workers who change jobs but do not change sectors are not captured by the above measure. In order to capture
those workers, it would be necessary to have information on employment changes at the firm level. In the model, we treat
labour as mobile but not perfectly mobile, even in the long-run. This means that there is a transformation elasticity for
labour between sectors that is less than infinite.
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As was shown to be the case for wages, the estimated effect on movement of labour is
relatively small. Here, no more than 0.7 per cent of the labour force is expected to move
across sectors as a result of measures taken to liberalise trade between the EU and US.
The impact is estimated to be somewhat bigger for less skilled workers than for more
skilled workers. The resulting changes are somewhat bigger for the EU than for the US,
but the effects are still quite small. To put this in perspective, this is a change following
full implementation. According to Eurostat, the average annual change in employment
in the EU in manufacturing before the crisis (2001-2007) was 2.1 per cent, and in the
years after the crisis this increased to 3.7 per cent. Taking this as a benchmark, if we
assume just 2 per cent labour turnover per year through natural entry and attrition,
then over five years we would have roughly 10 per cent labour turnover, such that the
labour displacement from FTA implementation over a five year phase in period will be
minimal by comparison. In this sense it ought to be easily absorbed through normal
entry and attrition rates. Additionally, the FTA-related labour movement is largely
driven by “pull factors” (higher wages). By this we mean that wages are going up, and
so the mechanics of labour reallocation will involve attraction of workers from lower to
higher paying sectors on net.
5.2.3.2. CO2 Emissions
Next, we move on to discuss the estimated impact on CO2-emissions. These are
summarized in Table 39 below.
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Table 39 Changes in CO2-emissions (in thousand metric tons), 2027 benchmark, 20
per cent direct spill-overs
Less ambitious
Ambitious
European Union
2.7
3.6
United States
2.9
3.9
Other
-1.5
3.8
Other OECD, high income
0.1
0.9
East Europe
-0.9
0.3
Mediterranean
-1.4
-1.6
China
1.4
4.3
India
-0.1
0.1
ASEAN
-0.5
-0.4
MERCOSUR
-0.1
-0.2
Low Income
0.2
0.8
Rest of World
-0.2
-0.3
Total, thousand metric tons
4.0
11.3
Total, percentage share of annual rate
0.02
0.07
Source: CGE calculations.
The less ambitious FTA scenario is estimated to lead to a total global increase of 4
and 11 thousand metric tons under the two different experiments respectively. CO2-
emissions are expected to increase in the EU and US by around 3 and 4 thousand metric
tons, respectively. On the other hand, emissions are expected to decrease somewhat
across some other countries. Looking at the percentage increase, the estimated changes
are shown to be very small, being 0.02 per cent in the less ambitious case and 0.07 per
cent in the ambitious case. Depending on future changes in the coverage of emissions
trading in the EU (increased and more binding coverage), and possibilities for future
introduction of such a scheme in the US, the net effect would then be even smaller than
reported here. It should be pointed out that the estimates in Table 39 can be considered
as comprehensive as the model considers all economic activities, including international
shipping and transport that are associated with changes in trade flows. The latter are
endogenous within the model as increases in trade flows lead to changes in demand for
transport services. As transport activities are modelled explicitly, this will lead in turn
to changes in emissions linked to these activities.
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5.2.3.3. Natural Resource Usage (Land intensity)
We now take a look at the resulting effect on the land use. In the model, land is an
explicit factor, like capital and labour. Increase in value added in sectors using land
translates into its more intensive use (more output per unit of land). Alternatively, in
sectors where activities fall, there will be a drop in land use intensity. By this we mean
there is less capital, labour, and inputs such as fertilizers in use on a given piece of land
when intensity falls. Our estimates of changes in land use intensity (based on total value
added activity for a fixed stock of land) are summarized in Table 40 below.
Table 40 Changes in land use (in per cent), 2027 benchmark, 20 per cent direct
spill-overs
Less ambitious
Ambitious
European Union
0.05
0.06
United States
-0.01
0.00
Other
0.00
0.01
Other OECD, high income
-0.01
-0.01
East Europe
0.02
0.03
Mediterranean
0.03
0.04
China
0.01
0.03
India
0.00
0.01
ASEAN
-0.04
-0.07
MERCOSUR
0.01
0.02
Low Income
0.00
0.00
Rest of World
0.01
0.01
Total
0.00
0.01
Source: CGE calculations.
The resulting impact from removing barriers to trade between the EU and the US on
the use of natural resources is negligible. The expected changes are practically zero
in all regions, including the EU and the US. These negligible results indicate that the
liberalisation measures will not impact significantly on land use in any of the economies
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5.2.4. Global Effects
Changing the conditions for trade between two major global trading partners, such
as the EU and the US, changes the trading conditions for other countries as well. In
a traditional set-up, when tariffs are lowered, this implies trade diversion and trade
creation due to relative as well as absolute changes in trading costs. In this set-up, the
additional measure of lowering of NTBs and assumption of spill-overs adds another
channel through which bilateral liberalisation potentially affects third countries (see
Section 4.2).
Overall, the rest-of-world impact hinges critically on the assumed potential for
streamlining of EU and US regulations in the process of negotiations and convergence
of EU-US standards, linked to scope for some resulting convergence on global standards
and cross-recognition as well. These effects imply some improvement of market access
for third countries, helping to offset trade diversion.
The purpose of this subsection is to take a closer look how liberalizing trade between
the EU and US is expected to affect the rest of the world. The estimated impact on GDP
is summarized in Table 41 below. In general, the increased trade between the EU and
the US is estimated to have a positive impact on other parts of the world.
As can be seen from the table, under the less ambitious scenario, the overall gain for
third countries is estimated to be 46.6 billion euros, which amounts to a percentage
increase of GDP of 0.07 per cent. In the more ambitious case, the increase would be
99.2 billion euros or 0.14 per cent of world GDP.
18
18 Excluding the EU and the US.
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Reducing Transatlantic Barriers to Trade and Investment – An Economic Assessment
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Table 41 Total effects on GDP for rest of the World (in million euros and per cent),
2027 benchmark, 20 per cent direct spill-overs
Less ambitious
Ambitious
Million euros
Per cent
Million euros
Per cent
European Union
68,274
0.27
119,212
0.48
United States
49,543
0.21
94,904
0.39
Total Other Countries
46,636
0.07
99,171
0.14
Whereof:
Other OECD, high income
15,942
0.08
36,322
0.19
Eastern Europe
1,019
0.14
2,328
0.33
Mediterranean
237
0.02
1,063
0.08
China
3,810
0.02
5,487
0.03
India
946
0.02
2,338
0.04
ASEAN
15,081
0.45
29,834
0.89
MERCOSUR
624
0.01
1,545
0.03
Low Income
1,064
0.09
2,366
0.20
Rest of World
7,913
0.05
17,887
0.12
Source: CGE modelling.
Looking at the selected regions a little more closely reveals that all other economies
are expected to experience welfare increases. Most notably, this is the case for ASEAN,
where GDP is expected to increase by 15.1 billion euros and 29.8 billion euros, or 0.45
per cent and 0.89 per cent respectively. The driver for ASEAN is the third-country
spill-overs combined with very high trade to GDP ratios in the ASEAN economies.
Basically, if there is a drop in global trade costs linked to indirect spill-overs, the
ASEAN economies benefit greatly from this.
Table 42 shows a regional breakdown of the change in exports. These results provide
insight regarding the pattern of results in Table 41. Not surprisingly, the primary effects
are realized in the FTA partner regions – the US and EU. However, the spill-over effects
also contribute to exports growth in third countries. This is especially true for ASEAN,
which is a region with a high trade to GDP ratio and with a structural focus in exports in
those sectors that see the greatest NTB reductions. With ASEAN, stronger GDP effects
also support strong trade effects.
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