Estimating the Effects of Regional Integration

Nigel Grimwade (LSBU)

Regional economic integration Definition: the process whereby separate national

economies are combined into larger economic regions

Two basic conditions:-1. Free movement of goods and factors of

production (labour and capital)2. Absence of discrimination Brought about in 2 ways:-1. Negative integration – removal of discrimination

(e.g. tariffs) and restrictions on movement2. Positive integration – creation of common

policies and institutions

Forms of regional economic integrationTypes of regional economic integration:-1. Preferential trading agreements (e.g. EU’s Lomé and

Cotonou Agreements)2. Free trade agreements – elimination of tariffs on all

trade between the member states (e.g. EFTA, NAFTA, AFTA)

3. Customs unions – internal free trade plus a common external tariff (e.g. EC/EU, Mercosur)

4. Common Markets – free trade in goods and services and free movement of capital and labour (e.g. SEM)

5. Monetary unions – adoption of a common currency, single central bank and common monetary policy (e.g. Euro zone)

Economic effects of regional integration Static effects - short-run, once-and-for all

increase/decrease economic welfare due to:-1. Reallocation of resources due to trade-creation

and trade-diversion2. Terms of trade effects – change in the ratio of

average export prices to average import prices Dynamic effects – long run, on-going increase in

national income due to:-1. Economies of scale (static and dynamic)2. Increased competition3. Increased investment (domestic and foreign)4. More rapid rate of technological innovation

Problems in estimating the effects of regional integration Which effects to measure – effects on trade,

national income, rate of economic growth What time period to consider – short- or

long-run What types of integration to cover – tariffs,

NTBs, services, factor mobility, monetary integration

How to estimate the counterfactual – what would have happened if integration had not taken place

Simple extrapolation Most early studies were concerned with the static

effects – trade-creation and trade-diversion Focused on trade (exports and imports) between the

members (intra-area trade) and trade with non-members (extra-area trade)

Made the simple assumption that intra- and extra-area exports/imports would have continued growing at the same rate had integration not happened (anti-monde)

Difference between actual trade and the anti-monde (the residual) is the integration effect

One major problem – this assumes that conditions in the post-integration period were the same as in the pre-integration

Intra- and extra-area trade share A better approach is to extrapolate intra-area and

extra-area exports/imports as shares of total imports (see diagram) e.g. Xij/Xi, Mij/Mi

Increase in actual intra-area export/import share compared with the anti-monde is evidence for an integration effect

But we have no way of knowing whether this is due to trade-creation or trade-diversion

Is greatly affected by (a) the number of countries involved and (b) the region’s share in total trade

Share may also be affected by an increase in the number of members over time

Residual imputationIntra-RegionalExport ActualShare% Trend

0 T1 Time

Problems with simple residual models Different factors may have affected intra- and extra

area exports/imports in the pre- and post-integration periods, such as:-

1. Rate of economic growth – import demand2. Phases of the business cycle3. Changes in relative prices 4. Changes in the exchange rate5. Structural changes6. Reductions in multilaterally negotiated tariffs So, we cannot assume that what happened in the pre-

integration period would have happened in the post-integration period had integration not happened

Shares of intra- and extra-area trade in national income/consumption Extrapolate share of extra- and intra-area

imports in GNP/GDP or…. Extrapolate share of extra- and intra-area

imports in apparent consumption (domestic production less exports plus imports)

An increase in share of AC coming from domestic sources is evidence for gross trade-creation

An increase in share of AC coming from partner countries is evidence for net trade-creation

A decrease in share of AC coming from rest of the world is evidence for trade-diversion

Balassa’s income elasticity of demand for imports approach Income elasticity of demand for imports

(∆M/∆Y) is calculated for pre- and post-integration period

Rise in income elasticity of demand for imports for intra-area imports is defined as gross trade-creation

Increase in income elasticity of demand for imports from member states is net trade-creation

Decrease in demand for imports from non-member states is trade-diversion

Found evidence for net trade-creation following the formation of the EC – but some trade diversion in agricultural goods

Use of a control group An alternative approach was to use a third

country as a normaliser or control group Assumption was that intra- and extra-area

imports would have grown at the same rate as imports of the normaliser country

Necessary that normaliser country was a similar country not affected by any special factors

But such an approach is heavily dependent on the country chosen

Intensity of Trade Approach Based on the idea that there exists some “natural” amount

of trade that will take place between any two countries If actual trade exceeds this natural amount, this suggests

trade is biased by other factors Such factors include membership of a regional integration

scheme Then, any increase in the degree of bias over time provides

a measure of the effects of integration Several studies have used an intra-regional trade intensity

index or trade concentration ratio:- Iij = Xij /Mj ÷ Mj /M

Where I is greater than one, this implies geographical bias in trade due to natural and institutional factors

Intensity of trade approach Increase in the index over time measures the

trade integration effect But trend over time gives a confusing picture

(see Table 2):- 1. No change in some cases e.g. EU, EFTA2. Upward trend in others e.g. Mercosur and

Andean Pact3. Downward trend in others Major weakness – lacks any proper measure of

natural trade and fails to take account of possible changes in factors affecting natural trade

Gravity Models Draws on Newton’s law of gravity in physics and the idea

that there is some “natural” amount of trade taking place between any two countries, i and j (intensity of trade)

In the original gravity model, bilateral trade flows are affected by two forces or masses - trade potential and trade resistance

Trade potential is shaped by size of each country’s GDP/GNP and population – and thus by per capita GDP/GNP

Trade resistance is negatively related to distance between two countries

But newer versions of the gravity models have added other variables to increase the explanatory power of the model

Gravity Models Newer versions of the gravity model have added other

variables:-1. Geographical size – negative relationship2. Adjacency3. Common language (or cultural affinity)4. RTA membership5. Landlocked or island economies6. Common currency7. Former coloniesusing a dummy variable for 2-7 A simple form of the gravity equation might be:-

log Xij = log A + β log Yi + β log Yj + μ log Hi + μ log Hj + γ log Ni + γ log

Nj + α log Dij + log εij

Gravity estimation Simple approaches is to use the gravity equation to

estimate the amount of trade expected had integration not occurred

Actual trade is then compared with predicted trade – the residual measures the integration effect,

But this approach cannot distinguish between trade-creation and trade-diversion

Better approach is to estimate trade flows for integration period only, using dummy variables for membership/non-membership of the same trading bloc

Coefficient of the dummy variable will measure how much extra trade was trade-creation and trade-diversion

An example: Frankel, 1997 Estimated the integration effects of 6 trading

blocs between 1965 to 1994 Found positive integration effect for all cases,

with strongest effects for ASEAN and ANZCERTA Strong effects were also found for Mercosur and

the Andean Community But there was no statistically significant effect for

the EU until after 1985 The EC bloc effect was stronger for the EC, but

not significant until after 1980 But the two EC enlargements of 1973 and 1985

had major effects

Computable General Equilibrium Models Involve construction of complex computer models

covering all the sectors in a country’s economy – including goods, services, firms, households, government, labour, etc.

Shows all the interconnections between different parts of the economy using a series of equations

Model is then calibrated for a particular year and the model is then subject to a shock to estimate the effects

Models may be single-country models (e.g. PRCGEM) or multi-regional (e.g. GTAP)

Models can be used to study the effects of regional integration

Uses of CGE Modelling Were first used to analyse the effects of NAFTA and

its enlargement to Central and Southern America Were also used extensively to study the effects of

APEC liberalisation More recently, several models have been used to

simulate the effects of the EU and its eastern enlargement

CGE models have also been used extensively to estimate the effects of multilateral trade liberalisation e.g. effects of the Uruguay Round

Can be used to predict what will happen (ex ante) as well as estimate what has happened (ex post)

Conclusions Important to have some idea of the size of the

effects from regional integration Wide variety of different approaches have been

used, but they give wildly different results Methodology used in this research has progressed

from the early days No studies can tell us exactly what has happened or

will happen because of the counterfactual problem But the use of econometric methods can give us a

fair estimate of the broad magnitude of these effects CGE models are especially useful for estimating the

long run effects on economic growth