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CONSEQUENCES OF THE WTO
ACCESSION:
THE ROLE OF ECONOMIC DISTANCE
Sergey Afontsev
Institute for World Economy and
International Relations
XIIth Annual Leontief Readings Conference
Saint Petersburg, February 15-16, 2013
Paper Objectives
Dynamics of Russian imports in 2013–2015 will be
affected by two major factors, i.e., global economic
recovery and trade cost reduction following Russia’s WTO
accession. Economic history provides only one
comparable example when post-crisis growth in Russian
and world economy coincided with a period of trade
liberalization in Russia (2001–2003).
The paper estimates the impact of import tariffs, economic
distance, and GDP growth in Russia and abroad on
Russian imports of goods differentiated by industries and
countries of origin. Research is based on the gravity
model of bilateral trade with monopolistic competition
using panel data on Russian trade with 150 countries in
2001–2003.
The Model: Consumers
Representative consumer in country j maximizes utility
function Uj by consuming differentiated good g given
Dixit-Stiglitz preferences reflecting his/her taste for
diversity:
 1/
n
i
Uj = (  k 1 xijk ) ,
N
i 1
(1)
where N is a number of countries, ni is a number of
varieties of good produced in country i, xijk is household
consumption of a variety k of good g produced in country
i,  is elasticity of substitution between goods in
consumption.
The Model: Consumers
Assume each firm produces only one good variety, with
all firms and all individuals within each country being
symmetric. Then budget constraint for a representative
consumer with income yj is
yj =  n p (1+tij)xij,
N
i 1 i ij
(2)
where pij is the c.i.f. price in country j of the good
produced in country i and tij is the ad valorem tariff rate in
country j for the good from country i.
The Model: Consumers
Assume there are ‘iceberg-form’ costs of transporting
goods from country i to country j, with fraction ij of goods
sent being lost during the transportation. Denoting good
price in producer country as pi and defining cijij/(1-ij),
we have
pij = pi/(1+cij).
(3)
The Model: Consumers
Then maximization of (1) given (2) and (3) gives us the
following expression for equilibrium demand in country j
for good from country i:
xij = (yj/Pj)(pi (1+cij)(1+tij)/Pj)-,
(4)
where
Pj = (ni (pi (1+cij)(1+tij))1-)1/(1-),
and  = 1/(1-).
(5)
The Model: Consumers
Summation of (4) over all consumers produces the
following result:
xij  qij = (Yj/Pj)(pi (1+cij)(1+tij)/Pj)-,
(6)
where Yj is gross domestic product of country j.
The Model: Producers
Each firm in each country produces output qi according
to the following technology:
qi = zikili1- - ,
(7)
where zi is an exogenous productivity term, ki (li) is the
amount of capital (labor) used by the firm, and 
represents fixed costs which are assumed to be identical
across countries.
The Model: Producers
Profit maximization with (7) ensures mark-up pricing rule,
as is characteristic of this class of models:
pi = (/(-1))((C/zi)riwi1-),
(8)
where ri is the rental rate on capital, wi is the wage rate,
and C=-(1-)-(1-).
Further, zero-profit condition under monopolistic
competition implies
qi = (-1),
(9)
i.e., each firm’s output is determined parametrically,
which is one more characteristic of the model class under
consideration.
The Model: Producers
The number of firms in country i equals
ni = ()-1ziKiLi1-,
(10)
while the factor endowment constraints under full
employment of both capital and labor give us
ni = Ki/ki = Li/li.
(11)
The Model: Equilibrium
Trade Flows
To solve for equilibrium trade flows in value terms (Mij),
we multiply (6) by pij and use (8) to obtain
Mii = (/(-1))Yj((C/zi)riwi1-)(pi (1+cij)(1+tij)/Pi)1-.
(12)
Using (10) and noting that C(riKi)(wiLi)1- equals country
i’s GDP (Yi), we have
Mij = (1/(-1)ni)YiYj (pi (1+cij)(1+tij)/Pi)1-.
(13)
The Model: Equilibrium
Trade Flows
Assume that (1+cij) is given by the non-tariff-barrier-totrade function of the following form (cf. Carrere, 2006):
(1+cij) =

 G
De
ij
(14)
where Dij is distance between countries, Gs are
‘geography’ dummy variables for each country, and s
are coefficients on these variables.
Given (14), we can rewrite (13) as
  G
Mij = (1/[(-1)ni])YiYj(pi Dij e   (1+tij)/Pj)1-.
(15)
Empirical Exercise
To test (15), we constructed the database on Russian
imports from 150 countries disaggregated by 16
industries. Countries included in the sample accounted
for 93.3 to 100 per cent of total Russian industry imports
in 2001–2003.
The total number of observations in the database equals
7200, of which 3340 observations correspond to nonzero imports.
Two methods are used:
 ‘Traditional’ loglinear estimation;
 Poisson maximum likelihood as recommended by
Westerlund and Wilhelmsson (2006) and Santos Silva
and Tenreyro (2006).
Empirical Exercise
Some variables in (15) are nonobservables. We propose
to use the following control variables/approximations for
these nonobservables.
 The level of internal prices pi is controlled for by GDP per
capita (higher domestic demand exercises upward
pressure on prices) and PPP to current exchange rate
ratio (PPP-spread). Large PPP spread can reflect low
engagement of a country in foreign trade (large
nontradable sector) and/or undervaluation of a national
currency, both circumstances contributing to the fact that
foreign consumers face lower prices for country’s
products.
 The number of firms is approximated by the population
size Li.
Empirical Exercise: Loglinear
Estimation
Equation (15) can be rewritten in logs as
lnMij = -lnni + lnYi + lnYj + (1-)lnpi + (1-)lnDij +
+ (1-)lnG + (1-)ln(1+tij) - (1-)Pj.
(16)
Making special assumptions about the form of non-tariffbarrier-to-trade function (14), we propose to estimate the
following empirical model:
lnMijk = 0 + ui + uk + 1lnYi + 2lnYj + 3ln(1+tijk) + 4ln(Yi/Li) + 5ln(PPPi) +
+ 6lnDij + 7Glli + 8GFSUi + 8GFCBi + 8lnPj + ijk,
(17)
Empirical Exercise:
Loglinear Estimation
Oil Intensity: Share of Oil and Oil
Products in Intermediate Consumption
Empirical Exercise:
Poisson Maximum Likelihood
Empirical Results: Summary
 The impact of partner country’s GDP on Russian imports
is strongly positive. In models for differentiated goods
and goods of ‘low oil intensity’, as well as in the general
sample, coefficients on partner country GDP are
statistically higher than 1, pointing to the scale
economies in exporting countries.
At the same time, we failed to find any statistically
significant impact of Russia’s own GDP on
country/industry import volumes.
Empirical Results: Summary
 Import tariffs do not affect import volumes in any model
specification. Though we can not rule out the hypothesis
that coefficients on the tariff variable and the distance
variable are the same in most specifications, the former
are never statistically significant.
This means that the present level of Russia’s MFN tariffs
does not influence decisions on import volumes.
 Coefficient on the distance variable appeared to be
strongly negative in all specifications, as predicted by the
basic logic of the gravity model.
Empirical Results: Summary
 Coefficients on the GDP per capita show that Russia
imports more differentiated goods from developed
countries. This can reflect a ‘taste for quality’ in respect
of differentiated goods (as developed countries are likely
to export higher-quality varieties of differentiated goods
AND/OR advantages of developed countries in
production of capital-intensive manufacturing goods.
 Higher foreign prices (lower PPP spread) quite logically
correspond to lower Russian imports (except for the case
of homogenous goods).
Empirical Results: Summary
 Soviet heritage in trade captured by dummy variables for
the former USSR and the former Communist block is still
quite remarkable as far as its impact on Russian imports
is concerned.
 Extremely low coefficients generated by Poisson
maximum likelihood estimation suggest that zero industry
imports from specific countries result from particular
patterns of trade specialization rather than prohibitive
impact of import duties and/or distance-related costs.
Implications for Russia’s WTO
Accession
Russia’s WTO accession is likely to affect
imports by reducing distance-related trade
costs rather than import tariffs that were
found to be not statistically significant in all
model specifications.
Implications for Russia’s WTO
Accession
Change in Export Structure Seems to
Shift EC for Total