REGIONAL COOPERATION AND ECONOMIC INTEGRATION

PART III:
differences It is worth noting that the Svaton and Warin analysis did not include GDP
per capita as a proxy variable for the wage differentials. More precisely, when GDP per
capita is excluded from equation (3), the GINI it-1
coefficient as a proxy variable for income
inequality switches the expected sign. In this way it is possible the form the supposition that
the Gini coefficient as a proxy variable sometimes changes the expected sign, especially
when it is simultaneously included with GDP per capita in the model. But further analysis
will show that this switching of the expected signs can also be attributed to something quite
different.
It is worth noting that the fixed effects estimator does not allow estimation for timeinvariant
variables (as for instance distance, border and common language). But Cheng
and Wall (2005) suggested a methodology which also enables estimations of the coefficient
for the time-invariant variables. In terms of econometric terminology, we first estimate
the regressions using the standard fixed effects estimator. As the time-invariant variables
are collinear with the country-pair individual effect, which precludes the estimation of
coefficients for distance, border and common language as time-invariant variables, we
estimate additional regression of the estimated country-pair effects on time-invariant
variables in order to filter out the importance of these variables in the fixed effects using
this equation
The results of the estimation using additional regression for the entire sample of countries
are robust. Cheng and Wall also argue that the standard fixed effects estimator for estimating
gravity models may suffer from estimation bias due to omitted or mis-specified variables.
They show that the introduction of period dummies and country-pair dummies largely
eliminates this problem. The two-way fixed effects estimator by prediction captures those
factors such as physical distance, the length of the border or contiguity, history, culture,
and language that are constant over the span of the data. We repeat a complete estimation
by introducing the so-called two-way fixed effects model, which additionally involved the
country-pair and time dummies in the regression model.
The estimated coefficients on the GDP per capita for the destination (GDPpc i,t-1
) country
remain always highly significant at 1 per cent confidence and positive for both the entire
sample of these countries or sub-samples of Developing, CEEC and EU-15 member states.
A somewhat surprising result is that the introduced methodology simultaneously changes
the expected signs on GDP per capita of the sending countries (GDPpc j,t-1
) as proxy
variables for wage differentials between two countries.
It is interesting that the destination country population as proxy variable for the size
differentials between the sending and destination countries (POP i.t-1
) repeatedly shows
a positive expected sign with highly significant values of the coefficients for either the
sample of all countries or each individual sub-sample of the countries and that the Gini
coefficient of the destination country (GINI it-1
) as a proxy for income inequality also shows
a negative expected sign for all the observed samples of countries in the present analysis
with mainly insignificant values of coefficients.
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