The migration model

The model used for the forecasting of the migration potential tries to explain how many people from CEE-10 will migrate to various regions of Austria if the economic development takes place according to one of the above mentioned scenarios, and the behavior of the citizens of CEE-10 is similar to that of the citizens of Club-Med. Taking into consideration the above mentioned facts, we decided to base the estimate of the scale of potential migration on a model built with the data concerning migrations from Spain, Greece and Portugal during the period 1983-95. The explained variable was the total increase of the number of Spaniards, Portuguese, and Greeks living in other EU countries between 1983 and 1995. The same model, used with the CEE-10 and Austrian data, was used to make a forecast of the increase of East Europeans living in regions of Austria during a period of ca.10-12 years after the accession .

The model explaining migration from Club-Med was estimated with a cross-section sample (specific data show the emigration from one of the South European countries to a given West European country per 1000 inhabitants of this South European country). We used the standard gravity model, in which “attracting” factors have the positive impact on migrations, while the “repelling” factors have the negative impact. In the standard gravity model the main “attracting” factor is the size of the economy and the income relation, while the main “repelling” factor is the geographical distance.

We used the following set of explanatory variables:

  1. Differences in incomes, measured by the ratios of GDP per capita between the country of emigration and the receiving country, at current exchange rates.
  2. Geographical distance between the country of emigration and the receiving country, measured as the average distance in km.
  3. Absorption capacities of the receiving country, measured by the population of this country (an estimate for the size of the labor market).
  4. Situation on the labor market in the receiving country, measured by the unemployment rate in this country (the higher the unemployment, the more difficult it should be to emigrate to this country).

Estimation results are presented in Table 4.

 

Table 4: Estimation results for the Mediterranean countries

(Migration/1000 pers.) = a (Population)b (GDP relation)x (Distance)m (Unempl.rate)l e g Dummy

Regression statistics

 

Parameter

Stand.error

t Statistic

p Value

Multiple R

0.941

Intercept

0.000

R square

0.886

ln(population)

1.683

0.231

7.273

0.000

Adjusted R square

0.788

ln(gdp relation)

1.717

0.418

4.110

0.001

Standard error

0.939

ln(distance)

-1.839

0.261

-7.036

0.000

F Statistic

23.2

ln(unempl.rate)

-1.301

0.488

-2.667

0.018

Significance F

0.000

Dummy (for Belgium)

3.408

1.000

3.410

0.004

Source: authors’ calculations

 

The estimated parameters are elasticities. Thus, for example, the third parameter can be interpreted in the following way: if the GDP relation between the country of emigration and an Austrian region increases (decreases) by 1%, the emigration pressure increases (decreases) by 1.717%.