1 Why do immigrants in Hungary have better employment figures ?

variables, β is the estimated coefficients and k is the number of variables. The first term of the right side of the equation is the constant effect, the second is the parameter effect and the third is the composition effect. The difference between the constants (ci – ch) is interpreted as the effect of unobserved factors, i.e. the difference that would be seen if the groups were identical both in terms of their composition and their estimated parameters (Galasi, 2002). The parameter effect is the difference between the estimated coefficients. It shows how much the difference would be between the rates if the constants were the same and the composition of the two groups was identical in terms of the variables examined. The composition effect is the part of the difference which is due to the difference between the averages of the variables. It indicates the difference between the employment rates of the two groups that would be observed if the probability of their employment were influenced to the same extent by the various factors and the constant were also the same. Two foreign-born groups are identified: one contains individuals born in Romania, Slovakia, Serbia or Ukraine (indicated as ‘From neighbouring countries’ in the Table), while the other category contains all others born outside Hungary. Our analysis mainly regards the latter as immigrant population. This differentiation is important since the migration to Hungary from neighbouring countries has special characteristics.1 Table 3.1.1. 1 presents the employment rates of the groups in the 25–64 age group. The employment rate of immigrant men is 11–12 per cent higher and the employment rate of immigrant women is higher by 5–8 per cent than that of the local population. In the group arriving from neighbouring countries, the rates are higher (although not much higher among men) than the rates of other immigrants. As it is shown in the main body of the text, the employment rate of those born abroad is higher than that of those born in Hungary. The aim of this analysis is to reveal the components of the difference between the rates. Regression analyses so far have indicated that if school attainment, age and place of residence of individuals are taken into account, the employment chances of the population born abroad do not, or do not significantly differ from those of the population born in Hungary. That is, the differences are mainly explained by the differences in the composition of the two groups. It is good practice to analyse the difference by a method that allows the observed variables to have different impacts between the groups. It is important because the difference between the employment rates may not only be due to differences in composition but also due to the dissimilar ways that certain characteristics contribute to the employment rate of the groups. The difference in average outcomes of certain groups can be decomposed into components using the Oaxaca–Blinder decomposition method (Blinder, 1973, Oaxaca, 1973). In the following analysis, the employment rates of the immigrant and native populations are compared, relying on a version of this method. First the probability of employment is estimated by the method of least squares separately for each group. Level of education, age, family status and other individual factors are taken into account. As a result of the estimation, the difference in the employment rates of the immigrant and recipient populations may be decomposed into components as follows: ∆E = Ei − Eh = (ci − ch) +