of the late 1990s. As we would expect given the structural transformation of

the early 1990s, the cohort effect decreases gradually as we move from 1983

back; the results indicate that the human capital of older people is valued

less than that of younger ones.

The estimate of the logarithm of the real wage index is 0.87 and strongly

significantly different from both 0 and 1. The high value of the estimate

confirms that the index is a good measure of the average real wages of our

sample, but the fact that it is less than 1 shows that the wages of respondents

in our sample are less cyclical than the average. The estimate of the logarithm

of monthly hours is low, at 0.35, confirming our claim that dividing monthly

earnings by hours worked is not a good way of obtaining hourly wages as

the rate of return to human capital (see also Maltzeva, 2009, for a similar


The residuals from equation (8) are used as the measure of the permanent

income of children and parents in equations (1)-(3) and (5).

Table 7 presents the OLS estimates of equation (1). The earnings elasticity

is about 0.33 and strongly significant. Equation (1) is also estimated for

the 20th, 40th, 60th, and 80th quantiles of the distribution of its dependent

variable by means of the quantile regression. The estimates of the effect of

parent’s earnings for the specified quantiles are shown in Table 2.

Table 2. The estimates of the earnings elasticity for quantiles

The earnings



0.20 0.40 0.60 0.80

0.2933*** 0.3537*** 0.3744*** 0.4695***

[0.0947] [0.0738] [0.0709] [0.0893]

*** Significant at .01 level.

Bootstrap standard errors are in brackets.

The results of the quantile regressions demonstrate heterogeneities in the

estimates, with the earnings elasticity increasing as we move up the (children’s)

wage distribution. But the Wald test of the hypothesis that the

earnings elasticities estimated for the 20th and 80th quantiles are equal to


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