Introduction
Intergenerational earnings mobility is a very wide issue, which was investigated by a multitude of scientists. Earnings mobility, which is an ability of workers to move across income brackets, can be studied in different respects, and the findings of every study vary in numbers and conclusions according to the different countries. They play an outstanding role in today’s science, as these findings not only fix the statistics of a certain historical period, but can also serve as a basis for the new comparative researches. In addition, learning the tendencies of the intergenerational earnings mobility can be useful for economics and other sciences, such as politics, sociology, psychology etc. What is more, the study concerns not only the intergenerational, but also the international earnings mobility.
Discussion
There are different approaches which can be used while studying the intergenerational earnings mobility, such as the OLS, 2SIV, IV, Transition Matrix, Quintile Regression approaches. They all are based on the statistics and the social researches which were made earlier. The main sources for the scientists to refer to are the Panel of Study of Income Dynamics, the National Longitudinal Surveys, and the works of other scientists. But the collected data is used differently in every approach.
Basically most of the surveys are made with the Ordinary Least Squares (OLS) approach. It is very useful, as it suggests a formula which can define comparatively precise volumes of intergeneration income mobility. However, this method is aimed at studying only some limited period of people’s lives, and therefore it is impossible to see the full image of the lifetime income with its help. The OLS approach underestimates the elasticity, as it uses the current earnings as a proxy for permanent income.
Another way of defining the coefficient of the intergenerational earnings mobility is the 2-Stage Instrumental Variable (2SIV) approach. It is rather comfortable to use and can be met in many works. This method uses two samples which are studied deeply, and it indicates the possible error: they have to be independent to make the estimators consistent. Another demand for this approach to work properly is the identical distribution of the instrumental variables in both samples.
The IV regression is one more method used by scientists. This approach, according to Solon, can cause an upward bias, as it has the “probability limit”: no calculations can predict the influence of the father’s incomes on his child’s earnings.
The next approach is the Transition Matrix method. Its aim is to analyze the movement between income quantities across the generations. It should be combined with other methods, because it cannot give the full information. Still, this method enables the researchers to define who and where moves in the earnings distribution.
Another method is the Quintile Regression, which is very detailed in examining all the facts. The limitation of this method’s accuracy is the underestimation of precise number of years, which is usually presented in the average. This can lead to an error in calculations.
The Occupational Income (Occ Inc) approach assumes that the transmission processes between permanent and occupational income is similar. The drawback of this approach is that the correlation between the terms is weak, and its findings can be comparatively insignificant.
The studies of the intergenerational earnings mobility were made in different countries, and thus we now have a chance to compare all the results. For instance, the most mobile country is Canada, where the numbers change even faster than in USA. Of course there are some factors which influence this process, for example, the changes in educational system caused a positive trend in intergenerational mobility for all types of earnings measure in Britain (Ermisch, 2005). The OLS and the 2SIV approaches showed that the greatest mobility was observed in this country in 1936-1980.
To compare, we can mention Australia, where the issue of the intergenerational earnings mobility was studied for a forty year period. The author of a survey concluded, that the value of the elasticity, which is about 0,2 has not changed (Leigh, 2007). The same stability was observed in Britain in 1950-1972, where the intergenerational elasticity was not even linear until late 60s. This data are relatively reliable, notwithstanding the research errors which can be caused by an inappropriate use of a certain method.
The economical studies, which developed their approaches and broadened specifications, have recently started to focus not only on the income relationships between the father and the son, but also between the father and the daughter. The findings made in Spain are rather surprising, as the regression coefficient of sons there is for 0,14 smaller than for the daughters. In Italy the family background is also very important for both the male and female children, but this country is much less mobile.
Another unexpected fact was mentioned in the study of the intergenerational earnings mobility in Chile (Miranda, 2007). It appeared that the mobility there is much lower for the younger chorts, unlike the tendencies in the European countries, where the group aged from 39 to 49 is the most mobile. However, the intergenerational elasticity there fluctuates from 0,52 to 0,67.
Every research suggests some ways of controlling and increasing the intergenerational earnings mobility in different countries. The solutions are mainly related to the policies and educational systems. Thus, Brazilian scientists are convinced that the public investment supporting equal opportunity can help to control the process of the mobility. This was also concluded by Asian economists, who do not underestimate the role of education and special training of the workers in forming a balanced economy of the country.
Having compared data of different countries, we made a study of the intergenerational earnings mobility of Hong Kong. Such study is very important, as Asian countries are the leaders of the world economy. The research contains the comparison of the current and the previous earnings of workers, the impact of socio-economic factors, the study of a lifetime income of a father and its influence on a child’s earnings etc. A fundamental material for us was the work of Dr James P. Vere (Vere, 2007), who works in the Hong Kong Institute of Economics and Business Strategy in Hong Kong. In his study he mentioned the age categories, genders and family factors as those which influence the earnings mobility. In his work he refers to the data of the General House hold Survey. This source can be considered to be very reliable, as it introduces the statistics of the data which were collected for a long period within different groups of people. His findings can be very useful for the economical study, as they focus on the facts, their reasons and possible results. Thus, he pays attention to the earnings mobility in Hong Kong in 1996-2005. The most mobile group of people turned to be male, dominantly of a young age, and educated in spheres of financing, insurance or business service. The author points to the fact that the policy implications play a very important role in the intergenerational earnings mobility. Even though his survey had a restricted sample of workers, the conclusions have their educational value. The author suggests that the education and training are the best ways to take control over this process.
Conclusion
In conclusion it must be said that learning of the intergenerational earnings mobility should be complex, which implies comparison and compounding of different approaches, referring to the statistics and researches of variable authors. Such way of investigating into the issue will enable the scientists to make valuable investments in economics.
Reference List
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