Descriptive statistics and regressions of 2D:4D and educational attainment based on RLMS data
We document the descriptive statistics and detailed regression outputs for educational attainment and measured 2D:4D ratios, based on the RLMS data (20th round, conducted in 2011–2012). Regression analysis is conducted using STATA 13, gologit2 which is a special code for the generalized ordered logit regression in STATA environment. We provide graphs of differences in means of 2D:4D ratios by educational attainment. Information about the distribution of self-identified nationalities and fields of university degrees of respondents is presented.
According to the common definition of unemployment, the unemployed are those who are not in paid employment or self-employment, are seeking work and are available for work. А job search model is estimated from a sample of the unemployed and from some extended samples of the jobless, obtained by loosening that definition gradually. Revealed similarities and differences constitute the result of the research.
This paper is devoted to the rational behavior in the sense of the educational level choice. The theoretical model is based on the discounted flow of personal’s utility function covered the period of the education and future work. Maximizing the flow under the budget constraint we received differential equation included the rate of income grow after the acquisition of education. The solution is the Mincerian type equation. The main result of the model is that the persons with rapid growth of their earnings profile should have the smaller slope coefficients of schooling in the earnings equation. The empirical part of the research is based on the Russian Longitudinal Monitoring Survey (RLMS) data set. The theoretical results have been confirmed by the regression analysis. Splitting the RLMS sample according to the respondents’ wage profiles we received that highly educated agents unlike the unskilled workers have higher income but slighter slope earnings profiles. It means that the workers expected the high growth of their incomes after the schooling are less inclined to receive higher level of education. Otherwise the persons who expected high income on the job start justify their hopes, but come across the low growth of the incomes.
The dominating goal of the research is to analyze the factors, creating incentives to manipulate the economic and political environment to increase personal wealth. Empirical part of the research is mainly based on the data of the "Russia Longitudinal Monitoring survey, RLMS-HSE”-2006
The author focuses her attention on the analysis of the general and the particular in the adaptation of specialists on the basis of the data collected in Russia by the NRI HSE in the course of monitoring the population’s economic situation and health (RLMS-HSE), comprising a vast body of classified information on the changes in the conditions and quality of life of the Russian people.
In this paper the public-private wage gap is estimated by means both of the OLS and the quantile regression, which will provide a more complex picture of the distribution of the public-private sector wage gap. The author finds the existence of significant public-private wage gap (about 30%) considering both observable and unobservable characteristics of workers and jobs. Using the decomposition based on quantile regression helps to answer the question about the nature of the wage differences. The author comes to the conclusion that the main reason for the gap is the institutional mechanisms of public sector wages in Russia. The analysis is based on the data from Russian Longitudinal Monitoring Survey (RLMS-HSE) 2000-2010.
Institutions affect investment decisions, including investments in human capital. Hence institutions are relevant for the allocation of talent. Good market-supporting institutions attract talent to productive value-creating activities, whereas poor ones raise the appeal of rent-seeking. We propose a theoretical model that predicts that more talented individuals are particularly sensitive in their career choices to the quality of institutions, and test these predictions on a sample of around 95 countries of the world. We find a strong positive association between the quality of institutions and graduation of college and university students in science, and an even stronger negative correlation with graduation in law. Our findings are robust to various specifications of empirical models, including smaller samples of former colonies and transition countries. The quality of human capital makes the distinction between educational choices under strong and weak institutions particularly sharp. We show that the allocation of talent is an important link between institutions and growth.