High school or college: where to go in order to successfully find a job and earn good money?

    Hello, Habr! Last summer, we published an article on the results of monitoring the employment of graduates. The project received active support from universities and all interested parties, thanks to which a number of improvements were made over the past year.

    Firstly, data on university graduates in 2014 and 2015 were collected and processed. The data for 2015 was processed and published just a few days ago (perhaps some of the readers noticed recent media publications on this subject). So now it is possible to analyze the monitoring results immediately for three years, tracing the dynamics of indicators. But we will talk about this in more detail in the next article.

    Secondly, they were collected, processed and published on the portal spo.graduate.edu.rudata on graduates of secondary vocational education in 2013 and 2014 years of release. For those who are not very versed in official terms, these are graduates of “colleges”, “technical schools”, etc. Here we will talk about the results of this monitoring, as well as their comparison with the results of monitoring universities, in this article.

    We tried to tell as much as possible about the project, so the article turned out to be quite voluminous and therefore divided into several parts. In the first, we will briefly talk about what secondary vocational education is and what to expect from it. The second will focus on monitoring results. A separate important section is devoted to an attempt to compare the results of secondary vocational education graduates with the results of university graduates. In other words, we will try to at least partially answer the eternal question “Is higher education really important?”, But from an objective, new point of view, relying on dry numbers.

    If you are too lazy to read the theory and other explanations, you can immediately go to the most interesting part - the results, but we strongly recommend that you familiarize yourself with at least the research methodology.

    Table of contents:
    1. Theoretical part
    - What is STR?
    - Stereotypes, features, expectations
    - Geography of study
    - Methodology
    2. General results
    3. Detailed comparison of HE and STR
    - Data preparation
    - Comparison metric
    - Comparison results
    4. Comparison of graduates of one university
    5. Conclusions

    Theoretical part

    What is open source software?

    To begin with, we will deal with the terms in order to correctly understand each other. What is secondary vocational education in general? As the name implies, this is, above all, vocational education.

    (Надо отметить, что с введением нового N 273-ФЗ «Об образовании в Российской Федерации», термин «высшее профессиональное образование» был упразднен и заменен на «высшее образование»).

    The leading task of this educational level is to teach students in the shortest possible time key skills and knowledge that will be enough to start working. Some specialties can be entered after the 9th grade. Nowadays such graduates are often called “working cadres” or “blue-collar workers”, i.e. people who work with their hands in factories, warehouses, hairdressers, shops, etc.

    Sometimes it is believed that open source software is more focused only on obtaining workers or not requiring in-depth knowledge of specialties. However, this is not quite true. Many, although by no means all, specialties that can be studied in higher education programs are also available in open source software. Of course, the curriculum and the intensity of training will vary. It should be noted that many universities can also teach in secondary vocational education programs.

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    STR is divided into:

    • training programs for skilled workers and employees (roughly speaking, what used to be called primary vocational education);
    • training programs for mid-level professionals.

    The latter, in turn, are divided into basic and advanced levels (training lasts about a year longer). If interested, then in more detail about the system of secondary vocational education in Russia can be found on one of the resources of the Ministry of Education and Science of Russia.

    For simplicity of presentation, hereinafter, we will call all graduates who have received secondary vocational education “graduates of secondary vocational education” or “graduates of technical schools”, and those who have graduated, - “graduates of higher education” or “graduates of high schools”. Although formally this is not entirely true, then immediately everyone understands.

    Stereotypes, features, expectations

    Secondary vocational education, as a rule, is considered less prestigious than higher education. Accordingly, it is believed that both salaries and employment with STR graduates are worse than those with higher education. However, at some point, an opinion began to become popular about the increasing value in the labor market of cadres of working specialties. We are talking, of course, about highly qualified professions, for example, the operator of a CNC machine. And, according to official statements , the popularity of open source software has really grown in recent years, including through projects such as Worldskills .

    A cursory analysis of the situation on the labor market shows that the first of the stereotypes is more likely true. To do this, we will use the well-known portal hh.ru and select vacancies that require "secondary special" or "secondary professional" education. And then compare with those where you need a "higher education." The figure below confirms that in general, specialists with higher education “cost” more:

    Figure 1. (Data as of July 4, 2017 for the region of Russia)

    If we calculate the average salaries offered, then for specialists with higher education they offer amounts ~ 1.24 times more .

    This is a very rough estimate of the labor market. If only because besides hh there are portals specializing in vacancies specifically for people with open source software, and the situation there may differ.

    At the same time, one should not forget that many specialties of STRs also have “freelance”. For example, a familiar example of a plumber taking money for work in his pocket, or a team of workers doing repairs without signing a contract. Unfortunately, it is impossible to estimate these revenues and their share using official data.

    Geography of study

    Obviously, both the average wage and the share of employment are highly dependent on the region. First, let's look at the differences in the geographical distribution of graduates. Is the popularity of HE and STR evenly distributed across Russian regions? How to evaluate what kind of education "prevails" in the region? Let us construct the dependence of the share of graduates of secondary vocational education and higher education on the total population. Considering that not all regions filled the monitoring data equally well, we will use the official statistics of the ministry (data taken for 2014, the situation is approximately the same for 2013), and not monitoring data.

    Figure 2

    Signed regions are marked in red. These are regions where the “bias” in the direction of a particular education is 2 or more times. Of course, our two capitals are striking - these are two large cities that have a clear bias towards the "tower".

    Now let’s take a look from a different angle: we calculate the share of graduates who studied in a particular region from the total graduation by the appropriate level of education:

    Figure 3

    Most of the points are located along a straight line, inclined at about 45 degrees to the abscissa axis - that is, in most cities the “contribution to production” of graduates in HE and STR programs is approximately the same. But, as one would expect, Peter and Moscow again stand out against the general background by a strong numerical superiority towards higher education. However, one should not lose sight of the fact that these regions are leaders in terms of the absolute number of graduates of open source software.

    This means that the geography factor should be taken into account when comparing HE and STR indicators: after all, in Moscow and St. Petersburg the situation on the labor market is better than in most regions. Thus, a significant part of university graduates will find it easier to find a job due to the “good” location of their educational organizations. Unlike their colleagues from technical schools.

    Monitoring technique

    I would like to repeat a couple of disclaimers from the previous article:
    1) Данные, представленные на портале, имеют множество разрезов. Их анализ можно производить различными способами и методами. Мы всячески приветствуем всех, кто хочет выполнить самостоятельный анализ наших данных. Все они бесплатно доступны на graduate.edu.ru для скачивания в различных форматах (требуется регистрация).
    Ниже приведен лишь один из вариантов такого анализа, позволяющий в первом приближении оценить результаты, а также сравнить показатели мониторингов СПО и ВО. Целью данной статьи являлся не глубокий научный анализ данных, а краткое знакомство читателей с проектом, его результатами и примерами возможного анализа.

    2) Для тех, кто нечасто имеет дело со статистикой. В общем случае, когда речь идет о статистических закономерностях, мы не можем говорить о том, что является причиной, а что — следствием. Хорошие доходы и относительная легкость в трудоустройстве выпускников престижного вуза NN не доказывает исключительную заслугу вуза в этом. Поскольку в престижные вузы поступает множество талантливых и способных учеников, вполне вероятно, что они достигли бы таких же или еще больших высот, обучаясь в другом вузе. Ответ на такие вопросы – тема отдельного большого исследования.

    For those who have not read our first article on this topic, we recommend that you familiarize yourself with it. If not with the results, then at least with the monitoring technique. This will help to avoid unnecessary questions.

    If you read laziness, the following is a brief summary of the methodology:

    1) The project was launched the year before last, together with several ministries and departments.
    2) Data on graduates (specialty, date of birth, year of graduation, etc.) are filled in by the educational organizations themselves in the FIS FRDO .
    3) Then the verified and correct data are transferred to the Pension Fund (with the exception of those who continued their studies at the next level of education and foreigners), which returns information about who receives what salary and in which region it works. Thus, only “white salary” is taken into account.

    PS If you know how to know “black salary” reliably without polls and blackjack , we invite you with your ideas in the comments, the Federal Tax Service will be very glad to such a project, and we will be happy to implement it. ;-)

    During the implementation of the ACT project, we received data on graduates of the 2013 release and “tracked” their employment in 2013, 2014 and 2015. The same was done with graduates of the 2014 release for the 2014 and 2015 years of employment, respectively. For simplicity, in the future we will replace the phrase "graduates of 20xx year of graduation in 20y year of employment" with "20xx-20uu". For example, "2013-2013", "2013-2015".

    Unfortunately, not all organizations implementing open source software have contributed to the FIS FRDO. In contrast to the monitoring of employment by the “tower”, where data were submitted for approximately 99% of graduates, during this project only about 2/3 of graduates were able to obtain data. This introduces some distortions in the results, but does not interfere with assessing the whole picture (we carried out a number of statistical checks that showed that the average share of employment does not depend on the volume of output). Let's hope that next time educational organizations will approach the issue of data reporting more responsibly.

    What sections can be analyzed? Collecting data from educational organizations is not an easy and quick task. Therefore, if for universities we managed to introduce additional sections of the data collected for graduates of 2014, then for the STR they are not. What is at stake will become clear from the following table:

    Table 1. Data Sections.

    Key Results

    Finally, we proceed directly to the figures obtained. Let us look at the summary table of monitoring results for Russia as a whole:

    Table 2. General results of monitoring STRs The

    table gives an idea of ​​the order of numbers. Those who remember the previous article will immediately pay attention to the relatively low share of employment and to the level of wages, which turned out to be below the national average (I recall that among university graduates the salary is approximately equal to the average for Russia).

    But we are interested not only in the STR itself, but also its comparison with the "tower". To do this, look at the charts that allow you to compare these two types of education in Russia as a whole (for graduates of the "tower" there is no data on employment in the year of graduation):

    Figure 4.Hereinafter, data are given for all graduates except those who continued their studies (unless otherwise indicated).

    Figure 5.

    Figure 6.

    Several conclusions can be drawn from the figures:

    1) The more years have passed since the release, the greater the share of employment and salary. By the way, note that open source software has a higher growth in the share of employment over time. There is a hypothesis that this is due to the large number of graduates leaving the army after graduation. But in this article we will not dwell on it. In addition, as mentioned above, an analysis of the dynamics of indicators over the years is the topic of our next article.

    2) Graduates of higher education have higher salaries and the share of employment. The result is quite expected, and the salary gap is almost 1.5 times, this is even more than the “headhunter” one.

    3) VET graduates are younger than VO graduates by about 4 years. The average age itself is quite high: 22.5 and 26.5 years, respectively. This should not be confusing: firstly, not everyone gets an education right after school, and secondly, among university graduates there are many who receive a second higher education.

    That's all, it would seem. The graphs above show a comparison of two levels of education. We got a very specific result - university graduates are better placed in jobs, receive higher salaries. But the strong difference in the age of graduates, the differences between specialties, as well as our geographical surveys at the very beginning of the article say that it was only the average temperature in the hospital, and it is impossible to compare the STR and the HE like that directly. Well, let's try to consider the issue in more detail.

    Detailed comparison of HE and STR

    We turn to the main thing - a detailed comparison of the two levels of education. The forehead comparison does not work, as we saw above. So it is necessary to select those segments of graduates of HE and STR that we can correctly compare with each other.

    The next section will describe the comparison methodology, the most impatient can skip it and go directly to the results .

    Data preparation

    Comparing graduates of higher education and vocational schools, we compare people who not only received different education, but also have different socio-demographic characteristics:

    1) High rates of the "tower" can be largely due to the dominance of this type of education in Moscow and St. Petersburg - cities with good ( relative to other regions) the situation on the labor market, where there are more opportunities and higher salaries. Therefore, it is necessary to adjust the calculations taking into account the region of employment of the graduate. We will take this feature into account in our metric used for comparison (see below).

    2) Among university graduates, many have received a second higher education, as well as those studying in absentia or "in the evening." Both of these groups have an obvious advantage, since at the time of graduation from the university they most likely already have work experience, that is, they start their careers not from scratch. This means that it is necessary to remove from the sample all those receiving not the first higher.

    3) Among graduates of high schools there are foreigners whose employment results rarely have a positive dynamics on average. So, we need to remove all foreigners from the sample.

    Thus, we need to select graduates who meet the following conditions: citizens of the Russian Federation, full-time students who have received education for the first time. This will allow a slight alignment of socio-demographic characteristics in both samples.

    As can be seen from Table 1 , we have all these data (citizenship, obtaining a second higher education, a form of training) for graduates of the Higher School of Education in 2014, but not for graduates of STR. However, this is not critical in view of the following features:

    • unlike the students of the “tower”, of all those receiving STRs, according to official statistics, only about 16% study non-full-time;
    • getting a second secondary vocational education is a much rarer situation than getting a second higher education;
    • the number of foreign students in the system of secondary vocational education and at all fluctuates in the area of ​​error.

    Therefore, it can be assumed that graduates of open source software satisfy this selection by default and in full, and we select only those who fit the conditions described above from university graduates. And further, unless otherwise indicated, we will mean by “graduates of HE” precisely “filtered” graduates.

    Let's see if this selection gave the effect we need (I remind you that such filtering was possible, starting only with the 2014 release):

    Figure 7.

    It can be seen from the age graph that we are already comparing categories of citizens that are much closer to each other. But, despite the fact that the average age of the samples is now closer to each other, this is not enough. Firstly, the difference is still more than a year, which is quite a lot, and, secondly, graduates very different in age can still be found within the sample.

    So, we need to look for cases where both graduates of both high school and secondary vocational education graduate at approximately the same age. The duration of training is mainly responsible for the qualification of a specialist (bachelor, master, mid-level specialist, etc.).

    For those who are interested in exactly how qualifications affect the duration of their studies, you can take a look at this Gantt chart.

    Рисунок 8. Так как речь идет о выпускниках 2013-2014 годов, на схеме присутствуют и отмененная ныне интернатура, и специалитет. На схеме приведены только наиболее популярные варианты продолжительности обучения на различных квалификациях и уровнях образования.

    The graduate specialty also affects the duration of training. In addition, it seems obvious that it is necessary to compare graduates working in approximately the same areas (it is strange to compare cooks with a medical professional, even if they completed training at exactly the same age).

    To summarize, we will compare graduates of the same specialties, whose age at the time of graduation is approximately the same: they spent the same amount of time studying and begin their careers conditionally "from scratch." That is, it is necessary to find such combinations of specialties and qualifications for which the age of graduates would not differ much (for a permissible take a discrepancy of 1 year). It turns out a kind of INNER JOIN of graduates of high school and vocational education on the condition of equality of specialty and age of graduation.

    To exclude emissions, we remove from the comparison the pair “specialty-qualification”, according to which there were less than a hundred graduates in one of the educational levels. Then 54 pairs will participate in the comparison.

    Comparison metric

    As we remember from the last article, we have two main indicators of employment - the average wage and the share of employment. For an objective comparison, it would be nice to consider both of them. At the same time, wages must be taken into account as adjusted to the average wage of the region in which the graduate was employed. The point here is not only in the high salaries of residents of metropolitan cities, but also, for example, in the high average salaries of the northern regions. A graduate receiving 50 thousand in Rostov and Kamchatka is two big differences.

    Thus, the assessment of employment will be considered for each pair of "specialty-qualification" according to the formula:


    3Pi- the salary of graduates in this specialty and qualification in the i-th region of employment;
    • n - the number of regions in which graduates of a given specialty and qualification were employed;
    • DT - the share of employment for this specialty and qualification in Russia as a whole.
    Этот показатель хорошо бы считать для каждого региона отдельно, но в данном случае мы не можем сделать это корректно. Выпускники мигрируют между регионами, а отслеживать миграцию мы можем только среди трудоустроенных выпускников. Сколько приехавших в регион выпускников осталось нетрудоустроенными, мы не можем знать, а, значит, не можем посчитать ДТ для отдельного региона.

    • Wed ЗП - the corresponding average salaries for 2015 by region and in Russia as a whole (according to Rosstat).

    In simple words: we adjust the salary of graduates in each specialty and qualification to the level of salaries in the region in which they were employed, and to the share of employment of graduates of this specialty.

    Comparison results

    Finally, the results of the comparison: in general, the distribution of job scores, as expected, is in favor of higher education. First, let's look at their distribution:

    Figure 9.

    But judging by the schedule, the advantage of VO cannot be called devastating. Therefore, we will look at these tables for a better understanding of the situation:

    Table 3. To save space in the post, we output only the best and worst lines.

    The full version of the table is available here. The table is grouped so that you can conveniently compare the results by specialty. An interactive version of the table in the first comment.
    It can be noted that in some cases the age of graduates of a basic level of training is higher than that of graduates of a higher level. Most likely, this is due to the peculiarities of the duration of training in specific areas of training within the framework of the relevant SSES.

    As expected, for most (but not for all) specialties, higher education graduates received a higher rating. In seven cases, representatives of STRs “won”, and in seven more the advantage of the “tower” is quite small (up to 2 thousand rubles). Thus, we can say that there are such specialties for which secondary vocational education in which in the general case is no less “profitable” than higher education.

    Naturally, this is only a comparison within the framework of existing indicators. Of course, in each case it is necessary to understand individually. The first (like any other) line of the table should not be perceived by nuclear students as proof of the incorrectness of the choice of educational level :). It is also necessary to remember that the equality of specialties between the two levels of education means only the general sphere of activity, but not the absolute identity of the acquired professions.

    Comparison of graduates of one university

    We could not help but include in the article a kind of “bonus track” - an analysis of universities that study according to the same UGSN both in HE and SPE programs. Suddenly it happens that graduates of open source software work better than their peers from a literally neighboring audience?

    Let's go along the beaten track and find such cases when the age of graduates of both levels of education is approximately the same. Only this time, instead of qualifying, we will use the university itself. In addition, now there is no need to take into account the region of employment, so we restrict ourselves to the share of employment and the average wage. We will also exclude too small issues (the division in pairs of "specialty-university" is smaller than in pairs of "specialty-qualification", therefore we take not 100 people for the threshold value, but 30).Just in case, I would like to warn applicants and their parents that these results should not be taken as the only right guide to action when choosing "university or college?"

    According to tradition, at first the distributions, which again go in favor of HE, and again the advantage does not seem critical:

    Figure 10. Distribution of the share of employment among university graduates studying both in HE programs and in STR programs.

    Figure 10. Distribution of the average salary among university graduates studying in both HE and SPE programs.

    And here is the list of such universities:

    Table 4. The

    full version of the table is available here.

    The situation is similar to that which was when comparing the pairs "specialty-qualification". The general “victory” is again for VO. However, the fact that some specialties of STRs managed to get around VO both in terms of employment and average wages seems a very interesting fact. I hope this table does not demotivate future agricultural specialists from KSTU :)


    We briefly acquainted you with the results of monitoring the employment of graduates of secondary vocational education organizations and made a small comparison with the results of similar monitoring on the "tower". We do not get tired of reminding that this is only one of the possible comparison methods, and we welcome everyone who decided to use our data for independent analysis (we recall once again the address of our portal - graduate.edu.ru ).

    One thing is for sure, despite all the assumptions: the STR loses in, but not “dry.” We must not forget about the "black" and the "gray" salaries. It is likely that graduates of STRs have a significantly greater role in generating income, which may reduce the advantage of HE.

    Unfortunately, so far we have to ignore in our comparisons one of the most important factors - the dynamics of changes in employment indicators. For example, the rapid growth of wages may well compensate for its low initial level.

    We hope that the monitoring project will continue and will develop in subsequent years, which will allow us to track the dynamics and a larger number of sections. Thanks for attention!

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