Publications

illustration: GEOpolitics

In October 2025, the Government of Georgia announced a higher education reform, which was presented as a response to seven key challenges identified within the sector. Among these challenges is the mismatch between the supply of higher education and labor market demand, which serves as the main justification for one of the most significant proposed changes - the centralized determination of student admission quotas for academic programs in public universities.

The Ministry of Economy and Sustainable Development, with the involvement of the Ministry of Education, Science and Youth, conducted labor market research. The findings of this research were publicly presented by Irakli Kobakhidze in February 2026. During the presentation, Kobakhidze stated that, according to the study results, the optimal number of students to be enrolled annually is 14,400, while approximately 32,000 students were admitted to higher education institutions in 2025. The study also showed that in several sectors there is an oversupply of individuals with higher education, whereas the labor market typically requires a greater proportion of vocational or general education. The findings further indicated a surplus of graduates in law, economics, social sciences, and humanities, while shortages were identified in fields such as nursing, construction, education (teaching), and energy. According to the government, quotas have been redistributed accordingly.

In recent months, Gnomon Wise has published several papers examining the potential risks that this higher education reform may pose to institutional autonomy and academic freedom. These analyses explore how the reform could undermine these principles. Beyond these concerns, it is equally important to assess the underlying document upon which the government based its decision to expand its authority in this manner. Namely, the key question is whether the labor market study genuinely supports the government’s conclusions and whether it justifies the centralized determination of quotas in public universities.

Methodological Limitations of the Presented Labor Market Research

Within the scope of the study, the entire public sector and 12,500 private enterprises were surveyed to assess labor demand. In addition, a macroeconomic forecasting model developed by Cambridge Econometrics was utilized. According to the authors, the study also accounts for the effects of major infrastructure projects such as the Anaklia Port and the Black Sea submarine cable. During the presentation, Irakli Kobakhidze stated that the study aligns with “best international practices,” including those of organizations such as the International Labour Organization (ILO), European Training Foundation (ETF), and European Centre for the Development of Vocational Training (CEDEFOP). However, based on the presented materials, lacking underlying quantitative data and technical parameters, it is difficult to conduct a comprehensive evaluation of the study. Moreover, concerns arise from the fact that the study was published after quotas had already been determined, limiting the possibility of validating its findings and engaging in evidence-based discussion. Notably, CEDEFOP itself emphasizes in its methodological guidance that public policy should not rely solely on economic forecasts, and that such projections should be considered as one input within a broader policy deliberation process.

According to the study, demand for individuals with higher education in the public and private sectors over the next five years will total 64,095. Since neither the published report nor Kobakhidze’s presentation included a detailed technical account of how the analysis was conducted, it can be inferred that overall employment growth was first estimated using the macroeconomic model, and then demand for higher education graduates was distributed based on survey data from public and private sectors. However, such surveys primarily reflect current labor demand, which is a weak basis for long-term forecasting. For example, a logistics company manager stating a need for two transport engineers is describing a present operational gap, not necessarily the sector’s needs five years ahead.

According to the presentation, the authors linked macroeconomic projections to the “National Qualifications Framework and the Classification of Fields of Study.” In doing so, they used the International Standard Classification of Occupations (ISCO) to map professions to educational fields. However, this tool provides only a general framework and fails to capture the complexity of real-world labor market dynamics. For instance, some graduates in law, economics, or social sciences may be employed in positions that, according to the study, do not formally require such degrees. A risk analyst or policy researcher with a law degree may not fall into any of the predefined categories. As a result, the finding that out of 3,598 law students only 678 graduates are needed annually presents an incomplete picture.

To address this informational gap, methods such as Process Tracing could be applied. This qualitative research tool allows for tracking graduates’ career trajectories over time and identifying where and in what positions they are employed several years after graduation. It enables the construction of causal pathways linking academic training to professional outcomes. For example, a philosophy graduate working as a data analyst or policy researcher might be incorrectly categorized in the government’s model as someone who “failed to use their degree,” whereas in reality, the analytical and research skills acquired through that discipline enabled their employment. Without such data, it is impossible to determine whether, for instance, an oversupply of sociology graduates is real or merely assumed. Kobakhidze’s claim that graduates are “doomed never to use their degree professionally” is therefore not sufficiently supported by the available data.

Furthermore, the study presents labor demand at a highly disaggregated occupational level. Methodologically, the narrower the forecasting category, the higher the probability of error. While it may be feasible to project overall growth in the information technology sector, it is far more difficult to assert that the market will require exactly 125 database administrators rather than,artificial intelligence specialists, for example.

This issue becomes even more problematic when considering the time dimension. A student enrolled in 2026 will enter the labor market in 4-6 years, by when, the economic landscape is likely to have changed significantly. Moreover, sectors that will be prominent in 2030 or 2035 may not yet exist or may currently be underdeveloped, and thus are not captured in the study. For instance, in the 1970s and 1980s, the South Korean government invested in engineering and computer science education when semiconductor production was still minimal. Any labor market study at that time would have failed to identify demand in this field. Instead, the government developed human capital ahead of market demand, and the industry subsequently absorbed it. While this does not imply that market signals should be ignored, it demonstrates that policies based solely on current demand, risk overlooking future opportunities. Employers cannot demand specialists for sectors that do not yet exist or are only emerging.

This dynamic is also evident in Georgia’s information technology sector. The study identifies it as one of the fastest-growing sectors, with 51,018 employees and an annual growth rate of 8%. Had the study been conducted 10 years earlier, when the sector was still underdeveloped, it would have indicated low demand. Based on such findings, the state might have restricted quotas, thereby hindering the sector’s development. Instead, some students pursued computer science and the industry naturally formed and expanded around this emerging human capital.

It is also noteworthy that time operates differently in education systems. Establishing or closing academic programs, building faculties, and accumulating research capacity takes years, sometimes decades. Therefore, decisions to reduce program capacity are complex and, in most cases, fall within the domain of university autonomy. Even in exceptional cases where the state intervenes, it must share responsibility with universities for ensuring that future labor market demand in that field will not increase; otherwise, such decisions risk becoming irreversible mistakes in the short to medium term.

Demand and Supply in the Labor Market

The authors of both the reform and the labor market research frame the mismatch between the labor market and higher education not as a demand-side issue, but as a supply-side problem. This approach is particularly noteworthy given that the labor market study itself primarily examines only the demand side, by asking managers which types of employees they need. However, academic research suggests that when individuals with higher education are employed in sectors where vocational or general education would typically suffice, this may indicate that the economy lacks the capacity to absorb highly qualified labor. In such cases, instead of encouraging investment in high-technology and innovation-driven sectors, the imposition of quotas on higher education aligns the education system with an existing, less productive economic structure.

Since Georgia’s economy currently relies largely on medium- and low-skilled labor, such a study may be useful for shaping vocational education policy. However, it is less suitable as a basis for the long-term development of higher education. Artificially aligning universities with current labor market conditions risks preserving and effectively freezing the existing economic structure. If the goal is to develop a high-productivity economy and stimulate new sectors, restricting the supply of higher education will only reduce the country’s potential to build a more advanced and complex economic system. Thus, placing the burden of adjustment solely on the education system overlooks the role of both the private sector and public policy in creating demand for highly skilled labor.

Conclusion

The labor market study presented in February 2026 may provide insight into current employer needs and sectoral demand. However, its limitations raise serious questions about the validity of using it as a basis for centrally determining university quotas. The study relies heavily on managers’ subjective expectations and present-day operational gaps, which do not adequately reflect long-term economic development trends. Moreover, the use of existing classification systems provides only a limited basis for linking specific degrees to specific occupations. This approach overlooks the interdisciplinary nature of higher education and the fact that graduates often apply their knowledge across a wide range of fields.

In addition, the study treats the mismatch with the labor market solely as a supply-side issue within the education system. In reality, if highly qualified individuals are employed in low-productivity sectors, this may reflect the economy’s inability to absorb knowledge, rather than an oversupply of graduates. Artificially restricting higher education to match current demand risks locking the country into its existing economic structure and limiting its capacity to develop new sectors.

To sum up, while the need for reform in Georgia’s higher education system is real, policy decisions based on this study may be detrimental to long-term intellectual capital and cannot be considered fully evidence-based. It is unlikely that restricting educational supply in line with current demand will resolve unemployment challenges. On the contrary, such an approach may hinder the country’s ability to build a high-productivity economy, one in which the knowledge generated within universities serves as a key driver of development.

For the complete document, including relevant sources, links, and explanations, please see the attached file.