Gábor Békés, economist at the Central European University (CEU) and senior research fellow at KRTK, argues that reducing policy and institutional uncertainty could give a significant boost to Hungary’s economy, which has been stagnating for nearly four years. He says that eliminating unpredictable, market-distorting measures and rent-seeking behaviour would release a large amount of suppressed entrepreneurial energy.
Why predictability matters
Békés illustrates the point with a personal example: irregular, sometimes hour-long delays on the Vienna–Budapest train force him to allocate extra time. He compares this to businesses facing unexpected special taxes, late-night laws or market-distorting subsidies. Reducing such uncertainty would allow longer-term, more efficient planning and could help close Hungary’s gap in regional productivity competitions.
Firm size and the case for regional markets
According to Békés, 2023–24 data show that Hungary has 30 domestically owned, non-listed companies with revenues exceeding HUF 100 billion, and only five of those were founded in the past ten years. He considers this number too small to generate, at scale, firms that matter at the European level. Given their limited size, he argues, Hungarian firms should prioritise expansion into neighbouring regional markets rather than distant ones: if domestic companies fail to reach sufficient scale, stronger Czech, Polish and Romanian firms could displace them at home.
Békés also notes that after the 2015 "eastward opening" policy was announced, the number of Hungarian-owned exporters to Asia declined, while the number of firms exporting at all rose by 15% by 2023. He attributes this to the distance and lack of market knowledge in Asia, which make it a risky and capital-intensive target for relatively small Hungarian firms.
What the state should — and should not — do
On policy, Békés warns against large-scale industrial subsidies that do not match domestic capabilities (for example, a risky one-trillion-forint support for battery manufacturing). Instead he prioritises:
- supporting training and retraining,
- improving infrastructure,
- redesigning EU-fund distribution to be simpler and more normative so it distorts competition less.
He suggests an example: if all companies that meet a few predefined conditions receive, normatively, AI-tokens equal to 1% of their revenues, then better firms gain more and competition is less distorted. He also favours encouraging more firms to list on the stock exchange, since public ownership enforces discipline, transparency and better corporate governance and makes the use of public funds more visible.
The state’s role is often indirect but important
Békés sees the state’s role largely as institutional and infrastructural: improving business education and management skills, and opening state data. He points to successes such as valasztas.hu and the electronic health record cloud (EESZT) as examples of digital public goods that can spur private-sector innovation.
AI: opportunity and risk
Békés identifies climate change, geopolitics and AI as the three strategic challenges facing Europe and Hungary. AI offers huge opportunities for firms but may widen disparities: countries with good education systems, openness and a culture of experimentation are likely to benefit most.
He argues that Hungarian firms should focus on adapting AI rather than on core model development. In adoption, he warns against two extremes: handing each employee autonomous AI agents or centralising adoption in a single AI guru/team. Instead, he recommends small-scale, experimental pilots in 5–15 person units. He points to late 2025 as a turning point: advances in large language models and tools like Claude Code made it possible for an average computer to process and extract information from large document sets, unlocking productivity potential.
Békés sees AI as both a labour-substituting and decision-support technology; its net labour-market effect depends on what tasks are automated versus what new tasks emerge. He expects demand for workers who use AI effectively, while human-centric occupations (e.g., nursing, psychology) may become more valued even as some administrative or marketing roles shrink.
Conclusion
For Békés, increasing predictability and cutting rent-seeking behaviour can free latent growth potential in Hungary. For firms, regional expansion is the most logical growth route; for policy, the focus should be on education, infrastructure, simpler normative access to funds and measures that support scaling and listing. In AI adoption, countries and firms with good education, openness and a willingness to experiment will gain the most.
Profile: Gábor Békés is a CEU lecturer and senior research fellow at KRTK, researching international economics, firm behaviour and productivity. His book Adatelemzés (with Kézdi Gábor) is used in 40 countries. He earned an MSc from the London School of Economics in 2000 and a PhD from CEU in 2007.
