Economic Analysis, Forecasts

Monthly Bulletin of Economic Trends I January 2020

Macroeconomic trends in Hungary
Hungarian economic tendencies will be presented in the article below via an overview of the most important macroeconomic indicators such as GDP, employment, gross wages, investments, industrial production and foreign trade, from directly after the crisis to 2019.

In 2009 the Hungarian economy found itself in a remarkably deep crisis. The recession was almost as severe as the transformational crisis (1991-1995) caused by the regime shift. The crisis resulted in plummeting economic performance - GDP fell 6.5% by the end of the year 2009. This downward tendency slowed down in the first half of 2010, turning into growth in mid-2010, and in the second half of the same year the growth rate was back at the pre-crisis level. Then in 2011, owing to the crisis of the Eurozone, the international economic environment became quite unfavourable again.

The Hungarian economy relapsed in 2012, with GDP dropping by 1.5%. Finally, recovery came in 2013 with a growth rate of 2.2%, and the next year saw a 4.1% growth year-on-year. There was a mild slowdown in 2015 and 2016 with growth rates of 3.5% and 2.2% respectively, followed by a surge to 4.1% in 2017. 2018 was a top year when GDP growth shot up to 5.1%. The first three quarters of 2019 saw similar growth rates. In the first two quarters, economy grew by 5.2%, and in the third quarter the rate was somewhat lower at 4.8% compared to the same period of the previous year.

Recovery after the crisis was much slower in Hungary than in its number one target country for exports, Germany. On all accounts, the Hungarian crisis was much deeper than the one Germany had to recover from. Furthermore, recovery in Hungary could only start later than in Germany. Although recession affected the two economies at an equal strength and at an equal speed, in the first quarter after the turning point in 2009 the German economy could recover remarkably quickly. By early 2011 the German economy had been back at pre-crisis levels and has grown almost unintermittently ever since. Hungary, on the other hand, had to deal with a prolonged recession, only reaching pre-crisis levels in the third quarter of 2014. The growth rate difference between the two economies levelled out between the first quarter of 2016 and the fourth quarter of 2017, and in 2018 the Hungarian growth rate spiked up and overtook that of Germany. In 2019 the Hungarian growth rate difference was 6-7% over Germany.

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Mellékletek:
MBET_20201

Gazdasági Havi Tájékoztató - 2020. január

Megjelent az MKIK Gazdaság- és Vállalkozáskutató Intézetének havi tájékoztatója.
A tanulmányokat a mellékletekben olvashatják magyar és angol nyelven.

Mellékletek:
GHT 2020 január
MBET January 2020

Monthly Bulletin of Economic Trends | July 2019

Corporate reactions to the raise of the minimum wage/guaranteed minimum salary of qualified staff

Our brief analysis examines the nine potential measures that can be reactions to the affects of the January 20191 raise of the minimum wage/guaranteed minimum salary for qualified staff. CEOs were asked to fill in the form below.

The raise of the minimum wage to HUF 149,000 and the guaranteed minimum salary of qualified staff to HUF 195,000 have resulted/will result in the following measures at your company in 2019:

wages of those earning above the minimum wage are also increased to avoid wage pressure
planned staff recruitment is cancelled
redundancies are made
projected investments are postponed
employees entitled for a raise are given new duties
employees entitled for a raise are reorganised to do part-time jobs
other benefits (e.g. perks) of employees involved are cut
variable pay (e.g. bonus) is decreased
prices are increased

Of the above measures, CEOs generally preferred to increase prices: More than one third (38%) of them have opted for that solution or responded to increase prices later this year. 32% of respondents reported the cancellation of planned staff recruitment. 30% of CEOs have given - or are planning to give - a raise this year to employees earning above the standard minimum wage in order to avoid a wage pressure. One quarter (25%) of the surveyed companies are planning to postpone projected investments. 15% and 13% of companies respectively chose to decrease fringe benefits and variable pay (e.g. bonuses). About one in ten businesses (12%) will redirect employees to part-time employment.or modify the duties of those eligible for a raise (11%). Redundancy was the least common reaction, performed by only 5% of surveyed companies.

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Mellékletek:
MBET 2019 July

Monthly Bulletin of Economic Trends | August 2019

Results of the July 2019 IEER Quarterly Business Climate Survey

The Quarterly Business Climate Survey of IEER is based on the survey of 400 CEO respondents about their business situation and expectations. According to the records taken in July 2019 the level of business confidence in Hungary decreased slightly compared to April 2019.

In July 2019 the Quarterly Business Climate Index dropped from 39 points to 33 (see Figure 1).

MBET August 2019

The Quarterly Business Climate Index was the highest for construction companies (+49 points), while for trading companies it was +43 points and for companies offering business services it was +35. Companies in the processing industry got the lowest score at +30 points. Trading companies experienced a 8 points increase quarter-on-quarter, while there was a 13 points decrease in case of companies in the processing industry compared to the previous quarter.

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Mellékletek:
MBET 2019 Aug

Monthly Bulletin of Economic Trends | September 2019

Opportunities of job automatisation in Hungary

Increased automatisation and digitalisation is regarded today as one of the most important phenomena of labour market change. Research concerning possible impacts usually start out from the presumption that for some existing tasks, human power will be replaced by machines as a result of technological development, so in those fields the demand for labour will decrease. In other fields – e.g. in the design and operation processes of new technologies – demand is expected to increase. According to estimates, the pace of automatisation will be above the European average in Central Eastern Europe, and its effects on the labour market will most probably appear in the region. HCIC IEER examined the automatability of jobs in Hungary and compared them with employment figures. The early findings of that research are presented in the following summary.

According to the results of the first research papers on the topic, automatisation primarily affects routine tasks that are made up of clearly describable and easily programmable sub-tasks. With tasks that are not repetitive, and thus can only be done by humans, robots and computers can only help in auxiliary roles. Routine tasks that are mostly manual, e.g. production, assembly of parts, conveying, sorting, etc. are the most easy to substitute, followed by more cognitive tasks like measuring, data registering, customer service etc. What is more, now even some complex tasks can be automated - made possible by the development of technologies such as machine learning and 3D printing.
However, in some fields automatisation has still not been solved, there are technical obstacles described that make it virtually impossible to automatise certain tasks. Such tasks are non-repetitive and/or abstract/complex, and they generally need skills which are non-mechanisable, such as dexterity, creative intelligence and social skills.

Employment categories in the FEOR register
As part of our research we defined the level of automatability for each job appearing in the Hungarian FEOR (Standard Classification of Occupations) register. To achieve this, we categorised the tasks listed in the FEOR job descriptions as automatable (-1) and not automatable (1). As the first step of such categorisation, we tagged automatable tasks and hindering factors with key words, and ran Zurvey, a text analysing programme, on the job descriptions to find matches for our key words. If a task contained a key word suggesting that automatisation may be hindered, we categorised it as not automatable. If there was a match for a key word describing automatability, the task was categorised as automatable. For uncategorised tasks, the keyword-based analysis was amended with manual coding.

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