An Examination of the Office Market in Budapest

Term Paper, 2018
27 Pages, Grade: 1,3


Table of Content

I. List of Figures

II. List of Tables

III. List of Abbreviations

1 Introduction

2 Definitions
2.1 Macroeconomy
2.2 Office market
2.3 Scoring

3 General information about Hungary and Budapest

4 Method of Investigation

5 Scoring model
5.1 Macroeconomic, political and legal conditions in Hungary
5.2 Demographic and socio-economic development
5.3 Infrastructure of the macro location
5.4 Soft location factors
5.5 Structure of the office supply
5.6 Structure of the office demand
5.7 Rental- and price level for office space in Budapest

6 Final score and conclusion

7 List of Literature

8 Appendix

I. List of Figures

Figure 1: Hungary’s age structure by sex and age

Figure 2: Motorways in Hungary

Figure 3: Map of Budapest’s submarkets

Figure 4: Annual new supply and Availability in the Pipeline

Figure 5: Split of Take-Up by Occupier Profile

Figure 6: Micromarket Map of Average Vacancy Rates

Figure 7: Range and Average Level of Asking Rents

II. List of Tables

Table 1: Comparison of political stabilities in EU countries

III. List of Abbreviations

Abbildung in dieser Leseprobe nicht enthalten

1 Introduction

In the period of low interest rates, the worldwide capital markets are flooded. To avoid that inflation lowers the value of capital, investors are forced to invest their money instead of putting it in savings books. The investment class ‘Real Estate’ became a popular alterna- tive to investing into bonds and stocks. Especially many institutional investors e.g. banks and pension funds have entered these Real Estate markets with large amounts of capital to invest. However, the financial crisis in 2009 illustrated how risky investments into these markets can be. Therefore, investors are trying to spread their investments over different regions and markets to minimize the unsystematic risk of total loss of capital when invest- ing in only one region or one market (e.g. currency decreases, natural catastrophes).1 By searching for new markets, the Eastern European countries attract many investors with promising yields. One of these markets is the office market in Budapest which is often waived but contains yields of more than 6%.2 This assignment examines the office market in Budapest. It will mainly focus on the usage of a scoring model to view and evaluate the office market from many different perspectives. In the end, one final score will represent the whole office market in Budapest in terms of its attractiveness for investments into Real Estate.

2 Definitions

2.1 Macroeconomy

Economic theory can be subdivided into micro- and macroeconomy. Microeconomy inves- tigates the decisions of individual economic subjects such as households or firms, where- as macroeconomy surveys the conjunctions between all individual economic subjects and analyses economic aggregates and phenomena such as the financial crisis in 2009.3 The most essential macroeconomic phenomena are the economic situation and the employ- ment of a country.4 Macroeconomies can be rated and compared to others by the national account system, balance of payments and other statistical vehicles such as the unem- ployment rate.5 Especially the parameters GDP and GNI which belong to the national account system are very important figures to measure the wellbeing of a national economy in comparison to other economies.

2.2 Office market

The office market is listed in the category of Real Estate submarkets separated by their type of use. It represents the submarket in which office space is traded. Furthermore, of- fice space is defined as space where generic desk activities are taking place and which is tradeable on the office market.6 Therefore, the most important market driver is the office employment and the number of office workers who are consuming office space directly.7 The office market can be separated into the supply and demand side. The supply side contains the stock of office space in a limited period of time in a defined area. It consists of all completed office spaces, regardless whether occupied or vacant.8 The demand side reflects the number of requests for spaces in a limited period of time in a defined area. Hereby it is negligible if the requests are made by potential tenants or potential owner- occupiers.9

2.3 Scoring

The term “Scoring” describes a point system which allows the operationalisation, valuation and different weighting of influencing factors with the goal of reducing complexity by ag- gregating the factors of different criteria to one single final score.10 In Real Estate portfolio management it is mostly used as a tool for measuring and comparing different investment opportunities, based on the assumption that the property with the highest score will be favoured to invest in. While most estimations are influenced by emotional and subjective beliefs, the scoring model implies a standardized, current and transparent approach to simplify the decision-making process.11 The model can be broken down into three sec- tions to reach the final score:

1. Choice of different criteria: It is very important to consider all relevant criteria for the object in the scoring model. If relevant criteria are missing or irrelevant criteria are includ- ed in the scoring, a comprehensive final result cannot be guaranteed because it may be distorted. Moreover, the criteria must be measurable to come to a quantified result. Qualitative criteria and factors are not measurable and need to be transformed into quantitative figures through assigning the factors to different valuation standards (e.g. location of an object can be rated due to school marks).12 Additionally, the quality of the data collection is important. It can be separated into internal and external sources and only safe and legit- imate sources should be used.13

2. Weighting: The weighting of each factor in each criterion and the weighting of each criterion in the final result has to be determined. The process of weighting should be orien- tated to the relevance of each factor or criterion for the object. If factors or criteria are weighted incorrectly, it could deceive the final result.14

3. Evaluation: Although scoring models seem to be very objective for a moment, espe- cially this part is based on subjective decisions. Qualitative criteria and factors do not fulfil the requirement of measurability and need to be transformed into quantitative figures through assigning the factors to different valuation classes (e.g. location of an object can be rated due to school marks).15

3 General information about Hungary and Budapest

Hungary is a landlocked country in Central Europe and is a member state of the European Union since 2004, although Hungary has not introduced the Euro as currency yet and still uses its own currency called Forint.16 The official language is Hungarian and 9.8 million people are currently living in Hungary, more than 1.7 million of it in the capital city Buda- pest which is located at the Danube river.17 Budapest can look back on a glorious history. Due to the classical composer Franz Liszt and his effect on the classical scene in Hunga- ry, it rose to fame as a classical centre in Eastern Europe.18 Shortly after this in 1871, Bu- dapest, as we know it today, was finally founded by the unification of the three cities Óbu- da, Buda and Pest.19 The capital city has been able to transfer its gloss level over time and was rated the 6th most popular tourist destination in Europe and the 25th most popular in the world in 2016.20 Furthermore, the Hungarian Parliament is located in Budapest and currently domiciles the ‘Third Orban Government’ which is responsible for many contro- versial disputes in the EU due to its right-populistic policy against democratic principles and human rights.21

4 Method of Investigation

The following scoring model for the examination of the office market in Budapest will be based on the highly regarded scoring model presented in “Entwicklung eines Immobilien- Portfolio-Management-Systems” which was published by Wellner in 2003. Because this seminar paper investigates the office market and not one single property, only the market dimension will be implemented in this scoring and the object dimension will be waived. All criteria from the template are adopted, but some factors were removed or replaced by other factors. If a factor is removed, its weighting will be equally distributed to the other existing factors to avoid modifications in the weighting proportions. While the first four cri- teria are investigating the general conditions in Hungary and Budapest, the last three cri- teria are directly examining the office market. Additionally, the weightings of all criteria in the final score were fully adopted from the empirically proven template of Wellner. To keep the paper in scope, the scoring model contains only the written explanations to the evaluation of the factors. The scores for each factor and criterion can be looked up in the scoring chart in the Appendix (see page 22, Chapter 7: Appendix).

5 Scoring model

5.1 Macroeconomic, political and legal conditions in Hungary

Whereas Wellner investigates the ‘regional development’ and ‘promotion of the economy’, these factors have been replaced through the factors ‘legal conditions, law enforcements and control of corruption’ as well as ‘political stability’. This replacement was undertaken because the legal and political aspects were not considered in the template of Wellner but may have a large impact on the market attractivity for investors.

Even though Hungary is a member of the EU, it has its own currency called the ‘Hungari- an Forint’. However, the Forint is heavily dependent on the Euro due to strong trade links. Accordingly, the monetary policy by the Hungarian Central Bank complies with the policy of the ECB. As a result, the interest rate for loans is on a record low of 0.9% and offers

Table 1: Comparison of political stabilities in EU countries

Abbildung in dieser Leseprobe nicht enthalten

great financing condi- tions for investments.22 Also the exchange rate risk seems to be low because the Hungarian Forint is very valueless by an euro exchange rate from 314.40 Forint for 1 Euro.23 This can be seen as an opportunity for foreign investors to invest now for a relatively cheap pur- chasing price at a weak Forint and receive rents which may increase due to a possible improvement of the exchange rate. The currency fluctuations of the Forint may also be influenced by the political situation in Hungary. In a ranking of the World Bank in which political stability as well as the absence of violence and terrorism were investigated, Hun- gary reached a score of 0.71 while a score of 1 would be the best and -1 the worst possi- ble score.24 Hungarians result may be seen as quite good by comparison to France (-0.06), Germany (0.76) or other European countries which mostly performed worse.25 Unfortunately, this result is from a study in 2016 and therefore the controversial policy of Hungary’s prime minister Orban and his populistic party is not included.26 Considering his collision course with the EU in topics like the refugee crisis and democratic principles, the results have to be relativized.27 Even a Hungarian withdrawal from the EU seems possi- ble, which would lead to a drastic change of the whole economic situation. Due to this image loss and the following unsure forecasts about the political stability many interna- tional investors may avoid investments into Hungary and Budapest. Therefore, this factor was rated with a score of only 35 in the scoring model.

However, the legal conditions are still very similar to the common conditions in other Eu- ropean countries due to the long membership in the EU and the contractual commitment to its regulations and prescriptions. No legal differences in the Real Estate business are identifiable.28 Although if the legal conditions seem good for investments, the law en- forcements are a problem. In another ranking of the same report of the World Bank, Hungary, with scores of 0.51 for law enforcements and 0.08 for control of corruption, does poorly in comparison to the average.29 Therefore, the good legal conditions cannot be pushed through court when it comes to law disputes which occur often in the Real Estate business. However, the current situation of the macroeconomy is of great importance for the success of an investment, because the tenants of office buildings are typically partici- pants of the macroeconomy. Therefore, a crisis may lead to vacant spaces and missing cash flows which are essential for the success of an investment. With a GDP of $26,701 per capita, Hungary ranges in the category of Greece, Poland and Turkey but far behind larger economies like Germany ($48,943/capita) and France ($41,364/capita).30 Surpris- ingly, the Hungarian economy is booming in recent years. This fact can be seen by taking a look at the Real GDP which defines the market value of all final goods produced in a country within a period of time measured at specific year’s average prices. The Real GDP of Hungary accounts to 3.91% in 2017 while the average in the OECD states estimates to 2.36%.31 This development may probably be a result of Hungary’s benefit from the EU aid money period which started in 2014, of a dropping unemployment rate to a record low of 3.9%32 as well as of the improved prospects of many firms.33 The main industries in Hun- gary are Automotive, Electronics, Pharmaceutics, Telecommunications & IT and the food industry.34 However, large typical office tenants (for example from the finance or insurance sector) are missing.

5.2 Demographic and socio-economic development

Investments in Real Estate are predominantly long-term investments because of its limited fungibility and its long holding periods. By analysing the demographic and socio-economic developments and forecasts investors become able of assessing long-term risks because both criteria belong to the category of hard location factors which cannot be influenced drastically. The factors ‘social structure’ and ‘educational level’ must be waived to reduce the complexity of this criterion.

The socio-economic situation can be measured by the unemployment rate and the in- come. The unemployment rate has decreased since 2013 from 12% to 3.9% in 2018.35 However, in the OECD rating of household net adjusted disposable incomes, Hungary ranks on place 32 from 38 participants. The income amounts to $16,821/capita which is nearly half of the OECD average of $30,563/capita.36 This shows, that many people are not paid fairly and legal regulations like minimum wages do not exist. The employment for minimum wages may also be the main rea- son, why so many Automotive and Electronic companies are produc- ing in Hungary. Additionally, the price plateau is 42% under the EU average and Hungary ranks on the 25th of 28 member states.37 Thus,living costs are comparatively low compared to the EU average which can be rated as positive in the scoring model.

Figure 1: Hungary’s age structure by sex and age

Abbildung in dieser Leseprobe nicht enthalten

In Hungary, the population growth rate is, with a score of -0.25%, negative. This means that the population is shrinking slightly, approximately about 4,000 people per month.38 This may also affect a decline of office workers in the long-term if the economic situation will stay similar. This approach may be enhanced by the age structure in Hungary which shows that in the next years many workers of the large generation between 58 and 62 (see Figure 2, above) 39 will retire at the Hungarian retirement age of 62 years and 6 months.40 Moreover, this development may end up in a pension financing problem. There- fore, a large demographic risk is already noticeable.


1 See Feik (2008), p. 53.

2 See Deka (2017b).

3 See Conrad (2017), p. 3.

4 See Engelkamp, Sell (2013), p. 158.

5 See Engelkamp, Sell (2013), p. 195.

6 See Dobberstein (1997).

7 See gif (2015), p. 6.

8 See gif (2004), p. 3.

9 See gif (2004), p. 4.

10 See Wellner (2003), p. 180.

11 See Füser (2001), p. 37.

12 See Wellner (2003), p. 205.

13 See Wellner (2003), p. 190.

14 See Wellner (2003), p. 194.

15 See Wellner (2003), p. 205.

16 See European Union (2018).

17 See VIENNA (2016).

18 See Friedrichs (1985), p. 637.

19 See Molnâr (1971), p.72.

20 See Euromonitor (2016).

21 See Tagesschau (2018).

22 See Magyar Nemzeti Bank (2018).

23 See Magyar Nemzeti Bank (2018).

24 See World Bank Group (2016).

25 See World Bank Group (2016).

26 See Tagesschau (2018).

27 See Deka (2017b), p. 11.

28 See CBRE (2017), p.3.

29 See World Bank Group (2016).

30 See Aggregate National Accounts, OECD (2017).

31 See OECD Economic Outlook (2018).

32 See Hungarian Central Statistical Office (2018).

33 See Schulte (2018), p.1.

34 See EUGO (2016).

35 See Hungarian Central Statistical Office (2018).

36 See OECD (2018).

37 See Eurostat (2015), p.1.

38 See Hungarian Central Statistical Office (2018).

39 See Hungarian Central Statistical Office (2017).

40 See Central European University (2018).

Excerpt out of 27 pages


An Examination of the Office Market in Budapest
University of Applied Sciences Aschaffenburg
Catalog Number
ISBN (eBook)
Real Estate Budapest Office Market Invest Immobilien Büromarkt Ungarn Hungary
Quote paper
Marvin Greim (Author), 2018, An Examination of the Office Market in Budapest, Munich, GRIN Verlag,


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