report on the situation in the residential and commercial ... · anna krawczyk regional branch in...

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Report on the situation in the

residential and commercial real

estate market in Poland in 2016.

Economic Analysis Department

Warsaw, 2017

The Report has been prepared at the Economic Analysis Department for the purposes of

NBP authorities. Opinions expressed in this report are opinions of the authors and do not

present the point of view of the authorities of Narodowy Bank Polski.

3

The Report has been prepared under the guidance of:

Jacek Łaszek Economic Analysis Department

with editorial assistance of:

Piotr Boguszewski Economic Analysis Department

Jarosław Jakbubik Economic Analysis Department

Piotr Szpunar Economic Analysis Department

Authors (chapters 1-4):

Hanna Augustyniak Economic Analysis Department

Jacek Łaszek Economic Analysis Department

Krzysztof Olszewski Economic Analysis Department

Joanna Waszczuk Economic Analysis Department

Monographs (underlined persons are also authors of parts of chapters 3-5):

Grażyna Baldowska Regional Branch in Warszawa

Ewa Barska Regional Branch in Bydgoszcz

Ewa Białach Regional Branch in Lublin

Henryk Borzym Regional Branch in Olsztyn

Izabela Czapka Regional Branch in Katowice

Paweł Decyk Regional Branch in Gdańsk

Krystyna Gałaszewska Regional Branch in Gdańsk

Izabela Hulboj Regional Branch in Zielona Góra

Jarosław Kiernicki Regional Branch in Bydgoszcz

Anna Krawczyk Regional Branch in Olsztyn

Barbara Krzemieniecka Regional Branch in Zielona Góra

Jolanta Książczyk Regional Branch in Łódź

Magdalena Kulig Regional Branch in Poznań

Andrzej Jakubowski Regional Branch in Warszawa

Robert Leszczyński Regional Branch in Białystok

Barbara Mach Regional Branch in Rzeszów

Łukasz Mach Regional Branch in Opole

Małgorzata Masiak Regional Branch in Wrocław

Łukasz Mikołajczyk Regional Branch in Opole

Maciej Misztalski Regional Branch in Wrocław

Renata Modzelewska Regional Branch in Warszawa

Urszula Mogielnicka Regional Branch in Lublin

Barbara Myszkowska Regional Branch in Warszawa

Zbigniew Opioła Regional Branch in Katowice

Sławomir Orliński Regional Branch in Kielce

Grażyna Osikowicz Regional Branch in Kraków

Jacek Perczak Regional Branch in Kielce

Kinga Przewoźniak Regional Branch in Kraków

Anna Stołecka Regional Branch in Rzeszów

Anna Tomska-Iwanow Regional Branch in Szczecin

Robert Tyszkiewicz Regional Branch in Łódź

Marta Zaorska Regional Branch in Szczecin

Hanna Żywiecka Regional Branch in Poznań

Summary

Summary

Table of contents

Summary ....................................................................................................................................................... 6

1. Introduction .............................................................................................................................................. 8

2. Real estate market sector ....................................................................................................................... 11

3. Developments in the residential real estate market in Poland in 2016 ........................................... 18

4. Trends in the commercial real estate market in Poland in 2016. ..................................................... 48

5. Convergence and differentiation processes observed in Poland’s local markets .......................... 58

Glossary of terms and acronyms .............................................................................................................. 75

List of abbreviations ................................................................................................................................... 79

Summary

Narodowy Bank Polski 6

Summary

In 2016 the residential and commercial real estate sector saw the following developments and

trends:

Average prices per 1 square meter of housing, both offer and transaction prices in the

local primary and secondary markets in Poland, were stable in the first half of the year

and increased slightly in the second half of the analysed period. The highest prices were

recorded in the primary and secondary markets of Warszawa and the six largest

voivodship cities (6M), especially in Gdańsk. The highest prices were noted in particular

in the case of transactions involving small dwellings (with an area up to 40 square meters)

and large dwellings (with an area exceeding 80 square meters). On the other hand, in the

market of the remaining 10 cities (10M) the highest prices per square meter of housing

were recorded in the case of small dwellings.

A rise in average rents (both offer and transaction rents) per square meter of housing was

observed. This may encourage wealthier households to purchase rental housing in the

future.

At the current level of rents, persons investing in rental housing have earned rates of

return exceeding yields on bonds or bank deposits and close to the rate of return on

investments in commercial real estate. It should be noted, however, that there is

significant difference in liquidity, transaction costs and risk between bank deposits and

investment in rental housing.

The primary market of the analyzed cities saw a significant rise in demand and supply.

High demand for housing was driven by growth in household wages, the persistence of

historically low nominal interest rates (on both deposits and loans), continuation of the

government-subsidized housing scheme MDM and its announced discontinuation after

2018. As a result, growth was noted in a number of developer dwellings purchased for

own housing needs and for investment purposes.

In 2016 growth in lending was positive and stable. Interest rates on mortgage loans and

growth in real household disposable income exerted a positive impact on

creditworthiness of households. Household receivables resulting from housing loans in

December stood at PLN 394.3 billion posting an increase by PLN 18.7 billion as compared

to the 2015.

The registered home selling time, both in the primary and in the secondary markets

shortened slightly as compared to the level observed in 2015. Home selling time in the

secondary market in Warszawa and 10M oscillated around 1.5-2 quarters, whereas in 6M

slightly increased and was approx. 2 quarters.

In 2016 approx. 163 thousand dwellings were completed and made available for

occupancy (10.2% y/y), the construction of approx. 174 thousand new housing

investments was commenced (3.3% y/y) and approx. 212 thousand building permits were

issued (12.0% y/y). The number of completed dwellings and new starts reached a record

Summary

Report on the situation in the residential and commercial real estate market in Poland in 2016. 7

level; yet, due to high demand and sales level no oversupply was noted in the housing

market.

In 2016, the rising demand in the housing market had a favourable impact on the

situation of real property developers. The estimated share of developers’ profit in the

price of new housing continued at a high level. The factors enabling real estate developers

to earn high rate of return on equity were the following: the structure of offered housing

matching the preferences and financial possibilities of home buyers, low and stable prices

of construction and assembly works in 2016 and persistently high number of sold

dwellings. The BaRN survey results show that the price of land for multi-family

construction in the largest cities increased slightly in year-on-year terms, which may

indicate that land banks are getting exhausted due to high demand for housing. Real

estate developers continued to finance construction with their own funds, with bonds and

loans.

In the majority of local markets the indicators of economic standing of households (low

registered unemployment rate, high level of wages), their housing and demographic

situation continued to improve. The number of residents in the largest cities increased.

On the other hand, smaller cities and towns saw outflow of their population.

Demographic burden ratio continued to worsen.

In the commercial real estate market growing imbalances were observed for another

consecutive year, especially as concerns office space, which had an impact on the vacancy

ratio in large cities. Growing supply of commercial real estate may lead to rent declines

which will impact owners’ income and may make it difficult for them to repay the debt.

Foreign investors investing abroad continued to dominate the real estate market.

In 2016 transaction rents for A class office space (quoted in EUR price/square

metre/month) showed slight increase in the analysed markets. Transaction rents for B

class office space (quoted in EUR/square meter/month) in Warszawa continued on a

slight downward trend. Transaction rents charged for retail space in shopping malls

expressed in EUR/per square metre/per month were stable, yet in other voivodship cities

they continued on a slight downward trend.

1. Introduction


1. Introduction

The real estate market is of key importance for the stability of the financial system and

macroeconomic stability. Excessive credit growth and related imbalances in asset prices, mainly

real estate prices, are generally the major source of systemic risk. The most expensive financial

crises were largely the result of boom in the loan-financed real estate market1.

The residential real estate sector encompasses construction of new housing, trade in the existing

housing stock, demand for housing generated by households, affected by the financial sector and

the regulatory sector. The real estate market and other sectors of the economy are strongly

correlated; consequently, they affect the country's macroeconomic and financial situation.

Therefore, monitoring and analysis of developments in the real estate market are essential for

NBP’s macroeconomic analyses and assessment of financial stability.

The commercial real estate sector is considerably smaller that the housing sector, yet is more

sensitive to cyclical fluctuations. In contrast to the housing market, there are considerable

imbalances in the commercial real estate market. Prices and hedonic appraisals of commercial

real estate across the market are on the rise despite declining rents and rising vacancy rates.

Increase in the value of the commercial properties improves creditworthiness of their owners,

making it easier for them to incur further loans. This is supported by low interest rates, especially

in the euro area, where most investors come from. This leads to growing tensions in the

commercial real estate markets, which after a rise in interest rates, may lead to a collapse in the

market. It is therefore extremely important for the stability of the financial system to monitor and

assess the situation in the residential and commercial markets on an ongoing basis.

The aim of the Report is to present complex results of analyzes of the developments in the

residential and commercial real estate market in 2016 and to provide information to interested

entities, including real estate market participants (educational mission of NBP). The Report is also

the implementation of formal obligations imposed on NBP as a result of its participation in the

Public Statistics Research Program2.

The Report is mainly focused on the 2016 developments, but some of the analyses goes beyond

that period. It highlights the main directions of changes in the real estate markets and identifies

the factors behind these changes. The Report also draws attention to the financial capacities of

home buyers and discusses the way in which housing demand is impacted by the government-

subsidized housing scheme MDM scheduled to terminate in 2018. The authors described the

phenomenon of increased developer housing construction and stabilization of offer and

transaction prices in the primary and secondary markets in the analyzed cities. They presented

the results of surveys of rents in the home rental market being an alternative to home ownership.

They discussed the situation in the commercial real estate market, highlighting a significant

increase in the supply of commercial real estate which fails to be matched by demand, leading to

1 Crowe C. et al. [2011], Policies for macrofinancial stability: options to deal with real estate booms, IMF Staff Discussion

Note, IMF, 25 February 2011.

2 Journal of Law of 4 September 2015 item, 1304 study reference no. 1.26.09 (079) point 10.

1. Introduction


growing vacancy ratios and a decline in rents. The further part of the Report focused on factors

affecting transaction prices per one square meter of commercial space for rent and analysed

factors determining rent levels. The last issues discussed in the Report are convergence and

differentiation processes and structural changes in the 16 local real estate markets in Poland. Due

to the local nature of housing markets the Report provides an in-depth analysis of sixteen

voivodship cities and Gdynia. In further chapters some of the analyses are based on aggregate

data. Data concerning housing markets are broken down into: Warszawa, 6 cities (6M: Gdańsk,

Gdynia, Kraków, Łódź, Poznań, Wrocław) and 10 cities (10M: Białystok, Bydgoszcz, Katowice,

Kielce, Lublin, Olsztyn, Opole, Rzeszów, Szczecin, Zielona Góra). Such a break-down is justified

by the comparable size and degree of development of the real estate markets.

The analysis of offer, transaction and hedonic prices per square meter of average housing in the

primary and secondary market and the analysis of the commercial real estate market are based

on the data obtained by analysts from the Regional Branches of Narodowy Bank Polski under the

survey of the housing market Real Estate Market Database (BaRN)3 and the commercial real

estate market (Commercial Real Estate Database (BaNK). As the survey covered a variety of

agents operating in the market (agents, developers, housing co-operatives, municipal offices,

consulting companies), this allowed the authors to obtain extensive information. The study also

relied on the database of PONT Info Nieruchomości (PONT) containing data on offer home

prices, the SARFIN database of the Polish Banks Association containing data on housing market

financing and AMRON database containing data on housing appraisal and transaction prices of

mortgage-financed housing as well as data on the primary residential market of company REAS.

The authors drew on the reports issued by the Polish Financial Supervision Authority (KNF) as

well as aggregate credit data released the Credit Information Bureau (BIK). The statistical data

published by the Central Statistical Office (GUS) and analyses including sectorial data have been

used in the structural analysis4. The authors also used the results of surveys of CBOS and TNS

Polska. The information about the commercial real estate market is also based on the data

provided on a voluntary basis by commercial real estate brokers, as well as real estate

management and consulting companies. The analysis was supported with knowledge of experts

of particular agencies5.

3 See: „Programme of statistical research of public statistics for 2016. Schedule to the Regulation of the Council of

Ministers of 4 September 2015 concerning the Programme of statistical research of public statistics for 2016” (Journal of

Laws of 2015, item 1304, page 185)". The study of residential and commercial property prices, study reference number

1.26.09 (079), was conducted by the President of Narodowy Bank Polski. Detailed information on BaRN database are

presented in Chapter 6 Convergence and differentiation processes in local markets in Poland.

4 This concerns, in particular, the study of Sekocenbud on the structure and costs of construction, study of the Polish

Agency for Construction Research (Polska Agencja Badawcza Budownictwa (PAB) concerning the construction sector

and many other organizations and associations operating in this market. The key ones included the Polish Federation of

the Real Estate Market (Polska Federacja Rynku Nieruchomości), Association of Employers – Manufacturers of

Construction Materials (Związek Pracodawców-Producentów Materiałów dla Budownictwa) and many others.

5 The authors relied on the data and information of the following agencies: CBRE, Colliers International, Cushman &

Wakefield, JLL, Knight Frank and associations: Retail Research of the Polish Council of Shopping Centres (Retail

Research Forum Polskiej Rady Centrów Handlowych), Polish Office Research Forum. The data concerning transactions

in the commercial real estate market are drawn from database of NBP and Comparables.pl. database.

1. Introduction


Technical terms have been marked with # and defined in the glossary of terms and abbreviations.

In the absence of data or in the case of insufficient quality of data, the authors relied on estimates

verified on the basis of expert and specialist opinions.

2. Real estate market sector



Gross housing investment slightly increased in 2016 to approx. 1.4% of GDP, and real estate

development construction accounted for approx. 50% of this value. The share of persons working

in the real estate sector in employment in the domestic economy in 2015 stood at approx. 7.5%

and was close to the level observed in the previous years. As a result of longevity of the housing

stock the recorded depletion of housing in Poland accounts for a mere 0.02% of the housing stock

(the 2005-2004 average), whereas the real long-term rate of depreciation can be estimated at

approx. 0.3-0.5% annually. Given the above data, we estimate that housing net investment

accounts for approx. 1% of GDP and real estate development ranges between 0.3 - 0.4% of GDP.

The share in construction and assembly production (including investment and repair works) in

GDP increased in 2016 by approx. 0.7 p.p and stood at approx. 4.9% (see Figure 1 and 2)6

Figure 1 Structure of housing construction in Poland

by type of construction (% of GDP)

Figure 2 Investor relations in housing

construction in Poland (%)

Source GUS. Source GUS.

The estimated value of residential real estate assets at the end of 2016 reached approx. PLN 3.17

billion (as against PLN 3.11 billion in 2015, see Figure 3). The value of commercial real estate

assets was approx. PLN 0.2 billion (as in 2015, see Figure 5). Despite large annual size of

construction the commercial and housing real estate stock is growing at a slow pace, which is its

structural feature. In Poland since the transition period the housing stock has been on a steady

rise. The first acceleration in the housing stock development was observed in the period directly

preceding and following Poland's accession to the EU. The second acceleration was seen in 2015

and 2016 and was driven by the serious of cuts in NBP interest rates. Foreign capital (assets)

invested in the commercial real estate, recorded a significant increase after 2000, when the

economic situation became more stable. The second acceleration in the commercial real estate

sector was observed after 2012 which was the result of series of cuts in ECB interest rates.

6 Decline in investment in 2016 was recorded in all Central and Eastern European countries, which was likely to be

driven by the cycle of EU funds spending.

0%

1%

2%

3%

4%

5%

6%

7%

8%

20

02

20

03

20

04

20

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20

07

20

08

20

09

20

10

20

11

20

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20

13

20

14

20

15

20

16

obiekty inżynierii lądowej i wodnej

budownictwo niemieszkaniowe

budownictwo mieszkaniowe

0%

10%

20%

30%

40%

50%

60%2

00

2

20

03

20

04

20

05

20

06

20

07

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08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

do PKB

do nakładów inwestycyjnych

do nakładów brutto na środki trwałe

civil engineering structures

commercial construction

housing construction

to GDP

to capital expenditure

to gross expenditure on tangible fixed assets



Figure 3 Estimated value of the housing stock in

Poland (in PLN billion)

Figure 4 Area of the housing stock in Poland (in

millions of square metres)

0

500

1 000

1 500

2 000

2 500

3 000

3 500

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

Warszawa 6M 10M PP

0100200300400500600700800900

1 0001 100

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

Warszawa 6M 10M PP

Note: 6M# – Gdańsk, Gdynia, Kraków, Łódź, Poznań, Wrocław; 10M# – Białystok, Bydgoszcz, Katowice, Kielce,

Lublin, Olsztyn, Opole, Rzeszów, Szczecin, Zielona Góra; PP# – remaining part of Poland. The estimate is based

on GUS data on the usable area of the housing stock in the analyzed cities. The housing stock was multiplied by

transaction prices of housing (average prices in the primary and secondary market) in 16 cities (NBP database),

and in other Polish cities by replacement prices. The graph shows aggregate values.

Source: NBP estimates, based on GUS, PONT Info. Source: NBP estimates, based on GUS.

Figure 5 Estimated value of the commercial stock in

Poland in PLN billion (left-hand axis) and

PLN/EUR exchange rate (right-hand axis)

Figure 6 Estimated area of the commercial stock in

Poland (in millions of square meters)

3

3,2

3,4

3,6

3,8

4

4,2

4,4

4,6

4,8

5

0

50

100

150

200

250

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Handel Magazyny

Biura, Warszawa Biura, pozostałe miasta

Kurs PLN/EUR (P oś)

-

5

10

15

20

25

30

35

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Handel Magazyny Biura, Warszawa Biura, pozostałe miasta

Note to Figure 5 and 6: The estimate is based on publicly available data on the commercial real estate stock.

Offices are modern office buildings, retail premises are shopping malls, and warehouses are modern, large-

format warehouses. The stock was multiplied by hedonic# transaction price of commercial real estate. Prices

given in EUR are translated into PLN. The graph shows aggregate values.

Source: NBP estimates based on databases of NBP and other consulting companies, transaction prices from

Comparables.pl.

The estimated value of residential and commercial real estate in Poland at the end of 2016

accounted for approx. 182% of GDP and approx. 54% of fixed assets in the economy, with the

residential real estate accounting for 171% and the commercial real estate for 12% of GDP (see

Figure 7 and 8). Despite the approx. 1.3% increase in year-on-year terms in the area of the

housing stock (see Figure 4), its current estimated value to GDP ratio decreased slightly as

compared to the 2015 figure, which results from a 2.7% GDP growth combined with approx. 2.1%

increase in the value of the housing stock. Real estate supply adjusts to demand growth through

construction of new buildings or demolition of the old ones. In the short term, housing supply

adjusts to demand growth with approx. 8-quarter delay resulting from the lengthy construction

Retail Office

PLN/EUR

Warehouse

Office, other cities Retail Warehouse Office, Warszawa Office, other cities



process, introduced regulations, missing or inadequate infrastructure or problems with the

availability of materials and transportation.

Although the commercial real estate stock is still growing much faster than the housing stock in

2016 it was 30-times smaller than the housing stock. It should be emphasized that warehousing

premises account for approximately one third of the stock. Yet, their share in the commercial real

estate in terms of value is rather small (Figures 5 and 6). Loans for commercial real estate,

excluding real estate developer loans for housing construction, granted by banks operating in

Poland amounted to approx. PLN 47 billion. Assuming that the LTV in the total stock (whose

value is estimated at PLN 223 billion) is 50%, the total value of these loans is PLN 111 billion.

Thus, it can be estimated that the loans granted indirectly and directly by foreign banks amount

to approximately PLN 64 billion.

Figure 7 Ratio of the estimated current value of

residential property assets (RPA, left hand axis) to

GDP and fixed assets (FA, right hand axis) in Poland

Figure 8 Ratio of the estimated current value of

commercial property asset (CP) to GDP and fixed

assets (FA) in Poland

50%

55%

60%

65%

70%

100%

120%

140%

160%

180%

200%

220%

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

MM / PKB (L oś) MM / ŚT (P oś)

Source: NBP estimates, based on GUS, PONT Info.

0,0%

1,0%

2,0%

3,0%

4,0%

5,0%

0%

2%

4%

6%

8%

10%

12%

14%

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

NK / PKB (L oś) NK / ŚT (P oś)

Note: see note to Figures 5 and 6.

Source: NBP estimates based on the databases of NBP

and other consulting companies, transaction prices

from Comparables.pl.

Both housing and commercial real estate are a capital good, which combined with land and

labour provide consumer services to the population or production services to other sectors of the

economy. In the majority of cases, the value of housing services is calculated by multiplying the

average area of housing by average rent rates in the local markets. Similarly, based on rental rates

and rented space, we can calculate the value of commercial real estate services. Rental rates in the

short term depend on the correlation between demand and supply, but in the long term, they are

dependent on the cost of housing and commercial real estate (physical capital), opportunity costs

and quality, influenced by many factors.

Although residential services are the subject of housing consumption, it is generally measured

with various measures of quantity and quality of housing capital, including the number of

dwellings, their area, the relation of housing capital to the population and households (the so-

called housing situation). When this measurement is made in physical units (i.e. flats, rooms) it is

de facto measurement of consumption at constant prices.

After 2000 Poland has seen a gradual improvement in its housing situation, which was associated

with the construction of new dwellings, renovation of the existing housing stock and

demographic processes curbing demand for new housing. This was also driven by a large

number of newly built dwellings, small scale of demolition of the existing housing stock and

diminishing population in some cities as a result of people migrating abroad. However, the

RPA/GDP RPA/FA CP/GDP CP/FA



increase in the housing stock played much greater role than migrations (Figure 12). The number

of dwellings per 1 000 inhabitants and the average usable housing area per person has increased,

while the average number of persons occupying the dwelling has fallen (Figures 9–11). In 2016

the average area of single-family house (individual investors) decreased from 135.5 m2 recorded

in 2015 to 134.6 m2 in 2016; the average housing area increased from 55.9 m2 in 2015 to 57.7 in

2016.

Figure 9 Number of dwellings per 1000 inhabitants Figure 10 Average number of persons occupying a

dwelling

320

340

360

380

400

420

440

460

480

500

520

540

560

2003

200

4

200

5

200

6

200

7

200

8

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6

Warszawa 6M 10M Polska

1,7

1,9

2,1

2,3

2,5

2,7

2,9

3,1

200

3

200

4

200

5

200

6

200

7

200

8

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6


Source: NBP estimates based on GUS. Source: NBP estimates based on GUS.

Figure 11 Average usable area of housing per

person (square metres)

Figure 12 Growth rate of the number of dwellings

in the housing stock and the number of inhabitants

in 2016 as compared to 2006 in Poland’s selected

cities.

20,0

22,0

24,0

26,0

28,0

30,0

32,0

200

3

200

4

200

5

200

6

200

7

200

8

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6


-10%

-5%

0%

5%

10%

15%

20%

25%

30%

35%

Rzeszó

w

Zie

lona G

óra

Wro

cła

w

Gd

ańsk

Kra

kó

w

Wa

rsza

wa

Ols

zty

n

Bia

łysto

k

Lub

lin

Po

zn

ań

Szczecin

Gd

ynia

Po

lska

Op

ole

Kie

lce

Bydg

oszcz

Ka

tow

ice

Łód

ź

dyn.zmiany zasobu mieszkaniowego dyn.zmiany liczby ludności

Source: NBP estimates based on GUS. Note to Figure 12: administrative city limits of

Rzeszów and Zielona Góra were extended in this

period

Source: NBP estimates based on GUS.

population change housing stock change



In 2016 the value of housing services in Poland, estimated on the basis of market rents, remained

unchanged as compared to the level recorded in the last four years and amounted to approx. 12%

of GDP. In Poland this figure is not included in GDP. Countries use various approaches in this

respect7.

The value of services generated by the commercial real estate (income from rent) for their owners

can be estimated at approx. 0.7% of GDP (Figure 14), namely less than in the developed countries

of the EU.

Figure 13 Estimated value of housing services

(imputed rent) in Poland in relation to GDP (%).

Figure 14 Estimated value of commercial services

in Poland in relations to GDP (left-hand axis, %)

0%

2%

4%

6%

8%

10%

12%

14%

III

200

6

III

200

7

III

200

8

III

200

9

III

201

0

III

201

1

III

201

2

III

201

3

III

201

4

III

201

5

III

201

6

Warszawa 6M 10M PP

3,0

3,2

3,4

3,6

3,8

4,0

4,2

4,4

4,6

4,8

5,0

0,0%

0,1%

0,2%

0,3%

0,4%

0,5%

0,6%

0,7%

0,8%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Magazyny Biura, Warszawa

Biura, pozostałe miasta Handel

Kurs PLN/EUR (P oś)

Note: The usable area of the housing real estate was

multiplied by rent rates (average offer and

transaction rents) in particular 16 markets according

to the NBP database. For the remaining parts of

Poland the rent rate was estimated at 50% of the

average rent rate calculated for 10M.

Source: NBP estimates based on GUS.

Note: The value of the commercial real estate was

multiplied by capitalization rates provided by

consulting companies.

Source: NBP estimates based on databases of NBP

and other consulting companies, transaction prices

based on Comparables.pl data.

In Poland income from rental of housing real estate is taxed with a lump sum tax on registered

revenue or according to the income tax scale8. According to the Ministry of Finance data, both

the number of taxpayers who pay a lump-sum tax on registered revenue as well as the amount of

this revenue are on the rise. At the end of 2016, the number of taxpayers declaring only lump-

sum tax amounted to 505 thousand persons posting a rise by approx. 50 thousand persons in

year-on-year terms or 11%. The amount of lump-sum tax receivables amounted to PLN 807

million posting a rise of PLN 106 million, i.e. 15% (Figure 15 and 16). The amount of the average

annual lump sum tax from home rental amounted to almost PLN 1.6 thousand (posting an

increase of approx. 3.6% y/y).

Also the revenue of local government entities resulting from property tax shows an upward

trend, rising from approx. PLN 12.1 recorded in 2006 to approx. PLN 20.7 billion, i.e. 3% more

than in 2015.

7 For example, in the United State the value of housing services is included in GDP and in 2016 is accounted for approx.

12.1% of GDP (according to the data of the National Association of Home Builders), and prices of housing services

(rents) are included in the inflation rate.

8 Property rate are set, in a resolution, the municipality council. Detailed information on real estate taxes may be found

at: http://www.finanse.mf.gov.pl/podatki-i-oplaty-lokalne/podatki-od-nieruchomosci .

Warehouse Office, other cities PLN/EUR

Office, Warszawa Retail

http://www.finanse.mf.gov.pl/podatki-i-oplaty-lokalne/podatki-od-nieruchomosci



The estimated share of property tax in 2016 measured both in relation to GDP and to the value of

the real estate assets (as tax on housing and commercial capital) amounted to approx. 1.2% of

GDP and approx. 0.7% of their assets. These figures remained broadly unchanged on the 2015

levels. In Poland, property taxes represent approx. 12% of gross value of services produced by

the aggregate real estate stock (see Figure 13, 14, 17). This shows that real estate in Poland is not

treated in any privileged way. The estimated tax value is tantamount to such taxes being taxed

with a 13% tax rate on their gross value (proceeds plus costs) and thus close to the CIT rate (19%).

Figure 15 Lump-sum tax under rental, sub-rental,

lease and sub-lease contracts ( thousands of persons,

left-hand axis) and proceeds from property tax (PLN

thousand, right-hand axis)

Figure 16 Number of taxpayers declaring income

resulting from under rental, sub-rental, lease and

sub-lease contracts (thousands of persons)

0

5 000

10 000

15 000

20 000

25 000

0

200

400

600

800

1000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Ryczałt należny

Liczba podatników wykazujących ryczałt należny

Przeciętna kwota ryczałtu należnego * 10000 (P oś)

Dochody jednostek samorządu terytorialnego z tytułu podatku od nieruchomości (P oś)

0

100

200

300

400

500

600

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Liczba podatników wykazujących ryczałt należny

Liczba podatników wykazujących przychody z najmu opodatkowane przyzastosowaniu skali podatkowej

Source: MF Source MF

Figure 17 Relation of proceeds from property tax (%)

8,0%

8,5%

9,0%

9,5%

10,0%

10,5%

11,0%

11,5%

12,0%

12,5%

0,4%

0,5%

0,6%

0,7%

0,8%

0,9%

1,0%

1,1%

1,2%

1,3%

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

podatki z nieruchomości / PKB (L oś)

podatki z nieruchomości / MMiK (L oś)

podatki z nieruchomości / UMiK (P oś)

Note to Figure 17: taxes on income of self-

government entities from property tax and lumps-

sum tax receivables; MMiN=value of housing and

commercial real estate assets; UMiK=value of

housing and commercial services;

Source: MF.

The activity of the banking sector involving services offered to the real estate sector in Poland

began to gain in importance after 2000 when high inflation and related interest rate dropped

significantly. At the end of 2016, assets of the banking sector in the form of loans for residential

properties accounted for 41.5% of total loans9 and approx. 24.2% of banks’ assets. The commercial

real estate sector, especially the sector of the largest commercial real estate, developed thanks to

foreign capital. The share of loans extended to the commercial real estate amounted to approx.

5.4% of the banking sector’s portfolios and approx. 3% of banks’ assets. Although portfolios of

9 Aggregate credit of the non-financial sector is made up of loans to households, enterprises and institutions providing

services to households; at the end of 2016 the aggregate credit exceeded slightly PLN 950.1 billion

(http://www.nbp.pl/home.aspx?f=/statystyka/pieniezna_i_bankowa/nal_zobow.html).

Value of a lump-sum tax

Number of a lump-sum taxpayers

Average lump-sum*1000 (RH)

Incomes of local government units from property taxes

taxpayers paying a lump-sum tax

taxpayers paying basing on taxation scale

Taxes/GDP (LH)

Taxes/MMiN (LH)

Taxes/UMIK (RH)



corporate property loans are still significantly smaller than their EU average (about 50%), they

are a significant factor for the financial sector’s safety.

Figure 18 Housing loan in Poland, quarter-on-quarter

changes in PLN billion (left-hand axis) and value in

PLN billion (right-hand scale)

Figure 19 Loans to corporations for real estate

purchases (in PLN billion, left-hand scale) and the

share of impaired loans (in % right-hand scale)

-100

0

100

200

300

400

500

-4

-2

0

2

4

6

8

10

12

14

I 20

04

I 20

05

I 20

06

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

sta

n

w m

ld z

ł

zm

iany k

wa

rta

lne

w m

ld z

ł

mieszkaniowe kredyty walutowe po korektach (zm.kw.) (L oś)mieszkaniowe kredyty złotowe (zm.kw) (L oś)stan kredytu mieszkaniowego (P oś)w tym stan kredytu walutowego (P oś)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

0

10

20

30

40

50

60

I 2

00

9

I 2

01

0

I 2

01

1

I 2

01

2

I 2

01

3

I 2

01

4

I 2

01

5

I 2

01

6

I 2

01

7

Kredyty na powierzchnię biurową

Kredyty na nieruchomości mieszkaniowe

Kredyty na nieruchomości pozostałe

Wskaźnik kredytów zagrożonych na nieruchomości mieszkaniowe

Wskaźnik kredytów zagrożonych na powierzchnię biurową

Wskaźnik kredytów zagrożonych na pozostałe nieruchomości

Source NBP. Data exclusive of BGK.

Source NBP.

Figure 20 Relation of housing loan in Poland to

GDP, housing assets, banks’ assets (left-hand axis)

and banks’ equity (right-hand scale)

0%

50%

100%

150%

200%

250%

300%

0%

5%

10%

15%

20%

25%

30%

I 2

005

I 2

006

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

KM / PKB KM / Majątek mieszkaniowy

KM / Aktywa banków KM / Kapitały własne banków (P oś)

Source: NBP, GUS.

PLN housing loan quaterly change (LH)

FX housing loan quarterly change (LH)

PLN housing loan stock (RH)

In which FX housing loan stock (RH)

ML/GDP

ML/banks ssets

ML/consumption

ML/bank equity

Office space loans Housing loans Other real property loans Impaired housing loan ratio Impaired office space loan ratio Impaired other real property loan ratio

3. Developments in the residential real estate market in Poland in 2016


3. Developments in the residential real estate

market in Poland in 2016

The cyclical nature of the housing market means that the phase of the cycle is an important factor

while evaluating the developments in the market, and the number of dwellings sold is one of the

basic measures of the phase of the cycle. In order to monitor cycles, speculation, and tensions in

the credit market we use home price indicators10.

Since 2014 the housing markets of Poland's largest cities has seen a recovery which in 2016

transformed into expansion (see Figure 21-22). In 2016, supply dynamically responded to high

demand (significant growth in new housing investment projects exceeding levels recorded in the

years 2006-2008). No considerable growth in lending was recorded, in contract to the previous

period marked with tensions. A significant rise in home sales combined with stable lending

points to a larger use of own funds of households, among other things, due to negative interest

rate on some bank deposits.

Figure 21 Housing cycle in the Warszawa market Figure 22 Housing cycle in 6M

-40 000

-30 000

-20 000

-10 000

0

10 000

20 000

30 000

0

5 000

10 000

15 000

20 000

25 000

30 000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

housing sold housing supplied

new mortgages, number new mortgages, value in mln PLN

new housing starts completed housing units

production indicator (r axis)

boom decline stagnation upswing boom

-40 000

-20 000

0

20 000

40 000

0

10 000

20 000

30 000

40 000

50 000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

housing sold housing supplied

new mortgages, number new mortgages, value in mln PLN

new housing starts completed housing units

production indicator (r axis)

stagnation upswingdeclineboom boom

Source: NBP, GUS, REAS, BIK. Source: NBP, GUS, REAS, BIK.

Real estate market analysis usually involves the analysis of demand and supply and market

equilibrium conditions (price, surplus, shortage, transactions). In subsequent stages, the analysis

focuses on demand and supply factors and their correlations in the short term, medium term and

long term. At present, two complementary approaches are used: indicator analysis and

econometric modelling. Econometric models typically represent processes in an aggregated

manner, while the indicator analysis provides a better insight into the operation and impact of

individual factors. Diagram of the model based on the economic indicators based on the

relationships observed in Warszawa and 6M is presented below (see Figures 24–29). This is an

analysis of the market equilibrium (see Figure 26) of selected housing market factors on the

demand and supply side.

10 See: Report on the situation in the residential and commercial real estate market in Poland in 2015.


Figure 23 Dwellings completed and dwellings under

construction 6M

Figure 24 Long-term cost 6M

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

I 2

00

6

I 2

00

7

I 2

00

8

I 2

00

9

I 2

01

0

I 2

01

1

I 2

01

2

I 2

01

3

I 2

01

4

I 2

01

5

I 2

01

6

I 2

01

7

Rozpoczęte Oddane kr.- 8 kw.

0

500

1 000

1 500

2 000

2 500

3 000

3 500

4 000

4 500

-40 000

-20 000

0

20 000

40 000

60 000

80 000

100 000

120 000

I 2

006

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

pozwolenia wsk.prod.mieszk.

produkcja budowlano-montażowa koszty bud.+ziemia (P oś)

Figure 25 Demand for housing 6M Figure 26 Housing market 6M Figure 27 Housing supply 6M

- 200

- 100

0

100

200

300

400

500

600

-300

-250

-200

-150

-100

-50

0

50

100

150

200

250

I 20

07

I 20

08

I 20

09

I 20

10

I 201

1

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

popyt całkowity szacowany popyt całkowity rzeczywisty

popyt konsumpcyjny (p.oś) popyt inwestycyjny (p.oś)

popyt spekulacyjny (p.oś)

0

1

2

3

4

5

6

7

8

9

0

10 000

20 000

30 000

40 000

50 000

60 000

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

wprowadzone w kwartale sprzedane w kwartale

oferta na koniec kwartału czas wyprzedaży oferty

10%

15%

20%

25%

30%

35%

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

cena mieszk.T RP koszt bud.mieszk.+ziemia

M.rozpoczęte (/10) stopa zwrotu (P oś)

Sources:

24 – GUS.

25 – GUS, PAB, Sekocenbud.

26 – REAS, GUS.

27 – REAS.

28 – NBP, GUS, Sekocenbud.

29 – NBP, REAS, GUS.

Figure 28 Housing prices 6M

-

2 000

4 000

6 000

8 000

10 000

12 000

2 000

12 000

22 000

32 000

42 000

52 000

62 000

I 200

7

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

oferta (L oś) kr.dost.mieszk.*100 (P oś) cena T RP (P oś)

under construction completed; moving avg.

permissions

building and construction output

housing production index

construction costs+land (RH)

construction costs+land

rate of return (RH)

price RPT

dwellings started

offered (LH) housing availability*100 (RH) price RPT (RH)

dwellings launched

dwellings offered

dwellings sold

selling time of dwellings

estimated total demand

consumer demand (RH)

speculative demand (RH)

real total demand

investment demand (RH)



In the long term, the supply of housing encompasses the entire housing stock, yet, the current

supply available in the market are dwellings offered for sale11. New dwellings are produced on

the primary (real estate developer) residential market (see Figure 25) and they are supposed to

meet new housing needs as well as the needs resulting from depreciation of the already existing

housing stock. Amid low market competition, growing demand for dwellings, supported by

government-subsidized housing schemes, translates into higher home prices and real estate

developers record high profits and rates of return on investment. This encourages them to further

develop their activity. On the other hand, amid strong competition supply effects prevail.

The characteristic feature of this market is the high and difficult to predict stock of built and

unsold dwellings. This is due to changing demand and, at the same time, long construction

period, which prevents fast adjustment of supply to demand. When the stock is high (measured

with the selling time), prices do not rise, or they grow with a delay despite rising demand. When

the stock is low, in response to growing demand, prices begin to rise and real estate developers

increase production. These reactions depend on the structure of the market (level of competition)

and real estate developers' forecasts of the market situation.

When there are no necessary regulations in the primary market home construction contracts

rather than dwellings are the object of transactions. The supply of contracts for developer

housing construction is driven by the expected rates of return on investment projects and the

expected size of demand. Apart from price growth the rate of return is also affected by cost

growth (rates of return are largely determined by the difference between the price of dwellings

and the cost of their construction and land purchase). Developers try to predict situation in the

market in a two-three years’ perspective, but they base their forecasts on the current and

historical data (see Figures 23 and 27). For that reason, the leading indicator demonstrating the

future size of construction are dwellings under construction and issued building permits (see

Figures 23 and 24).

Costs of construction include the cost of construction sites, and construction and assembly works

(labour, materials, equipment, overheads, construction profit), are largely depend on business

conditions in the real property sector and in the entire economy. Also rising demand for

construction and assembly output usually boosts its costs. Housing construction, however,

accounts for a small share in construction and assembly production in Poland, thus the condition

of the general construction sector is more important.

Consumer demand for developer dwellings in the largest cities is, to a great extent, determined

by the availability of loan-financed housing. The key factors affecting consumer demand in the

housing market are home prices and interest rates of loans. Housing demand satisfied with the

use of own savings is on the rise. Savers compare return on savings with potential return on

home rental. Housing investment sometimes also relies on bank lending, when rates of return

obtained from home rental are higher than cost of residential loans. As regards demand, there is

also a pro-cyclical speculation demand. It is observed when prices of dwellings rise, and this

upward trend - in the opinion of market participants - seems to be constant. Households make

11 It is common in Poland to sell dwellings under construction, thus sold dwellings are just contracts for housing to be

built in the future, usually in the period of the next 2-3 years.


Report on the situation in the residential and commercial real estate market in Poland in 2016.

current decisions and conclusions concerning the future usually based on the past experience.

Speculation involves buying houses at a low cost and reselling them in the future at a higher

price. The high cost of transaction is a deterring factor. However, some households are now

buying dwellings for precautionary reasons in order to protect themselves from rising prices in

the future. In the last two years, we have noted a considerable growth in consumer demand,

which dominated, and rise in investment demand, whose role was increasing with practically no

speculation effects.

3.1 Home prices

Prices of real property are an important indicator while identifying tensions in the real property

sector, informing about its economic effectiveness and an element creating other indicators.

In 2016, average prices per 1 square meter of housing12, both offer and transaction prices in the

primary and secondary markets in the analysed cities in Poland, were stable (see Figures 29-32).

A slight drop in RPT prices per square meter in Warszawa was related to a bigger number of

transaction in poorer quality dwellings13. A slight rise in RWO price in 6M was driven by a bigger

number of good location dwellings being offered for sale. The hedonic price#, i.e. the price taking

into account quality differences between the analyzed goods and the changing structure of the

sample of dwellings analyzed in subsequent quarters#, slightly increased, especially in 6M.

Figure 29 Average offer and transaction prices of

housing in Poland (PLN/1 square meter) in the

primary market

Figure 30 Average offer, transaction and hedonic

prices of housing in Poland (PLN/1 square meter) in

the secondary market

2000

3000

4000

5000

6000

7000

8000

9000

10000

III

200

6

III

200

7

III

200

8

III

200

9

III

201

0

III

201

1

III

201

2

III

201

3

III

201

4

III

201

5

III

201

6

Warszawa RPT 6M RPT 10M RPT

Warszawa RPO 6M RPO 10M RPO

2000

3000

4000

5000

6000

7000

8000

9000

10000

III

200

6

III

200

7

III

200

8

III

200

9

III

201

0

III

201

1

III

201

2

III

201

3

III

201

4

III

201

5

III

201

6

Warszawa RWT 6M RWT 10M RWT

Warszawa RWO 6M RWO 10M RWO

Warszawa hed. 5M hed. 10M hed.

Source NBP. Source NBP.

12 Data on housing prices in the primary and secondary market are derived from the BaRN real property pricing

database kept by Narodowy Bank Polski. More on the survey on the NBP website:

http://www.nbp.pl/home.aspx?f=/publikacje/rynek_nieruchomosci/ankieta.html.

13 This concerned mainly dwellings subject to limits imposed under the MDM government-subsidized housing scheme.

http://www.nbp.pl/home.aspx?f=/publikacje/rynek_nieruchomosci/ankieta.html



Figure 31 Ratio of transaction prices per square

meter of housing in the primary market to the

secondary market (PLN/sq. m)

Figure 32 Ratio of offer prices per 1 square meter to

transaction prices in the secondary primary market,

secondary market and the average of the primary

and secondary market.

0,80

0,85

0,90

0,95

1,00

1,05

1,10

1,15

1,20

1,25

III

200

6

III

200

7

III

200

8

III

200

9

III

201

0

III

201

1

III

201

2

III

201

3

III

201

4

III

201

5

III

201

6

Warszawa 6M 10M

0,000

0,200

0,400

0,600

0,800

1,000

1,200

1,400

0,95

1,00

1,05

1,10

1,15

1,20

1,25

1,30

1,35

III

200

6

III

200

7

III

200

8

III

200

9

III

201

0

III

201

1

III

201

2

III

201

3

III

201

4

III

201

5

III

201

6

Warszawa RP 6M RP 10M RP

Warszawa RW 6M RW 10M RW

O/T Warszawa (P oś) O/T 6M (P oś) O/T 10M (P oś)


In all the analyzed cities, prices per 1 square meter of housing in the primary market exceeded

prices in the secondary market, which were driven by their better quality and the fact that new

dwellings were better tailored to buyers’ needs14 (see Figure 64). The highest prices were noted in

particular in the case of transactions involving small dwellings (with an area up to 40 square

meters) and large dwellings (with an area exceeding 80 square meters). On the other hand, in the

market of the remaining 10 cities (10M) the highest prices per square meter of housing were

recorded in the case of small dwellings (see Figures 35 – 40).

The analysis of prices per square meter of housing in real terms (CIP-deflated prices) in the

primary market shows that these prices were higher than those recorded in the period of the

tensions observed in 2006-2008 (see Figure 33 and Figure 34). A slight drop in real transaction

prices in the last quarter could be attributed to both inflation and nominal price declines. Real

prices relative to the average wage growth in the corporate sector were significantly lower than

those observed during the period of tensions, especially in the secondary market in all analyzed

cities.

14 When purchasing a new dwelling from a real property developer the buyer must reckon with the costs of approx.

PLN 500-1000 per square meter necessary to finish the housing, depending on the materials used. Additionally, it may

take up to two years to occupy the dwelling. Dwellings in the secondary market are generally better located, do not

require investing any considerable resources, do not have garages, but they are readily available. Total additional costs

of transaction (notary’s fees, cost of registration in the Land and Mortgage Register, tax on civil law transactions, real

property broker’s fees) are higher in the secondary market, but the time it takes to occupy the housing is usually shorter.



Figure 33 Index of the average weighted transaction

price of 1 square meter of housing in the secondary

market and the real price to CPI (2006 Q3=100)

Figure 34 Index of the average weighted

transaction price of 1 square meter of housing in

the secondary market and the real price to CPI

(2006 Q3=100)

80

90

100

110

120

130

140

150

160

170

180

190

III

200

6

III

200

7

III

200

8

III

200

9

III

201

0

III

201

1

III

201

2

III

201

3

III

201

4

III

201

5

III

201

6

Warszawa RP T Warszawa RP T defl. CPI

6M RP T 6M RP T defl. CPI.

10M RP T 10M RP T defl. CPI

80

90

100

110

120

130

140

150

160

170

180

190

III

200

6

III

200

7

III

200

8

III

200

9

III

201

0

III

201

1

III

201

2

III

201

3

III

201

4

III

201

5

III

201

6

Warszawa RW T Warszawa RW T defl. CPI

6M RW T 6M RW T defl. CPI.

10M RW T 10M RW T defl. CPI

Source NBP, GUS. Source NBP, GUS.


housing in Warszawa in the primary market by area

(PLN/1 square meter; < 40 sq. m right-hand scale)


housing in Warszawa in the secondary market by

area (PLN/1 square meter)

0

5000

10000

15000

5000

6000

7000

8000

9000

10000

11000

12000

III 2

006

I 20

07

III 2

007

I 20

08

III 2

008

I 20

09

III 2

009

I 20

10

III 2

010

I 20

11

III 2

011

I 20

12

III 2

012

I 20

13

III 2

013

I 20

14

III 2

014

I 20

15

III 2

015

I 20

16

III 2

016

I 20

17

Warszawa RPT <40 Warszawa RPO (40; 60]

Warszawa RPT (40; 60] Warszawa RPO (60; 80]

Warszawa RPT (60; 80] Warszawa RPO >80

Warszawa RPT >80 Warszawa RPO <40

5000

6000

7000

8000

9000

10000

11000

12000III

2006

I 2

007

III

2007

I 2

008

III

2008

I 2

009

III

2009

I 2

010

III

2010

I 2

011

III

2011

I 2

012

III

2012

I 2

013

III

2013

I 2

014

III

2014

I 2

015

III

2015

I 2

016

III

2016

I 2

017

Warszawa RWO <40 Warszawa RWT <40

Warszawa RWO (40; 60] Warszawa RWT (40; 60]

Warszawa RWO (60; 80] Warszawa RWT (60; 80]

Warszawa RWO >80 Warszawa RWT >80



housing in 6M in the primary market by area (PLN/1

square meter)


housing in 6M in the secondary market by area

(PLN/1 square meter)

3000

4000

5000

6000

7000

8000

9000

10000

III 2

006

II 2

00

7

I 20

08

IV 2

00

8

III 2

009

II 2

01

0

I 20

11

IV 2

01

1

III 2

012

II 2

01

3

I 20

14

IV 2

01

4

III 2

015

II 2

01

6

I 20

17

6M RPO <40 6M RPT <406M RPO (40; 60] 6M RPT (40; 60]6M RPO (60; 80] 6T RPT (60; 80]6M RPO >80 6M RPT >80

3000

4000

5000

6000

7000

8000

9000

10000

III 2

006

II 2

00

7

I 20

08

IV 2

00

8

III 2

009

II 2

01

0

I 20

11

IV 2

01

1

III 2

012

II 2

01

3

I 20

14

IV 2

01

4

III 2

015

II 2

01

6

I 20

17

6M RWO <40 6M RWT <406M RWO (40; 60] 6M RWT (40; 60]6M RWO (60; 80] 6M RWT (60; 80]6M RWO >80 6M RWT >80

Source: NBP. Source: NBP.




housing in 10M in the primary market by area



housing in 10M in the secondary market by area


2500

3000

3500

4000

4500

5000

5500

6000

III 2

006

II 2

00

7

I 20

08

IV 2

00

8

III 2

009

II 2

01

0

I 20

11

IV 2

01

1

III 2

012

II 2

01

3

I 20

14

IV 2

01

4

III 2

015

II 2

01

6

I 20

17

10M RPO <40 10M RPT <4010M RPO (40; 60] 10M RPT (40; 60]10M RPO (60; 80] 10M RPT (60; 80]10M RPO >80 10M RPT >80

2500

3000

3500

4000

4500

5000

5500

6000

III 2

006

II 2

00

7

I 20

08

IV 2

00

8

III 2

009

II 2

01

0

I 20

11

IV 2

01

1

III 2

012

II 2

01

3

I 20

14

IV 2

01

4

III 2

015

II 2

01

6

I 20

17

10M RWO <40 10M RWT <4010M RWO (40; 60] 10M RWT (40; 60]10M RWO (60; 80] 10M RWT (60; 80]10M RWO >80 10M RWT >80


The comparison of the amount and the structure of housing prices in the primary market shows a

relatively high share of developers' profit, which is related to limited competition, typical for this

market, and price differences between sellers15. The share of profits differs across markets16 and

across years.

Figure 41 Gdańsk, estimated structure of

transaction price per 1 square meter of usable area

(building type 1122-302#)

Figure 42 Kraków, estimated structure of


(building type 1122-302)

0

1000

2000

3000

4000

5000

6000

7000

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

ziemia + zagosp.terenu projekt koszty budowy

koszt kredytu koszty ogólne zysk deweloperski

0

1000

2000

3000

4000

5000

6000

7000

8000

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 201

2

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17




15 See: Report on the situation in the residential and commercial real estate market in Poland in 2015.

16 More detailed description in Chapter 4.2. Housing supply.

land + development

loan cost

land + development

loan cost

design

overheads

design

overheads

construction costs

developers’ profit

construction costs




Figure 43 Łódź, estimated structure of transaction

price per 1 square meter of usable area (building

type 1122-302)

Figure 44 Poznań, estimated structure of transaction

price per 1 square meter of usable area in the primary

market (building type 1122-302)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17



0

1000

2000

3000

4000

5000

6000

7000

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17




Figure 45 Warszawa, estimated structure of



Figure 46 Wrocław, estimated structure of



0

1000

2000

3000

4000

5000

6000

7000

8000

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17



0

1000

2000

3000

4000

5000

6000

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17



Note to Figures 36-41: net transaction price (excluding VAT);


Rent rates in the analysed cities in Poland show long-term stability until 2015, whereas in 2016

the average rent rates (offers and transactions) increased in Warszawa and in 6M mainly due to

rising offer rents (see Figure 47). The rental market is becoming more transparent and is leaving

the grey economy; this is demonstrated by the growing number of tax returns of persons offering

their dwellings for rent17.

17 In the Information concerning tax on registered income for 2014 the Ministry of Finance provides that there were 39

thousand taxpayers in 2003, 108 thousand in 2006, 416 thousand in 2014, and 458 thousand in 2015.

land + development

loan cost

land + development

loan cost

land + development

loan cost

land + development

loan cost

design

overheads

design

overheads

design

overheads

design

overheads

construction costs


construction costs


construction costs

developers’ profit construction costs




Figure 47 Average monthly offer and transaction

home rental rates in Poland (PLN/1 square meter)

0

10

20

30

40

50

60

I 20

06

I 20

07

I 200

8

I 20

09

I 20

10

I 20

11

I 20

12

I 201

3

I 20

14

I 20

15

I 20

16

I 20

17

Warszawa 10M śr.waż.zasobem 6M śr.waż.zasobem

Source: NBP.

3.2 Housing supply

Housing supply encompasses dwellings offered for sale and for rent, involving both the existing

stock (secondary market) and new housing (primary market), adjusted for depletion and changes

in the intended use of dwellings18. Amid increasing demand for housing and a relatively rare

change of dwellings, the key factor in the equilibrium in this market is residential construction. In

Poland, the supply structure of housing has been stable since the late 1990s. In big cities,

developer construction is predominant, whereas investment projects of housing cooperatives are

of marginal, yet recently growing, importance. In medium-sized and small towns and in rural

areas, single-family houses dominate, to some extent, self-built houses (see Figure 48). It is

estimated19 that approximately 40% of developer housing purchases are loan-financed, which

translates into growing mortgage loan portfolio. Single-family housing development is, to a large

extent, based on own funds, and mortgage borrowing plays a supplementary role only.

Figure 48 Structure of housing construction forms in

Poland

010 00020 00030 00040 00050 00060 00070 00080 00090 000

100 000

ind

ivid

ual

deve

lop

er

co

op

era

tive

oth

er

ind

ivid

ual

deve

lop

er

co

op

era

tive

oth

er

ind

ivid

ual

deve

lop

er

co

op

era

tive

oth

er

housing completed housing underconstruction

building permits

IV 2013 IV 2014 IV 2015 IV 2016

Source GUS.

In 2016, strongly growing demand in the housing market had a favourable impact on the

situation of real property developers. The number of completed dwellings and new starts

18 Data concerning the size of the home construction market are available in Poland. However, there are no data

concerning contracts for developer housing construction and home sales in the secondary market.

19 NBP estimate.



reached a record level; yet, due to high demand and sales level no oversupply was noted in the

housing market.

The supply of new dwellings dynamically responded to high demand in 2016 (see Figure 43).

Approximately 163 thousand dwellings were completed and made ready for occupancy, i.e.

approx. 4.3 thousand more than in 2015 (year-on-year growth of 10.2%). As compared with the

previous year, the number of home construction starts increased by 5.5 thousand. In 2016 the

number of issued building permits for housing construction was higher by approx. 22.7 thousand

than the number recorded in the previous year (growth by 12% year-on-year).

From the point of view of the risk of an excessively violent cycle in the housing market, the

flexibility of the supply of new dwellings in relation to demand shocks is of particular

importance. It tells us how quickly the real estate development sector can adapt to increased

demand. Tensions may be measured by comparing the number of building permits and

dwellings under construction with the size of home sales. This comparison shows that if home

sales in the future remains at the current level, the forecasted housing production will be not

sufficient to meet housing demand. Charts 49 and 50 show that in 2016 housing supply matched

housing demand. At the beginning of 2017, however, certain developments suggested that

supply was getting stiff. These included: a decline in the number of completed dwellings on offer

on the market and a decrease in homes under construction measured by sales volume as well as

the rise in the number of projects under construction exceeding the growth in the number of

dwellings under construction.

Figure 49 Housing construction in Poland (number

of dwellings, rolling 4 quarters)

Figure 50 Indicator of residential projects and

dwellings under construction and dwellings offered

for sale in 7M.

-100

0

100

200

300

400

500

0

50

100

150

200

250

300

I 2

00

6

I 2

00

7

I 2

00

8

I 2

00

9

I 2

01

0

I 2

01

1

I 2

01

2

I 2

01

3

I 2

01

4

I 2

01

5

I 2

01

6

I 2

01

7

Tysiące

Mieszkania rozpoczęteMieszkania oddanePozwolenia na budowę mieszkańWskaźnik koniunktury (p.oś)Wskaźnik projektów w toku (p.oś)

0%

5%

10%

15%

20%

25%

30%

35%

40%

- 4,0

- 2,0

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

20,0

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

Mieszkania sprzedane 7M/1000

Projekty w toku 7M/1000

Budowa mieszkań w toku 7M

Oferta na rynku 7M/1000

M.gotowe w ofercie sprzedaży (p.oś)

Note to Figure 49: Indicator of trends in housing production is the sum of four quarters of difference between

commenced dwellings and finished dwellings ready for occupancy; indicator of projects under construction is

the sum of four quarters of difference between permits for housing construction and finished dwellings ready

for occupancy.

Note to Figure 50: Projects under construction are building permits minus completed dwellings ready for

occupancy; dwellings under construction are dwellings whose construction started minus completed

dwellings; both indicators are summed up in 4 quarters and then divided by sales in a particular period.

Source GUS. Source NBP based on Sekocenbud, REAS.

Situation of real estate developers

High demand in the housing market had a material and positive impact on the situation of the

real estate developers in 2016. The estimated share of the profit in one square meter of real estate

developer housing dropped slightly, yet continued on a high level (see Figure 52). In the group of

dwellings under construction dwellings completed building permits housing production index (RH) index of housing projects (RH)

dwellings sold 7M/1000 dwellings projects 7M/1000 dwellings under construction 7M dwellings offered 7M/1000 compleded dwellings/offered dwellings (RH)



companies employing more than 49 persons, there were slight decreases in revenues and profits,

which could have been the result of the cost of launching a large number of projects and tax

optimization. The situation was enhanced by stable prices of construction and assembly works in

the majority of the analyzed cities (see Figure 83). The growth of housing production was

financed with increasing, considerable share of equity and debt securities. Stock market indices of

real estate developers (see Figure 51) have been on the rise since 2012, but the rescaled indices are

at levels below the WIG20 index.

Figure 51 Rescaled stock exchange indices: WIG20

and for real property developer and construction

companies (2007 Q2=100)

Figure 52 Estimated ROE from housing projects

(building type 1122-302) and the reported rate of

return DFD#

0

20

40

60

80

100

120

I 2

004

I 2

005

I 2

006

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

II 2

007 =

100

WIG20 WIG-NIER. WIG-BUD.

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

Gdańsk Kraków Łodź Poznań

Wrocław Warszawa DFD

Note to Figure 52: the estimated rate of return on equity from typical new housing projects, under the

assumption of the currently applicable interest rates, banks’ requirements, production costs and net price;

calculation based on the diagram included in Annex 3 of the Report on the situation of the Polish market of residential

and commercial real estate in 2011.

Source GPW. Source NBP, Sekocenbud, GUS.

In order to assess the supply side of the real estate market, the financial condition of the

developers and20 their related parties was analyzed.

The analysis relied on the data from F-01 reports submitted to GUS in 2007 - 2016 by entities

involved in business activity classified as 41.10 in the Polish Classification of Business Activities21.

The results are broken down into two groups of companies (smaller - with the staff between 9

and 49 persons and larger - employing more than 49 persons). The source of valuable

supplementary information is the analysis of the financial data of seventeen real estate

developers included in the WIG-real estate22, whose current activity is concentrated in whole or

in major part on multi-family housing. NBP additionally carried out its own survey of the

economic situation in the second half of 2016 along with forecasts for the first half of 2017 among

20 Real estate developer - an investor, a natural or legal person, who invests in the construction of real estate

(residential, office, commercial and industrial real estate) for sale or rent. Typically, a real estate developer buys a

property, supervises the full investment process from the design stage to the completion of the building (including its

expansion or renovation) until its sale or rental (https://pl.wikipedia.org/wiki/Deweloper_budowlany).

21 PKD 41.10 - Development of building projects. When choosing PKD codes a company should take into account its

principal business activity. The code identifying this activity should be entered in the first place in the completed form.

The results of analysis The breakdown by NACE groups is conventional. Various data sets were used to confirm the

reliability of the results of the financial analysis.

22 On January 2017 WIG-real estate developers changed its name to WIG-real estate.



several developers involved mainly in residential and non-residential projects in Poland. The

information on the profitability of real estate development is supplemented with the results of

the analysis of particular housing projects carried out in 16 local markets by NBP Branches (the

price of land for multi-family housing, direct and indirect construction costs).

According to the GUS data the situation in the real estate development sector is good. Among the

analysed companies operating in the real estate development sector at the end of 2016, large

developers represented 18% of the surveyed companies, generating over 48% of sales revenue. In

both groups of entities, total employment increased to over 11 thousand persons. Increased

spending on projects under construction is indicative of high activity of developers on the

market. The stable level of completed premises is also confirmed by the lack of symptoms of

oversupply of housing. The launch of a considerable number of new investments reduced the

stock of building plots. According to the data derived from financial statements, third party

services, including outsourced services (approx. 70% in the case of large companies and approx.

75% in the case of smaller entities) are a dominant item in the structure of operating expenses,

and their volume has been on the rise for three years along with growth of the core business

activity.

Large companies (employing more than 49 employees) involved in the execution of projects and

construction works related to the construction of residential and non-residential buildings

(construction companies and real estate developers) in 2016 reported a decline in net profit as

compared to 2015 (down by approximately 33%), lower sales revenue (down by approximately

6%) and a decline in the cost of sales (down by approximately 5%). The average sales

profitability in 2016 was 3% and was 1.2p.p. lower than the year before. The share of revenues

generated by enterprises showing a net profit dropped to 82% of the revenues generated by all

the surveyed enterprises. The number of companies with a positive net result remained at a

stable level – 85% of the total of respondents.

Figure 53 Economic indicators of real estate

developers (PKD 41)

Figure 54 Share of enterprises showing net profit in

the total number of enterprises (PKD 41)

0

500

1000

1500

2000

0

10000

20000

30000

40000

50000

2012 2013 2014 2015 2016

mln

zł

mln

zł

Przychody ze sprzedaży

Koszt własny sprzedaży

Wynik finansowy netto

0

20

40

60

80

100

2013 2014 2015 2016

%

Deweloperzy wykazujący stratę nettoDeweloperzy wykazujący zysk netto

Source NBP based on GUS. Source NBP based on GUS.

Sales revenue

Cost of sales

Net financial result

Developers reporting a net loss

Developers reporting a net profit



Figure 55 Number of real estate developers

employing more than 49 persons

Figure 56 Number of real estate developers

employing 9 to 49 persons

0

20

40

60

0

2000

4000

6000

8000

liczb

a fir

m

liczb

a pr

acuj

ącyc

h

liczba pracującychliczba firm (P oś)liczba rentownych firm (P oś)*

0

50

100

150

200

250

0

1000

2000

3000

4000

5000

licz

ba fi

rm

licz

ba p

racu

jący

ch

liczba pracującychliczba firm (P oś)liczba rentownych firm (P oś)*


*/The number of profitable companies means the number of companies with a positive net result

The group of large companies, however, recorded a rise in the cost of core business close to the

net sales level. In 2016, as compared to the previous year, the number of large real estate

developers generating a positive net result decreased from 83% to over 79%. In this group of

entities return on sales (ROS 5.7%) was lower than in the previous years. The financial result,

lower than a year earlier, could have been the result of a significant increase in the number of

projects under construction, related costs and tax optimisation. Return on equity (ROE) and

return on assets (ROA) continued at stable and safe levels, which points to the effective

management of assets and the good financial condition of these entities. Equity capital plays an

important role in the financing of real estate developers. During the analysed period of 10 years,

the level of equity was kept at a safe level and allowed developers to cover any potential claims

of creditors. In 2016, equity accounted for over 43% of total liabilities. The share of bank loans

increased to approx. 8% and the share of debt securities, mainly bonds, increased to 18%. The

share of buyers’ own contribution rose to approx. 6% (the highest value in recent years).

Attention should be drawn to higher investment activity of large companies and increased bond

financing. In the group of large entities, financial liquidity deteriorated. Consequently, the ability

to repay liabilities also declined. The average debt collection period increased to approximately

189 days (in the last two years it was about 135 days) and the inventory turnover period rose

slightly – to more than 310 days. Over the past two years, the average receivables turnover ratio

declined to a safe 60-day period. The average debt ratios and debt coverage ratios worsened

slightly, yet remained at a safe level, confirming the safety of creditors of real estate developers,

including financial institutions.


developers employing more than 49 persons

Figure 58 Structure of assets of real estate developers

employing more than 49 persons

0

100

200

300

400

500

0

1000

2000

3000

4000

5000

6000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

mln

zł

Przychody ogółem Koszty ogółem Wynik finansowy netto

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

aktywa trwałe zapasy materiałów mieszkania gotowe

projekty w toku bank ziemi gotówka

należ. od odb.


Number of employees Number of firms (right axis) Number of profitable firms (right axis)*

Number of employees Number of firms (right axis) Number of profitable firms (right axis)*

Total revenue Total costs Net financial result

Fixed assets

Projects under construction

Receivables from customers

Stocks of materials Land bank

Finished apartments

Cash



Figure 59 Structure of liabilities of real estate

developers employing more than 49 persons

Figure 60 Sources of external financing of real estate

developers employing more than 49 persons (mln

PLN)

0

10

20

30

40

50

60

70

80

90

100

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

%

kapitał własny kredyty dłużne pap. wart. przedpłaty inne zobow.

0200400600800

100012001400160018002000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

długoterminowe kredyty

długoterminowe pożyczki, obligacje, papiery wartościowe

krótkoterminowe kredyty

krótkoterminowe pożyczki, obligacje, papiery wartościowe


Figure 61 Situation of real estate developers

employing more than 49 persons (mln PLN)

Figure 62 Costs of operating activity of real estate


PLN)

0,0

0,5

1,0

1,5

0

500

1000

1500

2000

2500

3000

3500

4000

2007200820092010201120122013201420152016

lata

mln

zł

mieszkania gotoweprojekty w tokubank ziemibank ziemi w latach prod. (P oś)

0

2

4

6

8

10

12

14

0

500

1000

1500

2000

2500

3000

2010 2011 2012 2013 2014 2015 2016

mln

zł

mln

zł

zuż mater i energii usługi obce

inne koszty dz. oper. wynagrodzenia (P oś)

Figure 63 Turnover of inventories, receivables and

liabilities of real estate developers employing

more than 49 persons (mln PLN)

Figure 64 Profitability of real estate developers


0

100

200

300

400

500

600

0

1000

2000

3000

4000

5000

liczb

a dn

i

mln

zł

przychody ze sprzedaży

okres ściągania należności w dniach (P oś)

okres regulacji zobowiązań krótkoterm. w dniach (P oś)

okres pokrycia zapasów w dniach (P oś)

0

5

10

15

20

050

100150200250300350400450500

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

Wynik finansowy netto ROS (Poś)

ROE (Poś) ROA (Poś)

Unfavourable level of the debt recovery ratio in

days – over 60 days, the inventory turnover time in

days ratio– over 200 days

Unfavourable level of ROS, ROE and ROA - below 0


Equity capital Loans Debt securities Pre-payments Other liabilities

Long-term credit

Long-term loans, bonds, securities

Short-term credit

Short-term loans, bonds, securities

Finished apartments Projects under construction Land bank Land bank in years of production (right axis)

Materials and energy used

Other operating costs

External services

Remuneration (right axis)

Sales revenue

Debt recovery ratio (right axis)

Period of short-term liabilities payment (right axis)

Inventory turnover time (right axis)


ROE (right axis)

ROS (right axis)

ROA (right axis)



Figure 65 Investment activity of real estate


PLN)

Figure 66 Debt ratios and debt coverage ratios of real

estate developers employing more than 49 persons

0

5

10

15

20

25

30

0

500

1000

1500

2000

2500

3000

3500

4000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

%

mln

zł

zobow. finansowe z tyt kredytów i papierów dłużnych

wartość nakładów inwestycyjnych

udział nakładów inwestycyjnych w amortyzacji (P oś)

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

wsk. ogólnego zadłużenia

wsk. pokrycia majątku kapitałem własnym

wsk. zabezpieczenia zob. finansowych kapitałem własnym

wsk. zadłużenia kapitału własnego

Note to Figure 66: Unfavourable levels of profitability ratios: total debt ratio – over 0.8 (80%), equity to assets

ratio – less than 100%, liabilities equity coverage ratio - over 1.25 (125%), debt-to-equity ratio - over 2.2 (220 %)


Figure 67 Liquidity ratios of real estate developers


Figure 68 Percentage of real estate developers

employing more than 49 persons reporting an

unsatisfactory level of selected indicators

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

0

1000

2000

3000

4000

5000

6000

7000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

aktywa obrotowe zapasyzob. krókoterminowe wsk. szyb. płynnności (P oś)wsk. płynności bieżącej (P oś)

0 10 20 30 40 50

firmy z ujemnym wynikiem

ROA ujemna rentowność majątku

ROE ujemna rentowność kapitału

ROS ujemny wynik ze sprzedaży

inkaso należności powyżej 60 dni

rotacja zapasów powyżej 200 dni

wsp. długu powyżej 0,8

szybka płynność poniżej 1

w %2016 2015 2014

Unfavourable level of the current ratio - below 1.2, quick ratio - below 1


A slightly different situation was noted in the group of smaller real estate developers in 2016. The

number of profitable entities in this group increased from approx. 71% to 74%. Average return on

sales (ROS 7.2%) was slightly higher than in the group of large real estate developers. For the first

time in the past 10 years, real estate developers achieved the level of equity considered as safe by

creditors (equity accounted for about 50% of total liabilities at the end of 2016). An important

source of financing in this group of entities are bank loans, which account for approx. 18% of

liabilities, and their value has been on a steady rise for several years. According to the accounting

records, third party services, including subcontracting services (around 75%) are also a

predominant item in the operating cost structure of smaller real estate developers. Financial

liquidity of smaller players in the industry is much better than that of large ones, and thus the

liabilities turnover ratio and inventory turnover time in days is shorter. On the other hand, for

four years the debt recovery ratio has considerably exceeded two months, which may point at

payment bottlenecks.

Real estate developers listed on the Warsaw Stock Exchange, who according to estimates

generate approx. 25% of housing sold on the primary market, play an important role in the

Financial liabilities due to credit and debt securities

Value of investment expenditure

Share of investment expenditure in amortization (right axis)

Total debt ratio

Equity to assets ratio

Liabilities equity coverage ratio

Debt-to-equity ratio

Current assets

Short-term liabilities

Current liquidity ratio (right axis)

Stocks

Quick liquidity ratio (right axis)

Quick liquidity below 1

Debt ratio below 0.8

Stock turnover above 200 days

Collection of receivables above 60 days

ROS negative return on sales

ROE negative return on equity

ROA negative return on assets

Firms with negative results



residential real estate market. The data submitted by companies listed on the WSE are an

important source of information on the situation in the real estate development sector, as these

companies face more restrictions in the use of tax optimization strategies. In 2016, sales of

dwellings put on the market by the seventeen real estate developers listed on the WSE exceeded

24 thousand dwellings and were over 13% higher than in the previous year. According to the

information submitted in the financial statements, the group of these entities in 2016 generated a

much higher profit and sales revenues compared to the previous year. The increase in the value

of stock in the structure of assets of this group may be indicative of a large number of new

investment starts. The principal source of financing is equity (over 46% share in the structure of

liabilities), whose profitability at the end of the year was at a satisfactory two-digit level. In 2016,

the value of external financing, both from bank loans and debt securities, including bonds,

increased (a rise of approximately 15%). Investment expenditure remained at a similar level. The

value of buyers’ own contribution increased, to exceed 13% in the structure of liabilities. The level

of core business expenses decreased to a favourable level of over 73% in relation to net sales

revenue. The receivables recovery ratio improved to 33 days. The period of short-term liabilities

payment was relatively long (268 days) as was the home selling period (513 days). On the other

hand, liquidity ratios deteriorated, yet remained at a safe level at the end of the year. Positive

operating and financial flows and negative investment flows are indicative of the development

activity pursued (profit generation, investment and incurring liabilities).


developers quoted on the Warsaw Stock Exchange

(mln PLN)

Figure 70 The structure of assets of real estate


0

100

200

300

400

500

600

700

800

0

1000

2000

3000

4000

5000

6000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

mln

zł

Przychody ogółem Koszty ogółem

Wynik finansowy netto (P oś)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

aktywa trwałe zapasy gotówka należ. od odb.

Source NBP based on financial statements. Source NBP based on financial statements.

Total revenue

Net financial result (right axis)

Total costs Fixed assets Stocks Cash Receivables from customers



Figure 71 The structure of liabilities of real estate


Figure 72 Sources of financing of real estate


(mln PLN)

0

10

20

30

40

50

60

70

80

90

100

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

%

kapitał własny kredyty dłużne pap. wart. przedpłaty inne zobow.

0

500

1000

1500

2000

2500

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

długoterminowe kredyty

długoterminowe pożyczki, obligacje, papiery wartościowe

krótkoterminowe kredyty

krótkoterminowe pożyczki, obligacje, papiery wartościowe


Figure 73 Turnover of inventories, receivables and

liabilities of real estate developers quoted on the

Warsaw Stock Exchange (mln PLN)

Figure 74 Investment activity of real estate


(mln PLN)

0

200

400

600

800

1000

0

1000

2000

3000

4000

5000

6000

liczba d

ni

mln

zł

przychody ze sprzedażyokres ściągania należności w dniach (P oś)okres regulacji zobowiązań krótkoterm. w dniach (P oś)okres pokrycia zapasów w dniach (P oś)

0,0

2,0

4,0

6,0

8,0

10,0

0

500

1000

1500

2000

2500

3000

3500

4000

4500

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

%

mln

zł

zobow. finansowe z tyt kredytów i papierów dłużnych

wartość nakładów inwestycyjnych

udział nakładów inwestycyjnych w amortyzacji (P oś)

Unfavourable level of the debt recovery ratio in days – over 60 days, the inventory turnover time in days ratio–

over 200 days


Figure 75 Profitability of real estate developers

quoted on the Warsaw Stock Exchange (mln PLN)

Figure 76 Liquidity ratios of real estate developers


0

5

10

15

20

0

100

200

300

400

500

600

700

800

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

Wynik finansowy netto ROS (Poś)

ROE (Poś) ROA (Poś)

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

0

2000

4000

6000

8000

10000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

mln

zł

aktywa obrotowe zapasyzob. krókoterminowe wsk. szyb. płynnności (P oś)wsk. płynności bieżącej (P oś)

Note to Figure 75: Unfavourable level of ROS, ROE and ROA - below 0

Note to Figure 76: Unfavourable level of the current ratio - below 1.2, quick ratio - below 1


Equity capital Loans Debt securities Pre-payments Other liabilities

Long-term credit

Long-term loans, bonds, securities

Short-term credit

Short-term loans, bonds, securities

Sales revenue

Debt recovery ratio (right axis)

Period of short-term liabilities payment (right axis)

Inventory turnover time (right axis)

Financial liabilities due to credit and debt securities

Value of investment expenditure

Share of investment expenditure in amortization (right axis)


ROE (right axis)

ROS (right axis)

ROA (right axis)

Current assets Short-term liabilities

Current liquidity ratio (right axis)

Stocks

Quick liquidity ratio (right axis)



Figure 77 Debt ratio and debt service coverage ratio

of real estate developers quoted on the Warsaw

Stock Exchange

Figure 78 Cash flows of real estate developers


0%

50%

100%

150%

200%

250%

300%

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

wsk. ogólnego zadłużenia

wsk. pokrycia majątku kapitałem własnym

wsk. zabezpieczenia zob. finansowych kapitałem własnym

wsk. zadłużenia kapitału własnego

-1000

-800

-600

-400

-200

0

200

400

600

800

1000

2007 2008 2009 2010 2011 2012 2013 2014 2015mln

zł

Przepływy operacyjne Przepływy inwestycyjne

Przepływy finansowe

Unfavourable levels of profitability ratios: total debt ratio – over 0.8 (80%), equity to assets ratio – less than

100%, liabilities equity coverage ratio - over 1.25 (125%), debt-to-equity ratio - over 2.2 (220 %)


Box 1. Results of a pilot study of the situation of real estate developers

In May 2017, selected NBP branches conducted a pilot survey involving real estate developers i.e.

companies carrying out residential and commercial development projects and construction work

related to building construction. The survey addressed selected aspects of the activity of the those

companies, including the assessment of the current economic situation (the second half of 2016 as

compared to the first half of 2016) and forecasts for the first half of 2017. Thirteen companies

participated in the survey. Approximately 80% of the surveyed developers were large companies

and more than 20% smaller companies. Approximately 62% of the respondents are involved in

housing projects only. The remaining respondents are involved in residential and commercial

construction projects and construction works connected with building construction.

In the business climate survey conducted among developers operating in Poland, real estate

developers positively assessed their current economic situation in the second half of 2016. More

than 60% of respondents felt their situation had improved as compared to the previous half.

According to others, their economic situation has continued to be strong. More than half of the

respondents recorded an increase in demand, while in the opinion of other respondents demand

continued at a similar level. Growing competition, uncertainty over the general economic

situation, legal regulations concerning the construction sector and the real estate market,

including restrictions in land availability rising costs of labour and materials, were listed as

barriers to business operations. In the second half of 2016, half of the respondents reported an

increase in the sale price of residential real estate. Over 40% of real estate developers have kept

their prices unchanged. According to the majority of the respondents, orders for the construction

of residential or non-residential buildings remained at the level observed over the previous six

months. More than 30% of companies declared an increase in the number of orders.

Total debt ratio

Equity to assets ratio

Liabilities equity coverage ratio

Debt-to-equity ratio

Operating flows

Financial flows

Investment flows



The model analysis of a residential project

The analysis of the real estate developer sector is based on the analysis of production

profitability. It is based on the analysis of the real estate development process, prices of sold

properties, and costs of production factors. Costs of labour, capital and land were further

separated from production costs, and then their share in the production costs of specific

properties was determined. As part of the analysis of prices of production factors, the following

is examined: average cost-based estimates of labour rates (according to the types of works; see

Figure 79), average prices and changes in prices of materials and rental of construction

equipment (see Figure 80), and prices of building land.

The analysis of real estate development process carried out by NBP since 2006 is based on the

specially prepared cost estimates of Sekocenbud covering the period 2007-2016, and on the model

of the complex “multi-family building”, including land development elements and utility

connections. The assumptions concerning the building are the basis to calculate the impact of

changes in production factors on construction costs.

The prices of building land have been monitored since 2014 by local analysts of NBP Regional

Branches with the use of statistical methods, comparison of pairs and adjusted mean, and with

the use of the mixed method. The estimates of prices per square meter of building land are

applied to the analysis of the structure of price per square meter of an average dwelling in the

analyzed cities.

The comparison of construction costs with home prices obtained on the basis of own study

carried out as part of public statistics research programme including the costs of building land

allows to quantify the structure of home price and developer profit. The knowledge of typical

investment projects used by developers allows for estimating the return rates on projects

acquired by them, which is the basic indicator enabling the assessment of their activity (see

Figure 52).

The majority of the respondents (approx. 70%) did not anticipate any changes in their economic

situation in the first half of 2017, including changes in demand for real estate and construction

works. The remaining developers expect their economic situation and profitability to improve. In

the survey carried out by NBP for the second half of 2016, developers estimated their land

resources to be sufficient for the construction for another 5.5 years or so. In the second half of

2016, as compared to the first half of 2016, almost half of the respondents recorded an increase in

net prices of development land. Three quarters of the respondents recorded an increase in the

cost of executing investment projects. The remaining group of respondents did not note any

changes. As regards problems that may be relevant for their economic situation, the respondents

listed rising prices of building land resulting from restrained access to land, and growing

production costs, including costs of construction materials and land.



Figure 79 Average gross cost estimate-based rates

(PLN/1 man-hour) in developer construction in

second quarters

Figure 80 Changes (y/y) in prices of construction

materials and rental rates of equipment in

developer construction

24,0

25,0

26,0

27,0

28,0

29,0

II 2

01

2

II 2

01

3

II 2

01

4

II 2

01

5

II 2

01

6

II 2

01

7

robotyokołobudowlaneinwestycyjne

robotyokołobudowlaneremontowe

roboty instalacjisanitarnych

roboty instalacjielektrycznychnych

roboty inżynieryjne

robotywykończeniowe(wysoki standard)

średnia

-5%

0%

5%

10%

15%

20%

IV 2

004

IV 2

005

IV 2

006

IV 2

007

IV 2

008

IV 2

009

IV 2

010

IV 2

011

IV 2

012

IV 2

013

IV 2

014

IV 2

015

IV 2

016

II 2

01

7

materiały bud. sprzęt bud.

Source NBP, Sekocenbud. Source NBP, Sekocenbud.

Figure 81 Structure of construction costs of a half of

building 1122-302 (PLN million) Figure 82 Changes in construction price of 1 square

meter of usable area of a residential building (type

1122-302)

0

1

2

3

4

5

6

7

8

9

10

11

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

mln

zł

robocizna materiały sprzęt koszty pośrednie zysk budowlany

90%

92%

94%

96%

98%

100%

102%

104%

106%

108%

110%

112%I

20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

robocizna materiały sprzęt

koszty pośrednie zysk budowlany RAZEM

ziemia+zagosp.ter.

Source NBP, Sekocenbud. Source NBP, Sekocenbud.

Note to Figure 82: the vertical line divides the expert estimate of land price from the more detailed analysis

carried out by NBP Regional Branches; the estimate is weighted with the area of the completed developer

housing in 6M.

In 2016 growth in construction costs and prices of construction materials remained positive. Land

prices are volatile, which is typical for this production factor, whose price in the situation of

growing demand is determined by marginal costs rather than the average ones (see Figure 82).

Figure 83 Predicted changes in prices of

construction and assembly works (+3M) and

growth in construction costs of usable area of a

residential building (building type 1121#)

Figure 84 Average construction price of square

meter of usable area of a residential building (type

1122-302; PLN)

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 201

2

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

Przewidywane zmiany cen robót bud.-montaż. (+3M) wg ankiety GUS

Dynamika kw/kw faktycznych kosztów budowy wg Sekocenbud

2400

2500

2600

2700

2800

2900

3000

3100

3200

3300

3400

3500

3600

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017


Source NBP based on NBP, Sekocenbud. Source NBP based on Sekocenbud.

construction-related works repair construction-related works

sanitary system works electrical system works engineering works finishing works (high standard) average

materials equipment rental

workman-ship

materials equip-ment

indirect costs construction profit

workmanship

indirect costs

land+developments

materials

construction profit

equipment

TOTAL

expected changes of prices of construction costs

dynamic of real construction costs



The condition of real estate developer companies improved as the structure of offered housing to

the demand structure was matched. Demand for small, 1- to 2-room dwellings still prevails in the

market as they are more liquid as an investment and available to consumers because of their low,

total price. They may serve both as housing for small households, as investment (housing for

rent), and as the last home for the retiring generation. Dwellings ≤ 50 sq. m prevailed in the

primary market, their offer was much more adjusted to the demand than that of dwellings >50 sq.

m (see Figures 85 – 86). The secondary market still saw larger mismatch of the housing offer to

demand in terms of usable area (see Figures 87–88).

Figure 85 Measure of adjustment of dwellings on

offer to demand* in terms of area ≤ 50 sq. m, PM in

Poland’s selected cities

Figure 86 Measure of adjustment of dwellings on

offer to demand* in terms of area ≤ 50 sq. m, PM in

Poland’s selected cities

-80%

-60%

-40%

-20%

0%

20%

40%

60%

I 2

00

7

I 2

00

8

I 2

00

9

I 2

01

0

I 2

01

1

I 2

01

2

I 2

01

3

I 2

01

4

I 2

01

5

I 2

016

I 2

017

Warszawa 6M 10M

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

35%

I 2

00

7

I 2

00

8

I 2

00

9

I 2

01

0

I 2

01

1

I 2

01

2

I 2

01

3

I 2

01

4

I 2

01

5

I 2

016

I 2

017

Warszawa 6M 10M

Note: Figure 85 shows the percentage short-term mismatch between supply (housing offered by real

property developers) and estimated demand (transactions) with regard to the area of housing in the primary

market, according to the data from the BaRN database. The mismatch is calculated as the ratio of the share of

housing units with usable area of up to 50 square meters offered for sale to the number of transactions

involving housing units with a total area of up to 50 square meters (the average figure for the last four

quarters). A positive result (above the black line) indicates the surplus of dwellings of a particular size, a

negative result – their deficit. Figure 86 is parallel for the primary market, figures 87-88 are parallel for the

secondary market.


Figure 87 Supply and demand mismatch*; dwellings

with an area ≤ 50 square meters – secondary market

in selected cities of Poland

Figure 88 Supply and demand mismatch*;

dwellings with an area > 50 square meters –

secondary market in selected cities of Poland

-60%

-50%

-40%

-30%

-20%

-10%

0%

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

Warszawa 6M 10M

0%

10%

20%

30%

40%

50%

60%

70%

80%

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

Warszawa 6M 10M




As a result of the high sales level recorded at the end of 2016, home selling time in the primary

market shortened (see Figure 89). In the secondary market in Warszawa and 10M home selling

time was variable in time, yet showed a slight downward trend. On the other hand, in 6M home

selling time has been on a rise since 2015 (see Figure 90). In the period from 2012 Q2 to 2015 Q2

Warszawa recorded an increase in home selling time which may be attributed to the fact that

sellers did not accept offering prices and purchase offers.

Figure 89 Selling time of dwellings on offer in the

primary market in selected cities (number of

quarters)

Figure 90 Selling time of dwellings on offer in the

secondary market in selected cities (number of

quarters)

2

3

4

5

6

7

8

9

I 2

012

III

201

2

I 2

013

III

201

3

I 2

014

III

201

4

I 2

015

III

201

5

I 2

016

III

201

6

I 2

017

Łódź Kraków Poznań Trójmiasto

Warszawa Wrocław 6 rynków

0,0

0,5

1,0

1,5

2,0

2,5

3,0

I 20

07

I 20

08

I 200

9

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

Warszawa śr. 6M śr. 10M

Source REAS. Note: Real data, 4-quarter average. Data non-comparable to

Figure 89.

Source NBP.

Box 2. Results of land price analysis in 2016 based on the BaRN database and reports of real

estate developers listed on the Warsaw Stock Exchange

Land for single- family housing construction

In Poland almost half of the housing needs are met by individual investors. According to GUS

data, the share of individual housing in the residential real estate in 2016 amounted to 47.8%. The

increase in the number of single-family houses is especially visible on the outskirts of cities or in

nearby locations forming an urban agglomeration, which boosts demand for land for single

family house construction.

The fact that land intended for single family house construction has different characteristics, is

equipped with different utilities, coupled with the absence of land development plans, makes the

analysis difficult.

In 2016 the BaRN database recorded approx. 1300 transactions involving land for single family

housing construction. The most popular plots, those with an area of 600-1200 square meters of

land were analyzed. Land located in voivodship capitals and in Gdynia was the object of

approximately 36% of the analyzed transactions. Out of these transactions, the highest price per 1

square meter of land intended for single family house construction was recorded in Warszawa

(PLN 595/ sq.m), Gdynia (PLN 497/ sq.m) and Poznań (PLN 371 / sq.m). Prices of land for single-

family housing outside city limits are significantly lower than in capital cities of voivodships,

e.g., in the Wielkopolskie voivodeship by 22%, while in the Pomeranian voivodship by as much

as 69%.

average 6M average 6M average 10M



Figure 91 Average price per square meter of land for single family housing

0

100

200

300

400

500

600

700

Stolica województwa Aglomeracja Gdynia

Source NBP.

Land for multi-family housing

The data collected in the BaRN database include transactions of purchase of land for multi-family

housing by real estate developers in voivodship cities. Information about 294 transactions

effected in 2016 was collected. The highest gross prices of plots were recorded in Warszawa (PLN

1522/sq.m), Kraków (PLN 1142 / sq.m), Wrocław (PLN 1081 /sq.m) and Gdańsk (PLN 999 / sq.m.).

For some cities, the information collected was insufficient to calculate a representative average

price. The prices of plots vary considerably. In the largest cities prices of plots of land can reach

up to several thousand per square meter (in the city centres for the high standard infill building

construction) while the prices of land on the outskirts can range from PLN 100-200/ sq.m.

Comparison of land prices is made difficult by the absence of information about planned

developments. The area of a future building is a factor determining the land price, thus, the

square meter of the residential usable area (PUM) would be the best indicator for comparison.

The data on transactions obtained by NBP branches from City Offices do not contain such data,

which makes it necessary to refer to the information on land purchases published by real estate

developers listed on the Warsaw Stock Exchange. In addition to the information about the area of

the plot of land, they also publish data on the planned areas of buildings. Data on approx. 40

transactions point out that in 2016 the highest net prices per square meter of usable area (PUM)

were recorded in Warszawa (PLN 1196/ sq.m.), (PUM) were recorded in Warszawa (PLN 1196/

sq.m.), Kraków (PLN 932 / sq.m), Poznań (PLN 850 / sq.m), Wrocław (PLN 798 PLN / sq.m)

and Gdańsk (646 PLN / sq.m). Comparison of these prices with the prices of dwellings on the

primary market gathered in the BaRN base in 2016 shows that the share of land prices in the price

of 1 square meter of dwellings amounted to approx. 17% in Warszawa, 16% in Kraków, 15% in

Poznań, 14% in Wrocław and 11% in Gdańsk. This share was at a level comparable to the 2015

level. Table: 1 Statistics on the sale of land intended for multi-family housing Price (PUM) - stock market report

Warszawa Kraków Wrocław Gdańsk Poznań

2015 1 263 1 051 768 465

2016 1 196 932 798 646 850

Price of sq.m. of housing (BARN)


2015 6 927 5 659 5 604 5 519

2016 7 084 5 864 5 682 5 880 5 796

Price (PUM) / price of sq.m. of housing (BARN)


2015 18% 19% 14% 8%

2016 17% 16% 14% 11% 15% Source NBP

capital city Aglomeration



23 The Act of 14 April 2016 on the suspension of the sale of Agricultural Property owned by the State Treasury and on

the amendment of certain acts (Journal of Laws 2016, item 585, as amended).

24 Irrelevant decisions within the meaning of article 2 point 1 of the Agricultural System Act (Journal of Laws 2016, item

252, as amended).

Agricultural land

On 1 May 2016, the 12-year protection period making it impossible for foreigners from countries

being contracting parties to the Agreement on the European Economic Area (mainly EU Member

States) and the Swiss Confederation to purchase agricultural land ceased to apply in Poland.

Laws limiting the trade in agricultural land were introduced on 30 April 2016. They were justified

by fears of land speculation. According to the new regulations, only farmers who can cultivate

land, churches, religious associations, national parks, local government units (e.g. municipality)

and the State Treasury may be the owners of agricultural land. Unrestricted trade in land is

permitted in the case of real estate up to 0.3 hectares. This is supposed to stabilize prices and

foster growth and development of family farms. According to the Act,23 state-owned agricultural

land will be at the disposal of the Agricultural Property Agency (Agencja Nieruchomości

Rolnych – ANR), and lease will be the principal method of agricultural land management.

In Poland in the years 1999-2016 the average price of agricultural land (per 1 ha) in private trade

increased nine times. After the Act entered into force, growth in the prices of agricultural land

slowed down to 2.9% as compared to 19.4% in 2015.

Figure 92 Average prices of arable land (per 1 ha) in private trade in selected voivodships in the years

1999-2016

-

10 000

20 000

30 000

40 000

50 000

60 000

Wielkopolskie Kujawsko-Pomorskie Opolskie

Warmińsko-Mazurskie Pomorskie Mazowieckie

Podlaskie Łódzkie Polska

-

10 000

20 000

30 000

40 000

50 000

60 000

Dolnoścląskie Śląskie Małopolskie

Lubelskie Zachodniopomorskie Lubuskie

Świętokrzyskie Podkarpackie Polska

Source Statistical Office Source Statistical Office

According to its data, the Agricultural Property Agency received 4,087 applications for the

transfer of ownership of agricultural land with an area of 11,542 ha from 30 April to 31 December

2016. 3,730 applications for agricultural land with an area of 10,116 hectares were granted a

positive decision, 52 (565 hectares) were turned down, and 305 applications (861 hectares) were

cancelled.24

The Act may be a barrier to new residential investments on the outskirts of cities and towns

(agricultural land) and areas not covered by the local area development plan. In a pilot survey

conducted by NBP among real estate developers in May 2017, nearly half of respondents

declared that in the last half-year period, compared to the previous half-year period, net land

prices of residential or commercial construction projects had increased, and half of them said that

the price had remained unchanged. Approx. 92% of real estate developers indicated that they had

land banks sufficient for investment in the coming years (for the period of 2 to 10 years).



3.3 Housing demand

In Poland, as in other developed countries, the housing sector is closely related to the financial

sector, which, to a considerable extent, funds the purchase and the construction of dwellings.

Therefore, the cost of credit (the interest rate) and other terms and conditions of loan granting

affect demand. Mortgage debt in Poland is below the European average.

In 2016 lending was stable in Poland. Interest rates on mortgage loans in PLN, standing at their

historic lows since 2015, exerted a positive impact on creditworthiness of households (see Figure

93). The growth of household real income, higher than the real interest rate paid on loans,

reduced the share of loan repayments in the average household budget. These phenomena were

favourable for borrowers and encouraged them to use bank financing while buying a house. Both

availability of credit (see Figure 94) and availability of loan-financed housing amid stable home

prices (see Figure 197) continued in 2016.

Figure 93 Interest rate on mortgage loans in nominal

terms

Figure 94 Estimates of available mortgage loans # in

weighted terms (left-hand scale) +ZKPK (right-hand

scale)

1%

2%

3%

4%

5%

6%

7%

8%

9%

I 200

5

I 20

06

I 20

07

I 200

8

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

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I 20

15

I 20

16

I 20

17

PLN nowe CHF nowe EUR nowe

PLN stany CHF stany

-10

-8

-6

-4

-2

0

2

100

150

200

250

300

350

400

450

500I

20

06

I 20

07

I 20

08

I 20

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I 20

10

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11

I 20

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I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

tys.

zł

Gdańsk Gdynia Kraków

Łódź Poznań Warszawa

Wrocław śr. 7M ZKPK P. oś

Note to Figure 94: weighting the increase in housing loan to households with the currency structure (since the

beginning of 2012 practically only PLN-denominated loans were extended); ZKPK – accumulated index of

changes in banks’ lending policy criteria showing the trend in changes (decrease=tightening of policy).

Source NBP. Source NBP, GUS.

PLN new

PLN stock

CHF new

CHF stock

EUR new

Index ZKPK Avg. 7M



Figure 95 Availability of loan-financed housing# Figure 96 Estimate of housing demand in PM in 6C

and its components

30

50

70

90

110

130

150

I 2

006

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

Gdańsk Gdynia Kraków Łódź

Poznań Warszawa Wrocław śr. 7M

- 200

- 100

0

100

200

300

400

500

600

-300

-250

-200

-150

-100

-50

0

50

100

150

200

250

I 20

07

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08

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09

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12

I 20

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I 20

16

I 20

17

popyt całkowity szacowany popyt całkowity rzeczywisty

popyt konsumpcyjny (p.oś) popyt inwestycyjny (p.oś)

popyt spekulacyjny (p.oś)

Note to Figure 96: the total factor of demand is composed in 60% by consumer demand (availability of loan-

financed housing), in 30% by the profitability of housing rental and in 10% by investor's speculation profit.

The weights have been expert-estimated, the index shows the moving average from two subsequent quarters.

Source NBP. GUS. Source NBP, GUS.

A considerable impact on demand in 2016 was also exerted by the government's housing policy.

Under the programme, over 27 thousand housing loan contracts were signed in the analysed

period for the total value of PLN 4.5 billion, whereby approx. PLN 700 million worth support

was extended. Approx. PLN 0.3 million went to the secondary market – out of approx. 11.5

thousand loans totalling approx. PLN 1.5 billion.

Figure 97 Limits of max. prices per 1 square meter in

the primary market under the government MDM

programme MDM in Poland's major cities

Figure 98 Limits of max. prices per 1 square meter

in the secondary market under the gov. programme

MDM in Poland's major cities

2000

3000

4000

5000

6000

7000

8000

9000

10000

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

Warszawa 6M 10M

2000

3000

4000

5000

6000

7000

8000

9000

10000

I 2

007

I 2

008

I 2

009

I 2

010

I 2

011

I 2

012

I 2

013

I 2

014

I 2

015

I 2

016

I 2

017

Warszawa 6M 10M

Note to Figures 97 and 98: The red vertical lines section off the period without government programmes

supporting the purchase of dwellings.

Source NBP based on BGK. Source NBP based on BGK.

As a result of the impact of all the factors discussed above, housing markets of the largest cities in

Poland saw a significant acceleration in developer housing purchases (see Figure 26). The

purchase of housing was financed both with loans and with buyers' own funds (see Table 2).

However, the scale of disbursements from bank deposits for this purpose cannot be captured

statistically in the aggregated financial flows in the national economy and it can be only

estimated based on the data derived from the housing and banking markets.

Avg. 7M

estimated total demand

consumer demand (RH)

speculative demand (RH)

real total demand

investment demand (RH)



Table 2 Estimated gross housing loan disbursement to households in Poland and estimated purchases of

developer housing financed both with cash and with loans in the seven largest markets (in PLN million)

Date Estimated value of disbursed

mortgage loans in Poland

Estimated value of housing

transaction in the PM in 7M

Estimated disbursements of

loans with own contribution for

housing purchase in the primary market

in 7M

Estimated value of home

purchases in the PM in

in 7M

Estimated share of cash home

purchases in the RP in 7M

2013 Q1 6295 2705 1121 1584 59%

2013 Q2 7867 3047 1428 1620 53%

2013 Q3 9140 3599 1690 1908 53%

2013 Q4 9084 4095 1773 2321 57%

2014 Q1 7571 3852 1478 2374 62%

2014 Q2 8899 3671 1737 1934 53%

2014 Q3 8894 3649 1736 1913 52%

2014 Q4 8122 3802 1585 2217 58%

2015 Q1 8996 4020 1756 2264 56%

2015 Q2 10640 4442 2077 2365 53%

2015 Q3 10341 4606 2019 2587 56%

2015 Q4 11237 4967 2194 2773 56%

2016 Q1 9742 5039 1902 3138 62%

2016 Q2 11661 5345 2276 3069 57%

2016 Q3 9632 5041 1880 3161 63%

2016 Q4 9933 6404 1939 4465 70%

2017 Q1 10945 6503 2137 4367 67%

Note: The estimates are based on the following assumptions:

In the period 2012 Q4-2014 Q4, the estimates of newly granted loans in Poland in individual quarters were based on

the increases in loans to households adjusted for loan amortization and flows between the foreign currency and PLN

portfolio, available in NBP reporting. The entire banking system and credit unions were taken into account. Starting

as of 2015 Q1, the estimated value of loan disbursements is based on the data collected from banks.

The estimated value of transactions in the primary market of 7 cities (Gdańsk, Gdynia, Kraków, Łódź, Poznań,

Warszawa, Wrocław) was calculated by multiplying the average price of dwelling by its average size in square

meters and the number of dwellings sold (based on the REAS data). On the basis of ZBP data it was assumed that

the value of newly granted loans for the purchase of housing in the primary markets of 7 C in 2012 accounted for

50% of the value of housing loans in those cities, whereas at the end of 2013 this share amounted to approx. 57%.

The estimated value of cash transactions constitutes the difference between the value of transactions in the market of

7 cities and loan disbursements, including own contribution. The home price and area data for all periods have been

updated.

Source NBP, REAS, ZBP, GUS.

The proportions of financing of growing housing construction changed (housing loan vs. own

funds) as in the previous year, the share of non-credit financing was on the rise. The growth in

lending was positive and stable (see Figure 99), and the level of housing loans (debt level)

continued to increase during the whole period, although lending in foreign currency practically

ceased.



Figure 99 Estimated loan disbursements (in PLN

billion, left-hand axis) and lending growth in 2012-

2015 (right-hand axis)

Figure 100 Estimated ROE on residential mortgage

loans denominated in PLN for banks in Poland

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

0

2000

4000

6000

8000

10000

I 20

12

III 2

012

I 20

13

III 2

013

I 20

14

III 2

014

I 20

15

III 2

015

I 20

16

III 2

016

I 20

17

Spłata kapitału kredytów złotowych

Różnica salda kredytów złotowych

Przyrost % na samych saldach (P oś)

Przyrost uwzględniający szacunek wypłat (P oś)

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

IV 2

00

8

II 2

00

9

IV 2

00

9

II 2

01

0

IV 2

01

0

II 2

01

1

IV 2

011

II 2

01

2

IV 2

01

2

II 2

01

3

IV 2

01

3

II 2

01

4

IV 2

01

4

II 2

01

5

IV 2

01

5

Obciążenie kredytów odpisamiEfektywny koszt finansowania kredytówEfektywne oprocentowanie kredytówSkorygowana marża odsetkowa na kredytachROE (p. oś)


In 2016 banks declared they would continue to tighten their prudential policy, which had the

opposite effect than interest rate cuts25. The historically low interest rate on mortgage loans and

the newly imposed tax on bank assets were offset by banks with growing interest margins,

having a particularly strong impact on demand in the case of long-term loans with low principal

instalments.

Figure 101 Currency structure of the housing loan

portfolio in Poland

Figure 102 Quality of the housing loan portfolio

in Poland

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

I 2

00

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01

1

I 2

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2

I 2

01

3

I 2

01

4

I 2

01

5

I 2

01

6

FX housing loan

PLN housing loan

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

0

50

100

150

200

250

300

350

400

I 2

009

III

200

9

I 2

010

III

201

0

I 2

011

III

201

1

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012

III

201

2

I 2

013

III

201

3

I 2

014

III

201

4

I 2

015

III

201

5

I 2

016

III

201

6

Kredyty hipoteczne mieszkaniowe (L. oś)

Wskaźnik kredytów zagrożonych na nier. mieszk. (P oś)

Wskaźnik kredytów zagrożonych na nier. mieszk. złotowych (P oś)

Wskaźnik kredytów zagrożonych na nier. mieszk. walutowych (P oś)


In Poland, the long-term household debt resulting from mortgage loans was on the rise, which

was driven by the development of the housing market and the financial sector. In the end of 2016

it reached the level of approx. PLN 394.3 billion. It accounts for approx. 23.9% of financial sector

assets and approx. 12.2% of the estimated value of the housing stock. Although the indebtedness

of the housing stock in Poland continues to grow, it is still relatively low in relation to household

consumption (approx. 36%) or as compared to this debt level in other EU countries. Currently,

25 In line with the conclusions of the Report on the situation of banks in 2016 (Polish Financial Supervision Authority -

KNF), there was a certain tightening of banks' lending policy as a result of self-regulation and measures taken by the

Office of the Polish Financial Supervision Authority and the sale of a portion of impaired loan portfolio.

Principal repayment of PLN loans

Differences in balance of PLN loans

Percentage growth on balance only (RH)

Growth including estimated disbursements (RH)

Loan write-offs Effective cost of loan funding Effective interest rate on loans Adjusted interest margin on loans

ROE (RH)

Housing mortgage loans (LH)

Impaired housing loan rate (RH)

Impaired PLN housing loan rate (RH)

Impaired FX housing loan rate (RH)



residential mortgage loans in Poland account for 238% of banks’ equity which means their

considerable impact on the sector's profitability. The relation of the estimated housing debt

servicing costs (principal and interest) to consumption in the national economy as of the end of

2016 slightly declined and amounted to approx. 1.7%, (see Figure 104).26 This means that changes

in interest rates on mortgage loans have a limited impact on the global consumption

In 2016, the geographical distribution structure of new loan agreements did not change, i.e. the

largest share of those loans was still observed in the remaining part of Poland (suburban zones,

smaller towns and rural areas). Typical housing loans with a high LTV ratio (i.e. above 80%) are

predominant in large cities, constituting approx. 45% of the portfolio of such loans.27 Housing

loans in the remaining part of the country are usually smaller loans supplementing own funds for

the purchase of building materials or dwellings in the secondary market (see Figure 103). This

means that housing markets of the largest cities decide about the security of the banking sector.

Figure 103 Geographical structure of new housing

loan value in Poland

Figure 104 Repayments of housing loans and their

relation to consumption (right-hand scale)

-

2

4

6

8

10

12

14

16

18

20

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

I 20

05

I 20

06

I 20

07

I 20

08

I 20

09

I 20

10

I 20

11

I 20

12

I 20

13

I 20

14

I 20

15

I 20

16

I 20

17

Mili

ard

y

Warszawa 6M 10M PP Polska (P oś)

-0,2%

0,3%

0,8%

1,3%

1,8%

2,3%

0

5

10

15

20

25

200

4

2005

2006

200

7

200

8

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6

mld

zł

GD.obsł.kr.M GD.obsł.kr.M / Spożycia (P.oś)

Source NBP based on BIK. Source NBP, GUS.

Figure 105 Relation of profitability of housing

rental to other forms of investment

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

4,5

5,0

5,5

III 2

006

III 2

007

III 2

008

III 2

009

III 2

010

III 2

011

III 2

012

III 2

013

III 2

014

III 2

015

III 2

016

najem do st.kred.mieszk.GD najem do st.obl.10l.najem do st.kap.nier.kom. najem do inw.finans.GDnajem do st.dep.stan GD

Source NBP, MF, reports of advisory companies.

Housing demand is usually divided into consumption-, investment- and speculation-driven

demand.

26 However, the lack of detailed data on borrowers makes it impossible to conduct an in-depth analysis. As a result, we

use approximate data, including the reference to consumption in the national economy.

27 According to the National report on housing loans and transaction prices of real property; AMRON-SARFIN 4/2016 (report

no. 30 of the Polish Banks Association).

Household housing

loan servicing costs Household housing loan

servicing costs/consumption

Rental to 10-y. bonds

Rental to households fin. investment

Rental to household housing loan

Rental as to commercial property cap. rate

Rental to household deposits

(RH)



Pure consumption demand is demand for housing for rent (purchase of a service). The purchase

of owner-occupied housing always includes an investment element, however, meeting housing

needs is of major importance for home buyer. The higher the own contribution, the more

important the investment element. A typical investment purchase is a purchase of housing for

rent, where proceeds from rent constitute income (buy to let). Speculation driven demand is a

short-term investment purchase, where the buyer expects income from the growth in home

prices after home resale. The speculation mechanism works like a self-fulfilling prophecy.

Growing home prices make home purchase profitable, thus there are new buyers bidding up

the price.

Banks are usually reluctant to finance investment housing and speculation housing construction,

so in those cases own financing, the so-called cash demand (usually financed with funds held at

banks) is more important. Investment demand often turns into speculation demand and may lead

to real property crises, as it has a destabilising impact on the financial system. Low interest rates,

which translate into low alternative costs and thus encourage speculation, may favour such

behaviour. Motivations behind such behaviour are observed alongside a favourable relationship

of rental income to the cost of credit or interest on bank savings. The investor also compares the

profitability of housing investment to the return on other assets available to them. The rental

market is developing, however, it has operated mainly in the grey economy. The main barrier to

the development of this sector is the absence of changes in the regulations that are detrimental to

the interest of property owners, i.e. the legislation discriminating against landlords in favour of

tenants.

In 2016 an increase was also noted in the number of applications for permits for the purchase of

residential and/or commercial real estate by nationals of other countries who plan to

permanently reside in Poland, including in particular, citizens of Ukraine (over 61% of

applications). According to the data of the Ministry of the Interior and Administration,28 the

number of permits issued to foreigners for the purchase of housing with the total area of

approximately 5.9 thousand square metres (as compared to 4.6 thousand square metres in 2015)

increased to 96 (against 68 in 2015). Such dwellings are usually purchased for cash. At the same

time, both the number and the area of real estate covered by the permits for the acquisition of

shares in companies holding real estate decreased significantly (y/y). Low interest rates on

deposits alongside increasing levels of rent for the lease of residential real estate boosted the

profitability of the purchase of rental housing as an alternative to bank savings and for

investment purposes (see Figure 105). Low interest rates on housing loans boosted investment

demand involving the purchase of rental housing with savings, additionally supported with

loans.

28 The obligation to obtain a permit for the purchase of real estate does not apply to natural persons and legal persons

who are nationals or entrepreneurs of the States being contracting parties to the Agreement on the European Economic

Area or the Swiss Confederation. Figures based on the data of the Ministry of the Interior and Administration are

available on the website: https://mswia.gov.pl/pl/bezpieczenstwo/koncesje-i-zezwolenia (str. 27-40).

https://mswia.gov.pl/pl/bezpieczenstwo/koncesje-i-zezwolenia

4. Trends in the commercial real estate market in Poland in 2016.


4. Trends in the commercial real estate market

in Poland in 2016.

The commercial real estate market,29 in particular the markets for office and retail space, is seeing

yet another year of imbalances involving oversupply of rental space. Foreign investors account

for the majority of the investments in this segment. At the end of 2016, the value of loans for

offices and other non-residential real estate granted by banks operating in Poland reached

approx. PLN 47 billion, posting a rise of PLN 1.8 billion as compared to the end-of-2015 figure.

This is a rather insignificant amount as compared to residential real estate loans. As the

imbalances in the office and commercial real estate market persisted and real estate developers

continued constructing new buildings, NBP in the Financial Stability Report, June 2017 upheld its

recommendation for banks regarding granting commercial property loans.30 These

recommendations, if followed, should limit any potential problems of domestic banks.

Sustained economic growth, low interest rates on foreign loans and persistently high rates of

returns in Poland motivate foreign investors to continue investing in commercial real estate,

despite the fact that the market is already saturated. Amid relatively stable demand for office

space, persisting supply increases vacancy rates and forces building owners to reduce their rents.

This situation can have a negative impact on investors' incomes, which can directly affect their

ability to service debt and, in the case of investment funds, dividend distribution. This

phenomenon is confirmed by falling transaction costs. There is also a growing risk for foreign

banks, as low rents can mean problems with loan repayment and may contribute to a decline in

the value of the real estate constituting the loan collateral. Faced with such risks, banks should

apply particularly prudent appraisal methods and assess the loan repayment capability of the

investor.

4.1 Transactions in the commercial real estate market, analysis of supply and demand

In the commercial real estate market, 2016 was another year with a record high value of

investment transactions. The value of these transactions amounted to EUR 4.6 billion, which is as

much as the record high 2006 figure (see Figure 106). According to Comparables.pl data, office

space transactions accounted for approx. 38% of the value of all transactions, commercial real

estate transactions for approx. 41% and warehouse space transactions for 18%, showing a 8p.p.

rise against the previous year. The major part of the transactions involved the change of the

29 A detailed analysis of local commercial markets is included in the Analysis of 16 cities.

30 Recommendation 6 contained in the Financial Stability Report February 2016 reads as follows: "Banks should pursue a

particularly prudent lending policy in the segment of commercial property loans. The situation in the major segments of

the commercial property market (office and retail property) suggests that imbalances have been growing, which amid

continually rising supply may result in increased credit risk. Banks should exercise utmost prudence in examining the

quality of loan collateral, the reality of assumptions concerning cash flows generated by the property and the borrower’s

loan repayment capacity."



owner of the already operating and leased commercial premises. Capitalization rates in the office

space market were running at 5-7%, whereas in the retail real estate market in major cities they

reached approx. 5.5%. Such low capitalization rates are indicative of liquidity surplus in the EU

financial market which is connected with the monetary policy pursued by the European Central

Bank.

Figure 106 Value of investment transactions in the

commercial real estate market (EUR billion)

0

1

2

3

4

5

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

I 2

017

Biura Handlowe Magazyny Pozostałe

Note: The 2017 data relate to quarter 1 only.

Source Comparables.pl.

The total value of loans granted by banks in Poland to enterprises for office real estate at the end

of 2016 amounted to approx. PLN 53 billion (see Figure 19) and was PLN 1 billion higher than in

the corresponding period of 2015. The stock of loans extended to enterprises in Poland and

intended for office space construction and other real estate amounted to PLN 15.5 and PLN

30.2 billion respectively. On the other hand, the value of loans extended to entrepreneurs for

housing (developer) real estate stood at PLN 6.2 billion. The share of loans classified as non-

performing loans in the total loans for office space construction remained unchanged at 5% and

in the case of loans granted for other real estate, the ratio remained at about 9%. The share of non-

performing loans dropped from 26% to 22%. Housing developer loans account for a small share

of assets of crediting banks and do not pose any significant credit risk. If Polish investors enter

the commercial real estate market on a large scale, bank debt of Polish investors resulting from

this real estate may be expected to grow. Since there are no official data on loans granted for

commercial real estate construction by foreign banks, this figure should be additionally estimated

by experts. Based on the estimated value of the office, retail and warehouse space, which

amounted to PLN 223 billion at the end of 2016, and given that the average real estate debt ratio

is 50%31, it can be assumed that the total value of these real estate loans in 2016 was PLN 111

billion. By deducting loans granted by banks operating in Poland, we obtain the estimated

amount of loans granted indirectly and directly by banks operating abroad, i.e. PLN 64 billion. It

should be added that information about investments in the commercial real estate and loans

31 In line with S Recommendation of the Office of the Polish Financial Supervision Authority, the LTV for the

commercial real estate is 75% or 80% if the part of the exposure exceeding 75% LtV is adequately hedged, or if the

borrower has submitted additional collateral in the form of a blockade of funds in a bank account or in the form of a

pledge on debt securities of the State Treasury or of NBP, denominated in PLN.

Office Retail Warehouse Others



granted for commercial real estate construction cannot be directly combined. In the case of an

investment project, data is collected only when the transaction actually takes place; yet, part of

the real estate is built by the owner or for the owner’s needs, so no sales transaction takes place

(for example, office buildings for the company's own needs, chains of retail stores). On the other

hand, not every investment transaction involves a rise in bank debt. When the property sold is

fully commercialized, the new buyer takes out a loan, but the seller can repay the loan earlier.

As at the end of 2016, office space in Warszawa exceeded 5 square meters, and in Poland - 9

million square metres. As a result of a strong growth in the real estate area by approx. 900

thousand square meters, the vacancy rate in major office markets increased by 1.1 p.p. to 12.6%

and in Warszawa by 1.9 p.p. to 14.2% y/y.32 Office space under construction is expanding, with

approximately 1.6 million square meters being currently built, of which approx. 700 thousand

metres in Warszawa. Such a sharp rise in supply will probably exceed significantly increase in

demand, if any.

The supply of office space totalled 11.2 million square metres at the end of 2015. In the analysed

period approx. 400 thousand square meters of new office space was completed and made ready

for occupancy, i.e. approx. 30% less than in 2015.33 Less intense activity of real estate developers

may result from growing saturation with office space per inhabitant (which was 252 square

meters per 1000 persons) and growing share of trade in electronics (accounting for approx.

10%).34

Transaction prices of office space, which are typically expressed in EUR per square meter,

remained stable all over Poland, except for Warszawa, where they came back to the 2014 level

after declines recorded in 2015 (see Figure 107). Movements in the hedonic price of office space

(which adjusts price changes driven by a change in the real estate sample being the object of

transactions) throughout Poland and in Warszawa was stable over the last three years.

Over the past few years transaction prices of office space throughout Poland have seen a slight

upward trend around which the price oscillates (see Figure 109 and 110). Movements in the

hedonic price are similar which results from a relatively small sample and the fact that in certain

years transactions in large voivodship cities are dominant, whereas in others transactions in

peripheral towns.

The analysis of the median of offer prices of small retail and service premises in Poland and in

Warszawa shows slight price declines; yet, in certain voivodship cities prices in 2016 remained

stable. On the other hand, the median of offer prices of small office premises in the majority of

markets remained stable, showing a downwards trend in Warszawa since the beginning of 2016.

This may be driven by strong competition generated by modern B class office buildings where

rents are a on gradual decline.

32 See: See the Colliers International "Market Insights - 2017 Annual Report" based on: Polish Office Research Forum,

2016.

33 See: See the Colliers International "Market Insights - 2017 Annual Report".

34 See: Knight Frank "Poland, Commercial Market 2016"



Figure 107 Average growth of office real estate in

Warszawa and all over Poland (EUR per sq.m.)

Figure 108 Growth of average and hedonic prices of

retail real estate (2004=100)

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dynamika ceny hedonicznej - Warszawa (L.oś)dynamika cen średnich - Warszawa (L.oś)dynamika ceny hedonicznej - Polska (P.oś)dynamika cen średnich - Polska (P.oś)


Figure 109 Average price of commercial real estate in

Poland (EUR per sq.m.)

Figure 110 Growth of average and hedonic prices of

retail real estate (2004=100)

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dynamika ceny hedonicznej

dynamika ceny średniej Source NBP. Source NBP.

Figure 111 Median of the offer selling price of small

retail and commercial premises in the secondary

market (PLN/sq.m)

Figure 112 Median of offer selling price of small

office premises in the secondary market (PLN/sq.m)

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Gdańsk Katowice Kielce Poznań

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Polska Wrocław Łódź Warszawa

Gdańsk Katowice Kielce Poznań

Source PONT, NBP material Source PONT, NBP material

Box 3. Re-estimation of the hedonic model of commercial real estate appraisal in Poland

The hedonic model of the analysis of commercial real estate transaction prices has been re-

estimated as the scope of the data has widened and more real estate attributes have been

obtained. The analysis is based on the hedonic analysis model involving the entire sample, with

price changes being captured by zero-one regression for individual years. We analysed the price

hedonic dynamic

average dynamic

avg. price - Warszawa avg. price - Polska

hedonic dynamic - Warszawa (LH)

avg. dynamic – Warszawa (LH)

hedonic dynamic – Polska (RH)

avg. dynamic – Polska (RH)



in euro per 1 square metre of rental space in buildings being the object of transactions, with the

transaction value exceeding EUR 5 million.

Office real estate transactions were analysed for the whole of Poland and for Warszawa, the

largest office market in Poland. In line with the theory, the logarithm of the total space offered

for rent in particular buildings was used as explanatory variables; yet, this variable turned out

to be irrelevant. The variable differentiating class A buildings from class B buildings is

econometrically significant and means that that the price offered for class A buildings is approx.

16-20% higher than that offered for class B buildings. The next variable is the age of the building

to which the number 2 was added prior to taking its logarithm. This is necessary as buildings in

the year of the transaction or even a year later were offered for rent, and no logarithm can be

taken from 0 or -1. The distance from the business centre of the city negatively affects the price

of the property, which means that distant real estate is cheaper.

While analysing the whole of Poland, we added zero-one variables that capture transactions in

large and small voivodship cities against the background of Warszawa. The average price

obtained in large voivodship cities is approx. 41% lower than in Warszawa, and in small

voivodship cities it is even 70% lower than in Warszawa. In 2009, the year of the global crisis,

very few transactions were recorded. Yet, among them there were transactions involving two

prime location and high quality office buildings in Warszawa, generating high transaction

prices. A zero-one variable office_prime was used to capture these very expensive transactions.

Thanks to the hedonic analysis, we obtain a price index that is more resistant to significant

changes in the composition of the sample – the hedonic index is more stable than the index

calculated based on normal average prices.

We analysed transaction prices of commercial real estate for the whole of Poland, and the

analysis did not show any significant differences between the prices in the agglomerations of

large and small towns (DuAglomer variable is irrelevant). As in the case of offices, the total

area for rent was taken into account, yet, it turned out it was irrelevant. Rent transaction

prices in the leading shopping malls in Warszawa were approx. 62% higher than in other

shopping centres across the country. The zero-one variable h_typ_Park did not show any

significant differences between the average price of a retail park as compared to the average

price of other shopping centres. This difference was captured by the variables related to the

number of individual stores in the shopping centre and the number of storeys. The more shops

and storeys, the higher the transaction price of square metre of space. The age of commercial

buildings does not significantly affect transaction prices, which can be explained by the fact that

older buildings are generally situated in prime locations, and commercial buildings are

relatively frequently modernized.



Table 3. Result of the regression of factors of the price per square meter of office space in Poland and in

Warszawa, in EUR

Poland Warszawa

coefficient Standard

error

t-studenta coefficient Standard

error

t-studenta

ln_pow_do_wynajmu -0.0324121 0.0262969 -1.23 0.0092159 0.028148 0.33

b_B class 0.2058833 0.0497925 4.13 0.1638369 0.057832 2.83

ln_wiek_plus2 -0.1148695 0.0285791 -4.02 -0.1098832 0.034962 -3.14

ln_Odleglosc -0.091903 0.0223087 -4.12 -0.1520405 0.028258 -5.38

Male -0.6921474 0.0808738 -8.56

Duze -0.4102283 0.0572523 -7.17

biura_prime 0.4415073 0.1814473 2.43 0.4288437 0.180446 2.38

rd2000 -0.109129 0.1786249 -0.61 -0.1136057 0.168509 -0.67

rd2001 -0.0632671 0.1919331 -0.33 -0.0451543 0.180225 -0.25

rd2002 -0.0909308 0.1685238 -0.54 -0.0785989 0.167404 -0.47

rd2003 -0.2416303 0.1693217 -1.43 -0.2417971 0.160305 -1.51

rd2005 -0.0716208 0.1266809 -0.57 -0.0637091 0.125669 -0.51

rd2006 0.0428019 0.1257254 0.34 0.0212017 0.126172 0.17

rd2007 0.0581623 0.1262706 0.46 0.1497615 0.127904 1.17

rd2008 0.185875 0.1345831 1.38 0.1935387 0.139022 1.39

rd2009 0.1936396 0.1926053 1.01 0.1433803 0.201282 0.71

rd2010 0.0980557 0.13718 0.71 0.1168478 0.137177 0.85

rd2011 0.1347934 0.1330026 1.01 0.1559557 0.132383 1.18

rd2012 0.2551666 0.1396695 1.83 0.2523422 0.141103 1.79

rd2013 0.0754175 0.1303112 0.58 0.1474183 0.131927 1.12

rd2014 0.1444157 0.1308658 1.1 0.2021403 0.143001 1.41

rd2015 0.1548699 0.1287425 1.2 0.1006262 0.15464 0.65

rd2016 0.1357094 0.1371522 0.99 0.1380621 0.188998 0.73

_cons 9.051514 0.3372553 26.84 9.118901 0.393645 23.17

Note: 276 observations for the whole of Poland, adjusted R-square 36%, 182 observations for Warszawa, adjusted R-square

37%



Transaction rents of commercial real estate35

Rents charged for A class buildings, which are generally fixed in EUR, showed a slight upward

trend in Warszawa as compared with the previously observed declines. On the other hand, other

analysed cities continued to see a slight downward trend. Rents charged for A class office space

in Warszawa were close to EUR 22 per square metre per month, rents for B class office space

were around EUR 14 per square meter per month, while in the remaining large cities they were

ranged from EUR 13 to PLN 15 per square metre per month. Rents charged for B class office

buildings, expressed in PLN, rose slightly in Warszawa, 6M and 10M.

Transaction rents charged for retail space in shopping malls expressed in EUR/per square

metre/per month for the whole of Poland demonstrated slight declines. It should be emphasized

that since 2015 Q4 the number of respondents has increased considerably, leading to a rise in the

35 The analysis of rents based on the BaNK data base conducted by NBP, quotations are made semi-annually.

Table 4. Result of the regression of factors of the price per square meter of office space in Poland, in EUR

coefficient Standard error t-studenta

ln_pow_do_wynajmu -0.0697881 0.0646604 -1.08

DuAglomer 0.0504473 0.0761542 0.66

CHprime 0.6236537 0.1991679 3.13

h_typ_Park -0.1713906 0.1358521 -1.26

ln_h_ilesklepow 0.1107734 0.0569622 1.94

ln_ilekondygnacji 0.118268 0.0636379 1.86

ln_wiek_plus2 -0.0203699 0.0464267 -0.44

rd2002 -0.0523027 0.3086301 -0.17

rd2003 -0.1448397 0.3326529 -0.44

rd2005 0.0078223 0.2354245 0.03

rd2006 0.2134757 0.2319794 0.92

rd2007 0.2564009 0.2419429 1.06

rd2008 0.5220004 0.2577177 2.03

rd2009 0.4032822 0.2619795 1.54

rd2010 0.1555369 0.2415507 0.64

rd2011 0.1890437 0.2274204 0.83

rd2012 0.3717169 0.2565952 1.45

rd2013 0.4587755 0.2330685 1.97

rd2014 0.2676526 0.2563636 1.04

rd2015 0.5071826 0.2335803 2.17

rd2016 0.3645676 0.2540688 1.43

_cons 7.481278 0.5470587 13.68

Note: 119 observations, adjusted R-square 24%



number of records in the database. Information on transaction rents for retail space is based on a

considerably larger sample. During the whole period we analysed rents for retail space ranging

from 100 square metres to 500 square metres. We analysed rents for retail space located in

economically important parts of the city.

Figure 113 Transaction rents for office premises

(average prices in EUR/sq.m./month)

10

15

20

25

II 2013 IV 2013 II 2014 IV 2014 II 2015 IV 2015 II 2016 IV 2016

Gdańsk A Katowice A Kraków A

Łódź A Poznań A Warszawa A

Warszawa B Wrocław pozostała Polska

Figure 114 Transaction rents for B class office

premises (average prices in EUR/sq.m/month)

30,0

35,0

40,0

45,0

50,0

55,0

60,0

II 2013 IV 2013 II 2014 IV 2014 II 2015 IV 2015 II 2016 IV 2016

10 miast 6 miast Warszawa

Note: Warszawa - A class office buildings,

Warszawa – B class office buildings

Source NBP.

Note: Gdańsk, Gdynia, Kraków, Łódź, Poznań,

Wrocław

Source: NBP.

Figure 115 Transaction rents for retail space in

shopping centres (shopping malls) with an area of

approx. 100 sq. m (EUR/sq.m/month)

20

25

30

35

40

45

50

55

60

II 2013 IV 2013 II 2014 IV 2014 II 2015 IV 2015 II 2016 IV 2016Trójmiasto Katowice Kraków

Poznań Warszawa Wrocław

pozostała Polska Łódź

It should be emphasized that since 2015 Q4 the number of records and respondents has increased

considerably, thus changing the size of the sample. We analysed rents for retail space located in

economically important parts of the city.

Source NBP.

rest of Polska 10M 6M

rest of Polska



36 Data used in the analysis (rents at the end of 2016) were collected by NBP as part of the Public Statistics' Statistical

Research Programme. Since the dominant part of the rents are paid in EUR, this currency was used in the analysis. The

object of the analysis are transaction rent rates per square metre of area per month whose logarithm has been taken. In

the case of offices, premises exceeding 100 sq. m. are analysed, and in the case of shopping centres, premises ranging

from 100 to 300 sq. m.

Box 4. Analysis of factors determining rent levels in offices and shopping centres in Gdańsk,

Poznań and Warszawa

Rents earned by office and retail space owners are income that allows them to repay their debt

and distribute dividends to shareholders. The level of rent that an investor can get from renting

a building affects the price of that building, through the expected rate of return. Thus, rents are

used to appraise commercial buildings which are rarely the object of transactions. Rent level is

determined by the correlation between supply and demand, while their diversity is the result of

the diversity of their attributes.

The developed models show factors affecting rents in the office and retail market.36 The analysis

shows a set of common factors in three large voivodship cities, but also significant local

differences, which are due in particular to different city layouts. Preliminary data analysis has

shown that rents of retail space vary considerably within each shopping centre, while rents in

office buildings do not show any significant variations within the same building. Therefore, in

the case of shopping centres, all rents are analysed separately and in the case of office buildings,

the average rent in the office is analysed.

The main conclusions for the office market of the three analysed cities:

The conclusions from the model analysis confirm that location is of considerable importance.

For Warszawa and Poznań the analysis measures the distance from the city centre, while the

Tri-City agglomeration is divided into several zones. In Warszawa, rents for class B buildings

are approx. 27% lower than rents for class A buildings, whereas rents for C buildings are up to

40% lower. In Poznań, rents in class B buildings are 16% lower than rents in class A buildings.

In the Tri-City agglomeration, there are no significant differences between building classes,

while the number of stores in the building in this city has a positive effect on rents. This is

probably due to the fact that in the best locations the land is the most expensive, so investors

build high office buildings. In Poznań and Warszawa, rents for space in older buildings are

lower than rents for space in newer buildings, but there is no such correlation in the Tri-City

agglomeration In turn, in the Tri-City agglomeration there are small limits on the number of

parking spaces, which have been largely used by older buildings. Newer buildings, generally in

a better technical condition, have fewer parking spaces, thus the Tri-City agglomeration sees a

negative relationship between the number of parking spaces and the level of rent in the

building. This may also explain the fact that in the Tri-City agglomeration the age of the

building has no negative impact on rent levels.



Table 5. Statistically important factors affecting rents of office space

Warszawa Poznań Tri-City

agglomeration

B class -0.268 -0.161

klasa C -0.405

ln_powierzchnia_do_wynajmu 0.065

ln_liczba_kondygnacji 0.197

ln_wiek_plus_2 -0.033 -0.087

ln_suma_parkingów -0.054

ln_Odleglosc -0.107 -0.082

lokalizacja Gdańsk-Oliwa 0.150

lokalizacja Gdańsk-reszta -0.209

Source NBP.

The main conclusions for the retail market of the three analysed cities:

In the case of the analysed shopping centres, location is another factor of considerable

importance. In Warszawa, the longer the distance from the centre the lower the rent. There is no

such correlation in the Poznań commercial real estate market. On the other hand, in the Tri-City

agglomeration space in shopping centres located in the city centre get 40% higher rents than

space located in remaining parts of the agglomeration. In Warszawa, local shopping centres and

outlets, and in Poznań centres specializing in furniture and home accessories, get lower rents

than other types of shopping centres. Moreover, in Warszawa and in the Tri-City

agglomeration, it is possible to distinguish shopping centres considered as leading ones, for

which significantly higher rents are charged than for other shopping centres (68% and 54%,

respectively). In Poznań, shopping malls located in the city business centre get 13% higher rents

than other shopping centres in the city. In addition, the size of the centre, the number of shops

and the number of parking spaces in the centre have a positive effect on rent levels. What is

interesting is the positive correlation between the age of the shopping centre (even taking into

account its modernization) and rent levels in Poznań and in the Tri-City agglomeration, which

may mean that there is higher demand for older shopping malls than for newer ones. This may

be explained by the fact that older shopping centres were built in prime locations. Regardless of

the location, the larger the leased premises, the lower the rent per square metre, which may be

indicative of the scale effect. Moreover, it was noted that rents in the Tri-City agglomeration

grow along with operating and maintenance expenses, which can be considered as a quality

indicator of the shopping centre. Table 6. Statistically important factors affecting rents of retail space

Warszawa Poznań Trójmiasto

CH_top 0,686 0,541

CH_lokalne_i_wyprzedazowe -0,297

Centra handlowe Trójmiasto 0,403

CH_centrum 0,132

CH_meble -0,351

ln_odległość -0,157

ln_pow_lokalu -0,400 -0,382 -0,318

ln_wiek_plus_2 0,157 0,139

Ln_suma_miejsc_parking. 0,162

Ln_eksploatacja 0,386

Ln_ile_sklepów 0,375

Source NBP.

5. Convergence and differentiation processes observed in Poland’s local markets


5. Convergence and differentiation processes

observed in Poland’s local markets

The majority of local markets saw a further improvement in economic indicators (unemployment

rate, wage level), housing and demographic indicators. The number of inhabitants in the largest

cities increased, whereas smaller cities and towns continued to see population outflow. The

demographic burden ratio continued to worsen.

Moreover, in 2016, due to the supply of new housing, the housing stock increased. As in the

previous years, growth in the number of dwellings in the housing stock varied across cities and

was dependent on the situation in the regional markets, and especially on local factors affecting

demand and supply. The largest number of dwellings – over 163 thousand – was completed and

made ready for occupancy for the last dozen or so years (this figure may compare to the 2008

figure only, when 165,000 dwellings were completed), more than 20 thousand of which were in

Warszawa alone. High demand for residential property boosted activity of real estate developers

and translated into more applications for building permits for new home constructions. In

voivodship cities, approximately 74 thousand building permits for new home constructions were

issued – the highest number for a dozen or so years, except for the year 2007, when 82.5 thousand

building permits were issued. Due to the large number of construction starts (in 2016 – 67

thousand dwellings), both in the analysed period as well as in 2015, the large number of home

completions is expected to continue in the near future.

Housing situation in 16 voivodship cities

According to NBP estimates, in 2016 the housing stock of 16 voivodship cities increased by more

than 61.8 thousand dwellings to reach the level of approx. 3.55 million dwellings at the end of

2016 (in the whole country it amounted to approx. 14.3 million). The largest scale of growth in the

housing stock in 2016 was observed in the group of the largest cities (ranging from 0.3% in Łódź

to 2.8% in Wrocław). In the case of smaller cities, growth ranged from 0.6% in Bydgoszcz to 2% in

Zielona Góra.37

2016 saw a further improvement in the housing situation of Poland’s voivodship cities. Increase

in the housing stock per inhabitant is driven by production of new dwellings, small scale of

housing stock depletion and a downward trend in the officially registered population, persisting

in some cities.38 Higher level of satisfaction of housing needs, measured with saturation and

population rates, continued to be recorded in the largest cities. Warszawa and Łódź stood out

37 An exceptional situation was seen in Rzeszów which recorded a 4% rise (y/y) in the number of housing units, driven

by a steady increase in the city area since 2006.

38 The officially recorded population is determined based on the CSO data on the population actually living in a given

place as per 31 December.



against the background of other cities. The number of dwellings per 1000 inhabitants exceeded

500 units and the number of persons in a dwelling was around 1.9.

Figure 116. Housing stock per 1000 inhabitants in 6M Figure 117. Housing stock per 1000 inhabitants in

10M

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Białystok Bydgoszcz KatowiceKielce Lublin OlsztynOpole Rzeszów SzczecinZielona Góra Polska


Figure 118. Average usable area of housing in the

housing stock per person (in sq. m) in 6M.


housing stock per person (in sq. m) in 10M.

50525456586062646668707274

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Białystok Bydgoszcz KatowiceKielce Lublin OlsztynOpole Rzeszów SzczecinZielona Góra



housing stock per person (in sq. m) in 6M


housing stock per person (in sq. m) in 10M

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2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Polska

192021222324252627282930

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Białystok Bydgoszcz Katowice

Kielce Lublin Olsztyn

Opole Rzeszów Szczecin

Zielona Góra Polska




Figure 122. Average number of persons in a

dwelling in 6M

Figure 123. Average number of persons in a dwelling

in 10M

1,81,9

22,12,22,32,42,52,62,72,82,9

3

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



2,12,22,32,42,52,62,72,82,9

33,13,23,3

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Demographic factors in 16 voivodship cities

As compared to 2015, the majority of the fundamental demographic factors in 2016 had a more

positive impact on the housing sector. In most voivodship cities the number of newly married

couples and the number of births increased, which boosted birth rates. This may mean that the

process of the baby boomers of the early 1980s becoming independent has not yet ended. In five

local markets the birth rate continued to be negative, but its decline, as compared to the previous

years, was lower. In the case of three cities – Opole, Poznań and Wrocław – the birth rate

achieved positive values in 2016, while in the previous year it was negative. Positive changes

were also observed in the migration balance. In most cities the migration balance improved and

positive values were recorded in ten voivodship markets (a year earlier positive values were

recorded in half of voivodship capitals).

The improvement in demographic indicators, however, was not strong enough to reverse

unfavourable trends in the population growth and its age structure, which have persisted for

several years. At the end of 2016, approx. 7.4 million people lived in voivodship cities. As

compared to 2015, the population increased by merely 8,000 people. The increase was mostly

observed in larger cities: Gdańsk, Kraków, Warszawa and Wrocław. As regards smaller cities,

increases were noted in Białystok, Rzeszów and Zielona Góra. The remaining voivodship

markets continued to see population decline. In addition, as in the whole of Poland, also in

voivodship cities the demographic burden index worsened further. Again, the share of the

working-age population declined to the benefit of the post-working and pre-working age

population. As in the previous years, in 2016 the share of the post-working age population

increased faster than the share of the pre-working age group.



Figure 124. Birth rate per 1000 inhabitants in 6M Figure 125. Birth rate per 1000 inhabitants in 10M

-7-6-5-4-3-2-10123

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



-4

-3

-2

-1

0

1

2

3

4

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16



Figure 126. Migration per 1000 inhabitants in 6M Figure 127. Migration per 1000 inhabitants in 10M

-6

-4

-2

0

2

4

6

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



-7

-5

-3

-1

1

3

5

7

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Figure 128. Marriages per 1000 inhabitants in 6M Figure 129. Marriages per 1000 inhabitants in 10M

3,0

3,5

4,0

4,5

5,0

5,5

6,0

6,5

7,0

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



3,5

4,0

4,5

5,0

5,5

6,0

6,5

7,0

7,5

20

02

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03

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09

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10

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11

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20

15

20

16





Figure 130. Growth rate of age indicators 2016/2002

in 6M

Figure 131. Growth rate of age indicators 2016/2002

in 10M

020406080

100120140160

Gdańsk

Kra

ków

Łódź

Pozn

ań

Wars

zaw

a

Wro

cław

production pre-production post-production

020406080

100120140160180

Bia

łyst

ok

Byd

goszc

z

Kato

wic

e

Kie

lce

Lublin

Ols

ztyn

Opole

Rze

szów

Szc

zeci

n

Zie

lona G

óra

production pre-prodiction post-production


Economic factors in 16 voivodship cities

2016 was another year in which economic factors had a positive impact on the situation of local

residential markets. As compared to 2015, there was an increase in employment, which translated

into a decline in the unemployment rate. The most marked decline in the unemployment rate was

recorded in the group of smaller cities (ranging from 0.4 p.p. in Opole to 1.7 p.p. in Białystok). In

larger cities, the decline was at the level of 0.5 p.p. - 0.6 p.p. Łódź recorded an exceptional fall in

the unemployment rate at the level of 1.6 p.p. Białystok was the only voivodship city where the

registered unemployment rate was higher than the national average, reaching the level of 8.3% at

the end of 2016. In local markets (except for Bydgoszcz and Gdańsk), the share of young people

below 34 years of age in the total number of the unemployed continued to decline gradually.

In 2016 wages increased in real terms as a result of rising wages in nominal terms and deflation

and the increase in household income thanks to the 500 plus family allowance scheme.

Improvement was also noted in home availability ratios in the primary and secondary markets in

most regional cities, indicating the number of square meters that can be purchased for an average

wage. This was driven by the fact that growth in average wages exceeded growth in transaction

prices of dwellings listed on particular voivodship markets. As compared to 2015, in most cities

the availability of residential loans and loan-financed housing dropped slightly in 2016. Despite

the tightening of the loan granting criteria, in 2016 voivodship cities recorded a 3.8% increase in

the number of new housing loans and 6.8% growth in their value in comparison to 2015. The

highest growth rate was recorded in the group of larger cities (growth ranging from approx. 3.5%

in Kraków to about 15% in Wrocław). The only exception was Łódź, where the scale of lending

was approx. 6% lower. As regards smaller cities, only Lublin, Szczecin and Zielona Góra

recorded a rise in the number of housing loans in 2016 compared to 2015. The remaining regional

markets recorded a decline in lending. The most considerable decline of 14% was seen in Kielce,

and the slightest of 1.4% in Białystok.

In 2016 the government-subsidized housing scheme MDM#, supporting home ownership,

continued to enjoy great interest. However, as the pool of funds intended for 2016 was already

exhausted in March and the first tranche intended for 2017 was already used in July, fewer

applications were submitted in 2016. After this period, the only possibility was to submit

applications for the co-financing of the purchase of housing with the funds disbursement date in



2018. In 2016 in 16 voivodship cities the total of 9.9 thousand applications were submitted for the

purchase of new housing with the loan amount of PLN 2.1 billion (as compared to approx. 11.9

thousand applications in 2015 with the loan amount of approximately PLN 2.6 billion). During

this period, households received approx. PLN 1.9 billion worth of loans for the purchase of over

8.9 thousand new dwellings in voivodship cities. In the case of the secondary market, the scale of

home purchase financing with the use of the MDM housing scheme was smaller. This was due to

the lower level of price limits as compared to primary market housing. Nevertheless, in 2016, in

16 voivodship cities approx. 2.8 thousand applications for the purchase of dwellings in the

secondary market for the amount of approx. PLN 434 million were submitted (as compared to

approx. 2.6 thousand applications for the amount of approx. PLN 404 million).

As in the previous years, the level of financing under the MDM housing scheme varied across

voivodship cities and was determined by the scheme’s price limits and the degree of availability

of dwellings meeting the scheme’s price criteria in particular housing markets. In 2016, the

maximum price limits per square metre of housing in most voivodship cities continued to be

lower than the prices quoted on the regional markets. The scale of the mismatch was the largest

in the largest cities: in Gdańsk, Kraków, Warszawa, Wrocław, Łódź and Poznań.

At the beginning of 2017, the MDM housing scheme continued to enjoy great interest, due to its

scheduled termination at the end of 2018. Already in February 2017, BGK stopped accepting

applications for 2017, and in April it stopped accepting applications for the first tranche to be

paid in 2018. Another tranche, as a result of the amendment of the Act of 27 September 2013 on

the government’s assistance for the first time home buyers is scheduled to be launched in August

2017.

Figure 132. Unemployment rate in 6M Figure 133. Unemployment rate in 10M

0

3

6

9

12

15

18

21

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Polska

0

3

6

9

12

15

18

21

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Białystok BydgoszczKatowice KielceLublin OlsztynOpole Rzeszów




Figure 134. Share of the unemployed aged up to

34 in 6M

Figure 135. Share of the unemployed aged up to 34 in

10M

252831343740434649525558

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Polska

27

30

33

36

39

42

45

48

51

54

57

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016




Zielona Góra Polska


Figure 136. Average wages in the enterprise sector

in 6M (PLN/month)

Figure 137. Average wages in the enterprise sector in

10M (PLN/month)

2000

2500

3000

3500

4000

4500

5000

5500

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Polska

2500

3500

4500

5500

1500

2000

2500

3000

3500

4000

4500

5000

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Białystok Bydgoszcz Kielce

Lublin Olsztyn Opole

Rzeszów Szczecin Zielona Góra

Polska Katowice


Figure 138. Housing affordability per average

wage (in sq. m) in 6M – PM

Figure 139. Housing affordability per average wage (in

sq. m) in 10M – PM

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

III 2006

I 2007

III 2007

I 2008

III 2008

I 2009

III 2009

I 2010

III 2010

I 2011

III 2011

I 2012

III 2012

I 2013

III 2013

I 2014

III 2014

I 2015

III 2015

I 2016

III 2016

I 2017



0,40,50,60,70,80,91,01,11,21,3

III 2006

I 2007

III 2007

I 2008

III 2008

I 2009

III 2009

I 2010

III 2010

I 2011

III 2011

I 2012

III 2012

I 2013

III 2013

I 2014

III 2014

I 2015

III 2015

I 2016

III 2016

I 2017


Source NBP, GUS. Source NBP, GUS



Figure 140. Housing affordability per average

wage (in sq. m) in 6M – SM

Figure 141. Housing affordability per average wage

(in sq. m) in 10M – SM

0,2

0,4

0,6

0,8

1,0

1,2

1,4III 2006

I 2007

III 2007

I 2008

III 2008

I 2009

III 2009

I 2010

III 2010

I 2011

III 2011

I 2012

III 2012

I 2013

III 2013

I 2014

III 2014

I 2015

III 2015

I 2016

III 2016

I 2017



0,4

0,6

0,8

1,0

1,2

1,4

1,6

1,8

III 2006

I 2007

III 2007

I 2008

III 2008

I 2009

III 2009

I 2010

III 2010

I 2011

III 2011

I 2012

III 2012

I 2013

III 2013

I 2014

III 2014

I 2015

III 2015

I 2016

III 2016

I 2017


Source NBP, GUS Source NBP, GUS

Figure 142. Availability of PLN-denominated

loans in 6M

Figure 143. Availability of PLN-denominated loans in

10M

707580859095

100105110115120125

IV 2

006

II 2

007

IV 2

007

II 2

008

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008

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009

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009

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011

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011

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012

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012

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013

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013

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014

IV 2

014

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015

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015

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016

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016



707580859095

100105110115120125

IV 2

006

II 2

007

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007

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008

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008

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009

IV 2

009

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010

IV 2

010

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011

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011

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012

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012

II 2

013

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013

II 2

014

IV 2

014

II 2

015

IV 2

015

II 2

016

IV 2

016



Figure 144. Affordability of loan-financed

housing (PLN-denominated loans) in 6M -

primary market

Figure 145. Affordability of loan-financed housing

(PLN-denominated loans) in 10M - primary market

30

40

50

60

70

80

90

100

110

IV 2

006

II 2

007

IV 2

007

II 2

008

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008

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009

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009

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010

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011

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011

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012

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013

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015

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016

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016



30

50

70

90

110

130

150

IV 2

006

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007

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007

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008

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008

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009

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009

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010

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010

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011

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011

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012

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012

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013

IV 2

013

II 2

014

IV 2

014

II 2

015

IV 2

015

II 2

016

IV 2

016




Zielona Góra




Figure 146. Value of loans in newly concluded

loan agreements (in PLN million) in 6M

(according to the borrower's domicile)

Figure 147. Value of loans in newly concluded loan

agreements (in PLN million) in 10M (according to the

borrower's domicile)

02 0004 0006 0008 000

10 00012 00014 00016 00018 00020 00022 000

2005 2007 2009 2011 2013 2015



0

1 000

2 000

3 000

4 000

5 000

6 000

2005 2007 2009 2011 2013 2015

Białystok Bydgoszcz Katowice Kielce

Lublin Olsztyn Opole Rzeszów

Szczecin Zielona Góra

Source BIK. Source BIK.

Figure 148. Gap/surplus between RNS/MDM

threshold prices and median transaction prices in

6M – PM

Figure 149. Gap/surplus between RNS/MDM

threshold prices and median transaction prices in 10M

– PM

-60%

-40%

-20%

0%

20%

40%

60%

80%

I 2007

III 2007

I 2008

III 2008

I 2009

III 2009

I 2010

III 2010

I 2011

III 2011

I 2012

III 2012

I 2013

III 2013

I 2014

III 2014

I 2

015

III 2

015

I 2

016

III 2

016

I 2

017



-60%

-40%

-20%

0%

20%

40%

60%

80%

I 2007

III 2007

I 2008

III 2008

I 2009

III 2009

I 2010

III 2010

I 2011

III 2011

I 2012

III 2012

I 2013

III 2013

I 2014

III 2014

I 2

015

III 2

015

I 2

016

III 2

016

I 2

017


Source NBP, BGK. Source NBP, BGK.

Housing construction in 16 voivodship cities

In 2016, the housing sector in voivodship cities developed with varied intensity. As in the

previous years, demographic and economic factors, local market conditions and legal regulations

had the strongest impact on the behaviour of supply chain actors. Increased activity of investors,

especially that of real estate developers as regards gaining new contracts and starting

construction, observed before the entry into force of the so-called “Real Estate Development Act”,

was reflected in 2016 in the number of completed dwellings. More than 163 thousand dwellings

were completed and made ready for occupancy – the largest number in the last dozen or so years

(except for the record in 2008, when more than 165 thousand dwellings were completed). In 16

voivodship cities, a record number of dwellings were completed in this period – more than 63

thousand, of which approx. 32% were in Warszawa alone. The largest increase in the new

housing stock as compared to 2015 was recorded in Szczecin (161% increase) and the lowest in

Gdańsk (12.7% increase). In six voivodship cities – Białystok, Bydgoszcz, Kielce, Łódź, Olsztyn

and Poznań – investors completed fewer dwellings. Developers in the local markets closely

monitored buyers' preferences to adjust their offers in terms of home size and price level. In most

cities developers continued to build smaller dwellings.



High demand and very good sales figures provided a significant incentive for investors to

acquire new contracts and start construction. In 2016, in 16 voivodship cities investors obtained

building permits for the construction of over 74 thousand dwellings, the highest figure in the last

dozen or so years (the only exception was 2007, when permits for the construction of over 82.5

thousand dwellings were issued). The largest number of building permits was issued in five

cities: Gdańsk, Kielce, Łódź, Rzeszów and Zielona Góra. In these cities in 2016 investors were

granted permits to build the largest number of dwellings for the last dozen or so years. Positive

growth in the number of issued permits, as compared to 2015, was also registered in Kraków,

Opole and Poznań. The remaining voivodship markets observed a downward trend.

The year 2016 was also a record year for new investments. In 16 voivodship cities investors

launched construction of nearly 67 thousand dwellings (a larger number was only recorded in

2015 with 69.5 thousand dwellings). In three cities – Gdańsk, Katowice and Rzeszów – the scale

of commenced investments was the largest in the last dozen or so years. Apart from these cities,

positive growth, as compared to 2015, was also recorded in Bydgoszcz, Kielce, Opole and

Warszawa. Other voivodship markets saw a decline. In 2016, more than 88% of new investment

projects in voivodship cities were launched by investors building for sale and for rent. Yet, their

activity in housing construction varied depending on the situation in the local markets. The share

of dwellings under construction was higher in the group of larger cities and ranged from approx.

70% in Łódź to approx. 97% in Warszawa. In the case of smaller cities, it ranged from approx.

50% in Rzeszów to approx. 87% in Białystok).

Figure 150. Number of completed and ready for

occupancy dwellings per 1000 inhabitants in 6M


occupancy dwellings per 1000 inhabitants in 10M

0

2

4

6

8

10

12

14

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



0

2

4

6

8

10

12

14

16

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016






occupancy dwellings per 1000 marriages in 6M


occupancy dwellings per 1000 marriages in 10M

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Figure 154. Average usable area of completed and

ready for occupancy dwelling in 6M

Figure 155. Average usable area of completed and

ready for occupancy dwelling in 10M

405060708090

100110120130140150160

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



405060708090

100110120130140150160

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016



Figure 156. Outlook for housing construction in 6M

0

5 000

10 000

15 000

20 000

25 000

30 000

35 000

40 000

45 000

50 000

55 000

60 000

65 000

70 000

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Mieszkania, na budowę których wydano pozwolenia Mieszkania, których budowę rozpoczęto

Gdańsk Kraków Łódź Poznań Warszawa Wrocław

Source GUS.

Permissions Dwellings started



Figure 157. Outlook for housing construction in 10M

01 0002 0003 0004 0005 0006 0007 0008 0009 000

10 00011 00012 00013 00014 00015 00016 00017 00018 000

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

Mieszkania, na budowę których wydano pozwolenia Mieszkania, których budowę rozpoczęto

Białystok Bydgoszcz Katowice Kielce Lublin Olsztyn Opole Rzeszów Szczecin Zielona Góra

Source GUS.

Figure 158. Indicator of trends in housing

production in 6M (in thousands; commenced

dwellings less competed and ready for occupancy

dwellings)

Figure 159. Indicator of trends in housing

production in 10M (in thousands; commenced

dwellings less competed and ready for occupancy

dwellings)

-11-9-7-5-3-113579

11

IV 2

005

II 2

006

IV 2

006

II 2

007

IV 2

007

II 2

008

IV 2

008

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009

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009

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010

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011

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014

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014

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015

IV 2

015

II 2

016

IV 2

016



-1,7-1,4-1,1-0,8-0,5-0,20,10,40,7

11,31,61,9

IV 2

005

II 2

006

IV 2

006

II 2

007

IV 2

007

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008

IV 2

008

II 2

009

IV 2

009

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010

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011

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011

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012

II 2

013

IV 2

013

II 2

014

IV 2

014

II 2

015

IV 2

015

II 2

016

IV 2

016





Analysis of data collected in the BaRN database

In 2016, over 418 thousand offers and sales of dwellings were registered in the BaRN database

(the primary and the secondary market combined; an increase of nearly 14% against the 2015

figure), of which more than 268 thousand dwellings were in the primary market (nearly 19%

more than in 2015). As in the previous years, the largest number of transactions was recorded in

Q4. In the whole of Poland, in 2016 Q4, housing transactions in the primary market accounted for

almost 30% of all the 2016 transactions. In terms of the number of records entered into the

database, Warszawa, with a 27% share of records in the database, held the leading position (a 2

point-decline against the previous year), followed by Gdańsk (11% share) and Kraków (10%

share). A slightly higher concentration of observations from the largest markets is recorded in the

primary market. Records from Warszawa accounted for almost 29% of all the primary markets,

those from Kraków for 13.2% and from Wroclaw for 11%. The rental market in the BaRN base

Permissions Dwellings started



includes over 17 thousand rent offers (the primary and the secondary market combined; number

close to the previous year’s figure) and 4,286 rent transactions (a 39% rise).

On average, around 532 real estate developers (approx. 16% more than in 2015) and 699 real

estate agents (approx. 26% more) participated in the 2016 listings.

Figure 160. Number of records in quarters in the BaRN database

0

10 000

20 000

30 000

40 000

50 000

60 000

70 000

80 000

90 000

100 000

110 000

120 000

III 2006

III 2007

III 2008

III 2009

III 2010

III 2011

III 2012

III 2013

III 2014

III 2015

III 2016

Oferty mieszkań Oferty najmu Transakcje mieszkań Transakcje najmu

Source NBP.

Primary housing market according to the BaRN database

In 2016 the primary market of the majority of voivodship cities recorded an increase in the price

of offered and sold dwellings. At the end of the year, the median of the offer price, as compared

with the corresponding period of 2015, was higher in nine cities, lower in six cities and remained

unchanged in one city. The growth rate varied, ranging from approx. 0.08% in Wrocław to 8.9%

in Gdańsk. In the case of transaction prices of new dwellings, the growth rate was positive in 15

voivodship cities. The highest increase in the median price was recorded in Gdańsk – 14.7%,

Opole – 6.3%, Szczecin – 4.9%, Łódź – 4.6% and Rzeszów – 4%; the median price increase was the

lowest in Kraków – 0.1% and Wrocław – 0.4%. Kielce was the only city where at the end of 2016

the median transaction price was 1% lower than a year before.

Also the secondary market of the majority of the analysed cities recorded an increase in home

prices in 2016. At the end of the year, the median of the offer price, as compared to the

corresponding period of 2015 was higher in 12 cities, with the sharpest increase of 7% noted in

Bydgoszcz and the lowest in Warszawa and Rzeszów of approx. 0.7%. A decline in the median

price was recorded in 4 cities, with the sharpest decline of 1.3% in Opole. In the case of the

median transaction price, its average growth rate stood at around 4% in 12 voivodship cities. The

strongest growth was recorded in Poznań – 8.2%, Bydgoszcz – 7.6% and Szczecin – 7%. On the

largest market, Warszawa, the increase reached 1.4%. In four voivodship markets – Katowice,

Kielce, Kraków and Zielona Góra – the median of the transaction price in 2016 Q4 declined as

compared to the corresponding period of 2015 by an average of approx. 0.8%.

In the primary market, the strongest growth in 2016 was recorded in Gdansk – 6.6%, Cracow –

3.7% and Bydgoszcz – 3%, while the smallest was in Białystok and Poznań – 0.3% and Kielce –

0.7%. Opole was the only city to record a slight decrease – approx. 0.7% of the price level. In the

dwellings; offers rental; offers dwellings; transaction rental; transactions



secondary market, growth in transaction prices of housing in 2016, as compared with 2015,

ranged from 0.6% in Warszawa to 5.8% in Gdańsk. Declines were recorded in only three cities –

Kraków (by 4.1%), Kielce (by 2.8%) and Łódź (by 1.3%).

The highest nominal prices, both in the primary and secondary market, were observed in the

largest markets. The primary market in Warszawa at the end of 2016 saw the median transaction

price at PLN 7529 /sq. m, in Kraków at PLN 6325 /sq. m, in Gdańsk at PLN 6300/sq.m., in Poznań

at PLN 6100/sq. m. and in Wrocław at PLN 6039/sq.m. The secondary market observed the

highest median transaction price as of the end of 2016 in Warszawa (PLN 7188/sq. m), Kraków

(PLN 5710/sq. m) and Wrocław (PLN 5389/sq. m).

For the six largest and most liquid markets home selling time also grew longer and was on

average 172 days (as compared to 157 days in the previous year). For 16 markets in Poland this

average was 162 days and was comparable with 2015.

Figure 161. Median selling offer price (PLN/sq. m) in

6M – PM

Figure 162. Median selling transaction price

(PLN/sq. m) in 6M – PM 6M - PM

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Figure 163. Median selling offer price (PLN/sq. m) in

10M – primary market

Figure 164. Median selling transaction price

(PLN/sq. m) in 10M – primary market

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Figure 165. Supply and demand mismatch; dwellings

with an area <= 50 square meters in 6M - primary

market

Figure 166. Supply and demand mismatch;

dwellings with an area <= 50 square meters in 10M

- primary market

-80%

-60%

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0%

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Note to Figure 165: mismatch (expressed in percentage) between supply (housing offers by real estate

developers) and estimated demand (housing transactions) as regards the area of housing, according to the data

derived from the BaRN database; the mismatch is measured as the ratio of the offered housing units with a

usable area of up to 50 square meters to the share of transactions involving housing units with an area of up to

50 square meters (the average for the last four quarters). A positive result (above the black line) indicates the

surplus of housing units of a given size, a negative result – their deficit. The above applies also to Figures 166-

169 and 173-176.


with an area <= 50 square meters in 6M - primary

market


dwellings with an area <= 50 square meters in 10M

- primary market

-70%-60%-50%-40%-30%-20%-10%

0%10%20%30%40%50%

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-100%-80%-60%-40%-20%

0%20%40%60%80%

100%120%140%160%

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Zielona Góra




Secondary housing market according to the BaRN database

Figure 169. Figure 147 Median selling offer price

(PLN/sq. m) in 6M – SM

Figure 170. Figure 150 Median selling transaction

price (PLN/sq. m) in 6M – SM

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Figure 171. Figure 147 Median selling offer price

(PLN/sq. m) in 10M – SM

Figure 172. Figure 150 Median selling transaction

price (PLN/sq. m) in 10M – SM

150020002500300035004000450050005500

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Białystok Bydgoszcz Katowice Kielce

Lublin Olsztyn Opole Rzeszów

Szczecin Zielona Góra



with an area <= 50 square meters in 6M - secondary

market


with an area <= 50 square meters in 10M - secondary

market

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0%

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dwellings with an area <= 50 square meters in 6M -

secondary market


dwellings with an area <= 50 square meters in 10M -

secondary market

-20%0%

20%40%60%80%

100%120%140%160%180%200%

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-50%-30%-10%10%30%50%70%90%

110%130%150%

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Figure 177. Figure 155 Average selling time in 6M –

SM

Figure 178. Figure 156 Average selling time in 10M –

SM

0306090

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Home rental market according to the BaRN database

Average offer and transaction rents as of the end of 2016 increased as compared to the end of the

previous year. Offer rents recorded an average growth of 6.3% whereas in the case of transaction

rents growth approximated 5.7%. The highest transaction rents, as in the previous years, were

noted in Warszawa (PLN 48.4/sq. m), Kraków (PLN 39.0/sq. m), Lublin (PLN 34.0/sq. m), and

Gdańsk (PLN 33.3/sq. m).

Figure 179. Average offer rents (PLN/sq. m) in 6M Figure 180. Average transaction rents (PLN/sq. m) in

6M

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Glossary of terms and acronyms



Arbitrage – A sale/purchase transaction of all tradable goods (e.g. merchandise, securities,

housing), making it possible to gain profits without any risk. The essence of Arbitrage is the

balancing of price differences of the same product in various markets or in the same market. In

case such a difference is higher than transaction costs, the investor will gain profit by purchasing

the product in a cheaper market and selling it in a more expensive market.

BaRN – Real Estate Market Database. The database containing offer and transaction prices of

housing in the primary and secondary markets and data on rent rates in 16 voivodship cities. The

data come from real estate brokers, housing cooperatives and real estate developers who

volunteered for the study and partially also from the Registers of Prices and Values of Real Estate

kept by particular counties. The data are gathered and verified by the Regional Branches of NBP.

Construction of dwellings in progress – elasticity of supply of new dwellings relative to demand

shocks; these are dwellings whose construction has been launched less dwellings completed and

made ready for occupancy.

Building type 1121 – an average residential multi-family five-storey building with an

underground parking space and retail premises on the ground floor, traditional construction

(over-ground part made of ceramic bricks), monitored by NBP since 2004 based on the data of

Sekocenbud. For the sake of convenience, it has been assumed that construction costs of 1 square

meter of parking space and retail space are close to the costs of housing sold in a shell and core

condition. The real price of 1 square meter of housing, based on construction costs, depends on

the share of the building's common area, different for various buildings. When calculating the

price of 1 square meter of usable area of housing to be paid by a consumer, we have assumed that

the building’s common area constitutes 20% of the housing area, and using this figure we made

an upward adjustment of the price of 1 square meter of housing. The developer's model of the

construction process described further in Article 3 of the “Report on the situation of the Polish

residential and commercial real estate market in 2011”,NBP 2012.

Budynek typu 1122-302 – half of the average residential multi-family five-storey building with an

underground parking space, monitored by NBP since 2004 based on the data of Sekocenbud; the

change in the type of the analysed building results from the termination of the cost estimation of

the building 1121. Analytical assumptions related to building 1121 have been maintained.

Shopping centre – retail real estate that has been planned, constructed and managed as a single

retail entity. It consists of common areas, with a minimum gross leasable area (GLA) of 5,000 sq.

m, and a minimum of 10 shops.

DI – Disposable Income, households’ gross disposable income.

Available housing loan – a measure specifying the potential maximum housing loan; expressed

in PLN thousand in a particular market, taking into account banks’ lending requirements and

loan parameters (i.e. interest rate, amortization period, minimum wage, as the minimum income

after payment of loan instalments). Important information is provided by the pace of changes and

regional differentiation rather than the value of the indicator alone.



Housing availability – – a measure of potential availability to pur-chase housing space at the

transaction price for an average wage in a particular city. It expresses the number of square

meters of housing that can be purchased for an average wage in the enterprise sector in a

particular city (GUS), at an average transaction price in a particular market (40% from the

primary market and 60% from the secondary markets according to the NBP database).

DTI – Debt to Income indicator defining the level of loan service costs (repayment) to the average

gross income available to households.

PONT – database holding data on housing real estate offer prices, gathered by the company of

PONT Info Nieruchomości.

Hedonic housing price index – reflects the ‘pure’ price, i.e. resulting from factors other than

home quality differences. We also analyse the price of a standardized dwelling, common in a

given market, based on an econometric model. The index adjusts the average price from the

sample to the change in quality of housing in the sample in each period. The hedonic price used

in the study says what would be the average price of the stable sample of dwellings from the

adopted reference period in subsequent periods, taking into account the actual "pure" change in

transaction prices. This distinguishes it from the average price growth, or the median in the

sample, which would strongly react to a change in the sample composition, e.g. by increasing the

price given a higher number of small dwellings with a higher price per square metre. More

information in the article by M. Widłak (2010) „Metody wyznaczania hedonicznych indeksów

cen jako sposób kontroli zmian jakości dóbr”[“Methods of computing hedonic price indices as

the way to control changes in goods quality”], Wiadomości Statystyczne no. 9.

IRR – (. Internal Rate of Return) – internal rate of return – method of economic assessment of

effectiveness of investment projects. An investment project is profitable when the internal rate of

return is higher than the terminal capitalization rate being the lowest rate of return acceptable to

the investor.

Affordability of loan-financed housing– measure specifying how many square metres of

housing at an average offer price in a particular market (PONT Info) may be purchased for a

mortgage loan obtained based on the average monthly wage in the enterprises sector in a

particular market (GUS), in view of loan parameters (interest rate, depreciation period, social

minimum understood as the minimum income after payment of loan instalments) and the bank’s

lending parameters. Index growth rate and spreads between particular markets also provide

important information.

LTV – (. Loan to Value) – ratio of the value of the loan granted or to the value of the loan

collateral.

DFD -an average large real estate development company, selected on the basis of economic

activity classification number PKD2007. A large real estate development company employs more

than 50 people.

MDM – Housing for the Young(MDM) – a new government-subsidized scheme intended to

support housing construction through subsidies to mortgage loans granted to households

meeting the following requirements: age below 35 years, no homeownership, housing usable area

not exceeding 75 square meters for a housing unit and 100 square meters for a single-family

https://pl.wikipedia.org/wiki/J%C4%99zyk_angielski

https://pl.wikipedia.org/wiki/J%C4%99zyk_angielski

http://pl.wikipedia.org/wiki/Kredyt_bankowy

http://pl.wikipedia.org/wiki/Po%C5%BCyczka



house. The scheme entered into force at the beginning of 2014. In 2015 the scheme was extended

to encompass the secondary housing market.

OOH – ( Owner Occupied Housing) dwellings inhabited by the owner.

P/I – (Price to Income), ratio determining the relationship, expressed in years, of the price of an

average dwelling in a particular market to the average available income.

P/R – ( Price to Rent), ration determining the relationship of the price of an average dwelling in a

particular market to the cost of rental of a similar dwelling.

Residential projects in progress - elasticity of supply of new housing to supply shocks; these are

permits for the construction of dwellings less dwellings completed and made ready for

occupancy.

Pre-let ( )– ease of commercial real estate during its construction period. Its level is determined by

the bank financing the investment in order to secure the income from investment.

PUM - usable area of housing The measure showing the number of metres of usable area of

housing that may be built on one square metre of land, specified in local area development plans.

Credit rationing ( ) – means restricted lending resulting from banks’ own assessment of growing

risk. In specific situations this may diminish the value of newly granted loans, despite the

absence of major changes in the current creditworthiness of the borrower, which may lead to self-

fulfilling forecast.

Recommendation S - collection of good practices regarding mortgage-secured credit exposures.

It was introduced in 2006 by the Polish Financial Supervision Authority, issued pursuant to

Article 137 item 5 of the Banking Law Act (Journal of Laws No. 72/2002, item 665, as amended).

Recommendation T- collection of good practices in managing the risk of retail loan exposures. It

was introduced in 2010 by the Polish Financial Supervision Authority, issued pursuant to Article

137 item 5 of the Banking Law Act (Journal of Laws No. 72/2002, item 665, as amended).

Re-commercialisation of commercial properties - re-lease of properties which were leased

before.

Rodzina na Swoim (RNS) – (Family on their own) – the governmental scheme intended to

support housing construction through subsidies to interest rates on housing loans, operating in

the years 2007-2012.

Sekocenbud –publishing house issuing quarterly data on construction costs. The team relies on

quarterly Bulletins of Prices of Buildings (BCO), Part I, large buildings.

Shell and core construction of new housing - it may be housing with concrete topping on the

floor and plaster on the walls and front door, to be finally finished by the buyer. The actual

standard of the shell and core construction may vary depending on the real estate developer. This

standard should be described in the home purchase contract.

Standard of office real estate– office space is classified according to the offered standard. The

classification depends on the age of the building, its location, possibility to customize the space,

technical specification (e.g. raised floors or suspended ceilings), underground and over-ground

parking lots and other factors important from the tenant’s point of view.

Capitalization rate – quotient of the net operating income that may be earned in the market and

the market price of real estate (in accordance with the Generally Applicable Domestic Principles

of Appraisal).



Housing situation - understood as an indicator of the degree to which housing needs of the

society are satisfied. It is described by such indicators as the number of dwellings per 1 000

inhabitants, the size of the average dwelling, the technical condition of housing, access to public

transport, measured by the average commute time.

TBS (Social Building Society) –a company operating under the Act of 26 October 1995 on certain

forms of subsidizing housing construction (consolidated text of the Journal of Laws No. 98/2000,

item 1070, as amended). IBS is engaged in the construction and administration of multi-family

buildings under rental, provision of management and administration services and conduct of

business related to housing construction and accompanying infrastructure. Initially, TBS offer

was meant to be addressed to non-affluent families eligible for loan subsidy from the National

Housing Fund (KFM). Tenants pay rent, which is usually higher than in municipal housing (as

the loan is repaid from the rent) but lower than the market rent.

Demographic burden ratio - ratio of the number of population in age groups resulting from the

statutory ability of work: pre-working age, working age and post-working age population.

Values are given as per 100 persons.

Vacancy Rate – relation of non-rented space to the accumulated (total) supply of commercial

space in a particular location, e.g. town or district.

Profitability ratios – ROA ( return on assets) – relation of net income to assets at the end of the

period, ROE ( return on equity) – relation of net income to equity at the end of the period,

profitability of net sales – net profit in relation to income on sales.

Professional rental– the process of leasing residential space especially constructed for housing

purposes; the owner of the home rental stock may be both a legal entity (municipality, local

government, real estate fund) as well as a natural person; in Poland this market is limited and

decapitalised.

List of abbreviations



500+ The government-subsidized scheme Family +

+3M 3-month changes

5M 5 cities: Gdańsk, Kraków, Łódź, Poznań, Wrocław

6M 6 cities: Gdańsk, Gdynia, Kraków, Łódź, Poznań, Wrocław

7M 7 cities: Gdańsk, Gdynia, Kraków, Łódź, Poznań, Warszawa, Wrocław

10M 10 cities: Białystok, Bydgoszcz, Katowice, Kielce, Lublin, Olsztyn, Opole,

Rzeszów, Szczecin, Zielona Góra

AMRON System for the Analysis and Monitoring of Real Estate Market Transactions

BaNK Commercial Real Estate Market Database

BaRN Real Estate Market Database

BGK Bank Gospodarstwa Krajowego

BIK Credit Information Bureau

CPI Consumer Price Index

DI Disposable income

DTI Debt to Income

GD Households

GUS Central Statistical Office

IRR Internal Rate of Return

EURIBOR Euro Interbank Offer Rate

IKM Individual Housing Escrow Accounts

jst local-government units

KNF Polish Financial Supervision Authority

KRS National Court Register

left-hand scale left-hand scale

LIBOR London Interbank Offered Rate

LTV Loan-to-Value

MDM Government-subsidized housing scheme Mieszkanie dla Młodych [Housing for

the Young]

NBP Narodowy Bank Polski

NFM National Housing Fund

NPM National Housing Scheme

NSP National Census

O/O District Branch

OOH Owner Occupied Housing

P/I Price to Income

right-hand scale right-hand scale

PAB Polish Construction Research and Forecasting Agency

PP Rest of Poland

PUM usable area of housing

RNS Government-subsidized housing scheme Rodzina na Swoim [Family on their

own]

RP Primary housing market

RPO Offer in the primary market

RPT Transaction in the primary market

RW Secondary housing market

RWO Offer in the secondary market



RWT Transaction in the secondary market

ROA Return on Assets

ROE Return on Equity

SARFIN Analytical System for the Real Estate Financing Market

TBS Social Building Society

EU European Union

WIBOR Warsaw Interbank Offered Rate

WIG20 Index including top 20 companies listed on the Warsaw Stock Exchange with

the highest value of publicly traded free-floating shares

ZBP Polish Bank Association

ZKPK Accumulated index of changes in banks’ credit policy criteria

report on the situation in the residential and commercial ... · anna krawczyk regional branch in...

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