HOUSING MARKET CYCLES IN THE CONTEXT OF BUSINESS CYCLES

Abstract

Housing markets as well as the overall economy develop unevenly. Business cycles are the result of the diverse dynamics of their development. The housing market, as one of the components of economic systems, is influenced by business cycles, at the same time affecting them as well. It should be noted, however, that the special nature of this market may determine a different course of housing market cycles in comparison with changes in business cycles. The aim of the paper is to identify similarities and differences in the shaping of the housing market cycle and the business cycle. The analysis will be conducted on the basis of experience from the Polish market and selected Western markets.

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HOUSING MARKET CYCLES IN THE CONTEXT OF
BUSINESS CYCLES
Konrad Żelazowski, PhD
Faculty of Economics and Sociology
University of Lodz
e-mail: kzelazowski@uni.lodz.pl
Abstract
Housing markets as well as the overall economy develop unevenly. Business cycles are the result of
the diverse dynamics of their development. The housing market, as one of the components of
economic systems, is influenced by business cycles, at the same time affecting them as well. It should
be noted, however, that the special nature of this market may determine a different course of housing
market cycles in comparison with changes in business cycles.
The aim of the paper is to identify similarities and differences in the shaping of the housing market
cycle and the business cycle. The analysis will be conducted on the basis of experience from the Polish
market and selected Western markets.
Key words: housing market, housing market cycles, business cycle.
JEL Classification: E30, E32, R31.
Citation: Żelazowski K., 2017, Housing Market Cycles in the Context of Business Cycles, Real Estate
Management and Valuation, vol. 25, no. 3, pp. 05-14.
DOI: 10.1515/remav-2017-0017
1. Introduction
The housing market is an important, yet special, sector of the national economy. Its importance is
derived from two main factors: the size of the housing market and the functions that residential
properties perform. In mature market economies, the share of the widely understood housing sector
(including housing management, housing financing and housing construction) in gross value added is
an average of 20% (LAMA, DENIS 2014, p. 5), whereas the scale of investment expenditure on housing
stands at 4%-6% of the national GDP (BANDT et al. 2010, p. 71).
Residential properties additionally perform a number of important socio-economic functions. They
meet the most basic needs of having a place to call home and a sense of security, as well as the needs
of a higher order, such as the possibility of forming social ties or meeting the needs of self-realisation.
Adequate housing is a measure of a decent life, and its absence is one of the main causes of so-called
social exclusion (MICKIEWICZ, WENCEL 2013, p. 2).
Residential properties are also an important component of household assets (compare: Table 1).
The purchase of a dwelling is the biggest investment in the case of many households, affecting other
aspects of their functioning, including decisions on starting a family, labour market mobility and
consumer spending, e.g.: in the framework of the wealth effect.
The size of the housing market and its strong links with other sectors of the economy constitute a
premise for the formulation of the hypothesis on a vital interdependence of the housing market cycle
and the business cycle. The paper is an attempt to empirically verify the course of housing market
cycles in relation to cyclical changes in the overall economy. An analysis of their synchronisation will
also be carried out based on housing market cycles and business cycles in the Polish market and
selected Western markets.
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Table 1
The importance of residential properties in household assets
Country Share of residential property in total assets (%)
1995 2000 2005 2010 2014
USA 44,8% 43,5%
50,7%
38,4%
37,5%
UK 47,7% 50,3%
59,6%
60,2%
59,0%
Switzerland n/a 57,4%
56,1%
60,0%
62,4%
Germany 52,0% 47,4%
44,4%
45,7%
n/a
Holland 31,5% 25,1%
26,6%
28,4%
26,3%
Finland n/a 78,3%
74,0%
76,3%
77,2%
Italy n/a 64,6%
69,0%
72,9%
73,3%
Poland n/a 79,8%*
66,6%
60,4%
n/a
*data for 2002.
Source: the author's own compilation based on the OECD data.
2. Literature review
2.1. Housing market cycles
The housing market, similarly to other markets as well as the overall economy, develops unevenly.
The analysis of changes in the activity of actors in the housing market and the dynamics of its main
aggregates allows the identification of specific components of the path of its development (TROJANEK
2008a, pp. 68-69; SOBCZYK 2000, p. 335):
– Trend – representing the long-term development trend of the housing market.
– Cyclical fluctuations – fluctuations in the levels of a given phenomenon occurring with variable
regularity due to changes in economic conditions.
– Seasonal fluctuations – regularly repeated on an annual basis fluctuations of economic
processes which are a result of the impact of natural factors (mainly the change of seasons), as
well as institutional or legal factors on the course of these processes.
– Random fluctuations – irregular fluctuations in economic activity that are a consequence of the
influence of random, incidental factors.
The manner in which business cycles are defined is paramount in the process of their
identification. Traditionally, business cycles are defined as "fluctuations occurring in aggregates
representing economic activity of nations that organise their production mainly through enterprises”
(SKRZYPCZYŃSKI 2010, p. 12). According to the classical definition, the business cycle consists of four
phases: crisis, stagnation, recovery and expansion. Identification of individual phases is associated
with the assessment of the dynamics of selected processes and economic variables in absolute terms
(KONOPCZAK 2009).
Nowadays cycles are increasingly defined as recurring oscillations of selected economic aggregates
along their long-term economic growth path (trend) (KUCHARSKA-STASIAK 2008, p. 31). In the course of
the cycle two basic phases are determined: recovery – growth in economic activity – and recession – a
decrease in economic activity relative to the long-term trend.
Based on the above-presented definitions of the business cycle, a classical housing market cycle
and a modern one can be distinguished (BRACKE 2013). In the classical approach, the housing market
cycle is therefore defined as "fluctuations in activity of this market (measured by changes in
residential property prices, the number of transactions or residential investments undertaken)
expressed in absolute terms through levels of the variable or through the growth rate of the variable"
(LIS 2015, p. 38). In the modern approach, the housing market cycle is characterised as: "demand,
supply, real estate prices and real estate stock tendencies to fluctuate around their long-term trends or
average values" (KUCHARSKA-STASIAK 2006, p. 104).
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Taking into account the specific nature of the housing market, in particular the differences in the
price elasticity of demand and supply, as well as time-consumption of processes of investment in
housing, it is difficult to talk about one universal housing market cycle. In the literature, two basic
types of housing market cycle are most frequently mentioned (KUCHARSKA-STASIAK et al. 2012, pp. 34-
35):
– Demand cycle – a cycle determined by changes in demand, more strongly correlated with the
economic situation, with an average duration of 4-5 years.
– Supply cycle – a cycle driven by changes in the activity of the supply side of the market, to a
lesser extent linked to the overall economic situation, with a longer duration of approx. 10
years.
The type of variable adopted in the analysis as a barometer of housing market cycles is a
supplementary criterion allowing a secondary division of housing market cycles into:
– Quantitative cycles – identified on the basis of economic parameters expressed in natural units
(e.g.: items), for instance, based on the number of transactions, or the number of dwellings
completed.
– Volume cycles – identified using volumes of the most significant variables of the housing
market, e.g.: the value of residential real estate transactions, values of started or completed
investments in residential real estate.
– Price cycles – identified on the basis of changes in residential real estate prices and rents.
2.2. The housing market cycle and the business cycle
Theoretical and empirical studies on the issue of the functioning of housing markets confirm the
important role of macroeconomic conditions in shaping their cyclic development. The housing market
and the economy interact with each other, and the channels of their mutual interactions are both direct
and indirect. The phase of expansion in the housing market is usually a consequence of economic
recovery (compare: Figure. 1). Economic growth and the accompanying increase in employment and
wages are an incentive for households to improve their housing conditions. In the phase of economic
prosperity, demand for real estate can be further stimulated by cheap and accessible mortgages. In
the conditions of rapidly growing demand, the housing market experiences growth in real estate
prices, which in turn induces developers to further engage in the construction market. In the initial
phase, the construction boom allows to maintain the period of prosperity. However, when subsequent
investments are completed, the increasing housing supply limits the demand pressure present in the
market. The housing market cycle reaches a turning point, after which a decline in trading activity in
the market as well as the scale of lending, and consequently a fall in prices are observed. The crisis in
the housing market deepens recession observed throughout the overall economy.
Interactions between the housing market and the economy may also have a more subtle, indirect
nature. As part of the wealth effect, changes in the value of residential real estate have an impact on
the level of household consumption expenditures. With the increase in the value of real estate assets,
households are willing to increase their own consumption, whereas a fall in the value of real estate
owned limits their spending in this area. Empirical studies emphasise that the real estate wealth effect
is stronger and longer lasting than the wealth effect caused by financial assets (TAKHTAMANOVA,
SIERMINSKA, 2008).
Real estate assets are also common as collateral for bank loans. Changes in the value of real estate,
however, have an impact not only on the security of the banking sector but also determine the
creditworthiness of property owners. Higher amounts of credit available to households during
periods of housing boom stimulate their consumer spending and investment expenditures (BELSKY,
PRAKKEN 2004).
Another area of transfer of cyclical impulses from the housing market to the economy is a rapidly
growing segment of financial products based on real estate. As the experience of the recent global
economic crisis shows, the expansion of the market of securitisation transactions carried out on the
basis of mortgages along with the accompanying credit default swap contracts and the development
of the derivatives market based on real estate indices can become a source of deep crisis not only in
real estate markets but also in the overall economy.
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Fig. 1. The mechanism of the housing market cycle. Source: BARRAS (1994).
Despite a number of identified areas of interdependence between the economy and the housing
market, there are no clear indications as to the direction of the relationship between business cycles
and housing market cycles. These relationships can be represented as three different concepts:
1. The first concept assumes that due to the importance of the housing market in the national
economy, changes in the activity of this market have a significant impact on the course of the
business cycle. The housing market can thus induce fluctuations in the overall economy
through a number of channels. Recognising the housing market as one of the driving forces of
business cycles, it should be assumed that the housing market cycle ought to precede the
business cycle (LEAMER 2007; GHENT, OWYANG 2009).
2. The second concept assumes that the housing market only reflects changes in macroeconomic
conditions. Changes and fluctuations observed in the housing market are therefore a
consequence of the processes taking place in the overall economy (CATTE et al. 2004). In this
approach, the housing market cycle may occur with some delay in relation to the business cycle,
or may be concurrent with it.
3. The third concept assumes that housing market cycles and business cycles are not closely
related. Different phases of the two cycles may be synchronised with one another but do not
have to be. Fluctuations in the housing market do not need to be necessarily accompanied by
business cycle fluctuations in the same direction, and overall economy fluctuations do not
always have to induce equally strong changes in the housing sector. As emphasised by Prof. E.
Kucharska-Stasiak: “real estate cycles can be more volatile and longer than business cycles – but
they can also be forced and shorter. Forces within the real estate sector are the source of these
differences.” (KUCHARSKA-STASIAK et al. 2012, p. 37).
3. Data and methods
Verification of the course, interdependences and synchronisation of housing market cycles and
business cycles was conducted on the basis of data on the Polish economy, as well as the economies of
Germany, France, Great Britain and Ireland. The price index of residential property for the secondary
Real estate marke
t
Economic upturn
Economic boom
Economic downturn
Real Econom
y
Financial sector
Credit expansion
Credit boo
m
Risin
g
interes rates
Recession Credit squeeze
Increased propert
y
demand
Suppl
y
shorta
g
es
Risin
g
rent
and prices
Buildin
g
boom
Increased supply
Slackening demand
Fallin
g
rent and prices
Propert
y
slump
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market was adopted in the study as the reflection of the housing market cycle and the GDP index for
the business cycle. Table 2 contains detailed information regarding the time series used in the study.
Table 2
Characteristics of data included in the research procedure
Country Variable Time interval Specificity of time series Source of data
Poland The price of 1 m2 of usable area
in real terms
(3Q2005 prices)
3Q2005-3Q2015 RPI – single base index
(3Q 2005=100)
PKO BP S.A., GUS
(Central Statistical
Office of Poland)
Real GDP (3Q2005 prices) 3Q2005-3Q2015 GDP – single base index
(3Q 2005=100)
GUS (Central
Statistical Office of
Poland)
Germany
France
UK
Ireland
The price of 1 m2 of usable area
in real terms (2010 prices)
1Q1971-4Q2013 RPI – single base index
(1Q 1971=100)
OECD Housing
Prices database
Real GDP (2010 prices) 1Q1971-4Q2013 GDP – single base index
(1Q 1971=100)
OECD Quarterly
National Accounts
Source: the author's own compilation.
The time series of the presented variables were seasonally adjusted using the X-12-ARIMA
method. In the next stage, Hodrick – Prescott (HP) and Baxter-King (BK) frequency filters were used
in order to isolate a cyclic component. The Hodrick – Prescott filter presented by the authors in 1997 is
a high-pass filter. Its nature lies in the elimination of high-frequency fluctuations from the series,
leaving the long-term trend (HODRICK, PRESCOTT 1997). Comparing the original time series and the
estimated long-term trend, it is possible to isolate a cyclical component (ULRICHS et al. 2014, p. 11). The
Baxter-King filter (Baxter, King 1999) proposed in 1999 is a bandpass filter which allows to eliminate
high and low frequency components from the time series (random fluctuations and the trend), thus
leaving a cyclic component (ULRICHS et al. 2014, p. 12).
In the case of the Polish economy, due to the significantly shorter research horizon, the analysed
cycles were isolated only on the basis of the Hodrick - Prescott filter (the application of the Baxter-
King filter would have involved an additional shortening of the time series).
Turning points in the course of cycles were identified using the Harding-Pagan algorithm. In the
first stage of the procedure local minima and maxima were identified using two-sided 4-quarter
windows:
– Peak at t: (Xt-4, … Xt-1 < Xt > Xt+1, … Xt+4).
– Trough at t: (Xt-4, … Xt-1 > Xt < Xt+1, … Xt+4).
The second stage verified alternation of local minima and maxima occurrence. When consecutive
minima (maxima) took place one after another, a quarter with the lowest (highest) value of cyclical
component was selected as the turning point in the course of the cycle (BRACKE 2013). In addition, it
was assumed that the minimum housing cycle length was 8 quarters, while the minimum length of a
single cycle phase (upward or downward), was 4 quarters.
In order to verify the degree of correlation and synchronisation of the analysed cycles, two
measures were used: cross-correlation coefficient and concordance index in the following formula
(AKIMOV 2015):
(1)
where:
- concordance index
- cycle phase in period t for market j (takes on the value of 1 in the growth phase and 0 in the
decline phase)
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- cycle phase in period t for market i (takes on the value of 1 in the growth phase and 0 in the
decline phase)
T – number of analysed periods.
The concordance index determines the number of periods in which the analysed cycles are in the
same phase (in the growth phase or the decline phase) in the percentage terms. At full cycle
synchronisation, the index takes on the value of 100%, in the absence of synchronisation the value of 0
(DOMAŃSKA, SERWA 2014, p. 33).
Fig. 1a. Housing market cycles and business cycles in Germany. Source: the author's own compilation.
Fig. 1b. Housing market cycles and business cycles in Germany. Source: the author's own compilation.
Fig. 2a. Housing market cycles and business cycles in France. Source: the author's own compilation.
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Fig. 2b. Housing market cycles and business cycles in France. Source: the author's own compilation.
Fig. 3a. Housing market cycles and business cycles in the UK. Source: the author's own compilation.
Fig. 3b. Housing market cycles and business cycles in the UK. Source: the author's own compilation.
Fig. 4a. Housing market cycles and business cycles in Ireland. Source: the author's own compilation.
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Fig. 4b. Housing market cycles and business cycles in Ireland. Source: the author's own compilation.
Fig. 5. Housing market cycles and business cycles in Poland. Source: the author's own compilation.
4. Empirical results
The isolated housing market and business cycles, in line with the modern definition, are presented as
periodic oscillations of the variables relative to the long-term trend (the percentage deviation of the
cyclical component isolated with the use of the HP filter and BK relative to the trend) (TROJANEK
2008b). The course of the cycles in selected economies is presented in Figures 1-5. The results of the
empirical analysis of the interdependence of the cycles in selected economies and the degree of their
synchronisation are shown in Table 3.
Table 3
Basic statistics on concurrency of housing market cycles and business cycles
Economy Cross-correlation coefficients
(the time shift of the business cycle relative to the housing market
cycle)
Concordance
index
Hodrick-Prescott filter
t-4 t-3
t-2 t-1
t0
t+1
t+2
t+3
t+4
German
y
0,427 0,419 0,406 0,393
0,371
0,317
0,247
0,160
0,055 52,9%
France 0,167 0,315 0,449 0,546
0,596
0,607
0,582
0,529
0,455 66,9%
UK 0,510 0,617 0,695 0,726
0,692
0,564
0,385
0,173
-0,055 76,7%
Ireland 0,481 0,551 0,603 0,636
0,645
0,577
0,481
0,369
0,248 60,5%
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Poland 0,169 0,391 0,587 0,723
0,780
0,661
0,480
0,254
0,013 78,0%
Baxter-Kin
g
filter
t-4 t-3
t-2 t-1
t0
t+1
t+2
t+3
t+4
German
y
0,398 0,404 0,399 0,388
0,365
0,316
0,247
0,159
0,058 64,9%
France 0,207 0,323 0,437 0,531
0,587
0,588
0,554
0,496
0,425 70,3%
UK 0,569 0,638 0,682 0,688
0,644
0,511
0,340
0,144
-0,056 75,0%
Ireland 0,576 0,673 0,738 0,764
0,745
0,684
0,588
0,471
0,343 71,6%
Source: the author's own compilation.
In most of the analysed economies, a significant correlation between the business cycle and the
housing market cycle can be observed. With the exception of the German economy, the cross-
correlation coefficients exceed the level of 0.6. Apart from Poland, for which the period of analysis was
significantly shorter, the isolated cycles were most strongly correlated in the case of the UK and
Ireland. In most cases, the housing market cycle was concurrent with or had a one-quarter lag relative
to the business cycle.
On the basis of concordance indices, it can also be noted that in at least 60% of the analysed time
interval, business cycles and housing market cycles remained in the same phase of the cycle.
Significantly higher concordance indices were recorded for Poland (78%) and the UK (76.7% for the
cycles isolated on the basis of the Hodrick-Prescott filter, and 75% for the cycles isolated with the use
of the Baxter-King filter).
5. Conclusions
The study confirms a significant similarity in the course of housing market cycles and business cycles
in selected economies. Although the correlation between cycles is significant, it is not complete. This
confirms the thesis that indicates that the course of housing market cycles is affected not only by
macroeconomic determinants but also by "special forces within the real estate sector".
Differences in the level of synchronisation of housing market cycles and business cycles in the
analysed economies should also be emphasised. Certain unique determinants of the functioning of
national housing markets, not covered by the study, such as the ownership, quantitative and
qualitative structure of housing stock, the system of financing of housing investments, as well as legal,
institutional and cultural factors, can have an impact on the situation.
6. References
AKIMOV A., STEVENSON S., YOUNG J., 2015, Synchronisation and commonalities in metropolitan housing
market cycles, Urban Studies Vol. 52, Issue 9, pp. 1665-1682
BANDT O., KNETSCH T., PEÑALOSA J., ZOLLINO F., 2010, Housing Markets in Europe: A Macroeconomic
Perspective, Springer Science & Business Media.
BARRAS R., 1994, Property and Economic Cycle: Building Cycles Revised, Journal of Property Research, No
11, pp. 183-197.
BAXTER M., KING R.G., 1999, Measuring Business Cycles: Approximate Bandpass Filters, The Review of
Economics and Statistics, 81(4), pp. 575-593.
BELSKY E., PRAKKEN J., 2004, Housing’s Impact on Wealth Accumulation. Wealth Distribution and Consumer
Spending. National Association of Realtors.
BRACKE P., 2013, How long do housing cycles last? A duration analysis for 19 OECD countries, Journal of
Housing Economics Vol. 22, Issue 3, pp. 213-230.
CATTE P., GIROUARD N., PRICE R., ANDRE C., 2004, Housing Markets, Wealth and the Business Cycle, OECD
Economic Department Working Paper No. 394.
DOMAŃSKA A., SERWA D., 2014, Synchronizacja cykli koniunkturalnych a podatność gospodarek krajów
Europy na skutki kryzysu gospodarczego 2008-2009 (Synchronisation of Business Cycles and Vulnerability
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of Economies of European Countries to the Effects of the Economic Crisis 2008-2009), Ekonomia nr 37, pp.
27-55
GHENT A., OWYANG M., 2009, Is Housing the Business Cycle? Evidence from U.S. Cities, Federal Reserve
Bank of St. Louis Working Paper 2009-007B, St. Louis.
HODRICK R.J., PRESCOTT E.C. , 1997, Postwar U.S. Business Cycles: An Empirical Investigation, Journal of
Money Credit and Banking, vol. 29, no. 1, pp. 1-16.
KONOPCZAK K., 2009, Analiza zbieżności cyklu koniunkturalnego gospodarki polskiej ze strefą euro na tle
krajów Europy Środkowo-Wschodniej oraz państw członkowskich strefy, Raport na temat pełnego
uczestnictwa Rzeczypospolitej Polskiej w trzecim etapie Unii Gospodarczej i Walutowej. Projekty
badawcze (Analysis of the convergence of the business cycle of the Polish economy with the euro area
compared to the countries of Central and Eastern Europe and the Member States, Report on the full
membership of the Republic of Poland in the third stage of the Economic and Monetary Union. Research
projects), Warszawa.
KUCHARSKA-STASIAK E., 2006, Nieruchomość w gospodarce rynkowej(Real Estate in Market Economy], PWN,
Warszawa.
KUCHARSKA-STASIAK E. red. 2008, Cykle rynku nieruchomości a sektor bankowy (Property Cycles and the
Banking Sector), Fundacja na Rzecz Kredytu Hipotecznego, Warszawa.
KUCHARSKA-STASIAK E., ZAŁĘCZNA M., ŻELAZOWSKI K., 2012, Wpływ procesu integracji Polski z Unią
Europejską na rozwój rynków nieruchomości (The Impact of Poland's Accession to the European Union on
the Development of Real Estate Markets), Wyd. UŁ, Łódź.
LAMA R., DENIS S., 2014, Housing and Business Cycles: Is the UK Different from Other Advanced
Economies?, IMF Country Report No. 14/234.
LEAMER E., 2007, Housing is the Business Cycle, NBER Working Paper 13428, National Bureau of
Economic Research, Cambridge.
LIS P., 2015, Cykle mieszkaniowe. Rola rynku i państwa (Housing Market Cycles. The Role of the Market and
the State), Wyd. UE w Poznaniu, Poznań.
MICKIEWICZ P., WENCEL K., 2013, Godne życie dla wszystkich – wykluczenie społeczne migrantów jako skutek
złych warunków mieszkaniowych (A Decent Life for All – Social Exclusion of Immigrants as a Result of
Poor Housing Conditions), Instytut Spraw Publicznych, Warszawa.
SKRZYPCZYŃSKI P., 2010, Metody spektralne w analizie cyklu koniunkturalnego gospodarki polskiej (Spectral
Methods in Analysis of Business Cycle in the Polish Economy), NBP, Warszawa.
SOBCZYK M., 2000, Statystyka. Podstawy teoretyczne, przykłady – zadania (Statistics. Theoretical Basis,
Examples and Exercises),Wyd. UMCS, Lublin.
TAKHTAMANOVA Y., SIERMINSKA E., 2008, The Effect of Wealth on Consumption Expenditures: Cross
Country and Cross Socio-Demographic Group Comparisons, Ekonomia (Ekonomia. Rynek, Gospodarka,
Społeczeństwo), Issue: 20, pp. 68—95.
TROJANEK R., 2008a, Wahania cen na rynku mieszkaniowym (Price Fluctuactions in the Housing Market),
Wyd. AE w Poznaniu, Poznań.
TROJANEK R., 2008b, Determinanty wahań cen na rynku mieszkaniowym (Determinants of House Price
Fluctuations), Studia i Materiały Towarzystwa Naukowego Nieruchomości – vol. 16 nr 4, Olsztyn,
pp. 85-98.
ULRICHS M., BŁAŻEJ M., JĘDRYCH J., 2014, Równoległy oraz wyprzedzający zagregowany wskaźnik
koniunktury, zegar koniunktury. Identyfikacja mechanizmów i przebiegu cyklu koniunkturalnego dla Polski.
Metodologia (Concurrent and Leading Aggregate Economic Sentiment Indicator, Business Cycle Clock.
Identification of the Mechanisms and the Course of the Business Cycle for Poland. Methodology), GUS,
Warszawa.
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