Financial Markets and Financial Regulation:

Sources of Instability or Growth?International Historical Perspectives

Muenster, Germany, April 12, 2012

Business Cycles in South-East Europe 1870-2000: A Bayesian Dynamic Factor Model

Dr Matthias Morys (University of York)Prof. Martin Ivanov (Bulgarian Academy of Sciences)

Business Cycles in Historical Perspective

• “Business cycle paradox”: Research on market integration suggests high degree of business cycle synchronisation but it cannot be detected in the data

• Example: Classical Gold Standard period: product and factor markets were highly integrated & quasi-universal fixed XRs (Daudin&Morys&O’Rourke 2010)

• BUT Research on business cycles finds low correlation of GDP growth / de-trended GDP

Source Average bilateral

correlation

Countries Time frame Statistical method:

correlation of

Backus&Kehoe (1992)

0.03 England, Germany

1870-1913 de-trended GDP

Artis et al. (2011) 0.09 England, France, Germany

1880-1913 de-trended GDP

Bordo&Helbling (2011 )

0.04 US, E, F, G, CH, Netherlands

1880-1913 GDP growth rates

Bordo&Helbling (2011)

0.09 F, G, CH, Neth.(European core)

1880-1913 GDP growth rates

Example: Research on core countries 1870s - 1913

• equally low correlation for peripheral countries and for core countries vis-à-vis peripheral countries

• literature as above & Bergman, Jonung for the Nordic countries

Business Cycles in Historical Perspective

• “Business cycle paradox”: Research on market integration suggests high degree of business cycle synchronisation but it cannot be detected in the data

• Example: Classical Gold Standard period: product and factor markets were highly integrated & quasi-universal fixed XRs (Daudin&Morys&O’Rourke 2010)

• BUT Research on business cycles finds low correlation of GDP growth / de-trended GDP

• Two ways to solve the business cycle paradox:(a) correlation between business cycle synchronization and market integration not necessarily positive (Krugman 1993): trade integration regional specialization reduced output synchronization due to industry-specific shocks(b) business cycle paradox as a figment of poor GDP data

Business cycle paradox a result of poor GDP data?

• 3 concepts to measure GDP (production, expenditure, income) often give different results (2001 and 2007-9 US recession; Übele (2011) for German GDP data 1851-1913)

• historical national accounts: interpolation reduces volatility• fine for GDP levels, but highly problematic for cycles• for a detailed critique see Ritschl et al. (2008) & Aiolfi et al. (2011)

South-East Europe: we have to make a virtue out of necessity!• Pre-WW I: GDP estimates on annual basis only for Austria-

Hungary (Schulze 2000), Bulgaria (Ivanov 2009) and Greece (Kostelenos et al. 2007)

• only Schulze (2000) in Maddison (2003)• Post-WW II: conceptual differences between System of National

Accounts and Material Product Accounting (East bloc counterpart)

Dynamic Factor Methodology as Solution to ‘Business Cycle Paradox’?

• Many time series discarded for GDP purposes but useful for business cycle studies

• In line with Burns&Mitchell 1946...(“... a cycle consists of expansions occurring at about the same time in many economic activities, followed by similarly general ... contractions...”)

• ... and the NBER business cycle dating procedure (with its emphasis on movements in employment over and above GDP data)

• CDFA has strong similarities to Principal Component Analysis• A cross-section of economic variables share a common factor; extracting

the common factor for the entire period delivers a business cycle index that is far more accurate than GDP

• Stock&Watson (2010): 250 series to analyse current US business cycle• Federal Reserve Bank of Chicago’s National Activity Index (CFNAI)• Economic history: Aiolfi et al. (2011), Ritschl et al. (2008),

Sarferaz&Übele (2009), Übele (2010)

Dynamic factor model

Static factor model(1) yt = λ0 + λ ft + εt

(n x 1) (n x 1) (n x o) (o x 1) (n x 1)

(2) yit = λ0i + λi ft + εit

(1 x 1) (1 x 1) (1 x o) (o x 1) (1 x 1)

common component idiosyncratic component

Dynamic factor model: allowance for dynamic properties(3) ft = Φ1 ft-1 + Φ2 ft-2 + … + Φp ft-p + ζt

(o x 1) (o x o) (o x 1) (o x o) (o x 1) (o x o) (o x 1) (o x 1)

(4) εit = φi1 εi,t-1 + φi2 εi,t-2 + ... + φiq εi,t-q + ηit

(all variables are scalars)

ft follows VAR(p) process, εit AR(q) process

What time series are we drawing on?All sorts of time series contain information on business cycles- Burns&Mitchell (1946): locomotive orders, pig iron production, bank

clearings- In recessions women buy more lipsticks but fewer clothes and men

replace their underwear less frequently (Greenspan apparently collected data of this sort, The Economist, 29.7.2011)

Our approach: 25 time series for each country1. Sectoral output indicators: agriculture; communication; industrial

output; mining; construction; transportation; fixed investment2. Fiscal indicators: government expenditure & revenues3. Financial indicators: M0, M3, domestic interest rate, mortgage

credit4. Trade indicators: REER, TOT; export & import5. Other indicators: real wage; population; CPI

Data mostly taken from official Statistical YearbooksFor Soviet bloc countries (Bulgaria, Romania, Yugoslavia) double-

checked with Western sources, mainly Vienna Institute for International Economic Studies

CDFA versus GDPEngland, France, Germany, Austria-H. 1879 - 1913

England(CDFA)

France(CDFA)

Germany(CDFA)

AH(CDFA)

England(GDP)

France(GDP)

Germany(GDP)

France(CDFA)

0.78 ***

Germany(CDFA)

0.81 *** 0.81 ***

Austria-H. (CDFA)

0.67 *** 0.78 *** 0.84 ***

England(GDP)

0.84 *** 0.66 *** 0.72 *** 0.69 ***

France(GDP)

0.28 0.55 *** 0.35 ** 0.49 *** 0.28 *

Germany(GDP)

0.22 0.15

0.36 ** 0.26 0.02 0.48 ***

Austria-H.(GDP)

0.23 0.30 * 0.22 0.39 ** 0.34 ** 0.35 ** 0.02

Extreme cases: Germany – England: 0.81 versus 0.02 Germany – Austria-Hungary: 0.84 versus 0.02

Business cycles England, France, Germany 1879-1913

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1

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1880 1885 1890 1895 1900 1905 1910

ENGLAND FRANCE GERMANY

Baring crisis 1890

American banking crisis 1907

Questions we want to ask with respect to South-East Europe1. Has there been an identifiable regional business cycle ?2. If so, to what extent it was synchronized with W. Europe ?3. How volatile and how persistent have SEE business cycles been compared to the ‘core’?4. Are global / regional or country-specific shocks dominant?

Countries included in our study• Austria(-Hungary), Bulgaria, Greece, Romania, Serbia/Yugoslavia• These 5 countries taken together have consistently accounted for

more than 85% of regional GDP from 1870 to the present day

Questions we want to ask with respect to South-East Europe1. Has there been an identifiable regional business cycle ?2. If so, to what extent it was synchronized with W. Europe ?3. How volatile and how persistent have SEE business cycles been compared to the ‘core’?4. Are global / regional or country-specific shocks dominant?

Countries included in our study• Austria(-Hungary), Bulgaria, Greece, Romania, Serbia/Yugoslavia• These 5 countries taken together have consistently accounted for

more than 85% of regional GDP from 1870 to the present day

Implications beyond SEE...• European region best suited for analysis of “regional business

cycles”: since when do they exist? (cf. Bordo&Helbling 2011, Artis et al. 2011, Aiolfi et al. 2011)

• SEE has more countries than Scandinavia (4), Iberia (2) or Central&Eastern Europe (1) which go back to the late 19th century

AH Gr Ro Se Bu E F G

Greece 0.060.230.60 *

Romania 0.30 *0.310.51

0.26 0.33 0.45

Serbia 0.34 *0.55 **0.87 ***

0.27 0.22 0.76 **

0.190.320.64 **

Bulgaria 0.34 *0.280.03

-0.07-0.25-0.45

0.270.37 *0.22

0.42 **0.250.15

England 0.67 ***0.49 **0.45

0.25 0.37 0.49

0.130.070.29

0.240.090.36

-0.07-0.29-0.55 *

France 0.78 ***0.85 ***0.88 ***

0.23 0.12 0.59 *

0.170.190.56 *

0.48 **0.46 **0.70 **

0.25 0.08-0.19

0.78 ***0.66 ***0.73 **

Germany 0.84 ***0.83 ***0.78 ***

0.08 0.25 0.57 *

0.190.230.59 *

0.34 *0.42 **0.73 **

0.18 0.07-0.18

0.81 ***0.77 ***0.84 ***

0.81 ***0.86 ***0.87 ***

Business cycle correlations 1875 – 1913 by country pairs:Full period, 1893-1913, 1903-1913

Business cycles of Austria-H., Romania and Greece

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82 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12

AUSTRIA ROMANIA GREECE

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3

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03 04 05 06 07 08 09 10 11 12 13

AUSTRIA ROMANIA GREECE

1881 - 1913 1903 - 1913

• For the later period we recognise upswings and downswings which are well-documented for other countries

Long upswing in the early 1900sInterrupted by the American Banking Crisis of 1907Another upswing in the 1910s

• Confirms qualitative evidence on SEE countries (Lampe&Jackson 1982)

AH Gr Ro Se Bu

Summary statistics for SEE-5Average r vis-à-vis SEE-5

0.260.340.50

0.130.130.34

0.260.340.45

0.300.340.61

0.24 0.17 -0.01

0.24 (0.24 without Bulgaria) 0.26 (0.33 “ “ ) 0.38 (0.64 “ “ )

Average r vis-à-visE, F, G

0.760.720.70

0.190.250.55

0.170.160.48

0.350.330.60

0.12 -0.04 -0.31

0.32 (0.37 without Bulgaria) 0.28 (0.37 “ “ ) 0.40 (0.58 “ “ )

Business cycle correlations 1875 – 1913 (summary stat.):Full period, 1893-1913, 1903-1913

• Business cycle integration starts at high levels (compared to previous studies) and increases the further we come to WW I: within SEE and vis-à-vis core

• Effect more pronounced when Bulgaria omitted (insufficient time span?)• But: intra-core synchronization levels higher (0.80) • no regional cycle; SEE increasingly participating in a pan-European cycle

• Increases in business cycle synchronization are statistically significant (Wilcoxon rank sum tests)

• Our main finding – increasing synchronization of SEE countries that, however, fails to reach core country levels – is consistent with research on market integration: emphasis on increasingly integrated good and factor markets before WW I but considerable cross-country differences remain (O’Rourke&Williamson 1999)

• “geography of synchronization”: Austria-Hungary and Serbia (on the Western edge of the Balkans) more strongly synchronized, followed by Romania, Greece, Bulgaria (in that order)

Business cycles 1875 – 1913: concluding remarks

Interwar period: What are our expectations?

Factors suggesting a decrease of synchronization• de-globalization (in particular reduction in trade and capital flows)• Currency instability

Factors suggesting an increase of synchronization• Great Depression as “global shock” (of extraordinary size)(Backus&Kehoe 1992, Basu&Taylor 1999)• Formation of trade areas and currency blocs might lead to increased regional

synchronization

Specific to SEE: border changes after WW I might increase synchronization• Yugoslavia, Romania gain at the expense of Austria, Hungary and (to a smaller

extent) Bulgaria• established trade relationships between cities/regions continue even if in

different countries after WW I• similar rational holds for bank lending• some evidence for this in the Yugoslav case (Aleksic 2009)

Business cycles II: Interwar PeriodBilateral correlations of cyclical component (1919-1941)

Bu Ro Yu Au Gr Germany France England

Bulgaria 0.71 0.72 0.59 0.14 0.26 0.22 0.46

Romania 0.71 0.82 0.68 0.19 0.42 0.32 0.41

Yugoslavia 0.72 0.82 0.79 0.24 0.46 0.51 0.56

Austria 0.59 0.68 0.79 -0.09 0.54 0.49 0.51

Greece 0.14 0.19 0.24 -0.09 -0.05 0.08 0.29

Average 0.54 0.60 0.64 0.49 0.12 0.32 0.32 0.44

Average excl. Greece 0.67 0.74 0.78 0.69 0.42 0.38 0.48

• Very high levels of business cycle integration between Bulgaria, Romania, Yugoslavia and Austria, but Greek case different

• Average correlation between these 4 countries at 0.72, with little change before and after 1929 (0.79 versus 0.77)

• Correlation intra-core and core-periphery increase after 1929 (to 0.66 & 0.63) but do not reach intra-SEE-4 synchronization level SEE regional business cycle

• Only exception is Germany which in the 1930s is as synchronized with SEE-4 as SEE-4 among each other (0.73)

How to explain the regional business cycle? And how to explain the Greek exception?

No accepted “narrative” of interwar business cycles but three factors are seen as particularly relevant (Ritschl&Straumann 2010):

(1) WW I: wartime recession (standard case) versus wartime boom (mainly neutral countries)? In case of wartime recession, peak normally 2 – 3 years after end of WW I

(2) impact on the national business cycle from tying to (in the 1920s) and untying from (in the 1930s) the gold standard

(3) development of bilateral trade patterns

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BULGARIA ROMANIAYUGOSLAVIA GREECE

(1) The effect of World War I

• All SEE countries follow standard pattern of wartime recession...• ... but Greece is involved for longer in hostilities due to Greek-

Turkish war (1919-1922)• Peaks follow end of hostilities with 2 – 3 year lag:

1920 for Austria, Bulgaria, Romania1921 for Yugoslavia1923 for Greece

Greece

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20 22 24 26 28 30 32 34 36 38

BULGARIA ROMANIAYUGOSLAVIA GREECE

(2) Business cycles and exchange-rate regime

Greece

• monetary stabilization in the 1920s almost simultaneous (Bulgaria, Greece: 1928; Romania, Yugoslavia: 1929); exception: Austria (1923)

• 1930s: Austria, Bulgaria, Romania, Yugoslavia adopt deflationary policies cum foreign exchange controls Greece leaves gold standard in 1932 and defaults

• Trough of Great Depression:• 1931 for Greece• 1933 for Austria, Romania, Yugoslavia• 1934 for Bulgaria• supportive of Eichengreen&Sachs (1985): early departure means quicker recovery

1929 1933 1937

Export to Germany

Bulgaria 42.5 45.1 47.1

Hungary 42.1 38.2 41.0

Romania 37.0 27.2 24.1

Yugoslavia 24.1 35.6 35.2

Import from Germany

Bulgaria 29.8 44.4 58.2

Hungary 33.2 39.5 44.2

Romania 36.6 27.8 40.1

Yugoslavia 33.0 29.3 42.7

Source: Warriner, 1939: 58.

(3) Trade patterns show increasing focus on Germany

SummaryOn Dynamic Factor Methodology• Can be employed successfully even for relatively short periods of time such as

the interwar period

Empirical findings• CDFA suggests much higher business cycle synchronisation than historical

national accounts

Pre-WW I• increasing business cycle synchronization, both within SEE and vis-à-vis the

core economies• SEE increasingly participates in pan-European business cycle (i.e., no regional

business cycle)

Interwar period• emergence of a regional business cycle based on similar wartime experience

(i.e. wartime recession), monetary developments and trade patterns• Greece is not part of this business cycle but Germany is

Thank you very much !

We are looking forward to your comments

matthias.morys@york.ac.uk

hadjimartin@abv.bg

Business cycles III: Postwar Period

Does trying to detect a regional business cycle make sense

despite the Iron Curtain?• Was there business cycle integration in the Soviet bloc at all?• Common external shocks: oil price shocks 1973/1979• SEE contains the two “unruly children” of the Soviet bloc:

(a) Yugoslavia: after 1949 (break with Stalin) opens economically towards the West by increasing trade and importing capital; even labour mobility (Gastarbeiter experience with West Germany)

(b) Romania: similar (though less pronounced) developments after the oil price shock; becomes IMF member in early 1980s

Do these interactions lead to a business cycle with Western Europe?

General finding for Austria/Greece confirmed: relatively high integration with E, F, G in the 1950s and 1960s, less so in 1970s but then again in the 1980s and 1990s.

Soviet bloc business cycle integration versus synchronisation with West Germany, 1950s – 1970s

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56 58 60 62 64 66 68 70 72 74 76

BULGARIA_ ROMANIA_

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1954 1956 1958 1960 1962 1964 1966 1968 1970 1972

YUGOSLAVIA_ GERMANY

- Bulgaria and Romania well integrated

- Yugoslavia fairly well integrated with West Germany but not at all with Bulgaria, Romania

Germany Yu Ro Bu

W. Germany 0.48 -0.30 -0.53

Yugoslavia 0.48 -0.31 -0.70

Romania -0.30 -0.31 0.56

Bulgaria -0.53 -0.70 0.56

Soviet bloc business cycle integration versus synchronisation with West Germany

Germany Yu Ro Bu

W. Germany 0.42 0.34 -0.39

Yugoslavia 0.42 0.57 - 0.12

Romania 0.34 0.57 0.28

Bulgaria -0.39 -0.12 0.28

1950s - 1970 1970 - 1988

• Not only Yugoslavia is connected to West European business cycle, but from the 1970s onwards also Romania

• Bulgaria appears increasingly isolated; supports the political history story that Bulgaria was a more “committed” member of the Soviet bloc

Germany Yu Ro Bu

W. Germany 0.48 -0.30 -0.53

Yugoslavia 0.48 -0.31 -0.70

Romania -0.30 -0.31 0.56

Bulgaria -0.53 -0.70 0.56

SummaryOn Dynamic Factor Methodology• Can be employed successfully even for relatively short periods of time such as

the interwar period

Empirical findings• CDFA suggests much higher business cycle synchronisation than historical

national accounts

Pre-WW I• increasing business cycle synchronization, both within SEE and vis-à-vis the

core economies• SEE increasingly participates in pan-European business cycle (i.e., no regional

business cycle)

Interwar period• emergence of a regional business cycle based on similar wartime experience

(i.e. wartime recession), monetary developments and trade patterns• Greece is not part of this business cycle but Germany is

Post-WW II• Onset of the Cold War almost completely extinguishes regional business cycle

integration• increasing links with the West of Yugoslavia, later Romania sees re-emergence

of a common business cycle vis-à-vis Austria (and West Germany)

Thank you very much !

We are looking forward to your comments

matthias.morys@york.ac.uk

hadjimartin@abv.bg

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20 22 24 26 28 30 32 34 36 38

BULGARIA ROMANIA YUGOSLAVIA

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20 22 24 26 28 30 32 34 36 38

BULGARIA ROMANIAYUGOSLAVIA GREECE

Business cycles in the interwar period: The Greek exception

Source Average correlation

Countries Time frame Statistical method:

correlation of

Morgenstern (1959)

0.83 E, F, G 1870-1914 concordance index(NBER tradition)

Backus&Kehoe (1992)

0.03 E, G 1870-1913 de-trended GDP

Artis et al. (2011) 0.09 E, F, G 1880-1913 de-trended GDP

Bordo&Helbling (2011 )

0.04 E, F, G, Ne, CH, US 1880-1913 GDP growth rates

Bordo&Helbling (2011)

0.09 F, G, Ne, CH 1880-1913 GDP growth rates

Uebele (2011) 0.61 E, F, G 1862-1913 CDFA business cycle indices

Raw slide related to table 1

Example: Austria-Hungary 1875-1913

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1875 1880 1885 1890 1895 1900 1905 1910

BUSINESS_CYCLE TRANSPORTATION

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1875 1880 1885 1890 1895 1900 1905 1910

BUSINESS_CYCLE MANUFACTURING

r = 0.76 r = 0.63

• transportation: transported goods in million tons (Statistical Yearbooks)• manufacturing : component of GDP reconstruction by Schulze 2010• transportation: quintessentially disaggregate data, raw data not influenced by

prices

• the individual series with the highest correlation are in our case: manufacturing, construction, transportation (often > 0.70), M0, M3, exports, government revenue

Some comments on data reconstruction / estimation

• SEE is often seen as terra incognita by cliometricians but a “new economic history” of SEE could easily be written

• Main source: official Statistical Yearbooks (publication of which started shortly after gaining political independence in 1870s & 1880s)

• Comparison with Mitchell’s Historical Statistics often shows major discrepancies

• For the post-WW II period, local sources for BG, RO & YU were double-checked with Western sources on Soviet bloc countries (Vienna Institute for International Economic Studies, Marrer et al.)

• First attempt ever to construct some of the time series based on a unified methodology for all countries: CPI, REER & TOT

• Time series are de-trended with HP filter (λ = 6.25)• Bayesian estimation (more flexible when dealing with short time series)