The business cycle in historical perspective 1870-2009 – change and continuity

1. The business cycle in historical perspective1870-2009 – change and continuity Stud. politJeppe Druedahl Supervisor: Paul Sharp Opponent: Ole Jahn Seminar: Topics in Economic History Department of Economics, University of Copenhagen Presented 5th of April 2011

2. Business cycles on the research agenda once again • The Great Recession has put business cycles on the research agenda once again • In 2009 World GDP fell 1.95 percent • Too large stocks • General over-capacity • Unemployment • – It is hard to imagine this being Pareto optimal • Properties of the business cycle • Which have remained constant? • Which have changed? • In what way have they they? • Can help us with • Testing the validity of theories in a broader context • Guiding us in which direction to develop the theories

3. What is the business cycle? (I) • Typical definition: “Business cycles are a type of fluctuation found in the aggregate economic activity of nations that organize their work mainly in business enterprises: A cycle consists of expansions occurring at about the same time in many economic activities, followed by similarly general recessions, contractions, and revivals which merge into the expansion phase of the next cycle; this sequence of changes is recurrent but not periodic; in duration business cycles vary from more than one year to ten or twelve years; they are not divisible into shorter cycles of similar character with amplitudes approximating their own.” (Burns and Mitchell, 1946, p. 3) • It is a quasi-cycle: “the length of the period and also the amplitude [is] to some extent variable, their variations taking place, however, within such limits that it is reasonable to speak of an average period and an average amplitude” (Frisch, 1933)

4. What is the business cycle? (II) • My definition: • Range: 2 to 8 years • Proxy: GDP • Two different types: • Classical business cycles (absolute fluctuations) • Growth cycles (fluctuations around trend) (modern) • My approach: Bird’s-eye view with many countries and long time periods focusing on overall patterns and tendencies • Alternative: Country specific analysis (narrative or model based)

5. What is the business cycle? (III) • Four different characteristics • The duration and persistence of the cycle • The amplitude and volatility of the cycle • The co-movement of variables with GDP • The synchronization of the cycle across borders • Five papers on something similar: Backus and Kehoe (1992), Bergman et al. (1999), Basuand Taylor (1999), Helbling(2010) and Artis et al. (2011). • Plan: • A little bit of theory • My data and detrending method • Each of the characteristics

6. Theory: Impulse and propagation • Basic idea following Frisch (1933): A shock affects the system and is then propagated (transmitted) through the economy and through time by varies mechanism creating the observed cyclical pattern. • RBC: Technology shocks and inter-temporal optimization • Keynesian: Demand shocks and nominal rigidities • Changes in the business cycle can come from • Different shocks • Different propagation (policy or structural changes) • Why different shocks? • If they have changed – something must have made them do so • Be aware: Shocks are always defined as deviations from the “normal” relationship determined by the particular model being used.

7. Data (I) – Variables • Variables • Annual GDP data for 19 countries 1870-2009 • For 12 countries also where possible: • C – Private consumption • G – Government consumption • I – Gross investment • If – Fixed investment • X – Exports of goods and services • M – Imports of goods and services • P – GDP deflator • Full data: Canada, Denmark, Finland, France, Italy, Japan, Netherlands, Norway, Spain, Swede, UK and USA • Only GDP: Australia, Austria, Belgium, (West) Germany, New Zealand, Portugal and Switzerland • Note: Only Western countries + Japan (selection bias)

8. Data (II) – Sources • Recent years: OECD • 1. priority: Official national statistic agencies, • 2. priority: Research projects at these agencies, central banks and similar • 3. priority: Remaining research projects • Only historical data from • National sources • Angus Maddison (acclaimed international scholar) • Resembles that of Backhus and Kehoe (1992) • Note: As general rule in this paper all country averages are calculated using the same countries in all periods. If a country lacks consumption data for the prewar period, it is not used to compute the average in the postwar period to insure consistency.

9. Data (III) – Quality • Quality: Bad – especially for the component and price series and at business cycle frequencies • Alternative GDP measure: Based on OECD and Maddison only (US is an exception) • It is possible that almost all the results presented here are figments of the data.

10. Data (IV) – Deflation, splicing, interpolation • Deflation of series was done using their own price indices whenever possible • Splicing was done using the level of the most recent series and growth rate of the old • GDP: No missing data points 1870-2009: • World Wars create for the other series • We look at the periods: • 1870-1913: Prewar • 1920-1939: Interwar • 1949-2009: Postwar • Interpolation done so break is in the middle of the gap • Components of GDP: Adjusted GDP growth rates • Prices: Three year moving average growth rate • The conclusions of the paper are robust to changes here

11. Data (V) – Detrending • Baxter-King bandpass filter • Uses spectral analysis to extract only cycles with periodicities ranging from 2-8 years • Below 2 years: Short run noise • Above 8 years: Trend movements • Applying the filter reduces the series with three years in both ends. To avoid this and following Bergman et. al. (1998) and Stock and Watson (1999) AR(4) forecasts and backcasts were used instead. • The natural logarithm was taken so the cyclical component can be interpreted as percentage deviations from trend

12. BK-filtered GDP for Denmark

13. Duration (I) • Spectral analysis: A stationary process can be represented as the superimposition of infinitely many orthogonal cosine waves with different frequencies. • The power (“probability”) of each wave can be determined by the power spectrum (shown in the periodogram): • Following Levy and Dezhbakhsh (2003) Bartletts method was used in the estimation (details given in the paper) • Note: Probably very large standard errors

14. Duration (II) - Periodogram for Denmark • Length of cycle: 1/w • Almost the same peak frequency in all periods

15. Duration (III) – Longer cycles • Note: Lower for the whole postwar period, the interwar period is very short + Great Depression.

16. Autocorrelation (I) • First order: Generally positive – not prewar • Higher order: Negative and more so through time • Possible explanation of GDP first order pattern: Negative first order autocorrelation is typical of white noise – measurement error or more important agricultural sector.

17. Autocorrelation (II) – first order • Prewar to BW: C (financial innovations + rising living standards = more smoothing), G (new fiscal policy and welfare state) and X rising. • BW to postBW: All rising except X – especially I (more knowledge and investment based economy). • Prices: Persistence does not equal rigidity, but the pattern matches that of the changes in the duration of the business cycle (except for GM period). • Similar results in Basu and Taylor (1999)

18. Autocorrelation (III) – higher order • I think it is hard to see any interesting patterns • The very large autocorrelation at higher order for investment is notable (same argument as before). • Short run price persistence can in models with staggered price setting (Taylor or Calvo) still explain the longer cycle (the higher GDP autocorrelation at higher lags) – but why more price rigidity? More information should do the opposite lowering uncertainty and thus menu costs?

19. Amplitude and volatility (I) – results

20. Amplitude and volatility (II) – explanations • Conclusion: Higher in interwar period, but otherwise secular fall (generally accepted in the literature) • Typical explanations • More important service sector • Activist fiscal and monetary policy • Improved inventory management • Innovations in financial markets • Stock and Watson (2003) for the postwar period: Rather “good luck” (explained partly by fewer price and productivity shocks) and better monetary policy. • My view: The Great Depression is an exception and the above explanations are necessary in the long historical perspective.

21. Amplitude and volatility (III) – ratios • C: Constant around 1, maybe with a falling trend (more consumption smoothing) • G: Has dropped in the postBW period (absence of wars and large automatic stabilizers) • If: Constant around 3 • I: Has risen – inventories must have become more volatile • X and M: Higher during interwar and BW characterized by low level of globalization • Prices: Rising until BW, fallen steeply in postBW – could be a sign of more rigid prices (stability could also leads to more consumption smoothing)

22. Co-movements (I) • Note: Non-significant coefficietns at a 5 percent level using the Newey-West estimator have been set to zero.

23. Co-movements (II) • C: Procyclical – correlated at lead and lag in the recent period (more smoothing) • G: Acyclical– only high in the heyday of Keynesianism in the BW period (notice: no correlation can imply good stabilization policies) • I and If: Procyclical – now as much as C (If somewhat lagging) • X: Procylical generally and acyclical in prewar. Interwar and BW can be explained by restrained capital mobility. postBW has to be explained by very synchronized business cycles (accepted – see following slides) • M: Procylical generally and acyclical in prewar. • Granger causality: Nothing at all – the problem is annual series.

24. Synchronization (I) – correlation coefficients

25. Synchronization (II) – test • Conclusion: Clearly rising except for a small fall from interwar to BW. • Also for cross of Europa and Anglo-Saxon (not always so in the literature) • Japan somewhat disconnected in the recent period • Significant: Yes. Generally • Wilcoxon Rank Sum Test: Null hypothesis of two independent samples having equally large value • Some of the small samples is a problem

26. 1870 WWI 2000 WWII Synchronization (III) – puzzle • Puzzle of the U-shaped globalization and the rising synchronization • Stylized view: More globalization More synchronization Level of synchronization Level of globalization 1973

27. Synchronization (III) – explanation • 1) Interwar period: • Unusual large global shock • Short period • Same beginning with WWI • 2) BW>prewar: • Less agriculture means fewer idiosyncratic shocks • Globalization has more width and depth in BW • A'Hearnand Woitek (2000): The low prewar correlation is a figment of the method(Kitchen and Junglarcycles) • Bordo and Helbling (2010) uses a FSVAR to find favorable evidence for these conclusions.

28. Conclusion • Notice: All the results can be figments of our data. • General conclusion: The business cycle is a rather constant phenomenon across countries and periods – with the interwar period being an outlier • 1) Longer cycles • 2) Less saw-toothed • 3) Lower amplitude • 4) More synchronized across borders

29. Conclusion • Changes in volatility ratios, autocorrelation structures and co-movements between GDP and the different variables are possible starting points for explaining this • Signs of increasing price rigidity and consumption smoothing have been found • Other explanations have focused on changes in fiscal and monetary policy • Sectorial changes is also an important factor • Extending the data set with more variable and using panel data methods could yield important results • Wages • Money stocks • Interest rates • Sectoral divisions • Employment • Consumer prices

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