Business Cycles 3. High Frequencies: Business Cycle

Business cycles The facts which define a cycle Theories explaining the phenomenon

3. High frequencies: Business cycle 3.1. The Stylised facts Williamson, Stephen (2010) Macroeconomics , Addison Wesley, Boston USA, 4 th edition, c. 3 Kydland, F. and E., Prescott (1990) “Business Cycles: Real facts and a Monetary Myth”, Federal Reserve Bank of Minneapolis Prescott, E.C. (1986) “Theory Ahead of Business Cycle Measurement”, Federal Reserve Bank of Minneapolis, Quarterly Review

«[The business cycle] is not dead, even though it has been muted for the past two decades. There is little doubt that the emergence of just- in time inventory programs and increasing service output has markedly diminished the amplitude of fluctuations in GDP. But human nature does not change. History is replete with waves of self-reinforcement enthusiasm and despair, innate human characteristics not subject to a learning curve. Those waves are mirrored in the business cycle.» Alan Greenspan (2007) op. cit. p. 490-491.

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Popular vision of the cycle

PORTUGAL: Wheat production per head

120

100

60 kg/hab.

0 1846 1896 1946 1996

2 GDP annual rate of growth PORTUGAL 1833-2011

10 %

0 1833 1853 1873 1893 1913 1933 1953 1973 1993

-10

-20

-30 Executive Master in Macroeconomics and Business João César das Neves Management and Banking

Business Cycle: USA

3 %

-11950 1960 1970 1980 1990 2000 2010

-3

-5

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3 Business Cycle: Brazil

0 1950 1960 1970 1980 1990 2000 2010 -2

-4

-6

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Business Cycle: Spain

0 1950 1960 1970 1980 1990 2000 2010 -2

-4

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4 Business Cycle: Angola

0 1950 1960 1970 1980 1990 2000 2010 -10

-20

-30

-40

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Volatility of GDP growth 10 year stand. deviation of growth rate US, Portugal 1880-2010

10 US 8 Portugal 6

0 1880 1900 1920 1940 1960 1980 2000

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5 Two visions of the cycle

“In general scientific use .. the word (cycle) denotes a recurrence of different phases of plus and minus departures, which are often susceptibles of exact measurement” Wesley Clair Mitchell Conference on Cycles (1922), quoted in Mitchell (1927) “Business Cycles: The problem and its setting” and in Kydland and Prescott (1989) “Business Cycles: real facts and a monetary myth” p.5. “the business cycle ... movements about trend in gross national product and ... regularities which are observed in the co- movements among different aggregative time series” Lucas, R. (1977) "Understanding Business Cycles” p.217, and Prescott (1986) “Theory ahead of Business Cycles Measurement” p.10.

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

Portugal: GDP (log) and HPtrend

11.5

10.5

9.5 1953 1963 1973 1983 1993 2003

6 Portugal: GDPcycle

0.1

0.08

0.06

0.04

0.02

0 1953 1963 1973 1983 1993 2003 -0.02

-0.04

-0.06

-0.08

-0.1

Stylised Facts in the Cycle

• The cycle is, in its own nature, instability. • What we look for are patterns in that instability • “Business cycles are all alike”

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7 Historical continuity

«Fortunately for policymakers, there is a degree of historical continuity in the way democratic societies and market economies function. This enables us to reach back into the past to infer inherently persistent stabilities that, while not having the certainty we attach to physical laws, nonetheless offer a window on the future (…) if we adopt Winston’s Churchill insight. “ The further backwards you look, the further forward you can see” .» Alan Greenspan (2007) op. cit. p. 464-465 .

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Stylised Facts of the Cycle 1/4

Persistence – Most macroeconomic series show strong persistence. First-order serial correlation of quarterly series is near 0.9. – Comparisons of the periods before and after the wars show no clear differences in product volatility. But it was much higher in the inter-war period. – Money growth rate persistence is small.

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8 Stylised Facts of the Cycle 2/4

Co-movement – Most macroeconomic series are pro-cyclical, with high contemporaneous correlation with the product. – The a-cyclical series (near zero correlation) are wages, government expenditures and capital stock. – Price levels, clearly pro-cyclical before the Second World War, became clearly counter-cyclical after. – Money reduced its correlation with the product since the war.

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Stylised Facts of the Cycle 3/4

Volatility 1/2 – Consumption of non-durable goods is less volatile than the product. Durables consumption is more volatile than product. Total consumption shows volatility similar to the product. – Investment is 2 to 4 times more volatile than the product. – Government expenditures are more volatile than product. – Capital is much less volatile, but capital utilization in industry is more volatile than the product.

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9 Stylised Facts of the Cycle 4/4

Volatility 2/2 – Total hours worked have similar volatility to the product. – Employment is as volatile as the product, while hours per worker are much less volatile, so much of volatility in total hours worked comes from changes in employment. – Labour produtivity (product per hour-man) is less volatile than product. – Real wage rate is much less volatile than product.

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10 Moments of cyclical variables 1/2 Portugal, 1953-2010 σσσσσσ σσσ ρρρ ρρρ ρρρ ρρρ ρρρ ρρρ ρρρ / y -1 -2 xy xy-1 xy-2 xy+1 xy+2

Y 3.52 1.00 73.68 26.92 100.00 73.68 26.92 73.68 26.92

C 3.58 1.02 68.39 26.54 88.83 76.58 36.85 58.58 17.44

G 3.95 1.12 58.78 13.46 49.05 47.27 34.55 33.15 7.70

I 10.16 2.88 65.77 22.61 77.07 58.81 21.49 57.36 21.08

E 8.01 2.27 66.40 26.74 47.69 23.16 -8.30 39.35 19.35

IM 9.49 2.69 64.96 27.04 75.10 49.89 12.55 68.18 40.03

TB 29.67 8.42 63.32 13.16 57.62 48.25 24.68 45.70 27.52

Moments of cyclical variables 2/2 Portugal, 1953-2010

σσσσσσ σσσ ρρρ ρρρ ρρρ ρρρ ρρρ ρρρ ρρρ / y -1 -2 xy xy-1 xy-2 xy+1 xy+2

L 2.51 0.71 72.16 30.73 66.12 55.23 21.07 48.16 15.76

K 1.92 0.54 86.53 55.65 57.09 66.92 56.96 30.32 1.21

r 77.75 22.08 33.78 19.71 -8.30 -26.34 -35.64 -0.22 6.07

w 5.94 1.69 83.89 56.45 43.51 59.55 65.62 26.13 11.59

M1 6.91 1.96 70.33 29.69 22.04 19.48 0.73 18.04 6.43

p 6.90 1.96 93.99 83.49 -50.15 -45.15 -33.92 -47.65 -35.44

11 “Business Cycles are all alike”

“Though there is absolutely no theoretical reason to anticipate it, one is led by the facts to conclude that, with respect to the qualitative behaviour of co- movements among series, business cycles are all alike . To theorectical inclined economists, this conclusion should be attractive and challenging, for it suggests the possibility of a unified explanation of business cycles, grounded in the general laws governing market economies ” Lucas, R. (1977) "Understanding Business Cycles,"

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The 2009 crisis

«Until the Lehman failure the recession was pretty typical of the modest downturns of the post-war period. There was a recession under way, led by the decline in housing construction. (…). After the Lehman bankruptcy, too, models (…) combined with new information, gave what turned out to be very accurate estimates of the private- spending reductions that ensued over the next two quarters. When Ben Bernanke, the chairman of the Fed, warned Hank Paulson, the then treasury secretary, of the economic danger facing America immediately after Lehman’s failure, he knew what he was talking about.» Lucas, Robert E. (2009) “In defence of the dismal science”, in The Economist , August 6th,Executive 2009 Master in Macroeconomics and Business João César das Neves Management and Banking

12 Financial crisis 1970-2007

Banking Currency Sov. debt Twin Triple 1970-79 4 51 7 0 0

1980-89 39 127 42 11 4

1990-99 74 120 7 27 3

2000-07 7 28 8 4 3

Total 124 326 64 42 10

Laeven, Luc and Fabian Valencia (2008) Systemic Banking Crises: A New Database, IMF Working paper, WP/08/224

Financial crisis 1970-2007

90 80 70 Banking crisis 60 Currency crisis 50 Sovereign debt crisis 40 Twin crisis 30 Triple crisis 20 10 0 1970- 1975- 1980- 1985- 1990- 1995- 2000- 2005- 74 79 84 89 94 99 04 07

13 Systemic Currency Debt Debt # Banking Crisis Crisis Restruc. W. Europe and N America 10 7 9 0 0 E.Europe and Central Asia 29 22 24 9 9 Mid.East and North Africa 14 12 23 5 5 Sub. Sah.Africa 43 39 68 24 22 South Asia 8 4 9 0 0 E Asia Pacific 14 9 24 2 2 L.America and Caribbean 25 29 54 24 24

In yellow: values per country above average; in orange the higgest number of crises

Financial crisis 1970-2007

50 Systemic Banking Crisis Currency Crisis 40 Debt Crisis 30 Debt Restructuring

e ia , m .Asia ;Car S ia;Pac. ; N.A ; C.As s ur SSAfrica A E E. L.Amer. W. E.Eur M.East;N.Afr.

14 Worst affected counties

S. Banking Currency Debt Debt Res. 1980 1989 1975 1981 1987 1982 Argentina 1993 2005 1995 2001 2002 2001 1983 1991 1976 1983 1989 Congo DR 1976 1989 1994 1994 1999 1978 1984 1991 Turkey 1982 2000 1978 1982 1996 2001 1976 1982 1987 Brazil 1990 1994 1983 1994 1992 1999 Dominican 1982 2003 1985 1990 2003 1994 2005 Rep. 2003 1982 Ecuador 1982 1998 1982 1999 1995 2000 1999 1972 1983 1990 1983 Uruguay 1981 2002 1991 2003 2002 2002

Rich and powerful counties S. Banking Currency Deb D.Res. Iceland 2008 1975 1981 1989 2008 Russia 1998 1998 1998 2000 Finland 1991 1993 Spain 1977 1983 Sweden 1991 1993 USAmerica 1988 2007 New Zeland 1975 1984 Japan 1997 Greece 1983 Italy 1981 Norway 1991 Portugal 1983 Unit.Kingdom 2007

15 Share of non-performing loans at peak (%)

100 90 80

70 60 50

40 30

20 10 0 e ia ia o a a a a n ia li b n n ic ria nd ad m p. ua n a ia on ublic and tvi nia a h e M cip p l ania la C Niger n La enti eroo u R Est Fin a Fas g Alba Alge an Niger Pri Colom Re n Jam am Lith Thai VietnaUruguay icarag aurita ArgentiPhilippines Ar Venezuela C N M can and i Burki l Afric Sierra Leone é ra nt Domin e C São Tom

Share of non-performing loans at peak (%)

100 90 80 70 60 50 40 30 20 10 0

9 0 1 2 3 4 80 83 87 95 95 97 97 98 00 9 9 9 99 99 99 9 9 9 9 9 0 1 1 1 1988 198 199 199 1 1 1 1 1 1 1 1 2

16 Gross fiscal cost (% GDP)

l i a ia ia in o ic ia nd na ay n c l s la tina ti tina u i pines mb ex ub Israel donia Braz ai en p Latvia weden en o Ben e one Th rg ili S Hungary M Thailand d A Sri LankArg Col Argen Parag NicaraguaMaurita Rep In Ph an Mac c

Domini

Gross fiscal cost (% GDP)

4 5 6 7 7 8 0 3 9 9 9 99 99 99 00 00 1977 1981 1983 1987 1988 1990 1991 1992 19 19 19 1 1 1 2 2

17 Output loss (% of GDP)

45 40

35 30

20 15

10 5

0 . f p y es e n ia a a m d o d ar ay O d a ya ne s ile ke p. eni in n o a ur asc w pin rain venia In ntin e Cha F Ch n Re a Ricag p B ent e K Le a T st Guinea ili Uk lo Turkeyg FinlanJordan c a Nor . Re h S r ColombiaVietn Uruguay i Mauritania m P A Arg rkina Co ad u M De Sierra B o, ntral Afr ng Ce Co

Output loss (% of GDP)

120

100

7 8 8 0 0 2 3 4 5 6 7 8 2 8 8 9 9 9 9 9 9 9 9 0 9 9 9 9 9 9 9 994 9 9 998 9 0 1 198 1 1 1 1991 1 1 1 1 1 1 199 1 1 2

18 Minimum real GDP growth rate (%)

0 India Peru Japan Kenya Kenya Eritrea Turkey Turkey Poland Nigeria Russia Norway Ecuador

-5 Romania Colombia Argentina Argentina Argentina Cameroon Venezuela China, P.R. China, Guinea-Bissau Slovak Republic -10 Congo, Dem. Of Rep. Congo, Congo, Dem. Of Rep. Congo,

-15

-20

Minimum real GDP growth rate (%)

-10 1976 1981 1982 1983 1987 1988 1989 1990 1991 1992 1993 1994 1994 1995 1995 1997 1998 2001

-20

-30

-40

-50

19 Some recent crises 1990-2013, selected countries, IMF data

GDP growth rate Unemployment rate 15 25

10 20

5 Argentina 15 Ireland 0 Greece 1990 1995 2000 2005 2010 Portugal 10 Iceland -5

5 -10

0 -15 1990 1995 2000 2005 2010

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Portuguese economic crises (GDP growth rate)

4 1983-88 2 1992-97 2002-07 % 2008-2010 0 0 1 2 3 4 5 6 2011-…

-2

-4

-6

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20 3. High frequencies: Business cycle 3.2. The interpretation of cycles

Lucas Jr., Robert E. (1977) “Understanding Business Cycles,” reprinted in Lucas (1981) Studies in Business Cycles Theory , MIT Press p.215-39. Lucas Jr., Robert E. (1980) “Methods and Problems in Business Cycles Theory”, Journal of Money Credit and Banking .

Classic References

Clèment Juglar France, 1819-1905

Joseph A. Schumpeter Austria, 1883-1950 Juglar, C. (1862) Des Crises Commerciales et de leur Retour Périodique en France, en Angleterre et aux États Unis , (Paris) Schumpeter, Joseph, (1939) Business Cycles: A Theorectical, Historical, and Statistical Analysis of the Capitalist Process (McGraw Hill, New York) Executive Master in Macroeconomics and Business João César das Neves Management and Banking

21 Classic Vision of the cycle

3 2 1

0 0 50 100 150 200 250 -1 -2 -3

Types of cycles

«We conclude that there is a theoretically indefinite number of fluctuations present in our material (...) Hence, we decide now to content ourselves, for the rough purpose of this volume, with three classes of cycles, to which we shall refer simply as Kondratieffs, Juglars and Kitchins (...) There is no rational justification that the writer can see for assuming that the integral number of Kitchins in a Juglar or of Juglars in a Kondratieff should always be the same (...) the system should always produce cycles of respectively somewhat less than 60 years , somewhat less than 10 years and somewhat less than 40 months » Schumpeter (1939) op.cit. p.143-4) Executive Master in Macroeconomics and Business João César das Neves Management and Banking

22 Classic References

Arthur Frank Burns Wesley Clair Mitchell U.S.A., 1904-1987 U.S.A., 1874-1948

Burns, A. and W. Mitchell, (1946) Measuring Business Cycles , New York: National Bureau of Economic Research.

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Scientificity of the Stylised Facts 1/2

“Koopmans [ (1947) “Measurement without Theory” ] presents two basic criticisms of Burns and Mitchell’s study. The first is that it provides no systematic discussion of the theorectical reasons for including particular variables over others in their empirical investigation. Before variables can be selected, Koopmans argued, some notion is needed of the theory that generates the economic fluctuations. With this first criticism we completely agree: Theory is crucial in selecting which facts to report.

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23 Scientificity of the Stylised Facts 2/2

“Koopman’s second criticism is that Burns and Mitchell’s study lacks explicit assumptions about the probability distribution of the variables (...) Koopmans repeatedly stresses this need for using a structural system of equations as an organizing principle. Economists, he argues, should first hypothesize that the aggregate time series under consideration are generated by some probability model, which the economists must then estimate and test” Kydland and Prescott (1989) "Business Cycles: real facts and a monetary myth", Federal Reserve Bank of Minneapolis

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Business cycles Theories explaining the phenomenon Models to replicate the facts

24 The epoch—making change in research • The «great depression» is much more than a massive cycle, with severity much beyond the current fluctuations • Its was a major challenge for Economic Theory, which the discipline was unable to cope with. • The result was a change in the general trend of research in business cycle, from the descriptive and interpretative approach of Juglar, Schumpeter and Burns-Mitchell to the new keynesian model, a revolutionary model of the whole economy • The line interrupted was revived only in early 80’s.

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The Holy Grail of macroeconomics

«To understand the Great Depression is the Holy Grail of macroeconomics. Not only did the Depression give birth to macroeconomics as a distinct field of study, but also –to an extent that is not always fully appreciated– the experience of the 1930s continues to influence macroeconomists’ beliefs, policy recommendations, and research agendas. And, practicalities aside, finding and explanation for the worldwide economic collapse of the 1930s remains a fascinating intellectual challenge.» Bernanke, Ben S. (2000) Essays on the Great Depression , Princeton University Press, p.5.

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25 The «Great Depression» Biggest Cyclical (peak to trough) GDP movements 1929-35 Chile -30,0 Poland -20,7 Indonesia -9,3 Canada -29,6 Czechoslovakia -18,2 Australia -9,2

USA -28,5 France -14,7 China -8,7

Peru -25,8 New Zealand -14,6 Switzerland -8,0

Germany -24,5 Argentina -13,7 Belgium -7,9

Venezuela -22,6 Bulgaria -12,7 Holland -7,8

Austria -22,5 Yugoslavia -11,9 Norway -7,8

Mexico -20,8 Hungary -9,4 Japan -7,3

Maddison, Angus (1995) Monitoring the World Economy 1820-1992 , OCDE, Paris., table 3-7

US unemployment 1900-1940

25.00

20.00 average 1930-40 16.4% 15.00

10.00 average 1900-29 5.13% 5.00

0.00 1900 1905 1910 1915 1920 1925 1930 1935 1940

26 Dow-Jones Industrial during the depression and war

400

350

300

250

200

150

100

0 1925 1930 1935 1940 1945

US inflation rate during the depression and war 15

0 Dec-24 Jun-30 Dec-35 Jun-41 -3

-6

-9

-12

27 Suicide rate (per 100,000)

15 USA New York 10

0 1925 1927 1929 1931 1933

Galbraith, J. K. (1955) The Great Crash , Hoghton Mifflin Co, Boston, chap.8

The Great Depression

«In the last few years there has developed something of a new consensus about the sources of the Great Depression. The distinctive claim of this emerging view (…) is that the proximate cause of the world depression was a structurally flawed and poorly managed international gold standard (…) For a variety of reasons, including among others of desire of the Federal Reserve to curb the US stock market boom, monetary policy in several major countries turned contractionary in the late 1920s –a contraction that was transmitted worldwide by the gold standard (…) What was initially a mild deflationary process began to snowball when the banking and currency crisis of 1931 instigated an international “scramble for gold”.» Bernanke, Ben S. (2000) Essays on the Great Depression , Princeton University Press, p.276.

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28 Background: the «gold-standard»

«Price-species mechanism» David Hume (1711-1776)

(1752) « Of the Balance of Trade »

CA deficit ⇒ Au leaves ⇒ M↓⇒ P↓⇒ Comp.↑⇒ Ex↑ ,Im ↓ , Def. ↓

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Background: the «gold-standard»

«Price-species mechanism» David Hume (1711-1776)

(1752) « Of the Balance of Trade »

CA deficit ⇒ Au leaves ⇒ M↓⇒ P↓⇒ Comp.↑⇒ Ex↑ ,Im ↓ , Def. ↓

Pays debt MV=PY e V constant Does not sterilizes «Optimism of elasticities»

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29 The Great War and Depression «In terms of “fundamentals” (…), ultimately, the war itself was the shock that initiated the Depression. The legacy of the war included –besides physical destruction, which was relatively quickly repaired– new political borders drawn apparently without economic rationale; substantial overcapacity in some sectors (such as agriculture and heavy industry) and undercapacity in others, relative to long-term equilibrium; and reparations claims and international war debts that generated fiscal burdens and fiscal uncertainty» Bernanke, Ben S. (2000) Essays on the Great Depression , Princeton University Press p. 73.

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Sources of non-neutrality

Disruptive effect of deflation – bank panics disturbe flows of credit – debt deflation – high real interest rates • monetary contraction depresses output, raising real interest rates • zero limit on nominal interest rates Reduced quality of financial services, primarily credit intermediation Nominal rigidity of wages (puzzle)

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30 Conclusion from the next graphs «First, observe the strong correspondence between gold-standard membership and falling M1 money supplies (a minor exception is Poland, which managed a small growth in nominal M1 between 1932 and 1936). Second, note the sharp declines in M1/Base and Reserves/Gold, reflecting (respectively) the banking crisis and the exchange crises (both of which peaked in 1931). Third (…) the tendency of gold-surplus countries to sterilize (that is, MB/Reserves tends to fall in countries experiencing increases in gold stocks» Bernanke, Ben S. (2000) Essays on the Great Depression , Princeton University Press p. 14.

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Monetary growth in the Great Depression 25

15 France 10 Poland Belgium 5 United kingdom 0 Sw eden 1930 1931 1932 1933 1934 1935 1936 USA -5

-10

-15

Earlier adjusters: United Kingdom and Sweden left the gold standard in 1931, USA in 1933 Late adjusters: Belgium left the gold standard in 1935, France and Poland in 1936

31 Money multiplier (M1/Base) in the Great Depression 4

3.5

3 France

2.5 Poland Belgium 2 United kingdom 1.5 Sw eden

1 USA

0.5

0 1929 1930 1931 1932 1933 1934 1935 1936

Earlier adjusters: United Kingdom and Sweden left the gold standard in 1931, USA in 1933 Late adjusters: Belgium left the gold standard in 1935, France and Poland in 1936

Gold reserves (tons) in the Great Depression 100

60 France Poland 40 Belgium United kingdom 20 Sw eden 0 USA 1929 1930 1931 1932 1933 1934 1935 1936 -20

-40

Earlier adjusters: United Kingdom and Sweden left the gold standard in 1931, USA in 1933 Late adjusters: Belgium left the gold standard in 1935, France and Poland in 1936

32 Sterilization (Base/Reserves) in the Great Depression 8

6 France 5 Poland Belgium 4 United kingdom 3 Sweden 2 USA

0 1929 1931 1933 1935

Earlier adjusters: United Kingdom and Sweden left the gold standard in 1931, USA in 1933 Late adjusters: Belgium left the gold standard in 1935, France and Poland in 1936

Two phases in Great Depression

«A metaphorical summary of the causes of world monetary contraction might be that damage resulted from “self-inflicted wounds” prior to the financial crises of 1931, and “forces beyond our control” between 1931 and 1933» Bernanke, Ben S. (2000) Essays on the Great Depression , Princeton University Press p. 111, cf p.155.

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33 Deposits of failing banks ($ millions)

500 Fall of 450 Creditenstalt, 400 Austria; May,11 1931 350 300 Bank holiday, 250 Black Thursday, March 6-9 October 200 1933 24,1929 150 100 50 0 1929,3 1930,3 1931,3 1932,3 1933,3

US Industrial production index in the Great Depression (1935-39=100)

120 Black Thursday, Fall of 110 October Creditenstalt, 24,1929 Austria; May,11 100 1931

90 Bank holiday, 80 March 6-9 1933 70 60 50 40 1929,3 1930,3 1931,3 1932,3 1933,3

34 Dow Jones Industrial Average

400 Black Thursday, Fall of October 24,1929 Creditenstalt, 350 Austria; May,11 300 1931 250

200 Bank holiday, 150 March 6-9 1933 100

50 0 1929,3 1930,3 1931,3 1932,3 1933,3

Liabilities of failing commercial businesses ($ millions)

120 Black Thursday, Fall of 110 October Creditenstalt, 100 24,1929 Austria; May,11 1931 90 80 70 60 50 40 Bank holiday, March 6-9 30 1933 20 1929,3 1930,3 1931,3 1932,3 1933,3

35 Inflation rate (%)

Bank holiday, 3 March 6-9 1933 1

-11929,3 1930,3 1931,3 1932,3 1933,3

-3 Fall of Creditenstalt, -5 Austria; May,11 -7 1931

-9 Black Thursday, October 24,1929 -11

-13

Keynesian revolution

Lord John Maynard Keynes Cambridge, 1883 - Tilton, 1946

Keynes, J. M. (1919) The Economic Consequences of the Peace Keynes, J. M. (1936) The General Theory of Employment, Interest and MoneyExecutive, Macmillan, Master in CambridgeMacroeconomics University and Business Press João César das Neves Management and Banking

36 The Revolution

CLASSICAL HYPOTESES Rationality of agents Equilibriumx of markets

KEYNESIAN HYPOTHESIS Marginal Propensity to consume: C = f(Y) Marginal Efficiency of capital: I=g(i) Liquidity Preference: L=L(Y,i) Wage Rigidity: w=w*

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Multiplier 1/2

“If the Treasury were to fill old bottles with banknotes, bury them at suitable depths in disused coalmines which are then filled up to the surface with town rubbish, and leave it to private enterprise on well-tried principles of laissez-faire to dig the notes up again (…), there need be no more unemployment and, with the help of the repercussions, the real income of the community, and its capital wealth also, would probably become a good deal greater than it actually is. It would, indeed, be more sensible to build houses and the like; but if there are political and practical difficulties in the way of this, the above would be better than nothing. The analogy between this expedient and the goldmines of the real world is complete. At periods when gold is available at suitable depths experience shows that the real wealth of the world increases rapidly; and when but little of it is so available, our wealthExecutive Mastersuffers in stagnationMacroeconomics or decline. and Business João César das Neves Management and Banking

37 Multiplier 2/2

Thus gold-mines are of the greatest value and importance to civilisation. Just as wars have been the only form of large-scale loan expenditure which statesmen have thought justifiable, so gold-mining is the only pretext for digging holes in the ground which has recommended itself to bankers as sound finance (…) Ancient Egypt was doubly fortunate, and doubtless owed to this its fabled wealth, in that it possessed two activities, namely, pyramid-building as well as the search for the precious metals, the fruits of which, since they could not serve the needs of man by being consumed, did not stale with abundance. The Middle Ages built cathedrals and sang dirges. Two pyramids, two masses for the dead, are twice as good as one; but not so two railways from London to York”. (General Theory 10, VI)

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Neoclassical synthesis

John R. Hicks U.K., 1904-1989 1937 - "Mr Keynes and the Classics: A Suggested Interpretation“

Paul A. Samuelson U.S.A., 1915-2009 1947 - Foundations of Economic Analysis

Franco Modigliani ITALY, 1918-2003 1944 “Liquidity Preference and the Theory of Interest and Money”

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38 “System of Equations” Approach

Jan Tinbergen Tjalling Koopmans Holland, 1903 -1994 Holland, 1910-1984 1949- “The Econometric Approach to 1935- On the Theory of Economic Business Fluctuations”, American Policy , North Holland Economic Review

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“System of Equations” Approach

If there are

• k objective-variables X 1, X 2, X 3, ... X K

• j instruments t 1, t 2, ... tj

• N-k unknown variables X K+1 , X k+2 , ... X N Then the economy may be written in the following way:

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39 f1 (X 1, X 2, ... Xk, X k+1 , X k+2 , ... XN, , t 1, t 2, ... tj) = 0 f2 (X 1, X 2, ... Xk, X k+1 , X k+2 , ... XN, , t 1, t 2, ... tj) = 0 . . fN (X 1, X 2, ... Xk, X k+1 , X k+2 , ... X N, , t 1, t 2, ... tj) = 0

To have a solution, as there are N - k + j unknowns for N equations, N - k + j >= N <=> j >= k If there are less instruments than objectives, the system is impossible

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New Classical Economics

Robert E. Lucas Jr. Yakima, Washington, 1937-

1976 - "Econometric Policy Evaluation: a Critique", Supplementary Series to the Journal of Monetary Economics , n.1 1977 - "Understanding Business Cycles," in Brunner, K. and A. Meltzer (eds.) Stabilization of the Domestic and International Economy , Carnegie-Rochester Conference Series on Public Policy 5: 7-29, Amsterdam, North-Holland.

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

40 Lucas “econometric critique”

A model whose estimation was based in a period where a certain policy was in place can not be used to test other policies ε yt+1 = f(yt,x t, t) y - state variable; x - exogenous factors ε - stochastic shocks as f is unknown, the analyst uses ε ε θ θ f(yt,x t, t) = F(yt,x t, t, t), where are parameters statistically estimated .

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

Lucas “econometric critique”

ε θ The model yt+1 = F(yt,x t, t, t) may be used for forecasting , which includes no theory, just statistics. But the normal use of these models was simulation , * testing several xt to see the results, and picking the x t * which generated the best y t.. This is scientifically inadmissible

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

41 Lucas “econometric critique”

“Invariance of parameters in an economic model is not, of course, a property which can be assured in advance, but it seems reasonable to hope that neither tastes nor technology vary systematically with variations in countercyclical policies. In contrast, agents’ decision rules will in general change with changes in the environment” Lucas, R. (1977) "Understanding Business Cycles,"

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“Our task”

“Our task as I see it (to restate my introduction somewhat more bluntly and operationally) is to write a FORTRAN program that will accept specific economic policy rules as “input” and will generate as “output” statistics describing the operating characteristics of time series we care about, which are predicted to result from these policies.” Lucas, R. (1980) “Methods and Problems in Business Cycle Theory”

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42 Real Business Cycles

Edward Prescott U.S.A., 1940- Finn Kydland Norway, 1943- Kydland, F.and E., Prescott (1982) "Time to Build and Aggregate Fluctuations", Econometrica 50, 6 Long, J. and C. Plosser (1983) "Real Business Cycles", Journal of Political Economy , 91 Executive Master in Macroeconomics and Business João César das Neves Management and Banking

Endogenous fluctuations

Jean-Michel Grandmont Toulouse, France, 1939-

Grandmont, J-M. (1985) "On Endogenous Competitive Business Cycles", Econometrica , 53, 5

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

43 3. High frequencies: Business cycle 3.3. Cycles and shocks

Williamson, Stephen (2010) Macroeconomics , Addison Wesley, Boston USA, 4 th edition, c. 5

Consumption smoothing

Ct+1 Future Consumption

W.(1+r)

W C Present Var W t Consumption

Var C t

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44 Types of shocks

• Technological shocks – Changes in technology (new techniques) – Natural shocks («acts of God», weather and agricultural uncertainties) – Socio-economic shocks (oil shocks, strikes, etc) • Political shocks – Changes in public taxes and expenditures – Changes in money stocks

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

Technological shock Y Effects Rise in Wages Rise in Product Ambiguous Labour

Labor L

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

45 Commodity prices in 2008

Price of oil ( € por barrel) Price of iron

100 120

100 75 80

50 60

40 25

0 0 2005 2006 2007 2008 2009 2005 2005.5 2006 2006.5 2007 2007.5 2008 2008.5 2009

Price of Zinc ( € per Ton) Price of uranium

4000 120 3500 100 3000 2500 80

2000 60 1500 40 1000 500 20 0 0 2005 2006 2007 2008 2009 2005 2005.5 2006 2006.5 2007 2007.5 2008 2008.5 2009

Commodity prices in 2008

Price of rice ( € per Metric Ton) Price of weat ( € per Metric Ton)

700 350 300 600 250 500 200 400 150 300 100

200 50 0 100 2005 2006 2007 2008 2009 0 2005 2006 2007 2008 2009 Price of cocoa ( € por ton) Price of corn ( € per Metric Ton) 2000 200 1900 180 1800 160 1700 140 1600 120 1500 100 1400 80 1300 60 1200 40 20 1100 0 1000 2005 2006 2007 2008 2009 2005 2006 2007 2008 2009

46 Commodity prices in 2008

Price of coffee (€ cent/pound) Price of sugar ( € cent. por libra)

120 29

100 27 25 80 23 60 21 40 19 20 17 0 15 2005 2005.5 2006 2006.5 2007 2007.5 2008 2008.5 2009 2005 2006 2007 2008 2009

Price of bananas ( € por ton) Price of rubber ( € cent. por libra)

1000 120

100 800 80 600 60 400 40

200 20

0 0 2005 2006 2007 2008 2009 2005 2006 2007 2008 2009

Total Employment (persons) Portugal

5500

5000

4500

4000 1000

3500

3000 1970 1975 1980 1985 1990 1995 2000 2005 2010

Executive Master in Macroeconomics and Business João César das Neves Management and Banking Source: OECD

47 Average hours worked per person Portugal

2050

2000

1950

1900

1850

1800

1750

1700

1650 1985 1990 1995 2000 2005 2010

Executive Master in Macroeconomics and Business João César das Neves Management and Banking Source: OECD

Real wage Portugal (1953=100)

350

300

250

200

150

100 1952 1962 1972 1982 1992 2002

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

48 GDP per hours worked Portugal

120.0

110.0

100.0

90.0

80.0

index index 2000=100 70.0

60.0

50.0 1985 1990 1995 2000 2005 2010

Executive Master in Macroeconomics and Business João César das Neves Management and Banking Source: OECD

Government expenditure

C Effects Rise in Product Rise in Labour Fall in Consumption Y 1 Ambiguous Wages

Labor L G1

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

49 Government consumption Portugal, % of GDP

0 1952 1962 1972 1982 1992 2002

Temporary vs permanent shocks

Y1 Y2

C 1 C2 C2

50 Real interest rate %, Portugal

0 1960 1970 1980 1990 2000 2010

-5 %

-10

-15

-20

-25

Executive Master in Macroeconomics and Business João César das Neves Management and Banking

Never as bad as the data

«So we have to be careful that we don’t believe everything we read in the papers. Things are never as bad as the last data that was released, nor are they as good. Likewise, policy should not be revised at every turn, nor rules changed by political whim. Meaning, we should be careful about accepting conventional wisdom as, well, being wise. One of the great disciplines of economics is that it challenges us to question status quo thinking.» (op. cit. p.1)

Executive Master in Macroeconomics and Business João César das Neves Management and Banking