1. Who Scared the Rocking Horse?
Andrew G Haldane
Chief Economist
Eton College Keynes Society
2 October 2014
2. Extraordinary Times
UK Euro area US
135
130
125
120
115
110
105
100
95
Real GDP (Index: 2004 = 100)
11%
Source: Thomson Reuters
Simple linear trend used for pre-crisis trends
2
135
130
125
120
115
110
105
100
95
90
Real GDP (Index: 2004 = 100)
11%
2004 2006 2008 2010 2012 2014
135
130
125
120
115
110
105
100
95
90
Real GDP (Index: 2004 = 100)
14%
2004 2006 2008 2010 2012 2014
90
2004 2006 2008 2010 2012 2014
3. 3
Extraordinary Times
Real GDP (Peak = 100)
120
115
110
105
100
95
90
85
1929 crash
1970s recession
1980s recession
1990 recession
2008 recession
0 1 2 3 4 5 6 7
Number of years following onset of recession
August 2014 IR forecast
Source: ONS
5. 18
16
14
12
10
8
6
4
2
0
UK (a)
US (b)
Germany (c)
1730 1790 1850 1910 1970
Per cent
5
Extraordinary Times
Source: GFD
Long-term rates
(a)UK interest rate is the yield on a 2.5% coupon Consol
(b)US interest rate is the constant maturity yield on a 10-year Treasury bond
(c)German interest rate is the yield on a 10-year German government bond
6. 30
25
20
15
10
5
0
1821 1861 1901 1941 1981
Per cent of GDP
6
Extraordinary Times
Bank of England balance sheet
7. 50
45
40
35
30
25
20
15
10
7
Extraordinary Times
5
0
Central Bank balance sheets
BoE
Federal Reserve
ECB
Bank of Japan
Per cent of GDP
1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011
8. 8
“If you hit a rocking horse with a stick, the movement of the horse
will be very different from the stick. The hits are the cause of the
movement, but the system’s own equilibrium laws condition the
form of movement”
Knut Wicksell (1918)
The Rocking Horse
9. Normal?
9
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
-5 -4 -3 -2 -1 0 1 2 3 4 5 0
No of heads No of tails
10. Abnormal?
10
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
-5 -4 -3 -2 -1 0 1 2 3 4 5 0
No of heads No of tails
16. Flash Crash, May 2010
11,000
10,800
10,600
10,400
10,200
10,000
9,800
14:20 14:30 14:40 14:50 15:00 15:10
Time
Index
Dow Jones Industrial Average
16
19. 19
Mapping the financial web
(a) A food web of predator-prey interactions between species in a freshwater lake
(b) The network of collaborations between scientists at a private research institution
(c) A network of sexual contact between individuals in the study
21. 21
Implications for Economics and Economic Policy
• There has never been a better time to be studying it!
• Crossing the disciplines – economics, physics, sociology, anthropology etc
• Mapping the network – economic, financial, social
• Communicating about policy –Twitter-driven crises
• Making policy “robust” – dogs and frisbees
22. 23
Connectivity
Notes: Superconnected companies are red, very connected companies are yellow. The size of the dot represents revenue.
Source: Vitali, S, Glattfelder, J and Battiston, S. (2011) “The network of global corporate control”.