[PPT] - Implications The 2018 Peston Lecture Silvana Tenreyro Monetary PowerPoint Presentation

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The 2018 Peston Lecture The Fall in Productivity Growth: Causes and Implications

Silvana Tenreyro Monetary Policy Committee, Bank of England 15 January 2018

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Preview of main points

Finance and manufacturing account for most of the fall in UK

productivity growth.

Post-crisis drag from finance should disappear as deleveraging

ends.

Slower manufacturing productivity growth may relate to a

reduced impact of cheap imported inputs from emerging markets.

Weak investment has been increasingly important for

manufacturing and aggregate productivity.

2018 Peston Lecture, Queen Mary, University of London

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Productivity growth has fallen

2018 Peston Lecture, Queen Mary, University of London

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4
3
2
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1 2 3 4 5 2000 2002 2004 2006 2008 2010 2012 2014 2016 Crisis Productivity (GDP per hour worked) Percentage change

n a year earlier

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Productivity fell below trend

2018 Peston Lecture, Queen Mary, University of London

100 120 140 160 180 200 220 240

99.9999

1977 1982 1987 1992 1997 2002 2007 2012

Productivity (GDP per hour worked) 1977-2007 trend 2009-16 trend

Log scale, 1977=100

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Historical productivity growth

2018 Peston Lecture, Queen Mary, University of London

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1 2 3 4 5 1770 1790 1810 1830 1850 1870 1890 1910 1930 1950 1970 1990 2010 Annual growth, 10 year moving average

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International productivity comparisons

2018 Peston Lecture, Queen Mary, University of London

7 Current price GDP per hour worked, 2016

20
10

10 20 30 40

Percentage difference from UK G7 average (excluding UK) Constant price GDP per hour worked, average annual growth rates, 2007-16

0.2

0.0 0.2 0.4 0.6 0.8 1.0 1.2 Per cent

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Why we care about productivity

It matters for welfare: consumption, leisure

2018 Peston Lecture, Queen Mary, University of London

8 20 40 60 80 50 200 800 3200 1831 1851 1871 1891 1911 1931 1951 1971 1991 2011

Productivity (GDP per hour worked, RHS) Real GDP per person (RHS) Consumption per person (RHS) Leisure (LHS)

Weekly hours not in work (out of 84) Log scale, Index 1831=100

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Why we care about productivity

It matters for welfare: real wages

2018 Peston Lecture, Queen Mary, University of London

9 50 100 200 400 800 1600 3200 1762 1787 1812 1837 1862 1887 1912 1937 1962 1987 2012 Log scale, Index 1762=100

Productivity (GDP per hour worked) Real wages

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Why we care about productivity: It matters for monetary policy

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95 100 105 110 115 120 125 4 8 12 16 20 24 28 32 36 Quarter Index: Quarter 0=100 1.6 1.8 2 2.2 2.4 4 8 12 16 20 24 28 32 36 Quarter Percentage change

n a year earlier
0.5
0.3
0.1

0.1 0.3 0.5 4 8 12 16 20 24 28 32 36 Quarter Per cent

0.5
0.3
0.1

0.1 0.3 0.5 4 8 12 16 20 24 28 32 36 Quarter Percentage points Baseline High productivity (no policy response) High productivity (optimal policy) Low productivity (no policy response) Low productivity (optimal policy)

Output gap Bank Rate Annual inflation Productivity

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Sector Pre-crisis (2000-07) average, pp Crisis (2007-09) average, pp Post-crisis (2009-15) average, pp Change in contribution, pp (% of total)

f which, change in capital

deepening contribution, pp

f which, change in labour quality

contribution, pp

f which, change in TFP

contribution, pp

f which labour

reallocation/other, pp Share of Sector in nominal GVA, 2007, % Actual change in quantity productivity growth, pp Actual change in revenue productivity growth, pp A: Agriculture, forestry and fishing 0.0

0.1

0.1 0.0 (-2) 0.0 0.0 0.0 0.0 1 3.2 6.2 B: Mining and quarrying

0.1
0.2
0.1

0.0 (1)

0.2

0.0 0.0 0.2 3

6.2
13.5

C: Manufacturing 0.5

0.1

0.1

0.5

(31)

0.1

0.0

0.3

0.0 12

3.5

1.3 D: Electricity, gas, steam and air conditioning 0.0 0.0 0.0

0.1

(4) 0.0 0.0

0.1

0.0 1

4.9
0.8

E: Water supply, sewerage and waste 0.0 0.0 0.0 0.0 (1) 0.0 0.0 0.0 0.0 1

2.1
6.1

F: Construction 0.0

0.3

0.2 0.1 (-10)

0.1

0.0 0.2 0.0 8 1.8 0.6 G: Wholesale and retail trade; repair of vehicles 0.4

0.4

0.3

0.2

(12)

0.1

0.0

0.1

0.0 13

1.1
1.0

H: Transportation and storage 0.1

0.3

0.1 0.0 (3) 0.0 0.0 0.0 0.0 5

0.7

2.6 I: Accomodation and food service 0.0 0.0 0.0 0.0 (3) 0.0 0.0 0.0 0.0 3

1.3

2.1 J: Information and communication (ICT) 0.3 0.1 0.1

0.2

(13)

0.1

0.0

0.1

0.0 7

3.0
1.0

K: Financial and insurance 0.4 0.2

0.3
0.6

(43)

0.1

0.0

0.5
0.1

9

7.1
11.7

L: Real estate (excluded) M: Professional, scientific and technical 0.3

0.1

0.1

0.2

(14)

0.1

0.0

0.1

0.0 8

2.7
1.2

N: Administrative and support service 0.0

0.1

0.2 0.1 (-8)

0.1

0.0 0.2 0.0 5 2.4 0.0 O: Public administration and defence 0.0 0.1 0.0 0.0 (0) 0.0 0.0 0.0 0.0 6 0.3 0.6 P: Education

0.1
0.2
0.1

0.0 (-2) 0.0 0.0 0.0 0.0 7 0.7

3.3

Q: Human health and social work 0.1

0.1

0.0 0.0 (1) 0.0 0.0 0.0 0.0 8

0.4
3.1

R: Arts, entertainment and recreation 0.0 0.0 0.0 0.0 (1)

0.1

0.0 0.0 0.0 2

1.0
0.1

S: Other service activities 0.0 0.0 0.0 0.0 (-3) 0.0 0.0 0.1 0.0 2 1.7 0.1 Total 2.0

1.6

0.4

1.5

(100)

1.0

0.1

0.8

0.2 100 Manufacturing, finance, prof. and ICT only 1.5 0.0

0.1
1.5

(103)

0.4

0.0

1.1
0.1

36 Other sectors 0.5

1.7

0.5 0.0 (-3)

0.6

0.1 0.2 0.3 64

Full growth accounting decomposition

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Sectoral decomposition of productivity growth

Slowdown: difference between pre and post crisis periods

2018 Peston Lecture, Queen Mary, University of London

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2
1

1 2 1995-2000 2000-07 2007-09 2009-15 Difference (09-15 minus 00-07) Percentage points

ICT

Prof. & scientific

Finance Manufacturing Other Total

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Decomposition of manufacturing productivity growth

Slowdown: difference between pre and post crisis periods

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4
3
2
1

1 2 3 4 5 2000-07 2007-09 2009-15 Difference (09-15 minus 00-07)

TFP Labour quality Capital services Total

Percentage points

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Measurement of value added

Statistical offices aim at capturing:

𝑟𝑢 − 𝑞 × 𝑛𝑢

𝑛

In practice, they deflate nominal value added,

𝑞 × 𝑟𝑢

𝑢 𝑧

− 𝑞 × 𝑛𝑢

𝑢 𝑛

, And obtain:

SD:

1

π

𝑢→0 𝑧 (𝑞 × 𝑟𝑢

𝑢 𝑧

− 𝑞 × 𝑛𝑢

𝑢 𝑛

) DD:

1 π

𝑢→0 𝑧 𝑞 × 𝑟𝑢

𝑢 𝑧

−

1 π

𝑢→0 𝑛 𝑞 × 𝑛𝑢

𝑢 𝑛

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Decomposition of finance productivity growth

Slowdown: difference between pre and post crisis periods

2018 Peston Lecture, Queen Mary, University of London

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8
6
4
2

2 4 6 2000-07 2007-09 2009-15 Difference (09-15 minus 00-07)

TFP Labour quality Capital services Total

Percentage points

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Slowdown: factor decomposition

2018 Peston Lecture, Queen Mary, University of London

16 Factor Pre-crisis (2000-07) Crisis (2007-09) Post-crisis (2009-15) Post-crisis difference (% of total)

TFP 0.6%

3.3%
0.2%
0.8%

(54%) Capital services 1.1% 1.0% 0.1%

1.0%

(66%) Labour services 0.4% 0.6% 0.5% 0.1% (-7%) Labour reallocation

0.2%

0.0% 0.0% 0.2% (-13%) Other 0.1% 0.1% 0.1% 0.0% (0%) Total 2.0%

1.6%

0.4%

1.5%

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Slowdown: international comparison

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3
2
1

1 2 3 4 5 6 7 00- 07 07- 09 09- 16 00- 07 07- 09 09- 16 00- 07 07- 09 09- 16 00- 07 07- 09 09- 16 00- 07 07- 09 09- 16 World EMEs EA US UK

TFP Capital Labour productivity

Percentage points

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Take away

Manufacturing and finance account for most of the UK productivity slowdown.
The Finance boom and bust can be traced to the pre-crisis growth in leverage

and the subsequent deleveraging post-crisis.

– As deleveraging runs its course, finance should stop detracting from average productivity.

Pre-crisis productivity growth in manufacturing may be related to offshoring and

rapidly falling prices of imported inputs.

– Going forward, global growth momentum should give a boost to UK manufacturing.

In aggregate weak investment has been the main drag on labour productivity

growth.

– As uncertainty is removed, investment could help recover lost ground.

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