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The Impact of the Financial Crisis on UK Company Performance
Rebecca Riley*, Chiara Rosazza Bondibene* and Garry Young**
*National Institute of Economic and Social Research & Centre for Macroeconomics**Bank of England & Centre for Macroeconomics
14 November 2013
Presentation at University of Glasgow Economics Seminar
Acknowledgements: The financial support of the Economic and Social Research Council grant reference ES/K00378X/1 is gratefully acknowledged.
Disclaimers: This work contains statistical data which is Crown Copyright; it has been made available by the Office for National Statistics (ONS) through the Secure Data Service (SDS) and has been used by permission. Neither the ONS nor SDS bear any responsibility for the analysis or interpretation of the data reported here. This work uses research datasets which may not exactly reproduce National Statistics aggregates.
Any views expressed cannot be taken to represent those of the Bank of England or to state Bank of England policy.
Preliminary results.
Disclaimer
The views expressed in this presentation are my own and not
necessarily those of the Bank of England
CCBS –Structure of Financial markets
• What has been the impact of the banking sector crisis on bank credit conditions experienced by UK companies?
• What is the evidence that this has affected the performance of UK companies?
Outline
Bank lending to PNFCs
2004 2006 2008 2010 2012-10
-5
0
5
10
15
20
PNFC M4Lx 12m growth rate
%oya
• bank lending weakened in early 2008 and has contracted since
5
Identification:intuition for credit supply shock
M4L
spread
CD
CS
CS
M
S
• credit supply shock is the dominant cause of weak lending growth
A timeline of the banking sector crisis
CDS premia of B6 banks
Perceived riskiness of bank debt shifted from middle of 2007
Jan 07 Jan 09 Jan 11 Jan 130
50
100
150
200
250
300
350
400
450
Barclays LBG RBS Nationwide Santander UK HSBC
bps
Run on Northern Rock
Lehman Brothers file for bankruptcy First Greek bailout
Mario Draghi speech
Recapitalisation of LBG & RBS
LTRO announcement bpsSpecial Liquidity Scheme
FLS announcement
5- year CDS premia for banks and PNFCs
(a) The latest observation for new bank loans is 2010 Q2, and the latest observations are 2010 Q1 for the other series.(b) The recession is defined as two consecutive quarters of falling output.(c) Sterling and foreign currency loans to PNFCs.(d) Calculated as a residual.
7
0
50
100
150
200
250
06 07 08 09 10
B6 average
BAE
BT
Diageo
Tesco
GlaxoSmithKline
Markets perceived some large companies as less risky than banks
Corporate credit availability reported by lenders in the Credit Conditions Survey
2007 2008 2009 2010 2011 2012 2013-250
-200
-150
-100
-50
0
50
-25
-5
15
35
55
75
95
115
135
Overall corporates (LHS)
Small businesses (RHS)
Medium businesses (RHS)
Large businesses (RHS)
Cumulated net percentage balances
According to lenders, availability of corporate credit fell sharply from mid-2007 before improving from early 2009.
Cost and availability of credit in the Deloitte CFO survey and the FSB survey
Q12007
Q2 Q3 Q4 Q12008
Q2 Q3 Q4 Q12009
Q2 Q3 Q4 Q12010
Q2 Q3 Q4 Q12011
Q2 Q3 Q4 Q12012
Q2 Q3 Q4 Q12013
Q2 Q3-100
-75
-50
-25
0
25
50
75
100
Credit is easily available (large PNFCs)
Credit is costly (large PNFCs)
Credit is easily available (SMEs)
Credit is costly (SMEs)
Net percentage balance of respondents in agreement
Large companies reported similar tightening then loosening of credit conditions. SMEs continue to report tight credit conditions.
PNFCs’ financial transactions(a)
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41-50
-40
-30
-20
-10
0
10
20
30
40
Recession(b)
Financial balance
New bank loans(c)
Other finance raised(d)
£ billions
(a) The latest observation for new bank loans is 2010 Q2, and the latest observations are 2010 Q1 for the other series.(b) The recession is defined as two consecutive quarters of falling output.(c) Sterling and foreign currency loans to PNFCs.(d) Calculated as a residual.
Large companies substituted finance from capital markets for bank loans.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2010 2012 2010 2012
Accepted Accepted after issues
Rejected, but found other funding Rejected
Existing-client applicants First-time applicants
SMEs with existing borrowing facilities find it easier to access new finance
By date of application
Outcome of applications for overdrafts and loans
Source: SME Finance Monitor
-100
0
100
200
300
400
500
600
2007 2008 2009 2010 2011 2012 2013
BBB corporate bond spread over 5y OIS
PNFC effective new lending spread over 3m OIS
Change since 2007 Q3(basis points)
Estimates of cost of credit for companies
Effective rates data likely to underestimate marginal cost of credit
Spreads over risk-free rates
Cost of credit edging lowerLoan rates offered to small businesses
0
5
10
15
20
25
30
35
0% - 3.99% 4% - 4.99% 5% - 5.99% 6% - 7.99% 8% - 10.99% 11% or more
2012 Q2 2013 Q2 2013 Q3
Percentages of respondents
Majority of SMEs who can borrow do so at rates of less than 5%.
• What has been the impact of the banking sector crisis on bank credit conditions experienced by UK companies?
• What is the evidence that this has affected the performance of UK companies?
Outline
Output per head has surprisingly stagnated after falling in the recession....
Notes: We exclude the following sectors: Agriculture, forestry and fishing (A), Mining and quarrying (B), Financial and insurance activities (K), Public administration and defence, compulsory social security (O), Education (P), Human health and social work activities (Q), Activities of extraterritorial organisations and bodies (U). Chart shows implied productivity from simple dynamic relationship between employment and output (dynpfit) and employment, output and net capital stock (dynpfit2).
0
2
4
6
8
10
12
Jun-
97
No
v-97
Ap
r-98
Sep-
98
Feb-
99
Jul-9
9
De
c-99
May
-00
Oct
-00
Mar
-01
Au
g-01
Jan-
02
Jun-
02
No
v-02
Ap
r-03
Sep-
03
Feb-
04
Jul-0
4
De
c-04
May
-05
Oct
-05
Mar
-06
Au
g-06
Jan-
07
Jun-
07
No
v-07
Ap
r-08
Sep-
08
Feb-
09
Jul-0
9
De
c-09
May
-10
Oct
-10
Mar
-11
Au
g-11
Jan-
12
Jun-
12
No
v-12
Ap
r-13
Actual & Dynamic Fitted Productivity: Main Sectors
prod
dynpfit
dynpfit2
actual
fitted
Initial decline In line with normal adjustment
... as employment has been strongerthan expected given output
Notes: We exclude the following sectors: Agriculture, forestry and fishing (A), Mining and quarrying (B), Financial and insurance activities (K), Public administration and defence, compulsory social security (O), Education (P), Human health and social work activities (Q), Activities of extraterritorial organisations and bodies (U). Chart shows fitted values from simple dynamic relationship between employment and output (dynpfit) and employment, output and net capital stock (dynpfit2).
actual
fitted
16500
17000
17500
18000
18500
19000
19500
20000
20500
21000
Mar
-97
Au
g-97
Jan-
98
Jun-
98
No
v-98
Ap
r-99
Sep-
99
Feb-
00
Jul-0
0
De
c-00
May
-01
Oct
-01
Mar
-02
Au
g-02
Jan-
03
Jun-
03
No
v-03
Ap
r-04
Sep-
04
Feb-
05
Jul-0
5
De
c-05
May
-06
Oct
-06
Mar
-07
Au
g-07
Jan-
08
Jun-
08
No
v-08
Ap
r-09
Sep-
09
Feb-
10
Jul-1
0
De
c-10
May
-11
Oct
-11
Mar
-12
Au
g-12
Jan-
13
Jun-
13
Actual & Dynamic Fitted Employment: Main Sectors
employment
dynefit
dynefit2
actual
fitted
Not compatible withlabour hoarding
Higher funding costs for impaired banks, leading to:
a) credit crunch: higher shadow cost of credit for given risk for new loansDirect impact:
• More costly for companies reliant on bank finance to finance working capital and investment• Productivity of constrained firms reduced relative to counterfactual, including for new
entrants
Indirect impact:• Some increase in market share of unconstrained companies, including delaying exit of
unconstrained dying companies.
b) forbearance: lower shadow cost of credit for given risk for existing loans• Capital constrained banks refrain from enforcing contracts so as not to crystallise losses on
their own balance sheets • Weak companies do not exit, also taking market share away from stronger ones.
Why banking sector impairment might impact adversely on productivity
But productivity weakness has not been most apparent in more bank-dependent industries
Bank Dependence:Gross loan to output ratio Productivity Growth in five years before
and after 2008q1Productivity shortfall
At 2013q2
Industry At 2008q1
Latest Pre-crisisPost-crisis
Swing
Accomodation and Food 0.71 0.6 11.9 -7.1 19.0 7.8
Construction (0.53) 0.5 -3.2 -2.3 -0.9 -4.5
Wholesale and Retail 0.35 0.25 13.2 1.1 12.1 3.9
Transport and Storage (0.32) 0.24 6.9 -21.7 28.7
Manufacturing 0.40 0.24 25.6 0.2 25.4 25.8
Administration and Support (0.27) 0.26 15.5 3.7 11.8 -5.5
Arts and Entertainment 0.61 0.29 9.6 -4.7 14.3 2.9
Professional and Scientific (0.23) 0.16 25.7 -11.0 36.7 -2.3Information and
communication (0.13) 0.13 28.6 1.0 27.6 35.5
Main Sectors 13.5 -5.5 19.0 8.8
Notes: Figures in parentheses show loan to output ratio in 2011q1 when earlier figures are unavailable. Productivity shortfall is percentage difference between actual productivity and predicted value based on pre-crisis dynamic relationship between employment and output.
More bank dependent
Productivity has stagnated irrespective of prior growth rate
– Productivity stronger than simple model in bank-dependent construction and weaker than simple model in bank-independent information and communication sector
0
5
10
15
20
25
30
Jun-
97
Jul-9
8
Aug
-99
Sep-
00
Oct
-01
Nov
-02
Dec
-03
Jan-
05
Feb-
06
Mar
-07
Apr
-08
May
-09
Jun-
10
Jul-1
1
Aug
-12
Actual & Dynamic Fitted Productivity: Construction
prod
dynpfit
dynpfit2
0
5
10
15
20
25
30
Jun-
97
Apr-
98
Feb-
99
Dec
-99
Oct
-00
Aug-
01
Jun-
02
Apr-
03
Feb-
04
Dec
-04
Oct
-05
Aug-
06
Jun-
07
Apr-
08
Feb-
09
Dec
-09
Oct
-10
Aug-
11
Jun-
12
Apr-
13
Actual & Dynamic Fitted Productivity: Information and Communication
prod
dynpfit
dynpfit2
Productivity has stagnated irrespective of prior growth rate
Higher funding costs for impaired banks, leading to:
a) credit crunch: higher shadow cost of credit for given risk for new loansDirect impact:
• More costly for companies reliant on bank finance to finance working capital and investment, but impaired banks restructure ailing companies raising their productivity
• Productivity of constrained firms reduced relative to counterfactual, including for new entrants absence of credit may act more to stop growth than slow it down
Indirect impact: unconstrained companies may have higher average productivity • Some increase in market share of unconstrained companies, including delaying exit of
unconstrained dying companies, but impaired banks force exit of ailing companies
b) forbearance: lower shadow cost of credit for given risk for existing loans• Capital constrained banks refrain from enforcing contracts so as not to crystallise losses on
their own balance sheets • Weak companies do not exit, also taking market share away from stronger ones.• Low interest rates and other consequences of impaired banking sector spill over to other
industries encouraging survival of weak companies
Why banking sector impairment might impact adversely on productivity
not obviously
Firm-level analysis throws light on these issues ARD dataset to 2011, micro-data based on a register of businesses:• data for manufacturing available back to 1974, total economy data (i.e.
including services) available from 1997• possible to measure entry and exit for the population of firms• but financial information only available for a subsample with a rotating
sample strategy (i.e. micro firms not included in consecutive years)• we therefore identify surviving firms wrongly classified as entry and exit
and exclude them• our firm level sample is weighted to be ‘nationally’ representative,
(weights = ratio of population to sample employment within a size, industry , survivor status and year cell)
• we exclude sectors not fully covered in the ARD and sectors where inputs are thought not to be directly comparable to measured outputs
• focus on GVA per employee.
DATA DESCRIPTION: Sample information
ARD sample sizes for decomposition analysis, by size of enterprise and survivor/exit status
Enterprise size (numbers employed)
Employment No. of enterprises
no. % of population no. % of population
Micro 0-9 exit 9132 0.78 4106 0.77
continuer 227 0.01 60 0.01
Small 10-49 exit 37601 6.40 1735 5.44
continuer 20148 0.99 746 0.71
Medium 50-249 exit 112468 25.65 1036 23.19
continuer 222600 12.30 1770 9.73
Large 250+ exit 588241 68.77 550 61.41
continuer 4568633 69.52 2674 62.86
Source: ARD and authors' calculations Notes: Average 2004-7; survivor/exit status evaluated over 4 years; a number of industries are excluded (see notes
above).
Entry and exit rates over four year periods
Source: Authors' own calculations using the ARD. Entry rate is share of employees in enterprises that did not exist four years earlier. Exit rate is share of employees in enterprises that do not exist in four years time.
0
0.05
0.1
0.15
0.2
0.25
0.3
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Exit rate (excl. micro firms) Exit rate Entry rate (excl. micro firms) Entry rate
DATA DESCRIPTION: Productivity in sampleGVA per head (£1000, 2008 prices)
survivor to t+4 exit survivor from t-4 entry
1998 35.7 28.9
1999 36.3 30.0
2000 36.7 30.8
2001 36.5 32.1
2002 37.1 32.6 36.1 38.0
2003 37.1 31.6 36.3 36.7
2004 39.8 32.3 39.0 37.1
2005 40.3 31.0 39.3 35.5
2006 40.6 34.2 40.2 36.6
2007 43.4 34.8 42.8 38.3
2008 43.5 40.3
2009 40.2 36.5
2010 42.6 36.8
2011 42.5 36.0
Survivors typically have higher productivity than new entrants and exitors
Decomposition of aggregate productivity growthWe use a sample-weighted version of new decomposition of GVA per head (Π):
Four components of aggregate productivity growth, the first two relevant for continuing firms (C):
1) Within -> positive if improvement in productivity is occurring within continuing firms
2) Reallocation -> positive if productivity of continuing firms in period 2 is higher among firms whose share of continuing firms has
grown (negative if fast growing firms are catching up).
3) Entry -> positive if entrants (N) have higher productivity than continuers at the time when entry takes place
4) Exit -> positive if firms that exit the market have lower productivity than continuers at the time when exit (X) takes place
Xi ciiNi cii
Ci cic
i
c
iCi ii
c
i
ss
s
s
s
s
s
s
)ln(ln)ln(ln
)ln)(ln()ln(lnln
111222
221
1
2
212
1
1
Decomposition of aggregate productivity growth
Proportionate changes (weighted change in log productivity) Decomposition of 4 year change in labour productivity
2003 2004 2005 2006 2007 2008 2009 2010 2011 Change in labour productivity
0.071 0.071 0.022 0.059 0.058 -0.021 -0.089 -0.076 -0.053
Survivors (within)
0.068 0.088 0.061 0.049 0.071 -0.068 -0.119 -0.062 -0.072 Survivors (between)
-0.067 -0.093 -0.087 -0.034 -0.053 0.007 -0.025 -0.059 -0.017
Entrants
-0.022 -0.024 -0.030 -0.035 -0.042 -0.055 -0.052 -0.047 -0.055 Exits
0.092 0.101 0.077 0.079 0.082 0.094 0.108 0.093 0.092
Employment share survivors (time t-4)
0.749 0.767 0.777 0.773 0.794 0.813 0.808 0.822 0.832 Employment share survivors (time t)
0.847 0.858 0.889 0.884 0.883 0.878 0.887 0.892 0.891
Employment share entrants
0.153 0.142 0.111 0.116 0.117 0.122 0.113 0.108 0.109 Employment share exits
0.251 0.233 0.223 0.227 0.206 0.187 0.192 0.178 0.168
Sample size survivors
6491 6603 7334 6142 6857 5573 5239 4314 4830 Sample size entrants
6576 6150 4259 3751 4268 3681 3191 3083 3159
Sample size exits
6205 5974 6338 5992 5704 5258 4851 3887 4308
Source: ARD and authors’ calculations
Notes: Excluded industries are Agriculture, Forestry & Fishing, Mining & Quarrying, Utilities, Financial & Insurance Activities, Real Estate Activities, Public Administration & Defence, Education, Human Health & Social Work Activities, Activities of Private Households & Extra-Territorial Organisations.
Decomposition of growth over overlapping four-year periods
Source: Authors' own calculations using the ARD. Chart shows productivity growth and decomposition in the four years to the year shown.
Components of UK labour productivity change over distinct four year periods
Source: Authors' own calculations using the ARD. Chart shows productivity growth and decomposition in the four years to the year shown.
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
2003 2007 2011 Swing
Exit
Entry
Reallocation
Within
Total
• Decline in ‘within’ component partly offset by more growth in higher productivity firms
Components of UK labour productivity change over distinct four year periods
Source: Authors' own calculations using the ARD. Chart shows productivity growth and decomposition in the four years to the year shown.
-20%
-15%
-10%
-5%
0%
5%
10%
15%
2003 2007 2011 Change
Exit
Entry
Survivors
Total
Swing in productivity growth is accounted for by lower productivity growth within continuers
Components of UK labour productivity change over distinct four year periods
Source: Authors' own calculations using the ARD. Chart shows productivity growth and decomposition in the four years to the year shown.
• Decline in ‘within’ component partly offset by more growth in higher productivity firms
Components of UK labour productivity change for Small firms
Source: Authors' own calculations using the ARD. Chart shows productivity growth and decomposition in the four years to the year shown (averages 2004-7 and 2008-2011).
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
2007 2011 Swing
Exit
Entry
Reallocation
Within
Total
• Entry component makes a more negative contribution for small firms.
Swing in labour productivity change by firm size
Source: Authors' own calculations using the ARD. Chart shows swing in productivity growth by firm size.
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
Small Medium Large
Exit
Entry
Reallocation
Within
Total
Percentage points
• Within component more significant for small firms, consistent with impact of indivisibilities
Swing in labour productivity change by industry
Source: Authors' own calculations using the ARD. Chart shows swing in productivity growth by broad industry sector
Percentage points
• Within component similar in different industries, but larger offsets in services & construction
Alternative decompositions of swing in labour productivity change
Source: Authors' own calculations using the ARD.
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
Mixture MP FHK BBH
Exit
Entry
Reallocation
Within
Total
Percentage points
• FHK and BBH exaggerate reduction in contributions from entry and exit. MP exaggerates reduction in within component as it overweights small firms.
Decomposition of growth over one-year periods
Source: Authors' own calculations using the ARD.
-15%
-10%
-5%
0%
5%
10%
15%
2003 2004 2005 2006 2007 2008 2009 2010 2011
Within Reallocation Entry Exit Total
• Changes in productivity growth driven by within component on one-year comparison.
Distribution of change in log productivity among survivors
Source: Authors' own calculations using the ARD. Data are employment population weighted.
• What accounts for shifts in productivity growth within firms?
Examine the potential for credit constraints to influence firms’ behaviour
Compare more and less credit constrained firms:• We observe companies’ gearing ratios, short term bank overdrafts
and loans, name of bank and indicators of financial performance• This analysis relies primarily on the FAME data
Use a company’s banker to identify whether the company is likely to have been credit constrained in the recession:
• Companies that borrowed from banks that became severely distressed in the crisis are more likely to have been credit constrained
• It is difficult to switch banks in a banking crisis
Preliminary analysis: Differences in company outcomes by advisor
Median changes in outcomes for surviving companies (over 4 year periods)
Change in log GVA proxy Turnover Short term Short term Gearingper head per head loans loans per head
2003/4 to 2007/8 Distressed Bank 0.064 0.067 0.198 0.183 -0.119Other Bank 0.062 0.059 0.146 0.139 -0.119
No Bank 0.075 0.059 0.147 0.077 -0.373
2007/8 to 2011/12 Distressed Bank -0.052 -0.040 0.069 0.102 -0.186Other Bank -0.030 -0.017 0.059 0.099 -0.149
No Bank -0.028 -0.024 0.082 0.068 -0.338
Swing Distressed Bank -0.116 -0.107 -0.128 -0.080 -0.068Other Bank -0.092 -0.076 -0.087 -0.040 -0.030
No Bank -0.103 -0.083 -0.065 -0.010 0.036
Relative Swing Distressed Bank versus Other Bank -0.023 -0.031 -0.042 -0.040 -0.038
No Bank -0.012 -0.024 -0.063 -0.071 -0.103
Notes: 31-35 thousand company-time observations; active companies in FAME that report turnover, employment and loans.
• Fall in growth is largest for those with a distressed banker (RBS and LBG). But significant falls for other groups too.
Preliminary analysis:Regression analysis of company outcomes by advisor
Regression estimates of the relative swing (base category = companies with no recorded banker)
GVA proxy Turnover Short term Short term Gearingper head per head loans loans per head
Recession period -0.115*** -0.088*** -0.081** -0.008 0.036(0.011) (0.009) (0.035) (0.036) (0.043)
Other Bank -0.009 -0.001 -0.001 0.042 0.258***(0.009) (0.007) (0.029) (0.030) (0.035)
Distressed Bank -0.003 0.011 0.052* 0.090*** 0.266***(0.009) (0.007) (0.029) (0.030) (0.035)
Other Bank*Recession period 0.013 0.006 -0.012 -0.017 -0.057(0.013) (0.010) (0.041) (0.042) (0.050)
Distressed Bank*Recession period -0.016 -0.025** -0.050 -0.067 -0.081(0.013) (0.010) (0.042) (0.043) (0.050)
Observations 31,497 34,911 34,911 34,911 27,865R-squared 0.048 0.059 0.005 0.003 0.008
Notes: active companies in FAME that report turnover, employment and loans.
Robust regression including 2-digit SIC07 dummies. Std errs in parentheses.
• Main driver of swing in productivity growth is recession period. Having a distressed banker affects turnover per head and balance sheet, but impact on GVA per head is not significant.
Preliminary analysis: Differences in company outcomes by chargeholder
• Fall in growth is largest for those with a distressed banker (RBS and LBG). But significant falls for other groups too.
Preliminary analysis:Regression analysis of company outcomes by chargeholder
• Main driver of swing in productivity growth is recession period. Having a distressed banker affects balance sheet, but impact on GVA per head is not significant.
EMERGING CONCLUSIONS• The reduction in UK labour productivity between 2007 and 2011
was first and foremost the result of a broad-based decline in productivity within companies
• The contribution to aggregate productivity growth from external restructuring did not fall during recession
• We can discern some possible direct impact of tightness of bank lending on– reduced contribution of entering firms to productivity change, especially for
small firms – reduced productivity growth of companies with distressed banker
• But these results suggest that other factors – eg demand weakness, uncertainty, wider forbearance - likely to be more important in explaining weakness of productivity growth