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

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PNFC M4Lx 12m growth rate

%oya

• bank lending weakened in early 2008 and has contracted since

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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

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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.

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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

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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

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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

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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%

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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

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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

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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).

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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

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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

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Actual & Dynamic Fitted Productivity: Construction

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Actual & Dynamic Fitted Productivity: Information and Communication

prod

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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

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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%

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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%

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0%

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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%

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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%

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-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%

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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