Do entrepreneurs really learn?Evidence from Bank data

Julian Frankish, BarclaysRichard Roberts, BarclaysDavid J Storey, Warwick Business School

Do Entrepreneurs really learn - or do they just tell you that they do?

Julian Frankish, Richard Roberts and David Storey

Mark Casson, “The Entrepreneur”

“Jack Brash starts with very little information. But information is generated continuously as a by-product of his trading activity, and Jack uses this information to the full. He learns from the deals that he makes, and he learns from the deals that fall through. By analysing his experience he is able to turn adversity to advantage”, page 386-7.

Key Questions

Do entrepreneurs “improve” with time?Do those with prior business experience do better?Is there evidence that they run their businesses more effectively the longer they have been trading?

The case for EL

Highly successful entrepreneurs have often failed in business previously.Entrepreneurship is about judgement which improves with experience.It is self evident that individuals learn.Entrepreneurs say they have learnt.

The case against EL

Entrepreneurial outcomes are strongly influenced by chance – you can’t “learn” to play the lottery!Entrepreneurs are optimists.You can’t learn if circumstances are always different - parenting!Evidence is always based on asking respondents, not on observing performance change.

Assumptions

It is not possible to directly measure entrepreneurial talent .Therefore, we require a proxy. Ours is new firm survival.

We assume those with lower have: Businesses that are less likely to survive their first two years of life.Are more likely to take “life threatening” actions.

There have been...

...many studies of the factors associated with business survival......a number of theoretical models put forward suggesting how entrepreneurs might ‘learn’……but almost no empirical tests of Entrepreneurial Learning EL.

We present three tests of EL using data on bank customers.

Testing for Entrepreneurial Learning

Those with prior business experience as an owner are more likely to have businesses that survive two years“Life threatening” actions will be less frequent as new businesses mature and the poor performers are “weeded out”

The Two “life threatening” measures are Sales volatilityUnauthorised borrowing

Our Tests of EL

Test 1: Are new firms that have owners with prior business experience as an owner more likely to survive for two years?Test 2 : Do new firms become less likely to have less volatile sales as they survive and gain more experience?Test 3 : Do new firms become less likely to borrow in an unauthorised manner from the bank as they survive and gain more experience?

Why these tests?

Test 1: Tests if those with prior business experience …learning…perform better.Test 2: Sales volatility presents cash flow problems for the new firm…which is a key cause of closure…so the learning entrepreneur would be expected to reduce volatility.Test 3: Unauthorised borrowing is “best” test because the owner is informed and financially penalised by the bank when this happens. There is no excuse for not knowing that this is viewed as undesirable behaviour.

Data

Dataset drawn from the customer records of Barclays Bank.Consists of 6,854 (non-financial) firms that started up with Barclays between March and May 2004.The dataset includes variables on structural firm characteristics, trading activity and certain personal characteristics of the owner-manager(s).

Data

The survival rates of new firms.

Chart A: Two Year Survival Rates (%)by data source

81.8

67 69.373.3

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VAT Barclays (account) Barclays (firm) Dataset

Chart B: Conditional Closure Rates (%)six months to...

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VAT Barclays (account) Barclays (firm) Dataset

Data

The characteristics of surviving and non-surviving new firms.

Survival Factors (structural variables only)significant at 5% level

period(1) (2) (3) (4)

legal: company + + + +sic: business services +sic: construction +sic: manufacturing +sic: other services +sic: property services +age + + +age 2 - -involved persons: male + -business experience: family +education: degree + -advice: princes trust - -advice: family/friends -advice: other -

Survival Factors (structural & trading variables)significant at 5% level

period(1) (2) (3) (4)

legal: company + + +sic: agriculture +sic: business servicessic: construction +sic: manufacturingsic: other services +sic: property services + +age +age 2 -involved persons: excess +involved persons: male + -business experience: family +education: degree +advice: enterprise agency/business link +advice: princes trust -advice: family/friends -advice: other -turnover + + +turnover (change) +volatility - - -volatility (change) - -excess: use - - -excess: use (change) + +excess: length - - -excess: length (change) -

Test 1: Are new firms that have owners with prior business experience as an owner more likely to survive for two years?

1. Those with only their own prior experience are not more likely to survive.

2. Those with family business experience are only more likely to survive in one six month period.

3. Those with both family and personal experience are not more likely to survive.

Test 2: Do new firms become likely to have less volatile sales as they gain more experience?

OLS model of volatility estimated over the two years of available data using surviving businesses only.Dummy variables for periods 2, 3 and 4.Higher (lower) volatility is linked to a reduced (increased) likelihood of survival. Volatility is significantly lower in each of periods 2, 3 and 4 than the first six months after start-up, but...…no significant differences in volatility between these latter periods.That is, volatility does not become steadily lower over time.

Test 3: Do new firms become less likely to borrow in an unauthorised manner from the bank as they survive and gain more experience?

Unauthorised borrowing - both incidence and intensity - significantly lowers survival rates in periods 2, 3 and 4.The incidence of excess rises in each period, from 29.9% in period 1 to 33.3% in period 4.The intensity of excess rises in each period, from 14.0% in period 1 to 20.7% in period 4.

Conclusion

Prior work has either assumed entrepreneurs learn or asked entrepreneurs whether they have learnt.It has also assumed that learning leads to enhanced performance.Our theory places a greater weight on chance and optimism.We provide three tests of learning – two of which are new.None provide support for idea that learning by founders is sufficient to improve new firm performance

Chart C: Volatility Distribution% of surviving firms, periods 1 & 4

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Step 3: Reduction in Volatility relative to Period 1all observations, 90% confidence intervals

0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13

Period 2

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Step 3: Reduction in Volatility relative to Period 1excluding extreme values, 90% confidence intervals

0.02 0.04 0.06 0.08 0.10 0.12

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Table 3: Structural variables, summary data% of surviving sample base

At start-up After 24 months

legal form company 38.2 42.4 sole trader 48.7 45.0business sector manufacturing 5.1 5.4 construction 14.5 14.8 retail 11.6 11.1 hotels & catering 8.8 8.2 business services 26.4 26.8 personal & leisure services 16.7 16.3age under 25 6.9 5.8 25-34 30.9 29.1 35-44 34.9 35.8 45-54 19.2 20.8 55-64 7.2 7.6 65 & over 0.9 0.9involve persons: excess 16.3 18.5involve persons: male 81.3 82.1business experience none 12.4 11.9 family 15.3 14.8 self 24.3 24.2 self & family 48.0 49.0education none 22.5 22.0 GCSE 32.6 32.5 A-level 17.1 17.2 Degree or higher 27.8 28.4advice enterprise agency/business link 10.4 10.0 accountant 36.4 37.6 solicitor 5.3 5.5 family/friends 30.2 29.3 other 11.6 10.5 any 50.3 50.4 two or more 11.4 11.0

Sample size 6,854 5,026

Table 4: Trading variables, summary data

period(1) (2) (3) (4)

turnover (£) mean 51,000 58,900 65,700 68,000 median 13,800 15,300 17,100 16,300turnover (change) mean +7,100 +5,200 -1,300 median +500 +300 -400volatility mean .76 .68 .64 .66 median .62 .52 .47 .49volatility (change) mean -.04 +.02 +.07 median -.06 -.01 +.03overdraft limit(% of sample)

9.4 20.6 25.2 26.7

OD limit use (mean) .046 .119 .170 .180OD limit use (change) .070 .051 .008OD limit pc mean .011 .040 .071 .137 median 0 0 0 0OD limit pc (change) mean +.028 +.032 +.067 median 0 0 0excess: use (mean) .299 .306 .327 .330excess: use (change) .025 .043 .011excess: length mean .042 .056 .063 .069 median 0 0 0 0excess: length (change) mean +.026 +.023 +.016 median 0 0 0

Sample size 6,587 5,974 5,351 5,026

Step 1: Conditional Survival Models

Estimate conditional survival models for each consecutive six month period in the first two years after start-up - enter structural variables first, followed by trading variables.This permits the role of factors in accounting for firm survival to alter over time.A number of variables are significant in one to three of the models, but not in all four.However, the models do indicate a set of core factors associated with an increased likelihood of business survival.