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• NZ Economic Development
• Small & Medium Enterprises
• Access to Finance
• NZ's Angel Capital Market
• Appendix IV

• Small & Medium Enterprises

• Access to Finance

• Sources of Capital
• NZ's Venture Capital Market
• 2004 Business Finance Survey
• NZ's Angel Capital Market
• Bank Lending Practices
• Media Statements

• Econometric Analysis of Survey
• Econometric and Statistical Analysis
• Successful Investment
  • All Angel Investors
  • Passive Investors
  • Active/Astute Investors
• The Typical Investor?
  • Question 29 (Investment Environment)
    • Principal Component Analysis
  • Question 21 (Investment Criteria)
• Conclusion

Econometric Analysis of Survey

The final response rate of the survey was 611 or 35.7% of the potential number. Of these, 348 could be described as angel investors. Our understanding is that both the absolute number of respondents and the response rate as a proportion of those approached, are very good by international standards for this subject. Indeed the number of respondents as a proportion of the likely total number of angel investors in the New Zealand population is probably quite high. Thus the survey delivers a considerable amount of descriptive information about angel investors.

While we should not ignore the possibility that there is some bias in the response rate owing to the sample selection method, the number of responses to any given question suggests that we can be reasonably confident about the answers - to that question. However, cross-tabulations of more than one question at a time are likely to contain much wider error margins, depending on the number of responses in each of the tabulated questions. This needs to be borne in mind when reading the analysis described below.

Econometric and Statistical Analysis

Simple statistical descriptions provide a useful overview of the characteristics of angel investors; their methods, preferences, opinions and so on. From these descriptions it is always tempting to draw inferences about links between variables and possible causative influences. For example, we may observe that most successful angel investments are by investors of high net worth and simultaneously that most successful angel investments are in manufacturing. Which of these has the stronger effect on returns and to what extent might wealth be a proxy for experience, via the effect of age?

Econometric analysis can be used to try to isolate the separate influences of the various underlying factors. Note, however, that even econometric analysis does not tell us anything about causation, especially with cross-sectional data. It will reveal where the true correlations exist (if the models are correctly specified), but we rely on theory and reasoning to establish causal links.

With the survey having so many questions it was originally our intention to undertake some form of factor analysis or principal components analysis on the whole dataset, in order to establish whether responses exhibited any form of clustering around certain attitudes or investor behaviour. This type of analysis is useful in situations where there is a group of variables that are reasonably closely related (such as age, income and education), making it difficult to identify robust relationships between variables. The survey response dataset does not have this characteristic. There are too many different types of questions for distillation into one or even a few dominant signals without some guidance from theory or other empirical research.

Also, from a purely practical perspective, the dataset contains too many missing values (non-responses), relative to the total sample size, to permit analysis of the whole sample at once. This means that some a priori selection of variables is required.

We have therefore chosen two approaches for the analysis of the dataset. Firstly we define two specific questions that seek to determine what factors contribute to a successful angel investment:

• What factors are associated with a successful exit (using the responses to Question 28 to define the dependent variable as the net number of successful exists)?
• What factors are associated with a high rate of return at exit (using the mid-points of the response options for Question 27 as the dependent variable)?

These questions are explored using multiple linear regression with a "general to specific" methodology. Sample size restrictions have forced us to omit industry type as an explanatory variable.

Secondly, in an attempt to return to the idea of a typical angel investor, we analyse two questions that ask investors about their opinions on a range of issues. Principal components analysis is used for this task. The two questions are Question 29 which asks about the angel investment market environment, and Question 21 which asks about angel investment criteria.

Based on the discussion in the body of the report we examine the above questions for three different groups of investors:

• All angel investors - those who answered "yes" to Question 1.
• Passive investors - those who reported "no other roles" under Question 23.
• Active/astute investors - those who reported "board member" under Question <23, and reported net household wealth above $2m under Question 36.

Successful Investment

All Angel Investors

Neither equation produces a strong fit. The exit equation reveals that number of successful exits is highest when angel investors have a preference to become involved at the early expansion stage. Also the greater the value of the funds invested, the greater the number of successful exits - perhaps indicating more care when more money is at risk, or perhaps acting as a proxy for experience. Awareness of investment opportunities is via other business contacts, not from family and friends.

Placing a high weight on a business's competitiveness or the relevant industry's regulatory burden does not enhance the probability of a successful exit.

The rate of return equation is reasonably consistent with the exit equation. In addition to amount invested, investors who place a high weight on the quality of the management team and who mentor to the target business enhance their rate of return. More time spent searching for investment opportunities also helps.

Passive Investors

Bearing in mind the small sample size, the results are as shown below.

The exit equation suggests that passive investors are a mixed group, with successful investors comprising both hobbyists and those desiring the challenge of building a business; and comprising both those who secure their opportunities through business contacts and those who secure them from friends and family.

The rate of return equation confirms the importance of spending time evaluating proposals, but dismisses the importance of time spent searching for opportunities. Investing at the seed stage has a positive effect on the rate of return, in contrast to investing at the expansion stage.

Active / Astute Investors

The exit equation implies that the successful astute/active angel investor prefers to invest at the expansion stage and in businesses that are consistent with their own expertise and experience. Referrals from family and friends has a positive effect, suggesting that for this group of investors, referrals from businesses contacts and other formal networks do not enhance the likelihood of successful exit. The group may be astute, but this does not mean that they shun informal networks.

The rate of return equation demonstrates the importance that this group of investors attaches to research and to achieving a financial return. Household income has a negative effect, but recall that this group is confined to people with a net household wealth above $2m.

The Typical Investor?

Question 29 (Investment Environment)

Filtered for respondents who are defined as angel investors (that is, answered "yes" to Question 1), the mean scores direct from the survey for each of the statements in Question 29 provide the following general picture:

1. Investors have difficulty finding investment opportunities in private business
2. Government policy is not conducive to such investment
3. Entrepreneurs have unrealistic valuations
4. Exiting the market is currently difficult
5. Target businesses lack experienced management
6. The amount of investment being sought is generally within what the investor can afford
7. Target businesses lack proprietary technology
8. Investors have adequate experience in mentoring and monitoring
9. Access to follow-on venture capital is not readily available
10. Investors are able to find deals that match their expertise and preferences
11. There is too much money chasing too few deals

[No significance attaches to the order above - it is just as given in the survey]

Principal components analysis allows us to see if these views (or some other combination of opinions) represent those of a "typical" angel investor. Such analysis shows that the first three principal components explain 89% (82%, 4% and 3% respectively) of the total variance.

The first principal component is consistent with all of the statements as worded above, suggesting that angel investors hold very similar views about the investment environment.

The table below shows the explanatory power of the 1st-3rd principal components for all angel investors, for passive investors, and for active/astute investors. The two subgroups show much less uniformity of opinion than the overall group.

For passive investors the first principal component is still completely consistent with the eleven statements given above, suggesting that while views are diverse, the single largest body of opinion is in accordance with the wider group of angel investors.

For active/astute investors, there is even more diversity. In addition, the signs on the 2nd, 6th, 9th and 10th, statements above are reversed in the first principal component. That is, there is a dominant group of active/astute investor who think that:

2. Government policy is conducive to such investment

6. The amount of investment being sought is generally not within what the investor can afford

9. Access to follow-on venture capital is readily available

10. Investors are unable to find deals that match their expertise and preferences.

Given the low degree of clustering for this group, not too much should be inferred from these results. Overall, while angel investors as a whole share similar views about the investment environment, sub-groups of investors show considerably more diversity.

Question 21 (Investment Criteria)

For this question the typical investor attached more than average importance to all criteria listed below except No 6.

1. Quality of management team
2. Personality and attitude of entrepreneur
3. Domestic market potential
4. International market potential
5. Competitive advantage
6. Physical location
7. Consistency with investment preferences
8. Regulatory burden
9. Quality of business plan
10. Consistency with own experience, expertise of knowledge

[No significance attaches to the order above - it is just as given in the survey]

Principal components analysis on the responses again reveals an integrated picture. The first three principal components explain 78% (64%, 8% and 6% respectively) of the total variance. All criteria have a positive weight in the first principal component, including physical location.

The table below shows the explanatory power of the 1st-3rd principal components for all angel investors, for passive investors, and for active/astute investors.

As with Question 29 these is more diversity of opinion amongst the subgroups than amongst the group as a whole.

For the passive investor group, the signs on each variable in the first principal component are not consistent with the typical responses for the whole group. In particular there are sign reversals on the 1st, 3rd, 6th and 9th criteria. That is, the quality of the management team, domestic market potential, and the quality of the business plan are given a low weight, while location is given a high weight - by passive investors. The same sign reversals apply to the active/astute group, with the 7th criteria (consistency with investment preference) also changing sign.

Conclusion

While the results for Questions 21 and 29 suggest a reasonable degree of consistency in market views and investment criteria for angel investors as a whole, particular sub-groups display much more diversity.

It could be that the two subgroups as defined here, although based on the results of the interviews in the environmental scan, cannot be adequately identified in the survey population. This could mean that the environmental scan has been somewhat misleading. Equally, if not more likely, however, is the possibility that although passive and astute investors are different in some key respects, their attitudes to angel investment are not the main differentiating factors. The size of the survey, the way the questions were asked, and the problem of missing values; all make it difficult to robustly identify the characteristics of passive and active/astute groups of investors.

The survey was primarily intended to capture information that could be used to describe the broad attitudes, behaviour and characteristics of angel investors, rather than supply the type of comprehensive data that is required for econometric analysis.

Should the opportunity arise to undertake another survey, the following changes are recommended:

• Where investors have more than one current investment, it would be extremely useful if the characteristics of each one were separately identified; for example industry, development stage, how discovered, degree of involvement and so on. Similarly for investments that have been exited, so that the characteristics of the investor could be separated from the characteristics of the investment - in an analysis of the types of exit and rates of return achieved. We recognise that this would significantly lengthen the questionnaire and would therefore increase the rate of non-response.
• Non-responses are a problem for econometric analysis, both because it reduces the number of usable observations and because the non-response may not be unbiased. For example some ethnic groups may be more likely to refuse to answer a question on ethnicity than other groups. Although the survey was rather long there is no suggestion that the response rate declined as respondents worked through the questionnaire, except at the very end where the traditionally sensitive questions about income and wealth were located.
• Meeting the twin objectives of both a shorter survey and a more detailed one is undoubtedly difficult. A necessary condition is that the survey has clear objectives and is designed with the type of analysis that is subsequently intended firmly in mind.
• The web-based survey system has the very substantial advantage of being fast and efficient, thereby reducing respondent burden. Like mail surveys, however, it is difficult to ensure an unbiased response rate.