2018THESIS Flashcards
What else could you have controlled for?
- Financial performance of portfolio companies
- The number of co-founders
- Education of co-founders and their previous experience
- Terms of the investment
What made you state hypothesis 1 about PCs of public funds having unclear exit strategies?
- Importance of exits and financial returns is lower due to the dual purpose
- Lower urgency of returns/lower need to prove exits as public funds do not raise money in the same way
What made you state hypothesis 2 about PCs of private funds pursuing IPOs more often?
- Reputation benefits from the public disclosure and attention of IPOs
- Investment focus more often on scalable industries (ICT especially)
- Also found by Isaksson in Sweden
What made you state hypothesis 3 about PCs of public funds having a lower intensity of exit-directed activities?
- Lower urgency of returns = Due to the capital source, there is a much lower need to prove exits
- Poor bonus/incentive structure for MDs of public funds, thus incentivizing exit focus less
What made you state hypothesis 4 about no significant difference between PCs focus on internationalization?
- Expansion into foreign markets is inevitable to reach a substantial size for successful exits = This goes for all portfolio companies from the small Danish market
What made you state hypothesis 5 about VCs perceived contribution towards internationalization to be higher among PCs of non-public funds?
- Knowledge-based / Resource-based view
- Public funds are geographically constrained in terms of their investments and can thus not get the same knowledge
- Public funds may want to keep jobs in domestic market due to dual purpose
- Non-public funds have better MDs due to incentive structure and the knowledge of captives parent-companies
Why are you not showing the 2 other forms of secondary sale as answer options?
The two other forms being VC fund selling share to other VC-fund OR to a financial institution.
These are uncommon and IF people had that planned, it could be written in “others”.
Also, we took the question from Isaksson’s survey.
Why the chosen methodology?
- Mixed method allowed us to better understand the characteristics of the Danish VC-industry.
- The survey provided many responses (quantitative) and is believed to much better represent the population rather than a qualitative approach surveying only 1 PC for each VC-fund type
- Alternatively, one could with very strong cooperation of PCs use number of markets and share of foreign sales (ACTUAL numbers) and already exited PCs exits to answer the research question but this would, first of all, be very hard to find these exited companies and next get them to put in the time necessary for such study.
Why early- and late-stage together?
Lockett et al. (2008) found that the later the stage of development, the less VC-funds contribute to the internationalization process due to internally developed resources.
We thus chose to separate SEED-stage from other stages as these are the earliest.
But stage is not significant for any of the final models - in fact, it is not even included in MODEL 3A and 3C.
What else could you have used instead of the Pearson’s chi-squared test?
When having expected counts below 5, Fisher’s exact test is an alternative (for 2x2 at least)
But using Chi-square as simply and then also comparable to Isaksson.
What would be the alternative to the use of a principal component factor analysis?
Three types of factor analysis:
- Principal component analysis
- Goal: DATA REDUCTION
- Exploratory factor analysis
- Goal: ESTIMATE THE PATTERNS OF RELATIONS BETWEEN THE COMMON FACTORS AND EACH MEASURED VARIABLE
- Confirmatory factor analysis
- Goal: SEEKS TO DETERMINE IF INDICATOR VARIABLES LOAD AS PREDICTED BY THEORY
What was the process of your backward selection of independent variables in your final regression model?
- Removing the variables with the highest p-value from the non-robust model
- Next, check if the r-squared ADJUSTED increases or not.
- If increasing, we will remove another variable until it stops increasing
- Lastly making the final model robust
What can explain PCs of public funds higher focus on internationalization? How could this be investigated further?
- Potentially wrong due to
- Non-response errors stemming from misunderstandings of question
- A latent variable not accounted for
- Potentially the right conclusion. Hard to explain and needs further research:
- Case studies with PCs may help OR further interviews with VC fund managers focusing on this topic
- PCs of public funds may find “internationalization to be important” as they are less internationalized than PCs of non-public funds. Being less internationalized is, however, best explained by public funds’ investments in earlier stages
- but… our models predict that PCs who export more, find international expansion more important
What is Kaiser-Meyer-Olkin’s (KMO) Measure of Sampling Adequacy?
Measures/tests whether a correlation matrix is adequate for factor analysis.
“a statistic that indicates the proportion of variance in your variables that might be caused by underlying factors”
As long as the KMO value is minimum 0.6, you are good
What is the K1 approach?
Strictly dropping factors with eigenvalues below 1 (Kaiser 1960) => for Kaiser-Meyer-Olkin
What is Bartlett’s Test of Sphericit?
“tests the hypothesis that your correlation matrix is an identity matrix, which would indicate that your variables are unrelated and therefore unsuitable for structure detection.” = and thus unsuitable for factor analysis.
As long as you can reject this null hypothesis, you are good.
What is Principal Component Factor Analysis?
“a method to create one or more index variables from a larger set of measured variables”
What is an Eigenvalue?
The values reported from the Kaiser-Meyer-Olkin test. Must be above 1 when using the K1 approach in determining number of factors.
What is a Scree plot?
Simply a plot of the eigenvalues.
Interpreting the scree plot = you should not include factors from the point where it stops dropping substantially / when it flattens out
What is Heteroscedasticity?
When the standard deviations of a variable increase with x = when the standard deviations are non-constant.
