Abstract
We use Canadian data linking information on venture capital (VC) financing with firm-level administrative data to compare performance of VC-backed and non-VC-backed firms. The richness of the data allows us to incorporate a wide range of firm-level information into creating a control group based on propensity-score matching. In particular, we use typical covariates reflecting firm performance and characteristics (e.g., size, age, industry, location) as well as measures of firm-level innovation such as research and development (R&D) expenditures that are often thought to be associated with the potential for high growth and the probability of receiving VC financing. Our results show R&D expenditures not only attract VC, but are also increased more intensely for VC-backed firms than non-VC-backed counterparts over the short-run. Further, we show VC-backed firms enjoy greater growth in wages and scale over the 5-year period. Overall, our results provide empirical evidence that VC financing is associated with the acceleration of the innovation and commercialization process accompanied by greater growth in wages and scale.
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Notes
The definition of an enterprise can be found at http://www.statcan.gc.ca/concepts/definitions/ent-eng.htm: The enterprise, as a statistical unit, is defined as the organisational unit of a business that directs and controls the allocation of resources relating to its domestic operations, and for which consolidated financial and balance sheet accounts are maintained from which international transactions, an international investment position and a consolidated financial position for the unit can be derived.
ILU is a continuous measure of the annual number of employees for a firm. Each individual receiving a T4 represents 1.0 ILU that is allocated to one or more firms according to the fraction of the individual’s total annual payroll contributed by the particular firm. This measure will partially account for firms that hire employees later in the year as well as individuals working more than one job, but does not account for differences in the number of hours worked across employees.
The IRAP Data does not contain information on the operating street address or postal code, and as a result, is linked based on the enterprise name, city and province. While the linkage is made using less information, the IRAP linkage achieves a higher initial rate of concordance due to higher quality matches among the firm names. This is not surprising as the recipients of IRAP funding are required to use their legal names, and as a result, are more likely to be exactly identified in the BR.
Although ubiquitous for their ease of use, NAICS codes are not necessarily ideal proxies for the market in which a firm competes as NAICS codes categorize firms based on production rather than on demand. VC investors focus on markets where they have technical knowledge or some form of expertise. Accordingly, a lack of investment activity among VC funds in a VC-financed firm’s NAICS code could indicate the assigned NAICS code does not accurately reflect the firm’s main market, or the firm may not have suitable analogues within that NAICS code.
A number of firms receive multiple rounds of VC financing, which is a standard practice in the industry. However, for the matching purpose, our focus is on how firm characteristics affect a firm’s probability of becoming VC-backed (i.e., receiving any kind of VC investment). Accordingly, for the VC-backed firms, only the observations up to and including the first round of VC financing are included in the regression.
By limiting the potential set of matches to the cohort based on the VC-backed firm’s province, industry and financing year, we are performing an exact matching over these covariates. This strategy makes sense since these covariates are categorical, and as such, it is possible to obtain a reasonably high match rate even through exact matching. Further, location and industry are not just important variables determining the likelihood of receiving VC financing. An identical match on these covariates allows us to fully control for industry-location-time-specific shocks.
See Rosenbaum and Rubin (1985) for a discussion on selecting a caliper size.
Defined as \( p = { \ln }\left( {{ \Pr }\left( {VC = 1} \right)/\left( {1 + { \Pr }\left( {VC = 1} \right)} \right)} \right) \).
We order the treatment firms based on their date of first financing to maximize the length of the longitudinal records of the treatment and control groups.
The sensitivity tests are not reported due to residual disclosure concerns that would violate Statistics Canada’s confidentiality requirements.
Our matching estimator requires two basic assumptions. First, there is a set of covariates, X, such that firm outcomes are independent of the treatment (i.e., VC financing) after controlling for these characteristics. As we are estimating the ATT, only mean independence (i.e., \( E\left[ {Y\left( 0 \right),Y\left( 1 \right)} \right] \bot (VC|X) \)) is necessary. See Heckman et al. (1997, 1998) for more information. Second, for all X, there is a positive probability of either receiving or not receiving a treatment (i.e., there is a region of common support).
R&D expenditures data is not available for the year 1999. Note that we do not include firm observations from 1999 when calculating growth rates for R&D in the subsequent sections. The dummy variable is for the sole purpose of achieving better matching among innovative firms financed in 1999.
We cannot replicate this exercise for other variables while maintaining Statistics Canada’s confidentiality requirements.
Organic growth in reference to employment generally refers to net job creation or destruction independent of employment reallocation. However, among our data, employment changes within the firm include non-organic changes (e.g., mergers, acquisitions or divestitures). While non-organic growth may amount to nothing more than job shuffling when viewed at the industry level, such growth could reflect important changes in capacity at the firm level.
Firms receiving their first round of VC financing prior to 1999 are removed if they are not present in the BR in 1999 or 2000.
Economic activity is defined as filing a T2, T4 or PD7 payroll remittance form. Firms receiving their first round of VC financing prior to 1999 are removed if they show no signs of economic activity in 1999 and 2000.
The threshold of 50% to determine whether a firm is the dominant component in the labour tracking relationship is not arbitrary and based on discussions between analysts from Statistics Canada and Innovation, Science and Economic Development Canada. In particular, thresholds based on figures greater than 50% are considered (e.g., 80%), and these are deemed to be too restrictive as firms routinely experience changes in employees through regular employee churns that account for more than 20% of their employees.
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Acknowledgements
We would like to thank Statistics Canada, the Canadian Venture Capitalist Association and the Small Business Branch of Innovation, Science and Economic Development Canada for assistance and comments throughout this project. In particular, we would like to thank Jim Valerio, Shane Dolan, Anne-Marie Rollin and Younes Errounda for their tireless efforts in the data development and descriptive analysis that made this research possible. We would also like to thank Thomas Hellmann, Javier Miranda, Mariagrazia Squicciarini, Robin Prager, Leonard Sabetti and participants at the 2014 OECD Conference on Entrepreneurship, Innovation and Enterprise Dynamics, the 12th Annual International Industrial Organization Conference and the 47th Annual Canadian Economics Association Meetings for their helpful comments and suggestions. Finally, we would like to thank two anonymous referees whose suggestions tremendously improved this paper.
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The views and opinions expressed in this paper are those of the authors alone and do not represent, in any way, the views or opinions of Innovation, Science and Economic Development Canada or of the Government of Canada.
Appendices
Appendix 1: Linking VC and IRAP data to STC data
In this appendix, we summarize the linkages among the VC, IRAP and STC Data. Both the VC (from Thomson Reuters) and IRAP Data are external to the firm-level databases at Statistics Canada. Accordingly, the linkages are done through names and addresses given that there is no common firm identifier among these data. CVCA (2013) provides full details on how the linkages are done. Table 11 provides the initial linkage results on the Thomson Data.
A number of VC-backed firms have suspected linkages in the BR, but these potential counterparts are not identical in either their names or addresses. This is not surprising as the data collection method used by Thomson Reuters do not necessarily produce the legal names of the firms. For these records, analysts from Statistics Canada and Small Business Branch of Innovation, Science and Economic Development Canada made the linkages manually, leveraging their expertise and public sources of information on these firms. There are 463 such firms, accounting for 16.8% of the total available for linkage. Including these firms, the initial linkages resulted in 74.3% of 2762 or 2053 firms linked to the BR.
Following the initial linkages, information from other STC Data such as T2, T4 and PD7 remittance slips are used to further check the validity of the linkages. In particular, we are concerned with firms that are identified as financed by VC but do not have any economic activities around the time of their first financing. The linkages of these firms are potentially erroneous as VC-backed firms are expected to be economically active. We remove the linkage if the firm is not identified in the BR within two years of the first VC financing (372 firms)Footnote 16; if the firm reports no economic activity (T2, T4 or PD7 reporting) in the year of or the year following the VC investment (81 firms)Footnote 17; if the firm reports revenues exceeding $50 million at the time of the first VC financing (11 firms); and if the firm suffers from inconsistencies between exit outcomes from the STC and Thomson Data (44 firms). These additional filters are similar to dropping outliers in a statistical analysis as we are dropping linkages that do not make economic sense. After applying these additional checks, we have 1545 VC-backed firms linked to the STC Data.
The linkage results for the IRAP Data are in Table 12. While it contains less information on the operating addresses of the firms, the IRAP Data have a much higher rate of quality linkage with 80% of the sample reporting an identical name in both the IRAP Data and the BR. This is likely the result of firms having to provide their legal names in applying for IRAP while the Thomson Data is indirectly collected through investing VC funds and limited partners. Overall, 83.6% of 7736 firms or 6468 firms in the IRAP Data are linked to the STC Data.
Appendix 2: Longitudinalization through labor tracking
An identification assigned to an enterprise in the BR, or BRID, is not designed to track a given enterprise over time. In particular, an enterprise’s BRID can change for reasons unrelated to any structural change (e.g., a change in the legal name). Conversely, an enterprise could maintain the same BRID, even after a substantial structural change including M&As.
Since we are examining growth metrics, it is important to correctly follow a firm over time (i.e., using longitudinalized data). Accordingly, the labor tracking methodology developed by Statistics Canada is implemented to identify firms over time. This procedure involves following masses of employment (i.e., individuals identified by their SINs in the T4 tax files) moving from one BRID to another. Depending on the nature of these relationships, we amended the respective BRID entries to arrive at a single longitudinal record for each firm within the treatment and control groups using the year they are matched as the base year.
Under the labor tracking, relationships among BRIDs are only identified when one BRID either starts or stops filing the T4 tax information, which we call a T4 birth or T4 death, respectively. Once a T4 death or birth occurs, Statistics Canada determines whether there is sufficient evidence of a relationship with another BRID by examining the size of the firms and the proportion of shared employees among the predecessor and successor BRIDs. The thresholds to determine whether a relationship exists are summarized in Table 13. Approximately, one-third of the BRIDs associated with firms in the treatment and control groups are involved in one or more labor tracking relationships meeting these criteria.
There are three basic types of labor tracking relationships: (1) death-to-birth, (2) death-to-continuer and (3) continuer-to-birth. While specific events in the firm’s life cycle cannot be identified with absolute certainty, these relationships as identified by the methodology roughly translate into a false death (i.e., the same firm reporting under a new BRID), an acquisition and a spin-off, respectively. Further, a BRID may be involved in multiple relationships (e.g., two deaths to a birth roughly corresponding to a merger). These relationships can become quite complex when a BRID is involved with many different types of relationships spanning several other BRIDs—a situation not uncommon among BRIDs corresponding to large firms.
For our purpose, we do not want to focus solely on organic growth within firms. Our objective is to measure the performance of VC-backed firms, and growth through acquisitions could be part of their strategy to expand the operations. At the same time, if the VC-backed firm is the target of a merger or acquisition, this is likely an exit for the VC investors and ideally the end of the longitudinal record. Regarding spin-offs, it remains unclear whether the new BRID reflects a separate entity or a change in the firm’s reporting practices. Accordingly, Statistics Canada connects records when the labor tracking suggests there has been a false death, and ends records when the labor tracking suggests the firm in the treatment or control group is acquired, or there was a substantial spin-off.
Statistics Canada applies a threshold based on 50% of shared employees for evaluating all the labor tracking relationships.Footnote 18 In particular, for a potential false death, the predecessor and successor BRIDs are connected into one longitudinal record if the successor BRIDs share 50% or more of the employees of the predecessor. For cases suggesting the firm in the treatment or control group acquiring another firm, the record is ended if the former represents less than 50% of the combined employment in the merged firm. For potential spin-offs, the record is ended if the spin-off exceeds 50% of the employment of the firm in the treatment or control group. Finally, for complex cases where a BRID is involved in many relationships, the 50% threshold is applied cumulatively, ending the record if the total employment associated with all the acquisitions and spin-offs exceeds 50% of the firm’s employment, whether in the treatment or control group.
The Thomson Data contains information on VC exits including initial public offerings, M&As and business failures. These data are used to supplement the exits identified through the labor tracking among firms in the treatment group.
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Kelly, R., Kim, H. Venture capital as a catalyst for commercialization and high growth. J Technol Transf 43, 1466–1492 (2018). https://doi.org/10.1007/s10961-016-9540-1
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DOI: https://doi.org/10.1007/s10961-016-9540-1