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Does start-up financing influence start-up speed? Evidence from the panel study of entrepreneurial dynamics

Abstract

Why are some entrepreneurs able to start a new firm more quickly than others in the venture creation process? Drawing on pecking order and agency theory, this study investigates how start-up capital structure influences the time to either new firm founding or quitting the start-up process. The temporal aspect of the start-up process is one that is often discussed, but rarely studied. Therefore, we utilize competing risk and Cox regression event history analysis on a nationally representative sample of US entrepreneurs to investigate how start-up capital structure impacts the time in gestation to particular kinds of start-up outcomes. Our findings suggest that external equity has an appreciable impact on new firm emergence over time, and that the percentage of ownership held by the founders attenuates the benefits of external equity.

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Notes

  1. 1.

    http://www.psed.isr.umich.edu.

  2. 2.

    For a comprehensive list of PSED studies, see Frid et al. (2015a).

  3. 3.

    This theory also suggests that there is no target debt–equity mix for a firm (Donaldson and Fox 2000; Myers 1984).

  4. 4.

    Access for the consolidated data set can be found at www.psed.isr.umich.edu.

  5. 5.

    The challenge of combining PSED I and PSED II is not based on standardizing the response codes to individual items, many of these are already standardized among the databases. The challenge lies in that there are subtle differences in the operational procedures utilized to as classification criteria for main transitions associated with conception, new firm birth, and quitting. In terms of conception, no single conceptual definition is reflected in the data collection procedures within the PSED studies. What the PSED does is it collects information on a broad range of start-up activities, along with their date of initiation, in order to identify the of beginning the start-up process in the PSED harmonized transitions data set. Moreover, the PSED has developed a multi-criteria outcome variable has been developed for use in the PSED harmonized transitions data set, which utilizes the date of the first activity within a 12-month window where at least two activities have taken place, excluding serious thought. To capture firm birth, the harmonized transition file uses the criteria of profitability. Respondents initially reporting on a profitable new firm, rather than a start-up, are identified and subsequently verified by the following three criteria: (1) positive monthly cash flow for 3/6 months; (2) revenue covers expenses; and (3) expenses include owner-managers salaries. Quitting from the start-up process is theoretically explicit compared to new firm status. However, it is measured in different ways within the two projects. In PSED I, the quit measure is based on the respondent’s claim they have terminated work on the start-up. In PSED II, the quit measure is based on the respondent’s claim that little recent work on the start-up has happened, no future work on the start-up is expected, and that future career plans do not include any effort on this start-up venture. For the consolidated data set, the advantage lies in the standardization of these procedures to facilitate consistency and replication among scholars interested in the temporal patterns of the nascent start-up process.

  6. 6.

    See Table 1 for detailed description of variables utilized to compute outcome time in months.

  7. 7.

    Each case was given equal weight in this procedure, which is adequate for hypothesis testing. It should be noted that findings do not represent the US population due to the deliberate oversample of women and minorities in PSED I.

  8. 8.

    Items include Q268, Q270, R771, S771, T771, R771A, S771A, T771A Q272, Q274, Q276, Q277A, Q279, Q281, Q282A, Q286, R-T770, Q268, Q270, R771, S771, T771, R771A, S771A, T771A/A-BQ12x_1 A-BQ12x_2 A-BQ12x_3A- BQ12x_4 A-BQ12x_5 BQ12x_6, A-EQ 13_1 A-EQ 13_2 A-EQ 13_3 A-EQ 13_4 A-EQ 13_5 B-EQ 13_6, A-ER21, AR4-ER4.

  9. 9.

    The trimmed mean is calculated similar to an ordinary mean, and the only difference is that 10 % of the extreme cases are omitted before calculating the mean. Specifically, the 5 % trimmed mean excludes the left-most (lowest) 5 % and right-most (highest) 5 % of cases, and then, the remaining observations are utilized to calculate the mean.

  10. 10.

    The PSED I cohort was followed over four years, and the PSED II cohort was tracked over six years.

  11. 11.

    The following control variables are used in this mode: internal funds greater than 51 %, total debt greater than 51 %, external equity greater than 51 %, and innovativeness while controlling for conception lag, team size, sweat equity in hours per member per month, total men, total Caucasians, total owners age 18–24, total owners age 25–34, total owners 35–44, total owners total 45–54, total owners 55–99, household net worth, total funds, growth preference, business planning, financial projections, industry experience, start-up experience, education, and industry.

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Acknowledgments

We thank Gavin Cassar for comments on earlier version of this manuscript. We also would like to thank Associate Editor Siri Terjesen and two anonymous reviewers for their developmental feedback and constructive comments during the review process. A prior version of this research was presented at the United States Association for Small Business and Entrepreneurship 2015 (Tampa, FL), where this manuscript was awarded Best Empirical Paper. We also would like to thank colleagues within the paper session where this work was presented for their helpful comments.

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Correspondence to Diana M. Hechavarría.

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Hechavarría, D.M., Matthews, C.H. & Reynolds, P.D. Does start-up financing influence start-up speed? Evidence from the panel study of entrepreneurial dynamics. Small Bus Econ 46, 137–167 (2016). https://doi.org/10.1007/s11187-015-9680-y

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Keywords

  • Start-up outcomes
  • Capital structure
  • Nascent entrepreneurship
  • New firm founding
  • Start-up financing
  • Event history analysis
  • Panel study of entrepreneurial dynamics

JEL Classifications

  • M10
  • M13
  • G32
  • M21