The gender gap in federal and private support for entrepreneurshipSmall Bus Econ

About

Authors
Dora Gicheva, Albert N. Link
Year
2015
DOI
10.1007/s11187-015-9664-y
Subject
Economics and Econometrics / Business, Management and Accounting (all)

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The gender gap in federal and private support for entrepreneurship

Dora Gicheva . Albert N. Link

Accepted: 19 May 2015  Springer Science+Business Media New York 2015

Abstract The role of gender in entrepreneurship has been thoroughly investigated. However, less is known about gender differences in access to private investment when attempting to develop a new technology. In this paper, we use data collected by the National Research

Council of the National Academies to estimate differences between the probability that a female-owned firm and a male-owned firm, both conducting research funded by the Small Business Innovation Research program,will receive private investment funding to help to commercialize the funded technology. We find that female-owned firms are disadvantaged in their access to private investment, especially in theWest andNortheast regions of the USA.

Keywords Private investments  Entrepreneurship 

Gender  Technology  Innovation

JEL Classifications L26  O31  O38 1 Introduction

There is a growing literature on gender differences in labor market outcomes, such as competition and business performance. However, research related to gender differences in financing market outcomes, especially technology-based market outcomes, is limited. In this paper, we quantify gender differences in access to private investment funding by small, technology-based companies to support the development of a new technology.

The role of gender in entrepreneurship has been thoroughly investigated. For example, Blanchflower and Meyer (1994), Reynolds (1997), and Blanchflower and Oswald (1998) showed that women are less likely to start a new business or to be self-employed than men. However, less is known about gender differences in access to private investment when attempting to develop a new technology. A preliminary investigation by Gicheva and Link (2013) suggested that women are less likely to attract private investments to support technology developed from a

Small Business Innovation Research (SBIR) award from the National Institutes of Health (NIH). This paper extends Gicheva and Link’s earlier work on this topic by expanding both the sample of awards to all relevant agencies and the structure of the empirical model. 2 Analytical model

Based on project and firm information from the

National Research Council (NRC) database of

D. Gicheva  A. N. Link (&)

Department of Economics, University of North Carolina at Greensboro, Greensboro, NC, USA e-mail: anlink@uncg.edu

D. Gicheva e-mail: d_gichev@uncg.edu 123

Small Bus Econ

DOI 10.1007/s11187-015-9664-y randomly selected SBIR-funded projects, we estimated1: Private Investmenti ¼ f X0ib   , where Private Investment measures the ability of a firm to attract private investment support for an ith SBIR-funded project and X is a vector of project and firm characteristics.

Data on 1027 completed Phase II projects were available in the NRC database on all relevant variables considered. These projects were funded through an

SBIR award at some point from 1992 through 2001 by one of five agencies: Departments of Defense (DoD) and Energy (DOE), NIH, National Aeronautics and

Space Administration (NASA), and the National

Science Foundation (NSF).2

Phase I awards assist firms to assess the feasibility of an idea’s scientific and commercial potential in response to the funding agency’s objectives; they currently provide up to $150,000 for a 6-month period.

A subset of Phase I recipients is invited to apply for a

Phase II award to develop further the proposed research, ideally leading to a commercializable product, process, or service. Phase II awards are up to $1,000,000 for a 2-year period.

The Small Business Reauthorization Act of 2000 mandated that, among other things, the NRC of the

National Academies conducts: ‘‘an evaluation of the economic benefits achieved by the SBIR program….’’

In its evaluation, the NRC conducted an extensive and balanced survey in 2005 from a population of 11,214 completed from Phase II projects. The total number of projects surveyed by the NRCwas 6408; 1916 projects responded, and of those, 1027 were completed before the survey date and reported all of the information needed for this study.3

Private Investment was measured dichotomously (PI) as well as by the ratio of the amount of private investment to the amount of the SBIR award

Table 1 Definition of the variables

Variable Definition Mean Standard deviation

Range

PI If owner of firm received any private investment funding for the development of the SBIR-funded technology (1 = yes) 0.2707 0.4445 0/1 $PI/$Award Ratio of the amount of private investment received to the amount of the SBIR award 1.215 9.91 0/207.1

Female If owner of firm is a woman (1 = yes) 0.1285 0.3348 0/1

Nascent If firm receiving the SBIR award is the first firm the owner ever founded (1 = yes) 0.4606 0.4987 0/1

Age Age of firm measured as (2005—year founded) 17.5 11.13 5/105

West Census region (= 1) 0.333 0.4715 0/1

Northeast Census region (= 1) 0.2795 0.4489 0/1

Midwest Census region (= 1) 0.149 0.3562 0/1

South Census region (= 1) 0.2386 0.4264 0/1

DOE Agency funding the SBIR project (= 1) 0.0798 0.2712 0/1

DoD Agency funding the SBIR project (= 1) 0.4674 0.4992 0/1

NASA Agency funding the SBIR project (= 1) 0.0857 0.28 0/1

NIH Agency funding the SBIR project (= 1) 0.2775 0.448 0/1

NSF Agency funding the SBIR project (= 1) 0.0896 0.2857 0/1 1 The NRC database is arguably the most complete source of publicly supported innovative behavior in small, technologybased firms in the USA. For a detailed discussion of the NRC database and of the SBIR program, see Link and Scott (2010, 2012). 2 These are five largest agencies with SBIR programs. Collectively, they account for over 97 % of all SBIR awards. 3 SeeWessner (2008) for more detail about the NRC’s sampling procedure. Selection is not an econometric problem (Link and

Scott 2010, 2012). Nevertheless, we did control for selection in the models presented in Table 2, and we rejected that selection was present. Our selection model controlled for the time since receiving the award and the amount of the award.