Determinants of the entrepreneurial gender gap in Latin America


This paper identifies a set of factors associated with the decision to become an entrepreneur and the variables that account for the gender gap in entrepreneurial activity in Latin America. We estimate logit models for entrepreneurial activity under three different definitions of an entrepreneur. We also estimate the gender gap by using Fairlie’s decomposition method. Depending on the definition of entrepreneur used, the overall gender gap varies from 4 to 13 % points. Differences in observable characteristics explain between 23 and 38 % of the total gender gap. The factors that explain both entrepreneurial activity and gender gap are: education, risk tolerance; own car as primary means of transportation; work satisfaction; and parent business ownership. Variables such as age, access to loans, and need for achievement are significantly associated with entrepreneurial activity, but they play a negligible role in explaining the gender gap.

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Fig. 1

Source: CAF household survey, 2012


  1. 1.

    For a recent literature review see Simoes et al. (2013).

  2. 2.

    The answers are provided using a 5-level Likert-type scale.

  3. 3.

    Table 10 in “Appendix” shows the percentage of information lost for each definition of entrepreneur.

  4. 4.

    In gender analysis, since females are considered a minority or disadvantaged group, it is a common practice to calculate the explained part using male coefficients as it is assumed that males have a “non-discriminatory” coefficient structure. Since the phenomena studied here may not be strictly due to discrimination, we use pooled coefficients in our estimations.

  5. 5.

    Yun (2004) presents a review of other detailed decomposition proposed in literature including his own method. Given that the specification of our models depends on the use of many categorical variables, in the present analysis we chose to present results using Fairlie’s decomposition.

  6. 6.

    We thank an anonymous referee for suggesting this possible explanation.

  7. 7.

    We are not able to perform estimations for separate countries due to the small size of the employer entrepreneur group.

  8. 8.

    We thank an anonymous referee for suggesting these possible explanations.

  9. 9.

    Results using male coefficients are reported in Table 8 in “Appendix.”


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We would like to thank the participants at the ICSB 2014 World Entrepreneurship Conference held in Dublin, Ireland, and two anonymous referees for their valuable comments and suggestions. We acknowledge the financial support we have received from Universidad Icesi. Jose Javier Morán provided excellent research assistance. The usual disclaimer applies.


This study was funded by Universidad Icesi, Cali, Colombia.

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Correspondence to German Lambardi.

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See Tables 4, 5, 6, 7, 8, 9, and 10.

Table 4 Economic and labor market indicators for sample countries
Table 5 Variable definition
Table 6 Descriptive statistics
Table 7 Logit estimates and odds ratios for the probability to become an entrepreneur—female
Table 8 Logit estimates and odds ratios for the probability to become an entrepreneur—males
Table 9 Fairlie’s decomposition using male coefficients
Table 10 Percentage of individuals, by definition of entrepreneur, who do not report income

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Bernat, L.F., Lambardi, G. & Palacios, P. Determinants of the entrepreneurial gender gap in Latin America. Small Bus Econ 48, 727–752 (2017).

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  • Entrepreneurship
  • Gender gap
  • Decomposition analysis
  • Personality traits
  • Latin America

JEL Classifications

  • L26
  • O17
  • J23
  • M13