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As the market churns: productivity and firm exit in developing countries

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Abstract

This paper uses a unique dataset from the World Bank’s Enterprise Surveys in 47 economies to analyze the conditions under which firms leave heterogeneous markets. Consistent with expectations, we show that firm productivity (and age) are significant determinants of firm exit. Cross-country analysis shows, however, that the relationship between productivity as well as age and exit is mitigated by some country-level factors. In particular, we show either’s effect is substantially weakened in low-income economies, economies with limited openness to international trade, and in economies with cumbersome bankruptcy procedures. To address issues of sample attrition and selection bias presented by survey-based estimates, corrections are applied using information when a firm’s operating status is uncertain. The expected negative relationship between firm labor productivity and the likelihood of exit is robust to these corrections, as is the negative relationship between firm exit and age.

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Notes

  1. Examples include Liu (1993), Liu and Tybout (1996), Bartelsman et al. (2004), Shiferaw (2009), Sandefur (2010), Klapper and Richmond (2011), Hallward-Driemeier and Rijkers (2013), and Eslava and Haltiwanger (2014).

  2. Several influential theoretical works include Jovanovic (1982), Hopenhayn (1992), Ericson and Pakes (1995), Olley and Pakes (1996).

  3. φ it could also denote the current resale value of the business.

  4. Broadly, these are considered factors of production. While fundamental, a firm’s capital k it presents several measurement complications, including that there is no reliable way to measure it for service firms in our dataset. As a result, we do not include capital directly in our firm-level co-variates, but consider it as proxied by firm size, though size may also capture other characteristics.

  5. It is important to note that distortions may also factor into firm productivity itself, particularly depending on how the concept is defined. For example Foster et al. (2008) lay out the difference between quantity-based and revenue-based productivity measures, noting that the latter are more often available but are unable to separate out distortions through such channels as market power or asymmetric information, each of which can affect the price and revenue function of a firm. Here, we note that the revenue function itself takes these into account and so we do not address revenue and quantity-based productivity distinctions.

  6. There is limited evidence on the link between firm exit and entry barrier policies, the few studies available indicating that these polices do not affect exits (Box 2008).

  7. Further, access to foreign markets enables firms to diversify sales and reduce exit risks arising from negative shocks to the domestic economy (Wagner and Gelübcke 2012; Bernard et al. 2002).

  8. Alternatively, several studies code firm exit as a firm falling below a certain threshold of (usually) employees.

  9. While issues of panel attrition bias have been thoroughly analyzed in numerous household (See Fitzgerald et al. 1998; Thomas et al. 2001; Alderman et al. 2000; Maluccio 2004; Khandker 2005), we have not encountered a thorough analysis of these effects in enterprise or business surveys, particularly in developing economies.

  10. To avoid further cluttering notation we omit country-level sub-scripts.

  11. This also includes firms that have exited the market by moving abroad or are no longer formally registered.

  12. We note that a third naive measure of exit is to consider Group 2 as exiting. For robustness, we ran regressions testing this and find no substantive differences; results are not reported here but are available on request.

  13. They use the Cox proportional hazard semi-parametric method to estimate firm duration or survival. While they find this to be preferable, such methods that are not generally dependent on observables require a full multi-period panel structure, which our data lacks.

  14. Rated by the interviewer.

  15. The initial round for Venezuela (2006) utilized a limited questionnaire and omits certain key covariates. As a result, we remove Venezuela for all analysis (n = 500) so as not to bias our results by the inclusion or exclusion of an entire survey round as new variables are introduced. Annex Table 1 provides the list of countries and survey years included in the analysis.

  16. The annualized exit rate is computed using compounded growth formula.

  17. As we are concerned with the average difference between the groups of exiters (attritors) and survivors within a country, the reported mean differences are the resulting coefficient(s) from an EXIT (ATTRITOR) dummy in the regression: Y =  α + β 1 EXIT it  + β ' COUNTRY' it  + μ it where Y represents the descriptive variable of interest and the vector COUNTRY’ is a series of country fixed effects. This avoids pooling problems across disparate countries at different income levels. In the regression specifications below this is addressed by the use of country-level fixed effects and market-level co-variates.

  18. For more information, the ES website includes a note on sampling methodology, here: http://www.enterprisesurveys.org/~/media/FPDKM/EnterpriseSurveys/Documents/Methodology/Sampling_Note.pdf

  19. Maluccio (2004)

  20. Maluccio (2004)

  21. Using the svy: prefix, Stata calculates an adjusted Wald test.

  22. For this reason and in the interest of space, we do not present further Heckman selection models here. All were run and are available upon request.

  23. This finding, though, has not been universal: Söderbom et al. (2006), for instance, find no or little relationship between firm age and exit.

  24. Bernard and Jensen (2007), for instance, find no significant evidence of a size effect on firm survival.

  25. That productive firms select to exporting has been widely documented. (see for instance, Haidar (2012))

  26. Odd-numbered columns in Table 7 are identical to those in Table 6.

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Acknowledgements

We are thankful to two anonymous referees and the journal editors for helpful comments.

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  1. Development Economics, Enterprise Analysis World Bank, 2121 Pennsylvania Avenue, NW F 4K-226, Washington, DC, 20433, USA

    Gemechu Aga & David Francis

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  1. Gemechu Aga
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  2. David Francis
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Correspondence to David Francis.

Appendix

Appendix

Appendix Table 1 Countries included and Sample size
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Appendix Table 2 Correlation Matrix for Firm-Level variables
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Appendix Table 3 Correlation Matrix for Market and country-level Variables
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Aga, G., Francis, D. As the market churns: productivity and firm exit in developing countries. Small Bus Econ 49, 379–403 (2017). https://doi.org/10.1007/s11187-016-9817-7

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