Published on Development Impact

Halloween Special: Small firm death, and did I mention zombies?

This page in:

With tomorrow being Halloween, I thought it perfect timing to discuss a paper about death and zombies. Small firms are an important source of income for the poor in developing countries, and the target of many policy interventions designed to help them grow. But we don’t actually know much about their death, with no systematic evidence available as to the rate of small firm death, which firms are more likely to die, and why they die. Indeed firm death often ends up being hidden in the attrition numbers of much of our data, and out of 35 published RCTs on interventions for small firms in developing countries, only 13 either report a firm death rate or look at death as an outcome.

My new working paper (ungated version) (with Anna Luisa Paffhausen) aims to provide systematic evidence on small firm death in developing countries. We spent several years cleaning and putting together data on more than 14,000 small firms from 16 firm panel surveys in 12 countries, enabling estimation of the rate of firm death over horizons as short as 3 months and as long as 17 years. Detailed questions added to nine of these panel surveys also enable us to dig deeper into cause of death.

What is the death rate of small firms?
Suppose you take a sample of firms that currently exist today (perhaps as the baseline for a planned intervention). How many of these firms should you expect to be alive one year from now, or five years from now?

Each of the 79 points in Figure 1 is a survey-time interval combination: e.g. the death rate over three years for firms in the Mexican Family Life Survey. The intervals are upper and lower bounds that account for attrition. The fitted curve shows the way the death rate varies with time.  The relationship is approximately linear over the first five years, with firms dying at an average of 8.3 percent per year over this interval.

Figure 1: Firm death rates over different time horizons
From the quadratic fit, 50 percent of firms are predicted to die within 6.2 years, while from the linear fit, 50 percent are predicted to die within 5.7 years. That is, half of all firms alive today in a country are likely to be dead within 6 years.

Which firms are more likely to die?
We examine death rates by owner and firm characteristics to establish stylized facts about which types of firms are more likely to die.

  • Young firms are more likely to die: a firm in its first year is estimated to have a 26 percent probability of failure in our data.
  • Among small firms, those with several workers are no less likely to die than one-person firms. Other studies find lower death rates for firms with 50 or 75 or more workers, but among firms with fewer than 10 employees, we don’t see differences in death rates with the number of employees.
  • Less profitable firms are more likely to die.
  • Retail firms are more likely to die than those in manufacturing or services.
  • Middle-aged owners have the lowest risk of their firm shutting down: the annualized death rate averages 18.0% for 20 to 24 year olds, compared to 9.6% for 45 to 49 year olds, and then starts rising again at older ages.
  • Firm death rates are higher for female-owners than for male-owners.

Firm death rates also seem to be higher in richer developing countries than poorer developing countries, as seen in Figure 2.
Figure 2: Annual Firm Death rates by GDP
Zombies or Phoenixes?
We define firm death as having occurred if a firm is open at one point in time, and then is reported as having shut down by the owner in a subsequent survey round. By shut down, we mean that the owner of the firm has decided to stop operating the firm, and no one else is operating it. It is not intended to include temporary closures of a few days or weeks that may occur when the owner is ill or away.

Nevertheless, we sometimes observe a firm to have closed down between survey rounds t and t+1, and then the exact same firm to be open again in survey round t. This type of zombie occurrence in which the dead firm reanimates to operate again is relatively rare: 6.2 percent of the firms in our sample are at some point observed to be zombies.
In contrast, it seems more common for a firm to close down, and then for the owner to open a different firm – perhaps a phoenix arising from the ashes of the old firm. Approximately 40 percent of owners of closed firms have opened a different firm within 3 years.

Why do firms die?
We consider three separate theories of firm death. The first views firm death as arising from firm competition and firm-level shocks causing firms to make losses and exit. Here firm death is involuntary, tends to cull less productive firms, and lowers the income of the owner. A second theory predicts firm death as arising from occupational choice decisions of the owner. Firm death can be voluntary here, with owners choosing to shut down when better outside opportunities arise, with less impact on poverty and less selectivity on productivity. A final theory is that firm death results from non-separability of business and household decisions due to imperfect markets. The result is that illness and shocks in the household can cause the business to have to close, resulting in income loss for the owner and not necessarily the least productive firms closing.

Using our cause of death data, we find that the most common reason for firm death is that less profitable and less productive firms end up making losses and closing. However, other small firms, particularly those run by women, close because of illness and family reasons, suggesting non-separability between the household and firm, while a minority of firms, largely run by more educated owners, close because better opportunities arise for the owner.

How might this be useful to you?

  • As a benchmarking tool: in my recent RCT of business training in Togo, I was surprised by how few firms had died, but until this paper, didn’t have much to compare to. Figure 2 above shows the death rate is not too different from the fitted line, and reflects the low income in the country. The rates in this study can hopefully be useful to others wondering whether death rates they see are normal or not.
  • As a planning tool for designing experiments: if you start with 500 firms now, the results suggest 40 or so will close each year – which matters for power calculations.
  • As a targeting tool for policy and intervention design: information on what types of firms are most likely to fail, and on the causes of death, should be helpful for either helping you avoid the firms most likely to die if your emphasis is on firm growth, or in targeting these types of firms if you are designing interventions/policies that are intended to help struggling firms survive.
  • As another example of using impact evaluation data to do more than just write a paper on the evaluation – see my old post on “one evaluation, one paper?” and Dave Evan’s post on how to write a paper using your baseline data for more on this (of course file this one under “how to write a paper using your panel data”).
  • Finally, if you or your children are all hopped up on sugar after trick-or-treating, the 37-page appendix in which we discuss all the gory details of carefully measuring firm death in each survey should serve as a wonderful sleep aid.


David McKenzie

Lead Economist, Development Research Group, World Bank

Join the Conversation

The content of this field is kept private and will not be shown publicly
Remaining characters: 1000