Attempts to examine impacts of training on business outcomes face additional difficulties when training influences the rate of business survivorship or the likelihood of business start-up. For example, Giné and Mansuri (2011) find that training led to a 6.1 percent reduction in business failures for male owners (significant at the 10% level only). If training leads to survival of relatively unsuccessful firms who would otherwise have closed, then a straight comparison of profits or sales by treatment status will understate the impact of training. Giné and Mansuri attempt to address the differential survival issue by bounding, an approach which has also been used in several other studies. Note that even if training has no impact on the rate of business survivorship or start-up, it may still affect the characteristics of who survives, again requiring authors to use non-experimental methods to attempt to deal with this selectivity. For example, de Mel et al. (2012) find that training (and grants) led to changes in the characteristics of who opens a business, even though the rates of ownership were no different in the treatment and control groups. They therefore use a generalized propensity score to reweight their regression estimates to correct for the selectivity they find on observables like ability and wealth.

# _Measurement Changed by Training_

A final challenge for measuring the impact of business training on business outcomes is measuring those outcomes. Start-up and survivorship are objective measures that can at least be somewhat verified, whereas measuring business practices, profitability, and revenues for most firms is more difficult. Business practices (e.g. keeping accounts, separating business and household expenses, advertised in the past month) are normally relatively easy concepts for firms to understand, and questions that firm owners are usually willing to answer. However, Drexler et al. (2012) note the possibility that treated individuals may _report_ doing certain behaviors (e.g. separating personal and business accounts) because the training told them this was important, rather than because they actually do this.

Measuring profits and revenues poses further problems. Owners of the smallest businesses typically do not keep written records of these items, and owners of larger firms who do keep records may be reluctant to share them (because of concerns about theft, or because of taxation issues). De Mel et al. (2009a) study several approaches to obtaining profits from microenterprises and conclude that, in their context at least, a simple direct question is more accurate and much less noisy than calculating profits from revenues and expenses. However, collecting profits has proved difficult for many studies, with several studies not collecting profit data at all (Valdivia, 2012; Giné and Mansuri 2011; Klinger and Schündeln, 2011), collecting it but not using it due to too much noise (Drexler et al, 2012), or collecting only profit margins on the main product, rather than overall profits (Karlan and Valdivia, 2011).<sup>7</sup> Most studies have collected revenue data (Bruhn and Zia, 2011 is an exception), but some have struggled with much lower response rates for revenues than for non-financial business questions (e.g. Drexler et al, 2012 have a 46 percent attrition rate on revenues compared to 13 percent for their questionnaire as a whole). Similarly, Bruhn and Zia (2011) note that about one-third of clients in their study did not provide profit data.

> 7 In addition profits are not examined in two studies which look at business start-up as outcomes – Field et al. (2010) and Premaud et al. (2012).

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