_L. Fox and A.M. Oviedo_ _Institutions and Labor Market Outcomes in Africa_ to increase their labor demand (or to lay off many workers) simultaneously, as well as an complementary capital needed (working or for investment) to keep all these workers busy.

In any event, this measure suggests that the observed dynamics of employment in these firms hide a potentially even more dynamic sector. Table 11 shows that there is a large variance in _D_ across countries, as it ranges from 0.1 percent of employment in Rwanda to over 100 percent in Kenya. More Francophone firms report they would have a larger workforce than Anglophone, and the average _D_ of 13.4 is also higher than the Anglophone average, equal to 10.3. Yet the Anglophone firms average _desired increase_ in employment is much higher than the average Francophone one. For those firms who, on the other hand, would like to reduce their workforce, the numbers are much smaller: on average these firms in Anglophone countries would reduce their employment by 3.2 percent, and in Francophone countries they would reduce employment by 6.1 percent.

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Comparing firms’ responses between the 2003 and 2006 waves for Tanzania and Uganda, it seems that between these two years there has been a dramatic change in obstacles to labor adjustment. Indeed, in 2003 firms reported large deviations between potential and current employment, but this difference almost disappears by 2006; simultaneously, we observe a dramatic increase in employment growth, as shown in Table 3.

Quantifying the association observed across countries in our survey data between regulation, and EPL in particular, and employment growth in SSA firms, Table 12 shows correlation coefficients between the DB overall and labor rankings and different measures of actual and potential employment growth.<sup>25</sup> Note that a countries’ DB labor and overall DB score is not well correlated, indicating that the correlation that Botero _et al._ (2004) observe between sub-catgories of the regulatory regime does not apply as strongly for EPL in Africa than in other areas.<sup>26</sup> But as weak as this association is, it is the only significant one in the table. All the rest are not very high, nor statistically significant. As noted before, net job creation is not a good indicator of total labor adjustment, which could be well correlated with regulation even if net job creation is not. However, we also find little correlation between potential labor adjustment _D_ and regulation, measured either with the DB indicator, or with firms’ perceptions.

In summary, a preliminary inspection of the relationship between employment creation and labor regulation at the firm level reveals several intriguing facts: (1) employment growth is high across our entire sample in spite of a very “hostile” regulatory environment, as measured by the DB scores; (2) employment growth is no different between the “better” and the “worst” regulated countries (measured by DB); (3) there is little difference between countries industrial structure which could be related to labor regulation; (4) labor regulation does not appear to be a concern to firm managers; (5) in the absence of restrictions, firms would expand, rather than contract their workforce; and (6) there seems to be a structural change (at least in two countries) between 2003 and 2006 that allowed firms to expand employment.

> 25 We are grateful to John Haltiwanger for suggesting that we use correlation matrices to summarize these trends. 26Another reason for the low correlation is that the EPL DB indicator is quite narrow, relative the range of EPL instruments. It does not, for example, cover the costs of dispute resolution, which Ahsan and Pagés (2007) have shown is one of the most important aspects of DPL for firms. See Fox and Gaal, (2008) for a critique of this indicator as it applies to Africa.

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