infrastructure sector is likely to hinder a private supply response to more general macroeconomic reforms.

Aterido et al. (2007) use employment growth as their dependent variable and regress on a large number of controls and objective business climate variables including three infrastructure ones: log of days with power outages, log of % of sales lost due to power outages and log of days without water. Their analysis is based on a sample of at least 80 Enterprise Surveys, considerably more than other papers. With respect to infrastructure, the authors find a significantly negative effect of power outages on employment growth for medium sized firms, and at least the expected sign for small and large firms.

Hallward-Driemeier and Aterido (2007) carry out a similar study with particular focus on Africa which produces interesting results. They regress employment growth on a variety of controls and business climate variables, including losses from power outages (% of sales), frequency of outages and whether a firm owns a generator as infrastructure indicators. They can confirm that a higher incidence of power losses is associated with a negative impact on employment growth. Interestingly, the authors find that African firms seem to have adapted to this problem to some extent so that given the frequency of outages, African employment growth is stronger than expected relative to the rest of the world. This has partly to do with the comparatively high incidence of generator ownership in Africa, which reduces the impact of power shortages from the public grid. However, another reason seems to be that a higher frequency of outages seems to have contributed to a disproportional concentration of African employment growth in very small firms, which are less capital intensive and thus less vulnerable to power outages in terms of employment effects.

Export status – whether or not a firm exports goods abroad – has also been studied as a dependent variable. As trade integration has often been associated with economic growth – both at the firm and country level – authors have been interested to test whether a relationship between business climate and export status can be found. Dollar et al. (2006) draw on a sample of firm level surveys from Bangladesh, Brazil, China, Honduras, India, Nicaragua, Pakistan and Peru to carry out probit estimations of whether the probability that a randomly chosen firm in a particular city exports is connected to business climate indicators (controlling for country and a number of other variables). They include ‘losses from power outages’ as their infrastructure indicator and find it to have a negative and significant impact on the probability of exporting in all their specifications.

Datta (2008) uses Enterprise Survey data from India to investigate the effects of a highway improvement program on the production efficiency of firms. Datta’s paper is particularly interesting for the way he exploits panel data to avoid the reverse causality problem stemming from the fact that better economic performance may attract more infrastructure, rather than more infrastructure causing firms’ efficiency to improve. Datta argues that if ‘the precise route of the highway was not manipulated to include some intermediate areas (counties, districts, cities) and exclude others based on factors correlated with the outcomes of interest, then the highway construction can be 17