With the exception of Ireland, transport is rated as an above average constraint only in ‘a handful of poor or war torn economies’. Telecommunications does not appear at all in Carlin et al.’s main ranking, possibly indicating the extent to which the rapid spread of mobile phones has reduced the importance of this constraint. It also underlines the need to update the objective survey questions referring to ‘mainline’ telephone services only.

An analysis of infrastructure statistics based on objective indicators is provided by Lee and Anas (1992) and Lee, Anas and Oh (1996; 1999) for Nigeria, Indonesia and Thailand. Their analyses are _not_ based on the standard Enterprise Survey (ES) data, but on three dedicated surveys that were carried out in the late 1980s and early 1990s. The infrastructure information they collected, however, is very similar to the one available in the ES database.<sup>39</sup> Lee et al. focus on the incidence of public infrastructure deficiencies, the extent of private provision responses to these deficiencies and the costs thereby imposed. They find large variations in the availability and quality of public infrastructure across the three countries, across regions within the countries and across firm sizes. In general, Nigeria tended to have a worse public infrastructure performance and a correspondingly higher incidence of private provision than Thailand and Indonesia. The authors speculate that the comparatively worse problems in Nigeria are related to the country’s (then) tighter restrictions on private provision arrangements. Aimed at protecting inefficient public suppliers, these restrictions prevented the emergence of private infrastructure provision regimes more efficient than the simple ‘one firm, one generator’ model.<sup>40</sup> The authors argue in favor of ‘[opening] up the markets for power, water and other various infrastructure services’ in order to improve service reliability and reduce system congestion.<sup>41</sup> However, Lee et al. do not explore this suggestion in detail and do not discuss possible implications and problems (such as equity-efficiency trade-offs).

A key finding of the study is the disproportionate way in which smaller firms are affected by infrastructure deficiencies. In all three countries, small firms relied far more on the public supply than larger ones and were thus subject to the bulk of the power failure incidents.<sup>42</sup> Lee et al. argue that this was not because the ‘burden of poor electricity or water supplies is less per unit of output’ for smaller firms, but rather due to economies of scale in private provision of electricity and water, which means it is relatively cheaper for larger firms to avoid the public system and provide their own power and water. This result finds support in the much broader analyses of 80+ Enterprise Surveys by Aterido et al. (2007) who examine the deviation of perceived constraints from the average ranking. They find that small firms report electricity as a greater relative constraint than larger firms.<sup>43</sup> The authors make the intuitive argument that smaller firms are ‘more likely to be

> 39 The key descriptive statistics can be calculated in both cases: number of firms that own a generator; number of firms that own a private well; production time and sales value lost due to public infrastructure interruptions _et cetera_ . Stratification and sample sizes are also similar in both cases (a couple of hundred enterprises per country and year, stratified by industries, regions/cities and firm size).

> 40 Lee, K.S., A. Anas and G. Oh. 1999: 2141.

> 41 _Ibid._ : 2149.

> 42 _Ibid._ : 2138. See also World Bank (2004): Box 6.10.

> 43 Note that Figure 6.4 in the World Development Report 2005 shows that a greater percentage of large than small firms rank infrastructure constraints as ‘major’ or ‘severe’. However, this is not inconsistent with smaller firms

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