6 residential or business line (normalized in the same way) was about 14 times larger in developing countries than in developed countries.

Even though the service is expected to become somewhat more affordable after the implementation of reforms, the elimination of cross-subsidies after the incumbent is privatized and the tariff rebalancing that often takes place may both increase the price of some services, including some of the residential services. Also, some characteristics of the reform process, such as the existence of exclusivity periods may influence the price upward. It is thus difficult to theoretically define the expected sign of the impact of reform policies on these indicators and hence on affordability.

Data on quality enjoys a much more limited coverage. There are some indicators on the quality perception of telephone services, but these are only available for two or three years at most. Thus, we rely on technical quality data reported by the telephone companies, which is available for a longer period of time. Specifically, we selected the number of reported telephone faults per 100 mainlines as a proxy for the quality of telephone services. The indicator is formally calculated by dividing the total number of reported faults during the year by the total number of mainlines in operation and multiplying by 100. It is important to note that the definition of faults might vary. Some countries include faulty customer equipment. Others distinguish between reported and actual faults found. There is also sometimes a distinction between residential and business lines. Another consideration is the time period as some countries report this indicator on a monthly basis; in these cases data are converted to yearly estimates. As measured here, quality seems to be remarkably worse in developing countries, with an average failure rate of 73%, compared to 19% in developed countries.

Our proxy for quality might be misleading in two ways. First, reporting faults might depend on the rules, regulations and dynamic of the sector in the country. Second, after reforms are implemented, companies may simply improve their reporting systems which may result in a larger number of the faults being measured. It is thus impossible to predict ex-ante the correlation between reform policies and reported faults because the improvements in reporting and measurement from regulatory reform may actually lead to a negative correlation. The net correlation is then the result of an actual performance change and a measurement change.

Finally, productivity is approximated by labor productivity simply because there is not enough data on capital and other inputs to get a better grasp of total factor productivity of the sector for a large enough number of countries and for a long period of time. Labor productivity data are also generated from the ITU database and approximated by the number of telephone mainlines per employee. This indicator is calculated by dividing the number of mainlines by the number of staff (with part-time staff converted to full-time equivalents) employed by telecommunications operators. Basic data reported in table 2 show that labor productivity is (on average) 2.5 times higher in developed than in developing countries. However, for both country groups, the expected correlation between productivity and reform policies is positive.

To provide a visual sense of performance at different scenarios of reform policies, we provide in table 3 a basic statistical summary that compares countries that have committed to reforms to those that have not as of 2003. We report the means, and below in parenthesis, we include the associated standard deviations and the number of