effectiveness of heavily funded development programmes and projects. How does this state of affairs affect the decision process of policy makers? Assessing the effectiveness and efficacy of social policies has become a growing concern of policy makers. A comprehensive understanding of the socio-economic progress requires broader measures of development that encapsulate social, equity, and environmental concerns. There is a growing reliance of policy makers on micro-statistics targeting on particular areas, sectors, and groups. At the same time, there is the need to see these data aggregated into policy-relevant indicators for measuring and monitoring progress. The process of measurement and aggregation are multi-faceted, while new emerging areas pose challenges for statisticians especially in dealing with data relating to the noneconomic dimensions of development.
Along with the diversity in the growth patterns among countries in Asia and the Pacific, there is a great differentiation in the level of statistical development among countries. Also the level of statistical development corresponds to the stage of economic development. In most of the developing countries, the statistical infrastructure remains inadequate and there are large statistical gaps. If one were to visualize a statistics map of countries in Asia and the Pacific, the notation "data not available" will be concentrated among the least developed and landlocked countries, countries in transition and the Pacific island countries. The same can be said about the accuracy and timeliness of the data that are available. Since a large part of the responsibility for the production of statistics still rests with the government, the development and the maintenance of the statistical infrastructure will remain a key function of any government in the future. Hence, there is a pressing need for most developing countries in Asia and the Pacific to speed up the development of their statistical systems to produce timely, reliable and relevant data for policy formulation and decision making. There is also the urgent task for these countries to catch up with the level of statistical development of the more developed countries. Thus, the developing countries have to deploy additional resources and expertise to bridge the statistical gaps, as well as to simultaneously develop and implement new statistical frameworks. This poses a tremendous strain on their national statistical offices
