The main findings of the district pilot project of labour‐intensive road construction and maintenance in Botswana and the implications for similar projects in South Africa

Unemployment has been identified as one of the main problems confronting South Africa. Recently, in order to improve rural infrastructure and create employment, several pilot projects of rural road construction have been initiated in South Africa. In such a context it is considered that attention should be drawn to a pilot project carried out some time ago in Botswana to examine the potential of labour‐intensive methods in the construction and maintenance of rural roads.

The main conclusion of the pilot project was that labour‐intensive methods were viable, although attention had to be paid to several critical factors. In 1982, following its evaluation of the pilot project, the Government of Botswana decided that over the next five years the technical and organisational methods developed during the pilot project should be replicated throughout Botswana.

After a brief survey of the background to the project, the paper summarises several important features of the pilot project and its main findings. The paper closes with some comments on the implications of this pilot project for those currently underway in South Africa.     

A hospital without walls

Pacific Presbyterian Medical Center has chalked up an impressive string of successes. What's ahead? A $20 million cancer center.     

THE SOCIAL ACCOUNTS FROM A CONSUMER'S POINT OF VIEW

After a short introduction, the first part of this paper (section 3 through 9) provides an outline of the revisions proposed to the System of National Accounts (SNA) of the United Nations which are now under discussion. These proposals were considered by an expert group at the end of 1964 and were accepted by the Statistical Commission of the United Nations in 1965 as the basis for further work on the extension and revision of the SNA. The aim of the revision is to provide a fully integrated system of accounts and balance sheets in which input-output, flows-of-funds and sector balance sheets are incorporated in a generalised accounting framework. Whereas the real side of the economy has been studied analytically in many countries (input-output analysis, demand analysis and so on) much less experience is available on modelling the financial side of the economy, apart from econometric work on saving behaviour, which is fairly widespread. Accordingly, the second part of the paper (sections 10 through 14) contains a discussion of financial model-building in which a number of possibilities are explored. The final topic discussed (section 15) is demographic accounting, by which is meant a framework for recording and analysing human, as opposed to economic, flows and stocks. The development of such a system arose out of the emphasis placed by the expert group on the integration of demographic and economic information.     

Air pollution-mortality models: A demonstration of the effects of random measurement error

Errors of measurement have long been recognized as a chronic problem in statistical analysis. Although there is a vast statistical literature of multiple regression models estimating the air pollution-mortality relationship, this problem has been largely ignored. It is well known that pollution measures contain error, but the consequences of this error for regression estimates is not known. We use Lave and Seskin's air pollution model to demonstrate the consequences of random measurement error. We assume a range of 0% to 50% of the variance of the pollution measures is due to error. We find large differences in the estimated effects on mortality of the pollution variables as well as the other explanatory variables once this measurement error is taken into account. These results cast doubt on the usual regression estimates of the mortality effects of air pollution. More generally our results demonstrate the consequences of random measurement error in the explanatory variable of a multiple regression analysis and the misleading conclusions that may result in policy research if this error is ignored.