Vulnerability and industrial hazards in industrializing countries: an integrative approach

The extra vulnerability of industrializing countries to environmental problems and industrial accidents cannot be understood or solved by a ‘normal’ scientific analysis. Aspects of the social and institutional context must be included, through analyses based on post-normal science. The standard two-dimensional classification of PNS is modified to have axes ‘social ‘and institutional vulnerabilities’ and ‘complexity of technological hazards’. The analysis is mainly applied to the case of the relatively rare accidents with catastrophic potential. In these, the deaths per accident in India, Mexico and Brazil are much greater than in the industrialized countries. This discrepancy arises partly from location of such plants near residential communities for marginalized workers and their families. Other socio-political factors are relevant, as the role of these countries in the global production system, the enforcement of safety and planning laws, quality of housing, and lifestyle of residents. Reducing the vulnerability of industrializing countries will therefore require major social policies and a comprehension of the limits of the normal scientific and economic approaches to such problems.     

DS-optimal designs in one way ANOVA

Characterization and construction of optimal designs using the familiar optimality criteria, for example A-, D- and E-optimality are well studied in the literature. However the study of the Distance Optimality (DS-) criterion introduced by Sinha (1970) has very recently drawn attention of researchers. In the present article, we consider the singularly estimable full rank problem of estimating the full set of elementary treatment contrasts using the DS optimality criterion in the set up of a one way ANOVA model. Using a limit argument it turns out that a CRD in which difference between any two allocation numbers is at the most unity is uniquely DS-optimal. Acknowledgement. We are thankful to Prof. B. K. Sinha for suggesting the problem to us and many helpful discussions with him. We are also thankful to the referees for drawing our attention to the reference of Bischoff (1995) and many helpful comments.     

Budget deficits and real interest rates: Updated empirical evidence on causality

Using error-correction model (ECM) estimation, the paper empirically examines the causality relationship between the federal government budget deficit and the ex ante real interest rate yield on high grade long term tax free municipal bonds in the U.S. To clarify this deficit or interest rate relationship, the budget deficit is measured by the primary budget deficit, which excludes net interest payments by the Treasury. In a model that includes federal personal income tax rates and net international capital flows, as well as money supply growth, the ECM estimates strongly suggest a bi-directional relationship between the primary budget deficit and the ex ante real interest rate yield. Budget deficits apparently do matter! William Simon's concerns were justified.The author is indebted to P. A. V. B. Swamy for ideas and helpful suggestions and Will Perry for data assembly and processing.     

Additive and Multiplicative Uncertainty Revisited: What Explains the Contrasting Biases?

above the certainty level while for additive uncertainty the price should be lower than the certainty level. This note gives an intuitive explanation for the result after first presenting a parsimonious review of the two models. We also discuss which, if either, of the two models is more realistic. Received December 14, 2001; revised version received July 16, 2002 Published online: April 30, 2003 We thank referees for helpful comments. Ciaran Driver would like to acknowledge the research facilities from ANU, Canberra for their help in writing this paper.