Issues in the estimation and application of latent structure models of choice

Our paper provides a brief review and summary of issues and advances in the use of latent structure and other finite mixture models in the analysis of choice data. Focus is directed to three primary areas: (1) estimation and computational issues, (2) specification and interpretation issues, and (3) future research issues. We comment on what latent structure models have promised, what has been, to date, delivered, and what we should look forward to in the future.     

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.     

Bivariate and multivariate scaled association models. An application to homogamy of social origin and education in Hungary between 1930 and 1979

In this article we compare bivariate and multivariate models for homogamy of social origin and education to test whether bivariate models of homogamy lead to biased results. We use data on Hungarian couples married between 1930 and 1979 and loglinear models of scaled association. The results indicate some differences between bivariate and multivariate analyses. At each point of time bivariate models overestimate homogamy, both with respect to education and social origin. However, results on trends in time do not differ much between the two analyses. The exception is the period 1940–1959, in which bivariate analysis showed decreasing educational homogamy, and multivariate analysis showed an increasing trend. The latter finding can be explained by declining homogamy of social origin, as well as the weaker reproduction and cross-effects in this period.     

专门化、多样化和中国地区工业产业增长的关系

本文通过分析中国29个省（除西藏外）的30个工业产业在1988－1997期间的数据。揭示了工业结构和经济增长之间的关系。本文除研究了传统的生产要素的影响外，重点探讨了产业专门化、专业多样化、竞争度和一省发展的初始水平等因素的作用。结果表明，一个产业外部工业环境的多样性和产业内的竞争度有利于产业的增长，但产业专门影响为负。工业结构对于增长的影响在很大程度上依赖于产业的性质及其地理位置。