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.     

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。