江苏居民收入分配差距及其治理分析

改革开放以来,江苏居民收入普遍提高,人民生活得到很大改善,但近年来居民收入开始出现差距并且日益扩大,已成为影响社会稳定和经济发展的重要问题。文章首先分析了江苏居民收入分配的现状,然后剖析了影响居民收入分配差距过大的成因,在此基础上提出了防止居民收入差距过大的治理对策。     

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.