FDI与上海经济增长关系的实证分析

本文根据1991～2002年上海的外商直接投资(FDI)和GDP时间序列数据,研究了FDI与上海经济增长之间的关系。研究结果表明,上海经济增长与FDI之间并不存在直接的因果关系。FDI对上海经济增长的直接作用并不明显,我们认为FDI对经济的推动作用体现在其“溢出效应”上。     

企业成长过程中组织结构演进规律及动因

阐述企业成长过程中组织结构的演变规律,运用管理学及经济学相关理论,揭示组织结构演变的内在动因。分析表明,随着企业的成长,组织结构呈现从直线职能制到事业部制的规律性变化,从管理学意义上,这种变化极大地降低了生产成本和流通费用,从而取得了管理协调的“速度经济”;从经济学意义上,则意味着管理分工导致企业运营效率提高;更深层次看,是一个分权的、控制权较为明晰的组织模式被逐渐使用,最终导致一个均衡权力结构模型———联邦分权式事业部制的产生。     

The econometrics of female labor supply and children

This is a survey of applied econometric research on the effects of children on female labor supply. Reasons for interest in the topic, and a basic model and terminology, are reviewed. Concerns are raised about the possible endogeneity of child status variables, and about the instrumental variables approach for dealing with this problem. Alternative ways of conceptualizing and estimating child status effects are considered, together with selected empirical evidence. Relevant developments from the household demand literature are summarized. Basic issues of model choice are also discussed.     

On Rao score and PearsonX 2 statistics in generalized linear models

The identity of the Rao score and PearsonX ² statistics is well known in the areas where the latter was first introduced: goodness-of-fit in contingency tables and binary responses. We show in this paper that the same identity holds when the two statistics are used for testing goodness-of-fit of Generalized Linear Models. We also highlight the connections that exist between the two statistics when they are used for the comparison of nested models. Finally, we discuss some merits of these unifying results. Work financially supported by cofin. MIUR grants 2000 and 2002.     

Missing data and forecasting in multivariate time series: An application of the common components dynamic linear model

Summary The paper deals with missing data and forecasting problems in multivariate time series making use of the Common Components Dynamic Linear Model (DLMCC), presented in Quintana (1985), and West and Harrison (1989). Some results are presented and discussed: exploiting the correlation between series, estimated by the DLMCC, the paper shows as it is possible to update state vector posterior distributions for the unobserved series. This is realized on the base of the updating of the observed series state vectors, for which the usual Kalman filter equations can be applied. An application concerning some Italian private consumption series provides an example of the model capabilities.     

A vector of quarters representation for bivariate time series

In this paper it is shown that several models for a bivariate nonstationary quarterly time series are nested in a vector autoregression with cointegration restrictions for the eight annual series of quarterly observations. Or, the Granger Representation Theorem is extended to incorporate, e.g., seasonal and periodic cointegration.     

中国经济增长模式转型：供给结构视角分析

本文从供给结构角度分析了自1978年以来中国经济增长模式转型的特征，并针对存在的问题提出了相应的解决对策，旨在寻求经济增长模式转型的有效路径。     

Joint tests of non-nested models and general error specifications

This paper is concerned with joint tests of non-nested models and simultaneous departures from homoskedasticity, serial independence and normality of the disturbance terms. Locally equivalent alternative models are used to construct joint tests since they provide a convenient way to incorporate more than one type of departure from the classical conditions. The joint tests represent a simple asymptotic solution to the “pre-testing” problem in the context of non-nested linear regression models. Our simulation results indicate that the proposed tests have good finite sample properties.     

Optimal designs for generalized linear models

Summary This paper solves some D-optimal design problems for certain Generalized Linear Models where the mean depends on two parameters and two explanatory variables. In all of the cases considered the support point of the optimal designs are found to be independent of the unknown parameters. While in some cases the optimal design measures are given by two points with equal weights, in others the support is given by three point with weights depending on the unknown parameters, hence the designs are locally optimal in general. Empirical results on the efficiency of the locally optimal designs are also given. Some of the designs found can also be used for planning D-optimal experiments for the normal linear model, where the mean must be positive. This research was carried out in part at University College, London as an M.Sc. project. Thanks are due to Prof. I. Ford (University of Glasgow) and Prof. A. Giovagnoli (University of Perugia) for their valuable suggestions and critical observations.     

A Comparative Study of Model-based Tests of Independence for Ordinal Data Using the Bootstrap

When analyzing categorical data using loglinear models in sparse contingency tables, asymptotic results may fail. In this paper the empirical properties of three commonly used asymptotic tests of independence, based on the uniform association model for ordinal data, are investigated by means of Monte Carlo simulation. Five different bootstrapped tests of independence are presented and compared to the asymptotic tests. The comparisons are made with respect to both size and power properties of the tests. Results indicate that the asymptotic tests have poor size control. The test based on the estimated association parameter is severely conservative and the two chi-squared tests (Pearson, likelihood-ratio) are both liberal. The bootstrap tests that either use a parametric assumption or are based on non-pivotal test statistics do not perform better than the asymptotic tests in all situations. The bootstrap tests that are based on approximately pivotal statistics provide both adjustment of size and enhancement of power. These tests are therefore recommended for use in situations similar to those included in the simulation study.