出口二元边际、行业异质性与劳动生产率

基于行业异质性视角,文章主要考察出口二元边际对劳动生产率的影响.利用UN Comtrade数据库,采用HK指数法测度中国出口深度边际和出口广度边际,发现中国出口产品种类基本覆盖了世界全部种类的90％.进一步地,借助聚类分析方法综合多种因素区分行业劳动技能异质性,出口二元边际与劳动生产率关系的实证结果显示:总体上出口深度边际显著推动劳动生产率提高,出口广度边际对劳动生产率产生抑制作用.更为重要的是,出口深度边际对劳动生产率的促进作用仅存在于高技能行业,受限于行业产品技术含量和劳动技能水平等,低技能和中等技能行业出口深度边际出现贫困化增长现象.出口种类扩张的生产率损失超过出口溢出效应的生产率收益,出口广度边际对高中低技能行业劳动生产率具有不同程度的负向影响.     

中国城镇化对服务业影响的区域差异——基于系统GMM模型的实证研究

目前中国服务业的发展离不开城镇化这一现实背景.文章选取2005-2015年省际面板数据,运用动态面板模型系统广义矩估计(SGMM)方法分别就城镇化对全国服务业发展的影响及其区域差异所做的实证研究结果表明:在全国层面上,城镇化水平对服务业发展有较显著的促进作用,但促进作用还比较小;在区域层面上,东部、中部、西部三大区域城镇化对服务业发展的影响也较小,且存在较明显的地区差异.基于研究结果,文章提出了从战略高度上重视加快新型城镇化进程以促进中国服务业更好发展,同时根据各区域的实际情况制定适宜的以城镇化促进服务业发展的政策措施等相关建议.     

A Unified Approach to Estimating and Testing Income Distributions With Grouped Data

We propose a unified approach that is flexibly applicable to various types of grouped data for estimating and testing parametric income distributions. To simplify the use of our approach, we also provide a parametric bootstrap method and show its asymptotic validity. We also compare this approach with existing methods for grouped income data, and assess their finite-sample performance by a Monte Carlo simulation. For empirical demonstrations, we apply our approach to recovering China's income/consumption distributions from a sequence of income/consumption share tables and the U.S. income distributions from a combination of income shares and sample quantiles. Supplementary materials for this article are available online.     

Empirical Characteristic Function Estimation and Its Applications

Abstract

This paper reviews the method of model-fitting via the empirical characteristic function. The advantage of using this procedure is that one can avoid difficulties inherent in calculating or maximizing the likelihood function. Thus it is a desirable estimation method when the maximum likelihood approach encounters difficulties but the characteristic function has a tractable expression. The basic idea of the empirical characteristic function method is to match the characteristic function derived from the model and the empirical characteristic function obtained from data. Ideas are illustrated by using the methodology to estimate a diffusion model that includes a self-exciting jump component. A Monte Carlo study shows that the finite sample performance of the proposed procedure offers an improvement over a GMM procedure. An application using over 72 years of DJIA daily returns reveals evidence of jump clustering.     

MRF和GM模型高光谱图像地物标记

利用马尔可夫随机场和高斯混合模型构造了一种对高光谱图像进行地物标记的新方法。该方法利用PCA降维后的高光谱图像及其差分图像的先验信息建立高光谱图像的随机模型,并把最大后验估计作为地物标记优化的评判标准,用模拟退火算法实现地物标记。实验结果显示该算法是一种精确、高效、稳定的图形标记算法。     

RECENTERED AND RESCALED INSTRUMENTAL VARIABLE ESTIMATION OF TOBIT AND PROBIT MODELS WITH ERRORS IN VARIABLES

Since Durbin (1954) and Sargan (1958), instrumental variable (IV) method has long been one of the most popular procedures among economists and other social scientists to handle linear models with errors-in-variables. A direct application of this method to nonlinear errors-in-variables models, however, fails to yield consistent estimators.

This article restricts attention to Tobit and Probit models and shows that simple recentering and rescaling of the observed dependent variable may restore consistency of the standard IV estimator if the true dependent variable and the IV's are jointly normally distributed. Although the required condition seems rarely to be satisfied by real data, our Monte Carlo experiment suggests that the proposed estimator may be quite robust to the possible deviation from normality.     

GMM Estimation with persistent panel data: an application to production functions

This paper considers the estimation of Cobb-Douglas production functions using panel data covering a large sample of companies observed for a small number of time periods. GMM estimatorshave been found to produce large finite-sample biases when using the standard first-differenced estimator. These biases can be dramatically reduced by exploiting reasonable stationarity restrictions on the initial conditions process. Using data for a panel of R&Dperforming US manufacturing companies we find that the additional instruments used in our extended GMM estimator yield much more reasonable parameter estimates.     

FDI对中国经济增长的区域效应和动态效应

以我国各个省市作为横截面单元,利用各横截面单元1988~2005年的样本组成面板数据,进而建立动态面板数据模型来考察FDI对我国不同地区经济增长的影响。结果表明,FDI对我国经济增长具有促进作用,但是滞后2期FDI对我国经济增长具有负面影响。同时,FDI对不同地区的影响有显著差异,对东部地区而言,FDI对经济增长的效应最为明显。     

Provincial Conditional Income Convergence in China, 1953-1997: A Panel Data Approach

This paper examines the tendency towards income convergence among China's main provinces during the two periods: the pre-reform period 1953-1977 and the reform period 1978-1997 using the framework of the Solow growth model. The panel data method accounts for not only province-specific initial technology level but also the heterogeneity of the technological progress rate between the fast-growing coastal and interior provinces. Estimation problems of weak instruments and endogeneity are addressed by the use of a system generalized method of moments (GMM) estimator. The main empirical finding is that there is a system-wide income divergence during the reform period because the coastal provinces do not share a common technology progress rate with the interior provinces.