所有制结构、研发资源错配与研发回报率的相互关系——基于2005-2007年中国工业企业的经验数据

从研发资源错配的角度,以2005-2007年中国工业规模以上(微观)企业层面数据为样本,运用计量回归方法和数值模拟技术,研究了企业所有制结构与研发资源回报率之间的关系。研究表明,非国有企业的研发资本回报率比国有企业高,表明非国有企业受到较强的研发资源约束。数值模拟显示,当消除不同所有制企业之间的研发资本错配现象,把更多的研发资本从研发效率较低的国有企业重新配置到研发效率较高的非国有企业,可以使中国工业的研发产出提高2.9%⁶.4%。     

含控制因子的R/S分析的H参数估计及应用

R/S分析法是揭示金融时间序列长记忆性的主要方法之一。针对经典R/S与修正R/S分析法之不足,对R/S分析法进行改进,设计含控制因子的R/S统计量,并应用蒙特卡洛模拟说明改进的方法比经典R/S与修正R/S分析法在估计H指数上的有效性。运用新方法对上证综合指数和深圳成分指数收益率序列的长记忆性与两市的平均非周期循环长度进行实证分析,研究表明：沪、深股市的收益率序列都具有长记忆性,但是沪市的收益率序列不存在明显的平均非周期循环长度,而深市的收益率序列则存在一个大约308天的平均非周期循环长度。     

Estimating a covariance function having an un unknown scale kakameter

The structure of a family ρ of measures corresponding to a zero-mean Gaussian process with covariance αR(s,t) is discussed. When R itself is known (R and T completely arbitrary), it is shown that ρ is either homogeneous or composed of singular measures, depending on whether the reproducing kernel Hilbert space H(R,T) is finite- or infinite-dimensional. For the case dim H < ∞ the MLE α is given; when dim H = ∞ an almost sure discriminator is constructed. More generally, it is shown that when R itself depends upon a parameter θ (not necessarily a scalar) and certain broad assumptions are met, one may describe the orthogonal decomposition of P and estimate both a and θ.     

Book Reviews

Book reviewed in this article:
Van Wijngaarden, A. (Editor). Report on the Algorithmic Language ALGOL 68. Second printing by the Mathematisch Centrum, Amsterdam, ME101
David, F. N., Barton, D. E., Ganeshalingam, S., Harter, H. L., Kim, P. J., Merrington, M., and Walley, D. Normal Centroids, Medians and Scores for Ordinal Data. Series: Tracts for Computers
Hadley, G. Elementary Statistics
Hultquist, Robert A. Introduction to Statistics
Haber, A., and Runyon, R. P. General Statistics
Sachs, L. Statistische Auswertungsmethoden. Second edition
Johnson, N. L., and Kotz, S. Distributions in Statistics: Discrete Distributions
Anderssen, R. S., and Osborne, M. R. (Editors). Data Representation
Zuwaylif, F. H. General Applied Statistics
Schmitt, S. A. Measuring Uncertainty: An Elementary Introduction to Bayesian Statistics
Breipohl, A. M. Probabilistic Systems Analysis
Larson, H. J. Introduction to Probability Theory and Statistical Inference
Klugh, Henry E. Statistics: The Essentials for Research
Mosteller, F., Bush, R. R., and Green, B. F. Selected Quantitative Techniques and Attitude Measurement
Harnett, D. L. Introduction to Statistical Methods
Krutchkoff, R. G. Probability and Statistical Inference
Haber, A., Runyon, R. P., and Badia, P. Readings in Statistics
Milton, R. C. Bank Order Probabilities: Two Sample Normal Shift Alternatives     

An R Package for Value at Risk and Expected Shortfall

Value at risk and expected shortfall are the two most popular measures of financial risk. But the available R packages for their computation are limited. Here, we introduce an R contributed package written by the authors. It computes the two measures for over 100 parametric distributions, including all commonly known distributions. We expect that the R package could be useful to researchers and to the financial community.     

BOOK REVIEWS

Book reviewed in this article:
Real Variable. By J. M. Hyslop.
Basic Mathematics for Students of Economics. By R. S. G. Rutherford
Kendall, Maurice G., and Buckland, William R. A Dictionery of Statistical Terms.
Kendall, Maurice G., and Buckland, William R. A Dictionery of Statistical Terms—Supplement
Pearson, K. Mathematical Contributions to the Theory of Evolution.     

On the relationship between levinson recursion and the r and s arrays for arma model identification

Motivated by the papers of Woodward and Gray (1979) and Gray, Kelly and McIntire (1978) on the R and S array approach to ARMA modeling, the authors show that the R and S array algorithm is completely equivalent to Levinson recursion. Since entries in the R and S array can be computed by either algorithm, the equivalence provides greater insight into the R and S methodology as well as its links to Akaike's AIC or FPE. Numerical simulations serve to highlight the differences between the various approaches as well as illustrate the problems associated with exact methods. The K and S array approach is shown to be an effective procedure for determining ARMA model orders.     

Book Reviews

Book reviewed in this article:
Asymptotic Expansions for General Statistical Models. By J. Pfanzagl with the assistance of W. Wefelmeyer.
Canonical Analysis: a review with applications in ecology. By R. Gittins.
Contrast Analysis: Focused Comparisons in the Analysis of Variance. By R. Rosenthal and R. L. Rosnow.
Asymptotic Distribution Theory in Nonparametric Statistics. By Manfred Denker.
Quality by Experimental Design. By T. M. Barker.     

中国工业经济研发活动及其影响因素——基于2004-2008年面板数据的分析

应用2004-2008年中国大中型工业企业行业面板数据,从投入和产出两个层面探讨中国工业经济研发活动的影响因素,特别地分析了产权结构对创新活动的影响。结果表明：企业规模和研发投入之间存在较为稳定的正相关关系,“倒U型”假说成立;企业规模与研发产出的关系比较模糊,特别是如果使用专利数量衡量创新,企业规模和专利数量之间没有必然的联系,表现在资本密集型行业和劳动密集型行业的差异;国有资产比重增加无论对研发投入还是研发产出都有抑制作用,技术机会系数对于研发活动有显著的正影响。     

On the asymptotic distributions of the r and s arrays for identifying an arma process

The R and S arrays of an autoregressive moving- average process have been used for determining the orders of the process. In this paper the asymptotic distributions of the R and S arrays are presented.     

BOOK REVIEWS

Book reviewed in this article:
Statistical Inference – Based on the Likelihood. By A. Azzalini.
Inference and Asymptotics. By O.E. Barndorff-Nielsen and D.R. Cox.
Analysis of Variance, Design and Regression, Applied Statistical Methods. By R. Christensen.
Review of Cyclic and Computer-Generated Designs. By J.A. John and E.R. Williams.
The Exponential Distribution: Theory, Methods and Applications. Edited by N. Balakrishnan and Asit P. Basu.     

BOOK NOTICESs

Statistics in Schools throughout the World. Edited by V. Barnett. Voorburg: International Statistical Institute.
Statistical Tables for the Social, Biological and Physical Sciences. By F. C. Powell.
Elementary Statistics Tables. By H. R. Neave.
Statistics Tables. By H. R. Neave.
Regression Techniques for LGA Population Estimation. By P. J. Hughes and C. Y. Choi.
Capture-Recapture and Removal Methods for Sampling Closed Populations. By G. C. White, D. R. Anderson, K. P. Burnham and D. L. Otis.
Handbook of the Normal Distribution. By J. K. Patel and C. B. Read.
Edgeworth Expansions for Linear Combinations of Order Statistics. By R. Helmers.     

1961 Section Officers,Committees and Association Representatives

The multiple correlation coefficient, R (or r, in the simple case), is frequently used in evaluating regression models. Statistical significance is the usual criterion for judging R. Various views of its practical significance should also be considered. One practical measure is the percent reduction in the standard deviation of the response variable achieved by the model. A graph giving this as a function of R and percent loss in degrees of freedom is presented. This measure is compared with others which are sometimes appropriate.     

BOOK REVIEWS

Book reviewed in this article:
Calder, R., Benjamin, B., Passmore, R., Pirie, N. W., and Clark, C. Pood flapplies and Population Growth.
Moran, P. A. P. The Statistical Processes of Evolutionary Theory.
Guenther, W. C. Analysis of Variance.
Trumpler, R. J., and Weaver, H. F. Statistical Astronomy.
Grenander, U. Probabilities on Algebraic Structures.
Freeman, H. Introduction to Statistical Inference.
Fisher, R. A., and Yates, F. fitatistical Tables for Biological, Agricultural and Medical Research. Sixth Edition.
Owen, D. B. Pactors for One-sided Tolerance Limits and for Variables Sampling Plans.     

Note on estimation of reliability under bivariate pareto stress-strength model

In this paper, we discuss the problem of estimating reliability (R) of a component based on maximum likelihood estimators (MLEs). The reliability of a component is given byR=P[Y<X]. Here X is a random strength of a component subjected to a random stress(Y) and (X,Y) follow a bivariate pareto(BVP) distribution. We obtain an asymptotic normal(AN) distribution of MLE of the reliability(R).     

Reviews

Books reviewed in this issue.
Survival and Event History Analysis: a Process Point of View
O. O. Aalen, O. Borgan and H. K. Gjessing
Applied Spatial Data Analysis with R
Roger S. Bivand, Edzer J. Pebesma and Virgilio Gómez-Rubio
Introduction to Scientific Programming and Simulation Using R
O. Jones, R. Maillardet and A. Robinson
Simulation and Monte Carlo, with Applications in Finance and MCMC
J. S. Dagpunar     

不同渠道经费对科学与技术贡献的比较研究——基于空间面板模型的估计

基于中国科技投入产出的省际面板数据,用国际三大检索论文作为基础科学的产出变量,用授权专利作为应用技术的产出变量,采用空间相关指数Moran’s I分析了中国基础科学与应用技术的空间依赖与扩散,采用空间滞后模型分析比较了企业研发经费、政府研发经费、银行科技贷款对基础科学与应用技术贡献的弹性。研究结果表明,中国基础科学与应用技术的空间依赖比较明显,空间相关指数Moran’s I均值分别为0.510和0.492,由于基础科学与应用技术的溢出机制并不相同,因此基础科学的空间相关指数波动更大。政府研发经费的绩效总体良好,研发人员全时当量对技术创新的贡献更加明显,银行科技贷款的绩效较低,知识与技术溢出对研发要素投入弹性具有"挤出效应"。     

Reviews

Andersen, P. K., Borgan, O., Gill, R. D. and Keiding, N. Statistical Models based on Counting Processes
Anderson, T. W. and Finn, J. D. The New Statistical Analysis of Data
Azzalini, A. Statistical Inference—based on the Likelihood
Borodin, A. N. and Salminen, P. Handbook of Brownian Motion—Facts and Formulae
Brockwell, P. J. and Davis, R. A. Introduction to Time Series and Forecasting
Chapman, M. and Wykes, C. Plain Figures
Clarke, G. M. and Kempson, R. E. Introduction to the Design and Analysis of Experiments
Goldstein, H. and Lewis, T. (eds) Assessment: Problems, Developments and Statistical Issues; a Volume of Expert Contributions
Grenander, U. Elements of Pattern Theory
Högnäs, G. and Mukherjea, A. Probability Measures on Semigroups
Levitas, R. and Guy, W. Interpreting Official Statistics
van der Linden, W. J. and Hambleton, R. K. (eds) Handbook of Modern Item Response Theory
Ross, S. M. Simulation
Simonnet, M. Measures and Probabilities
Small, C. G. The Statistical Theory of Shape
van der Vaart, A. and Wellner, J. A. Weak Convergence and Empirical Processes with Applications to Statistics     

企业规模、创新能力与“熊彼特假说”——基于中国工业企业数据的研究

基于构建的非线性R&D活动投入产出弹性模型,以2007年《中国工业企业数据库》中35 369个企业样本的截面数据为研究对象,分析了企业创新能力与企业规模之间的关系特征.研究发现:在不同的企业规模定义下,R&D活动产出效率与企业规模之间呈现不同的关系,这一结论与已有研究不同.将企业分为高技术企业和中低技术企业之后,发现技术水平因素并不影响R&D活动产出效率与企业规模之间的关系.