Decomposition of Technological Change and Factor Bias in Indian Power Sector: An Unbalanced Panel Data Approach

Technological change and factor bias in the Indian power sector are analyzed using a translog cost function. Various components of technological progress and factor bias are identified and estimated, using a 21 year unbalanced panel data of Indian states and union territories. Heterogeneity across states is incorporated in the model using a variance component model. Appropriate corrections are made for unbalanced panel data. Empirical results show that the annual average rate of technological progress has been 2.4% for the country as a whole. Accumulation of knowledge and increasing scale are found to be the major factors contributing to technological progress. In contrast, the effects of factor price changes and fixed capital accumulation on technological progress have been unfavorable. Pure factor bias measure indicate saving in the use of fuel and labor, and increased use of materials. Tests are performed to check the curvature properties of the underlying technology.     

Investment in Africa's Manufacturing Sector: A Four Country Panel Data Analysis

Firm level data for the manufacturing sector in Africa, presented in this paper, shows very low levels of investment. The importance of profit effects on investment is investigated using a flexible accelerator, a specification based on the Euler equation and a simple generalisation of these specificiations. There are controls for firm fixed effects. It is shown that the profit effect is very similar for both the accelerator and Euler equation specifications. A comparison with other studies shows that, for small firms, the effect is much smaller in Africa than for other countries. Reasons for the relative insensitivity of investment to profits in African firms are suggested. For the most general specification tested there are no significant differences in the size of the profit effect across the four countries in the study.     

Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor

Abstract

This paper considers the problem of prediction in a panel data regression model with spatial autocorrelation in the context of a simple demand equation for liquor. This is based on a panel of 43 states over the period 1965–1994. The spatial autocorrelation due to neighbouring states and the individual heterogeneity across states is taken explicitly into account. We compare the performance of several predictors of the states’ demand for liquor for 1 year and 5 years ahead. The estimators whose predictions are compared include OLS, fixed effects ignoring spatial correlation, fixed effects with spatial correlation, random-effects GLS estimator ignoring spatial correlation and random-effects estimator accounting for the spatial correlation. Based on RMSE forecast performance, estimators that take into account spatial correlation and heterogeneity across the states perform the best for forecasts 1 year ahead. However, for forecasts 2–5 years ahead, estimators that take into account the heterogeneity across the states yield the best forecasts.     

Durations in Panel Data Subject to Attrition: A Note on Estimation in the Case of a Stock Sample1

In the empirical analysis of unemployment durations or job durations, it is generally assumed that the stochastic processes underlying labour market behaviour and the behaviour concerning participation in a panel survey are independent. As a consequence, spells that are incomplete due to attrition can be treated as spells that are subjected to independent right censoring. However, if the assumption of independence is violated, i.e. if for example the probability of dropping out of the panel is related to the rate at which a job is found, then attrition may have to be modelled and estimated jointly with the unemployment duration distribution to avoid biased estimates of the rate at which individuals become employed. A way to model the joint dependence is by means of stochastically related unobserved determinants. We discuss some properties of these kinds of models and state conditions needed to estimate such models in the case of stock sampled duration data.     

会计信息与股票价格关系分析

一直以来会计界试图通过会计信息解释股票价格。本文在总结国内外理论与实证研究的基础上,分析了这一研究领域的发展,并通过引入剩余收益模型,探讨会计信息与股票价格之间的关系。     

基于面板数据的我国制造业R&D投入对专利产出的影响实证分析

基于2000年-2005年制造业29个行业的数据,运用面板数据模型实证研究了我国制造业R&D投入对专利产出的影响。结果表明:我国制造业各行业R&D经费投入对专利产出的影响显著,技术密集度较高的行业R&D经费投入弹性系数较高,反映了这些行业存在着较大的技术创新机会;而R&D人员投入弹性系数较低,说明我国制造业行业存在着冗员现象。针对分析结果,我们提出了相应的对策建议。     

黄金期货价格与我国黄金采选业股票价格关系的实证研究——以山东黄金股票价格为例

本文通过对我国黄金期货价格和相关股票价格之间关系的研究,试图把握其内在规律,为相关行业、企业、市场参与者和市场监管部门提供有价值的市场信息,从而可以正确认识我国目前黄金期货市场的价格发现功能,以及股票市场的运行效率。     

我国的货币供应与股指的相关性分析

M1、M2-M1的同比增速以及M2-M1的增速差与股指走势的相关性较高,经常被用于预测股指的变化,因此本文将从理论分析以及实证分析两方面对各个指标与股指的相关性进行。     

基于异质面板因果检验的债务与盈利关系研究

以1994年-2004年沪深股市具有连续数据的179家A股上市公司的面板数据为样本,采用Hurlin的格兰杰因果关系检验修正模型对债务与盈利之间的相互关系进行了检验,证明了企业盈利和负债之间存在着相互影响。固定效应的变截距模型的回归结果表明负债对盈利起负的作用,而长期债务对企业盈利则起正的促进作用,并且资产负债率对企业盈利的影响比债务期限结构的影响要大。     

交通基础设施投资对经济增长推动作用研究——基于中国省级面板数据分析

本文依据生产函数模型和我国1994-2007年度30个省级地区(重庆市包含在四川省内)面板数据分析交通基础设施投资对我国各省份经济增长推动作用,得出在规模报酬不变条件下,我国各省份交通基础设施投资产出系数,进而得出经济越发达地区,交通基础设施投资对于经济增长贡献越大的结论。     

Bootstrap J-Test for Panel Data Models with Spatially Dependent Error Components,a Spatial Lag and Additional Endogenous Variables

We develop a bootstrap J-test method for testing a panel model against one non-nested alternative when the competing specifications are estimated by Feasible Generalised Spatial Two Stage Least Squares/Generalised Method of Moments (FGS2SLS/GMM). Both models incorporate spatially correlated error components, thus accounting for spatial heterogeneity via random effects, and accommodate endogenous regressors other than the spatially lagged dependent variable. The proposed scheme is applied to a testing problem involving non-nested wage equations as motivated by the Wage Curve literature and the New Economic Geography theory. Results show that our bootstrap test is a reliable and effective procedure for correcting asymptotic reference critical values and distinguishing between the two rival hypotheses.     

我国股票市场与经济增长弱相关性的实证分析

我国股票市场与经济增长之间究竟存在怎样的关系,在理论界一直存在争议,本文对二者之间的关系进行了理论研究并通过经济计量学中的多元回归模型展开了实证分析,最后得出我国股票市场与经济增长之间存在弱相关性的结论。     

股票数据初探——移动平均与烛状图分析

论文讲述了如何利用Python对多只股票进行数据分析,并且分析每只股票间的异同。运用Python,可将股票数据进行可视化处理,例如,运用线性图展现出股票随时间的变化情况;利用烛状图了解每只股票每日闭市与开市相比的盈利或者亏损情况;利用移动平均值直观地观察在规定时间内股票价格变动,了解股票价格是否稳定。论文以制定更好的决策为目的,从数据可视化入手,提供优质有效的数据信息,运用数据挖掘技术对微软、苹果、谷歌等多只股票价格波动趋势进行研究。     

我国证券投资基金重仓持股变动对股票价格波动性影响的实证研究

文章采用了2006年第一季度到2008年第四季度国内证券投资基金公布的季度数据,运用动态面板数据模型对我国证券投资基金重仓持股变动与股票价格波动性之间的关系进行了实证研究。结果表明,在牛市中证券投资基金重仓持股比例的变化与股价波动性成正向关系,加剧了股价的波动;在熊市中证券投资基金持股比例变化与股票价格波动性成反向关系,起到了稳定证券市场的作用。     

The Relationship Between Stock Market Returns and Technical Efficiency Innovations: Evidence from the US Airline Industry

This paper analyzes the association between two firm performance measures: stock market returns and relative technical efficiency. Using linear programming techniques (Data Envelopment Analysis and Free Disposal Hull), technical efficiencies are calculated for a panel of eleven US airlines observed quarterly from 1970–1990. A relationship, between efficiency news in a quarter and stock market performance in the following two months, is found. A risky arbitrage portfolio strategy, of buying firms with the most positive efficiency news and short-selling those with the worst news during this time frame, results in zero beta risk yet yields annual returns of 17% and 18% for the two methodologies.     

Centres and Peripheries in Finland: Granger Causality Tests Using Panel Data

Abstract

Despite their importance from a policy point of view, empirical studies on the effects of growth centres in their regions are rare. This paper analyses mutual relationships between growth processes in centres and their surrounding hinterlands in 19 Finnish regions. Annual population data from the period 1970–2004 are used. A novel testing procedure based on an extension of the Granger causality definition in a panel data context is applied. Heterogeneity between regions is allowed. Both the homogeneous non-causality hypothesis and the homogeneous causality hypothesis are rejected. Causal processes prove to be heterogeneous. Causality from centres to peripheries is found for nine regions and causality from peripheries to centres for twelve regions. Rapidly growing and large centres, in particular, have negative effects on their hinterlands.

Centres et banlieues en Finlande: tests de causalité de Granger faisant usage de données de panel

RÉSUMÉ?En dépit de leur importance sur le plan de la politique, les études empiriques sur les effets des centres d'expansion dans leurs régions sont rares. La présente communication analyse, dans dix-neuf régions de la Finlande, les rapports réciproques entre procédés d'expansion dans les centres et leur arrière-pays environnant. Pour ceci, on utilise des données sur la population annuelle remontant à la période 1970–2004. On applique une nouvelle technique de test basée sur une extension de la définition de Granger dans le contexte de données de panel. L'hétérogénéité entre les régions est admise. Tant l'hypothèse de la non causalité homogène que celle de la causalité homogène sont rejetées. Les techniques causales s'avèrent être hétérogènes. On relève une causalité des centres aux banlieues dans neuf régions, et des banlieues aux centres ville dans douze régions. Notamment, les centres ville de grande taille et en pleine expansion ont un effet négatif sur leur arrière-pays.

Centros y periferias en Finlandia: Ensayos de causalidad de Granger utilizando datos de panel

RÉSUMÉN?A pesar de su importancia desde un punto de vista de políticas, los estudios empíricos sobre los efectos de los centros de crecimiento en sus regiones son escasos. Este trabajo analiza las relaciones mutuas entre los procesos de crecimiento en los centros y sus interiores vecinos, en diecinueve regiones finlandesas. Se utilizan datos anuales de población entre el período de 1970–2004. Se aplica un nuevo procedimiento de ensayo basado en una extensión de la definición de causalidad de Granger dentro de un contexto de datos de panel. Se tiene en cuenta la heterogeneidad entre regiones. Se rechazan tanto la hipótesis de no causalidad homogénea como la hipótesis de causalidad homogénea. Los procesos causales demuestran ser heterogéneos. Causalidad de centros a periferias se encuentra en nueve regiones, y causalidad de periferias a centros en doce regiones. Los centros grandes y de rápido crecimiento, en particular, tienen efectos negativos sobre sus interiores.

     

我国零售企业库存成因分析及控制策略研究

随着我国零售行业的迅速发展以及大量外国零售巨头的涌入,零售业的竞争日趋白热化。我国大部分零售企业尚处于整合、发展期,经营和管理水平落后于国外同行。尤其是作为零售企业核心技术之一的库存控制存有诸多缺陷。如何合理库存,加快资金周转．提升企业竞争力是我国零售企业必须解决的课题．     

库存周转分析的准确性研究

分析了目前在库存周转分析中存在的由于周转分析的复杂性而产生的周转参数的不准确性问题,分析了产生这种不准确性的原因,提出了解决的建议和一种新的周转指标用于企业或仓库以及物流系统节点的周转分析。     

当前猪肉价格上涨原因及对策分析

六月份以来,全国猪肉价格快速上涨,很多地方猪肉价格突破历史高位,引起社会各界的广泛关注,如何理性看待这一轮猪肉价格上涨,以及如何建立、健全市场体系、体制,防止猪肉价格再次出现大起大落,是文中研究的主题。