A NEW APPROXIMATE GLS ESTIMATOR FOR THE REGRESSION MODEL WITH MA(1) DISTURBANCES

This paper introduces a new approximate GLS estimator for the regression model with MA(1) disturbances, which outperforms both the Balestra (1980) and the Park and Heikes (1983) approximations and which is almost as efficient as the exact GLS estimator.     

Generalized least squares and maximum likelihood estimation of the logistic function for technology diffusion

Given a simple stochastic model of technology adoption, we derive a function for technological diffusion that is logistic in the deterministic part and has an error term based on the binomial distribution. We derive two estimators—a generalized least squares (GLS) estimator and a maximum likelihood (ML) estimator—which should be more efficient than the ordinary least squares (OLS) estimators typically used to estimate technological diffusion functions. We compare the two new estimators with OLS using Monte-Carlo techniques and find that under perfect specification, GLS and ML are equally efficient and both are more efficient than OLS. There was no evidence of bias in any of the estimators. We used the estimators on some example data and found evidence suggesting that under conditions of misspecification, the estimated variance-covariance of the ML estimator is badly biased. We verified the existence of the bias with a second Monte-Carlo experiment performed with a known misspecification. In the second experiment, GLS was the most efficient estimator, followed by ML, and OLS was least efficient. We conclude that the GLS estimator of choice.     

ORDINARY LEAST SQUARES ESTIMATION OF A DYNAMIC GAME MODEL

Estimation of dynamic games is known to be a numerically challenging task. A common form of the payoff functions employed in practice takes the linear‐in‐parameter specification. We show a least squares estimator taking a familiar OLS/GLS expression is available in such a case. Our proposed estimator has a closed form. It can be computed without any numerical optimization and always minimizes the least squares objective function. We specify the optimally weighted GLS estimator that is efficient in the class of estimators under consideration. Our estimator appears to perform well in a simple Monte Carlo experiment.     

Limiting efficiency of OLS vs. GLS when regressors are fractionally integrated

We show that previous results on the asymptotic efficiency of OLS vs. GLS in the context of trending data carry over to regressors of the fractionally integrated type.     

Money,inflation and untested common factors

Bairam's (1990) model of world inflation is reconsidered. This model gives the surprising result that increases in the money supply act to decrease inflation rates. I find that this result is due to the imposition of an untested (and invalid) common factor restriction. This restriction is implicit in the generalized least squares (GLS) transformation for autocorrelated regression residuals. Bairam's autocorrelated residuals appear to be caused by mis-specified dynamics. In a more correctly specified model money supply increases have the expected positive influence on inflation rates. The prevalence of the GLS transformation, and the rarity of testing for implied common factor restrictions, suggests that there may be other, equally mis-specified, models existing in the literature.     

A note on market structure and the search for exhaustible resources

This paper allows for country-specific and time-specific factors in the demand for international reserves by applying the error-components model. Forecasts based on the GLS parameter estimates are shown to be superior to those based on the OLS estimates.     

Asymptotic inference in regression models with autoregressive errors having roots on the unit circle

An inference procedure is proposed for regression models with stationary regressors and non-stationary autoregressive errors. It is shown that the usual GLS or Cochrane–Orcutt procedure should be done in reverse order by starting the estimation from the error structure.     

A note on the dynamic adjustment of the demand for international reserves by LDC's

The dynamics of the adjustment of the demand for international reserves by LDC's is analyzed. Using a GLS procedure on pooled cross section-time series data it is showed that, contrary to previous results, the speed at which actual reserves adjust to desired reserves is very fast: in one year 95 percent of this adjustment is completed.     

实际控制人股权结构特征影响公司负债水平吗

本文以我国635家非金融公司2004—2009年平衡面板数据为样本,应用GLS方法分析实际控制人股权结构特征对公司负债的影响。研究发现:控制权与公司负债负相关;所有权和控制权的分离程度与公司负债负相关,实际控制人对负债的"利益转移限制"效应和"破产威胁"效应产生"壕沟"反应;实际控制人属性与公司负债正相关,国家控制公司的负债水平高于非国家控制公司的负债水平;所有权和控制权的分离程度与公司负债之间的负相关关系在国家控制公司变弱。     

中国服务外包基地城市竞争力对离岸发包方需求决策的影响——基于中国14个服务外包基地城市的面板数据分析

本文基于中国14个服务外包基地城市的面板数据,对中国服务外包基地城市竞争力对离岸服务外包发包方的需求决策影响程度进行了研究。研究表明,首先,解释变量Supo,Infr,Humr,Cost和Proc的估计系数的符号均和理论假说1、假说2、假说4、假说5和假说6的预期相一致。其次,商务环境、制造业外包经验的协调力量和制造业外包经验的独立力量,高度影响了外国发包方对14个城市的服务外包的需求决策。再次,基地城市的基础设施的高效率足以抵消其成本竞争力的劣势。同时,本文还指出,中国基地城市的现有和潜在的人力资本供给的规模和结构同代表服务外包主流的业务流程外包(BPO)和知识流程(KPO)外包的需求之间存在结构性矛盾。     

Spatial panel data analysis with feasible GLS techniques: An application to the Chinese real exchange rate

Recent panel data approaches stress the importance of the location interdependence. Little has been done in the Balassa-Samuelson literature accounting for spatial dependence in the panel data context that allows for spatial autocorrelation. By utilising the recently developed Kapoor et al. (2007) spatial panel feasible GLS methods, we find that the Balassa-Samuelson effect in the Chinese economy during 1985 until 2000 generally does not appear to hold. However, the black market exchange rate tends to be more compatible with the theory.     

政府规模与公共服务水平关系研究——基于中国省际面板数据的分析

本文运用1997-2006年中国21个代表性省市相关数据,在Lynn MacDonald(2008)的模型基础上进一步拓展,引入其他一些决定模型的因素,运用固定效应GLS(Cross-Section Weiht)计量方法考察政府规模与公共服务水平之间的关系.实证分析表明,政府规模与公共服务水平呈正相关关系,这与当前政府机构改革中"精简机构"的改革思路有所偏离,从而引发我们对政府机构改革中"精简机构"实质的重新思考与定位.     

Gasoline demand in the OECD: An application of pooling and testing procedures

This study utilizes a pooled inter-country data set, finding the long-run price-elasticity falls in the range ?0.55 to ?0.9, depending on the choice of pooled estimators. The estimators included the OLS, within-, and between-country estimators, plus five feasible GLS estimators. Even allowing for a ten-year distributed lag on price to reflect changes in auto-efficiency characteristics, the within-country estimator yields appreciably more inelastic estimates than did the O:S estimator, which was heavily influenced by the between- or inter-country variation. This difference raises intriguing questions for future research.     

Nonparametric Generalized Least Squares in Applied Regression Analysis

This paper compares a nonparametric generalized least squares (NPGLS) estimator to parametric feasible GLS (FGLS) and variants of heteroscedasticity robust standard error estimators (HRSE) in an applied setting. NPGLS consistently estimates the unknown scedastic function and produces more efficient parameter estimates than HRSE. We apply these various approaches for handling heteroscedasticity to data on professor rankings obtained from RateMyProfessors.com. We find that the statistical significance of key variables differs across seven versions of HRSE, leading to different conclusions, and a standard parametric approach to FGLS suffers from misspecification. NPGLS combines the virtues of both of these parametric approaches.     

The Box-Cox transformation-of-variables in regression

The application of the Box-Cox transformation to the dependent and independent variables is discussed. Maximum likelihood and iterative GLS estimators are used and bootstrapping is carried out to compare the bootstrap sample variability with the finite sample variability (RMSE) and improve RMSE estimation. The biases of parameter estimators were shown to be substantial in small samples. The standard errors obtained from the Hessian matrix were a poor measure of the finite sample variability. Thet-ratios of the linear parameter estimators may not be normally distributed in small samples.The authors acknowledge the helpful comments of two referees.     

Fixed effects with interpersonal and intertemporal covariance

The paper considers the estimation of a fixed effects time series-cross section model where errors have both unspecified interpersonal and intertemporal covariance. Efficient estimators in the form of GLS are suggested, which can be implemented on the data in their actual form or in deviations from time-means. As an empirical example, the determinants of new residential construction activity in the New England states of the US during the 80's are investigated. Results show substantial sensitivity to changes in the interest rate and the unemployment rate, whilst responses to changes in income are more muted. Long term factors related to the region are also influential.     

天津市服务业技术进步贡献率的测算与分析

利用天津市1978—2006年的时间序列数据,估算了天津市服务业的资本存量;以此为基础,应用广义最小二乘法(GLS)对C-D生产函数进行回归分析,测算并分析了天津市服务业技术进步贡献率。得出如下结论:天津市服务业的技术进步贡献率仍然较低,服务业发展处于资本驱动阶段。最后提出促进服务业的健康协调发展、提高技术进步贡献率的对策建议。     

财政农业支出对农村居民消费影响的经验分析

本文采用广义最小二乘法对财政农业支出与农村居民消费的关系进行了经验性探讨。结果表明:财政用于农业支出对农村居民消费有拉动效用,其中,支农支出和农业基本建设支出对消费有明显促进作用,但未发现农业科研和农村救济费对消费有影响。笔者结合财政支农资金总量及结构变动趋势,认为建立财政用于农业支出的长效投资机制,倾向于农业生产性投资的支出结构,是刺激农村消费的有效途径。     

Tests for additive heteroskedasticity: Goldfeld and Quandt revisited

A number of new tests for heteroskedasticity have recently become available. Using Monte Carlo methods this paper explores the small sample properties of some of these tests in the context of additive heteroskedasticity. Lagrange multiplier and Wald tests (and variants thereof) are found to be inferior to the likelihood ratio and Goldfeld and QuandtF tests. This is a reconfirmation of the conclusions obtained byGoldfeld/Quandt [1972] in their study of additive heteroskedasticity. The paper also contains some new results onAmemiya's GLS estimator of the additive heteroskedastic structure.     

Public expenditure,income distribution,and growth in OECD countries

Economic growth and the several topics related to it have been studied by economists since their earliest publications. Two different approaches to this area can be found in Neoclassical and Endogenous growth models. The economic growth analysis has focused its attention on the factors that influence the growth of nations, such as fiscal policy or improvement of human capital. Nevertheless, it is also interesting to study the effects of income distribution on economic growth to determine if it has positive effects on growth. The aim of this paper is to study these effects. The authors will develop a theoretical model in which they will introduce public capital in a typical Cobb-Douglas production function. They will estimate OLS, GLS, and SUR fixed effects models for time series and cross-sectional data.