Designs for estimating an extremal point of quadratic regression models in a hyperball

This paper is devoted to studying optimal designs for estimating an extremal point of a multivariate quadratic regression model in the unit hyperball. The problem of estimating an extremal point is reduced to that of estimating certain parameters of a corresponding nonlinear (in parameters) regression model. For this reduced problem truncated locally D-optimal designs are found in an explicit form. The result is a generalization of the results of Fedorov and Müller (1997) for onedimensional quadratic regression function in the unit segment. Received February 2002     

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High-Dimension Regime

In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.     

Spatial modelling of claim frequency and claim size in non-life insurance

In this paper, models for claim frequency and average claim size in non-life insurance are considered. Both covariates and spatial random effects are included allowing the modelling of a spatial dependency pattern. We assume a Poisson model for the number of claims, while claim size is modelled using a Gamma distribution. However, in contrast to the usual compound Poisson model, we allow for dependencies between claim size and claim frequency. A fully Bayesian approach is followed, parameters are estimated using Markov Chain Monte Carlo (MCMC). The issue of model comparison is thoroughly addressed. Besides the deviance information criterion and the predictive model choice criterion, we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. We give an application to a comprehensive data set from a German car insurance company. The inclusion of spatial effects significantly improves the models for both claim frequency and claim size, and also leads to more accurate predictions of the total claim sizes. Further, we detect significant dependencies between the number of claims and claim size. Both spatial and number of claims effects are interpreted and quantified from an actuarial point of view.     

基于VAR模型的山东省经济增长波动分析

本文通过建立向量自回归模型,运用脉冲响应函数和预测方差分解的方法对山东省经济增长的波动情况进行了实证分析。研究结果表明:各变量对山东经济增长的影响均不太明显。这说明山东经济一直保持稳定快速发展的势头。     

中国财产保险需求影响因素的实证研究

运用中国1980-2009年的相关数据,引入六个解释变量,采用逐步回归方法,对中国财产保险需求的影响因素进行了实证分析,结果表明:与人寿保险需求截然不同,经济增长、人均收入、风险意识对财产保险需求未发现有显著影响;而固定资产投资、汽车拥有量和货物运输量对财产保险需求有着显著的推动作用.实证结果进一步解释了财产保险市场结构严重失衡的状况.     

Stock Price Index and Exchange Rate Nexus in African Markets

This paper examines the relationship between stock price index and exchange rate in six African markets using monthly data for the period January 2007 to October 2015. A quantile regression approach is used. This methodology is shown to perform better than the ordinary least squares estimators, particularly when the conditional distribution is heterogeneous. Our empirical evidence reveals an interesting pattern in the association of these two financial markets in Africa, which shows that the negative relationship between stock and foreign exchange markets is more apparent when exchange rates are extremely low or high. The negative relationship between the two variables is in line with the portfolio balance effect.     

A quantile regression approach for estimating panel data models using instrumental variables

We introduce a quantile regression approach to panel data models with endogenous variables and individual effects correlated with the independent variables. We find newly developed quantile regression methods can be easily adapted to estimate this class of models efficiently.     

Trade credit in SMEs: a quantile regression approach

This article analyses the determinants of the trade credit in Spanish manufacturing small and medium-sized enterprises (SMEs) from a new perspective. Specifically, we focus on the relationship between trade credit and other relevance financial resources: bank credit and self-financing. For the first time in the literature, a quantile regression approach is used, which takes into account the heterogeneity of firms in different quantiles of trade credit distribution. Our results show that the relationship between trade credit and other financial sources presents dissimilarities, including differences in sign, on SMEs with different degrees of trade credit. Our findings help to clarify the confusing results achieved in previous research on this topic.     

Financial stress,sovereign debt and economic activity in industrialized countries: Evidence from dynamic threshold regressions

We analyze how the impact of a change in the sovereign debt-to-GDP ratio on economic growth depends on the level of debt, the stress level on the financial market and the membership in a monetary union. A dynamic growth model is put forward demonstrating that debt affects macroeconomic activity in a non-linear manner due to amplifications from the financial sector. Employing dynamic country-specific and dynamic panel threshold regression methods, we study the non-linear relation between the growth rate and the debt-to-GDP ratio using quarterly data for sixteen industrialized countries for the period 1981Q1-2013Q2. We find that the debt-to-GDP ratio has impaired economic growth primarily during times of high financial stress and only for countries of the European Monetary Union and not for the stand-alone countries in our sample. A high debt-to-GDP ratio by itself does not seem to necessarily negatively affect growth if financial markets are calm.     

服务业发展与人均收入的关系:基于分位数回归的实证研究

利用118个国家和地区1980-2005年服务业发展和人均收入的非平衡面板数据,采用分量回归的方法,在Fuchs的基础上对两者的关系进行研究。结果发现,服务业就业比重和人均GDP之间存在着显著并且稳定的正相关关系,服务业就业比重随着人均GDP的增加逐渐提高,这与Fuchs研究结论相同;与Fuchs不同的是,本文通过分位数回归还可以看出人均GDP的需求效应在服务业发展的不同阶段的影响程度的变化。在服务业发展的较低阶段,人均GDP的需求效应对服务业发展的作用较大;在服务业发展的较高阶段,人均GDP的需求效应对服务业发展的作用相对较小。