Model Averaging Using Fractional Polynomials to Estimate a Safe Level of Exposure

Quantitative risk assessment involves the determination of a safe level of exposure. Recent techniques use the estimated dose-response curve to estimate such a safe dose level. Although such methods have attractive features, a low-dose extrapolation is highly dependent on the model choice. Fractional polynomials, basically being a set of (generalized) linear models, are a nice extension of classical polynomials, providing the necessary flexibility to estimate the dose-response curve. Typically, one selects the best-fitting model in this set of polynomials and proceeds as if no model selection were carried out. We show that model averaging using a set of fractional polynomials reduces bias and has better precision in estimating a safe level of exposure (say, the benchmark dose), as compared to an estimator from the selected best model. To estimate a lower limit of this benchmark dose, an approximation of the variance of the model-averaged estimator, as proposed by Burnham and Anderson, can be used. However, this is a conservative method, often resulting in unrealistically low safe doses. Therefore, a bootstrap-based method to more accurately estimate the variance of the model averaged parameter is proposed.     

Estimates of Money Demand Functions for Estonia

This paper examines the money demand function of Estonia in the period 1995–2006. Since Estonia has a currency board system, euro area interest rates are taken into account. We apply different cointegration procedures like the Engle–Granger, the dynamic OLS, and the Johansen procedure to estimate the long-run relationship among money, output, and interest rates. The results show that it is difficult to find a cointegrating relationship for the broad money aggregate M2. For the preferred relationship including euro area money market rate and euro area bond rate a dynamic equation is estimated. This dynamic equation is stable for the whole period. The change of the anchor curreny in the currency board and the accession to the European Union do not alter the relationship.      

A Bayesian estimation of lag lengths in distributed lag models

Dynamic regression models are widely used because they express and model the behaviour of a system over time. In this article, two dynamic regression models, the distributed lag (DL) model and the autoregressive distributed lag model, are evaluated focusing on their lag lengths. From a classical statistics point of view, there are various methods to determine the number of lags, but none of them are the best in all situations. This is a serious issue since wrong choices will provide bad estimates for the effects of the regressors on the response variable. We present an alternative for the aforementioned problems by considering a Bayesian approach. The posterior distributions of the numbers of lags are derived under an improper prior for the model parameters. The fractional Bayes factor technique [A. O'Hagan, Fractional Bayes factors for model comparison (with discussion), J. R. Statist. Soc. B 57 (1995), pp. 99–138] is used to handle the indeterminacy in the likelihood function caused by the improper prior. The zero-one loss function is used to penalize wrong decisions. A naive method using the specified maximum number of DLs is also presented. The proposed and the naive methods are verified using simulation data. The results are promising for the method we proposed. An illustrative example with a real data set is provided.     

On screening samples in the laboratory and factors in factorial investigations

Procedures such as group testing and fractional replication can greatly reduce the workload. The former is especially efficient when the presence of a characteristic in samples is low. Fractional replication can greatly reduce the amount of experimentation when some of the parameters associated with a factorial are nonexistent or negligible. Supersaturated fractional replication can be used to efficiently screen factors when it is suspected that they may not affect a process but it is desired to check this suspicion. There are many types of grouping and pooling material in an investigation. Some of these are discussed as are the interrelationships among the above procedures.     

Breaking alias chains in fractional factorials

Some experimenters carry out their investigation in stages. They begin with an initial 2^n-p fraction of resolution IV, in which the main effects are clean and the interactions are aliased in chains, Then, having analyzed the initial experiment, they plan further runs to isolate certain interactions by breaking the chains. In this paper a method called semifolding, for choosing the points in the second experiment, is presented.     

重庆市金融发展与城乡收入差距的实证研究

根据重庆市1985—2012年的数据,采用单位根检验,协整检验和误差修正模型对重庆市金融发展与城乡收入差距的关系进行了实证分析,结果表明金融发展规模的扩大显著缩小了城乡收入差距,金融发展效率的改善扩大了城乡收入差距。对此提出政策建议：重庆地方政府应降低普通大众获得金融资源的门栏,扩大金融发展规模,加大支农投入力度,大力扶持第三产业发展,在发展第二产业的同时鼓励发展服务业,以改善重庆城乡收入分配不合理的现状,实现社会和经济的稳定发展。     

基于变结构协整的股指期货跨期套利

随着中国股指期货市场成交量的扩大和流动性的加强,合约间价差的变化更加复杂和多变。为了改进传统跨期套利策略的效果,使用允许结构突变的变结构协整模型对价差进行建模,设计了一套完整的程序化交易策略,并选取IF1311,IF1312,IF1401和IF1402的真实高频交易价格数据进行实证研究。结果表明：中国股指期货合约价格存在大量突变现象,变结构协整模型策略在3对合约间的交易表现相较于传统模型策略,能捕捉到更多交易机会、更高的收益率和更大的夏普比率。     

Parameter Identification for Drift Fractional Brownian Motions with Application to the Chinese Stock Markets

This article deals with the problem of estimating all the unknown parameters in the drift fractional Brownian motion with discretely sampled data. The estimation procedure is built upon the marriage of the variation method and the ergodic theory. The strong consistencies of these estimators are provided. Moreover, our method and two existing approaches are compared based on the computational running time and the accuracy of estimation via simulation studies. We also apply the proposed method to the real high-frequency financial data within a window of 4 h in the trading day from the Chinese mainland stock market.     

中国农业出口贸易与环境污染关系的实证研究

在估算中国农业环境污染排放量的基础上,运用Johansen协整分析、Granger因果关系检验和脉冲响应分析对1995-2010年中国农业出口贸易总额和农业环境污染之间的长期变化关系进行实证分析.结果表明:从长期来看,中国农业贸易出口额和农业环境污染之问是正向的关系,且农业出口贸易规模的变化是导致农业环境污染排放量变化的原因.脉冲响应分析则进一步从动态的角度验证了农业出口贸易规模对农业环境污染的正向影响程度及滞后趋势.并在实证分析的基础上提出了优化农业出口贸易结构,健全、完善与农业贸易有关的环境规制政策以及逐步推进农业环境成本内部化等建议.     

金融发展与出口贸易结构优化

在综述相关文献的基础上，利用协整检验、因果关系检验和脉冲响应函数等计量方法，根据中国1985-2006年的数据，从金融发展的规模、结构和效率三个方面对金融发展与出口贸易结构的关系进行实证分析。实证结果表明：金融发展与出口贸易结构优化之间存在着长期的协整关系，我国要促进金融体制的改革，提高金融效率，进一步促进贸易结构的优化。