对经济增长的时间序列分析

时间序列分析在经济运用中作用十分明显。利用1980～2003年国内生产总值的相关资料,运用时间序列分析,应用SAS软件对经济增长时间序列进行模型识别、拟合、估计和预测,预测结果较为满意。而改革开放以来,投资在经济增长中的作用越来越明显,在对经济增长序列进行时间序列分析的同时,也结合回归分析建立经济增长和投资的回归-时间序列组合模型来进行分析。     

A Review of Nonparametric Time Series Analysis

Various features of a given time series may be analyzed by nonparametric techniques. Generally the characteristic of interest is allowed to have a general form which is approximated increasingly precisely when the sample size goes to infinity. We review nonparametric methods of this type for estimating the spectral density, the conditional mean, higher order conditional moments or conditional densities. Moreover, density estimation with correlated data, bootstrap methods for time series and nonparametric trend analysis are described.     

Short Time Series Analysis: C Statistic vs Edgington Model

Young's C statistic (1941) makes it possible to compare the randomization of a set of sequentially organized data and constitutes an alternative of appropriate analysis in short time series designs. On the other hand, models based on the randomization of stimuli are also very important within the behavioral content applied. For this reason, a comparison is established between the C statistic and the Edgington model. The data analyzed in the comparative study have been obtained from graphs in studies published in behavioral journals. According to the results obtained, it is concluded that the Edgington model in experimental designs AB involves many measurements while the C statistic requires fewer observations to reach the conventional significance level.     

A Time Series Analysis of U.K. Lottery Sales: Long and Short Run Price Elasticities

This paper estimates the long- and short-run elasticities for Lotto. It is particularly concerned with the dynamic response to price variations since, for some goods, this has sometimes been used to infer the presence of addiction. The price elasticity is identified through variation in the expected value of a Lotto ticket induced by rollovers whose high frequency results in surprisingly high variation in the expected value of holding a ticket. Unit root tests are applied to the series in order to identify their time series properties and to avoid a spurious regression problem. The series are found to be stationary. We apply instrumental variables to account for the endogeneity which arises due to correlation between the expected value and the dependent sales variable. The estimated long-run elasticity exceeds the short-run elasticity and this supports the hypothesis that there is an element of addictive behaviour in sales. The Lottery is regulated and the regulator's objective is to maximize sales. Our estimated long-run price elasticity of demand is inconsistent with revenue maximization and we find that greater revenue for the 'good causes' could be raised from the game if a smaller proportion of sales revenue were allocated to them.     

Monetary Policy in the Greenspan Era: A Time Series Analysis of Rules vs. Discretion*

Relationships between the Federal funds rate, unemployment, inflation and the long‐term bond rate are investigated with cointegration techniques. We find a stable long‐term relationship between the Federal funds rate, unemployment and the bond rate. This relationship is interpretable as a policy target because deviations are corrected via the Federal funds rate. Deviations of the actual Federal funds rate from the estimated target give simple indications of discretionary monetary policy, and the larger deviations relate to special episodes outside the current information set. A more traditional Taylor‐type target, where inflation appears instead of the bond rate, does not seem congruent with the data.     

基于拟牛顿法确定参数的时间序列迭代模型

为解决时间序列参数估计收敛速度慢,迭代次数多,效率低的问题,建立了一种基于拟牛顿法的参数估计方法。实例表明,由此所建立的时间序列迭代模型稳定可靠,拟合、预测精度高,能够有效的表征形变量随时间的变化规律。