Large sample estimation and prediction for explosive growth curve models

Asymptotic distributions of maximum likelihood estimators for the parameters in explosive growth curve models are derived. Limit distributions of prediction errors when the parameters are estimated are also obtained. The growth curve models are viewed as multivariate time-series models, and the usual time-series methods are used for prediction. Estimation constrained by a hypothesis of homogeneity of growth rates is also considered.     

Fitting of self-exciting threshold autoregressive moving average nonlinear time-series model through genetic algorithm and development of out-of-sample forecasts

Self-exciting threshold autoregressive moving average (SETARMA) nonlinear time-series model is considered here. Sufficient conditions for invertibility and stationarity are derived. Parameter estimation algorithm is developed by employing real-coded genetic algorithm stochastic optimization procedure. A significant feature of the work done is that optimal out-of-sample forecasts up to three-step ahead and their forecast error variances are derived analytically. Relevant computer programs are written in statistical analysis system (SAS) and C. As an illustration, annual mackerel catch time-series data are considered. Forecast performance of the fitted model for hold-out data is evaluated by using Naive and Monte Carlo approaches. It is found that optimal out-of-sample forecast values are quite close to actual values and estimated variances are quite close to theoretical values. Superiority of the SETARMA model over the SETAR model for equal predictive ability through Diebold–Mariano test is also established.     

更富裕是否意味着更幸福?基于横截面时间序列数据的分析(2003-2013)

四十年前,经济学家伊斯特林提出了“幸福感悖论”:短时期内个人和国家的财富水平与幸福感都正向相关,而在长期背景下,经济增长并不会显著提高整体幸福感水平。本文使用横跨十年的全国代表性横截面时间序列数据直接检验了财富与幸福感的关系,结果证实了“幸福感悖论”。研究发现,虽然在短时期内,无论是家庭人均收入还是省份的人均生产总值都与幸福感有显著的正相关,但在经济高速发展的十年内(2003-2013),省份人均生产总值的变化与幸福感的变化之间并没有显著相关。     

高频数据驱动的连续时间模型估计

现代金融经济学中连续时间模型能够更方便地描述重要经济变量的动态过程如股价、汇率和利率等。为连续时间模型提出了一种高频数据驱动的二阶段估计方法,增强了连续时间扩展模型的弹性和可操作性。以Vasicek模型为例给出了该方法的应用实例,首先在第一阶段使用实现波动率方法估计出模型的扩散项参数,然后使用实际数据的稳态分布的前向方程估计漂移项参数。此方法对模型初始设定和优化算法依赖程度低,结果较为稳定可靠。     

Nonlinear models for ground-level ozone forecasting

One of the main concerns in air pollution is excessive tropospheric ozone concentration. The aim of this work is to develop statistical models giving shortterm forecasts of future ground-level ozone concentrations. Since there are few physical insights about the dynamic relationship between ozone, precursor emissions and/or meteorological factors, a nonparametric and nonlinear approach seems promising in order to specify the forecast models. First, we apply four nonparametric procedures to forecast daily maximum 1-hour and maximum 8-hour averages of ozone concentrations in an urban area. Then, in order to improve the forecast performances, we combine the time series of the forecasts. This idea seems to give encouraging results. This work was supported by a MURST grant. The authors would like to thank two anonymous referees for their helpful comments.     

An efficiency result for the empirical characteristic function in stationary time-series models

It is shown under general conditions that arbitrarily high asymptotic efficiencies can be obtained when the parameters of a stationary time series are estimated by fitting the characteristic functions of the process to their empirical versions. A consistency and a central limit result are also given.     

中国食用粮食消费总量的时序预测

粮食消费预测是安排粮食生产、调整粮食种植结构、制定粮食安全和农业可持续发展战略的重要理论依据。利用粮食消费量与时间之间的相关关系 ,采用SPSS程序包进行筛选 ,建立我国食用粮食消费总量的时序预测模型。研究结果表明 ,所建立的三个时序预测模型的拟合度等统计指标高度显著 ,运用所建模型对所获资料进行的内推预测比较准确 ,但外推预测结果因影响因素多 ,其准确性有待时间和实际的检验     

Statistical analysis for negotiation support

In this paper we provide an overview of the issues involved in using statistical analysis to support the process of international negotiation. We will illustrate how the approach can contribute to a negotiator's understanding and control of the interactions that occur during the course of a negotiation. The techniques are suited to the analysis of data collected from ongoing discussions and moves made by the parties. The analyses are used to illuminate influences and processes as they operate in particular cases or in negotiations in general. They do not identify a best strategy or outcome from among alternatives suggested either from theoretical assumptions about rationality and information-processing (see Munier and Rullière's paper in this issue), from personal preference structures (see Spector's paper in this issue), or from a rule-based modeling system (see Kersten's paper in this issue). This distinction should be evident in the discussion to follow, organized into several sections: From Empirical to Normative Analysis; Statistical Analysis for Situational Diagnosis; Time-Series Analysis of Cases, and Knowledge as Leverage Over the Negotiation Process. In a final section, we consider the challenge posed by attempts to implement these techniques with practitioners.     

对消费者信心指数的质疑

因为要质疑用简单平均法测算的消费者信心指数算法的合理性,所以研究消费者信心指数的二级构成指数间的相互关系,研究发现,各二级指数间相互影响,二级指数间有信息重复。这会导致简单平均算法计算的信心指数放大了某些因素的影响,会产生系统性偏差,导致信心指数的失真。因此,用因子分析方法对消费者信心指数进行修正,研究发现修正后的信心指数与宏观经济变量的相关程度更高。