西藏人口转变中的劳动适龄人口变动趋势

以1990和2000年西藏自治区人口普查资料为基础,对未来西藏人口的发展态势作了预测。预测分析显示,西藏正处于人口快速转变之中。未来25年内,随着总人口的变动,西藏劳动适龄人口的规模、年龄结构、比重也将发生显著变化,2010—2030年间将会出现劳动力适龄人口比例最大,社会总负担比最轻的“人口红利”期。西藏应抓住这一有利时机,大力发展教育、农牧业及副产品加工业、旅游业以及外贸和边贸,以实现真正的“人口红利”。     

Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions

The forecasting of sales in a company is one of the crucial challenges that must be faced. Nowadays, there is a large spectrum of methods that enable making reliable forecasts. However, sometimes the nature of time series excludes many well-known and widely used forecasting methods (e.g., econometric models). Therefore, the authors decided to forecast on the basis of a seasonally adjusted median of selected probability distributions. The obtained forecasts were verified by means of distributions of the Theil U² coefficient and unbiasedness coefficient.     

Forecasting Vector ARMA Processes With Systematically Missing Observations

The following two predictors are compared for time series with systematically missing observations: (a) A time series model is fitted to the full series X_t , and forecasts are based on this model, (b) A time series model is fitted to the series with systematically missing observations Y _τ, and forecasts are based on the resulting model. If the data generation processes are known vector autoregressive moving average (ARMA) processes, the first predictor is at least as efficient as the second one in a mean squared error sense. Conditions are given for the two predictors to be identical. If only the ARMA orders of the generation processes are known and the coefficients are estimated, or if the process orders and coefficients are estimated, the first predictor is again, in general, superior. There are, however, exceptions in which the second predictor, using seemingly less information, may be better. These results are discussed, using both asymptotic theory and small sample simulations. Some economic time series are used as illustrative examples.     

A Prediction Interval for M Estimators*

There has been much work in the area of estimating the center of a symmetric population. If one allows for the possibility that the population may be heavy-tailed then robust procedures, and in particular M estimators, have proven quite popular. In this paper we consider the following problem: given a random sample, produce an interval such that the M estimator derived from a future random sample (from the same population) will lie in that interval with some preassigned probability. Clearly such an interval is of use, especially in quality control where prediction is vital. In this paper such an interval is proposed based on asymptotic theory. A simulation study was run for a variety of sample sizes (the sizes of the observed and future samples need not be equal) and distributions. The particular M estimator of choice is that based on the biweight ψ function. The proposed interval performs reasonably well relative to the best that can be achieved asymptotically.     

Combining Economic Forecasts

A method for combining forecasts may or may not account for dependence and differing precision among forecasts. In this article we test a variety of such methods in the context of combining forecasts of GNP from four major econometric models. The methods include one in which forecasting errors are jointly normally distributed and several variants of this model as well as some simpler procedures and a Bayesian approach with a prior distribution based on exchangeability of forecasters. The results indicate that a simple average, the normal model with an independence assumption, and the Bayesian model perform better than the other approaches that are studied here.     

On the Specification of Propensity Scores,With Applications to the Analysis of Trade Policies

A vector autoregression is fit to recent U.S. data on wheat prices, wheat export sales, wheat export shipments, and exchange rates. Forecast error decompositions and out-of-sample forecasts indicate that exchange rates have little influence on wheat sales and shipments.     

Multiperiod Forecasts of Interest Rates

The accuracy of forecasts of interest rates over different forecast horizons and time periods is examined. The results indicate a deterioration in “absolute” forecast accuracy measured by the mean absolute error and the root mean squared error but no decrease in “relative” accuracy measured by the Theil coefficient with an increase in the forecast span. The results also indicate a decline in accuracy in periods of volatile interest rates. Support is found for the hypothesis that the ratio of the variability of predicted changes to that of actual changes falls with an increase in the forecast horizon.     

Out-of-Sample Forecast Tests Robust to the Choice of Window Size

This article proposes new methodologies for evaluating economic models’ out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. The study shows that the tests proposed in the literature may lack the power to detect predictive ability and might be subject to data snooping across different window sizes if used repeatedly. An empirical application shows the usefulness of the methodologies for evaluating exchange rate models’ forecasting ability.     

我国海上油田钻井完井投资测算方法研究

本文分析了我国海上油田钻井完井投资测算的现有方法,针对存在的问题和不足,从内生变量的选择、相关系数、变量的影响程度等方面进行分析研究,提出以作业周期、井深、水深三个因素进行测算的新方法。     

2011—2050年云南省人口红利预测分析

以云南省"六普"数据为基础,运用CPPS方法对云南省2011—2050年的人口红利进行预测。预测结果显示,云南人口红利的特点主要是:开启时间晚,闭合时间早;红利期短,约36年,其中真正人口红利期为21年。据此探讨了人口红利的制约因素,并提出延长和拓宽人口红利的对策建议。