基于精算估计方法的养老保险再分配效应研究

利用2008年中国健康与养老追踪调查(CHARLS)数据,基于精算估计方法测算了居民的各种养老金财产及其对家庭财产分布的影响。研究发现,在养老保险制度范围内,社会养老保险的保障水平较高,产生了较大的正向再分配效应,大幅度降低了居民财产分布的不平等程度。但在全体居民范围内,由于较低的覆盖范围,社会养老保险财产并没有明显改变居民财产的分布差距。

基于精算估计的我国城镇职工养老保险代际收入再分配效应分析

基于精算估计的方法,以终身纯转移率作为衡量指标,结合中国养老保险改革的“新人”“中人”“老人”的划分特点来探讨中国现行城镇职工养老保险的代际收入再分配效应,并分析不同收入组、延迟退休、个人账户记账利率、缴费年限四个维度对代际收入再分配效应的影响。结论表明:中国现行城镇职工养老保险使得男性、女性终身纯转移率随着年龄的增大而减小,整体体现为逆向的代际收入再分配效应,在不同收入组的情况下还能实现正向的代内收入再分配效应;延迟退休政策有利于提升男性年轻在职个体的效用以及降低女性临近退休个体的效用,会进一步扩大代际收入差距;个人账户实际收益率达到记账利率标准可以实现个体效用水平的提高;增加缴费年限有利于提升效用水平,但难以保持代际公平。

Architecture design of GPS software receiver and implementation of its acquisition algorithm with fine frequency estimation

The design of a global positioning system （GPS） software receiver is introduced. This design uses the concept of software radio, and it consists of the following parts： front-end, acquisition, tracking, synchronization, navigation solution and some assisting modules. In the acquisition module, the acquisition algorithm based on circular correlation is utilized. The input data and the local code are converted into the frequency domain by means of the fast Fourier transform （FFT）. After performing circular correlation, the initial phase of the C/A code can be obtained and the cartier frequency can be found in 1 kHz frequency resolution, which is too coarse to use for the tracking loop. In order to improve the frequency resolution, the fine frequency estimation through a phase relationship is then achieved, by which, the frequency resolution is improved dramatically. Experiments show that the inaccuracy of the carrier frequency can be estimated within a few hertz by the fine frequency estimation method, and the fine frequency attained can be directly used for the tracking loop.

Estimation of Organic Matter Content in Coastal Soil Using Reflectance Spectroscopy

Rapid determination of soil organic matter(SOM) using regression models based on soil reflectance spectral data serves an important function in precision agriculture. "Deviation of arch"(DOA)-based regression and partial least squares regression(PLSR)are two modeling approaches to predict SOM.However,few studies have explored the accuracy of the DOA-based regression and PLSR models.Therefore,the DOA-based regression and PLSR were applied to the visible near-infrared(VNIR) spectra to estimate SOM content in the case of various dataset divisions.A two-fold cross-validation scheme was adopted and repeated 10 000 times for rigorous evaluation of the DOA-based models in comparison with the widely used PLSR model.Soil samples were collected for SOM analysis in the coastal area of northern Jiangsu Province,China.The results indicated that both modelling methods provided reasonable estimation of SOM,with PLSR outperforming DOA-based regression in general.However,the performance of PLSR for the validation dataset decreased more noticeably.Among the four DOA-based regression models,a linear model provided the best estimation of SOM and a cutoff of SOM content(19.76 g kg^(-1)),and the performance for calibration and validation datasets was consistent.As the SOM content exceeded 19.76 g kg^(-1),SOM became more effective in masking the spectral features of other soil properties to a certain extent.This work confirmed that reflectance spectroscopy combined with PLSR could serve as a non-destructive and cost-efficient way for rapid determination of SOM when hyperspectral data were available.The DOA-based model,which requires only 3 bands in the visible spectra,also provided SOM estimation with acceptable accuracy.

Accuracy Improvement of Zenith Tropospheric Delay Estimation Based on GPS Precise Point Positioning Algorithm

In the precise point positioning(PPP),some impossible accurately simulated systematic errors still remained in the GPS observations and will inevitably degrade the precision of zenith tropospheric delay(ZTD) estimation.The stochastic models used in the GPS PPP mode are compared.In this paper,the research results show that the precision of PPP-derived ZTD can be obviously improved through selecting a suitable stochastic model for GPS measurements.Low-elevation observations can cover more troposphere information that can improve the estimation of ZTD.A new stochastic model based on satellite low elevation cosine square is presented.The results show that the stochastic model using satellite elevation-based cosine square function is better than previous stochastic models.

New self-calibration schemes for accelerometers in platform INS

To ensure success of precise navigation, it is necessary to carry out in-field calibration for the accelerometers in platform inertial navigation system(PINS) before a mission is launched.Traditional continuous self-calibration methods are not fit for fast calibration of accelerometers because the platform misalignments have to be estimated precisely and the nonlinear coupling terms will affect accuracy. The multi-position methods with a "shape of motion" algorithm also have some existing disadvantages: High precision calibration results cannot be obtained when the accelerometer's output data are used directly and it is difficult to optimize the calibration scheme. Focusing on this field, this paper proposes new fast self-calibration methods for the accelerometers of PINS. A data compression filter is employed to improve the accuracy of parameter estimation because it is impossible to obtain non-biased estimation for accelerometer parameters when using the "shape of motion" algorithm. Besides, continuous calibration schemes are designed and optimized by the genetic algorithm(GA) to improve the observability of parameters. Simulations prove that the proposed methods can estimate the accelerometer parameter more precisely than traditional continuous methods and multi-position methods, and they are more practical to deal with urgent situations than multi-position methods.