基于人口預(yù)測(cè)模型的我國(guó)養(yǎng)老保險(xiǎn)研究
本文選題:人口預(yù)測(cè) + 養(yǎng)老保險(xiǎn)。 參考:《安徽大學(xué)》2013年碩士論文
【摘要】:我國(guó)在改革發(fā)展初期勞動(dòng)年齡人口占總?cè)丝诒戎剌^大,撫養(yǎng)率比較低,為經(jīng)濟(jì)發(fā)展創(chuàng)造了有利的人口條件。近幾十年經(jīng)濟(jì)持續(xù)快速增長(zhǎng)已經(jīng)成為一個(gè)世界“奇跡”。然而20世紀(jì)后期,為控制人口的急劇增長(zhǎng),我國(guó)推行了計(jì)劃生育政策,這使得人口出生率迅速下降;同時(shí)隨著國(guó)家經(jīng)濟(jì)的發(fā)展,人民生活條件的改善,我國(guó)人口平均壽命得到了延長(zhǎng),出生率的下降和人口平均壽命的延長(zhǎng)這兩種因素聯(lián)合起來(lái)加快了我國(guó)人口老齡化的進(jìn)程。如今中國(guó)早已步入了老齡化國(guó)家行列,并且人口重心不斷趨于后移,這給我國(guó)養(yǎng)老保險(xiǎn)體系帶來(lái)沉重負(fù)擔(dān)。 為了更好的量化人口結(jié)構(gòu)變化給我國(guó)養(yǎng)老保險(xiǎn)體系帶來(lái)的影響,本文首先建立了人口預(yù)測(cè)模型,該模型由人口轉(zhuǎn)移模型和基于時(shí)間序列理論構(gòu)造的新生人口預(yù)測(cè)模型兩個(gè)模型結(jié)合而成;趪(guó)家統(tǒng)計(jì)局調(diào)查統(tǒng)計(jì)得到的各個(gè)年齡階段的人口數(shù)隨著時(shí)間推移而呈現(xiàn)出規(guī)律性變化的原理,本文構(gòu)造了人口轉(zhuǎn)移率。利用人口轉(zhuǎn)移率和國(guó)家統(tǒng)計(jì)局中各個(gè)年齡階段的人口數(shù)據(jù)既可以向前預(yù)測(cè)未來(lái)人口數(shù),也可以向后推出在國(guó)家統(tǒng)計(jì)局網(wǎng)站上不能尋找到的各個(gè)年齡階段歷史人口數(shù)據(jù)。但該模型不能得到新生人口數(shù),為了得到新生人口數(shù),本文還構(gòu)造了新生人口預(yù)測(cè)模型。由于該人口預(yù)測(cè)模型只是進(jìn)行了局部預(yù)測(cè),整體大部分?jǐn)?shù)據(jù)是利用人口轉(zhuǎn)移特征和統(tǒng)計(jì)規(guī)律得到,這充分利用了以往統(tǒng)計(jì)信息和人口年齡分布結(jié)構(gòu),從而極大的改善了預(yù)測(cè),減少了誤差。該模型充分利用了十一年的人口統(tǒng)計(jì)數(shù)據(jù),這樣大大降低了對(duì)單次人口統(tǒng)計(jì)數(shù)據(jù)精確度的依賴(lài),并且由于其中包含了兩次人口普查,由該模型的構(gòu)造原理可知該模型還擁有每隔十年便向更準(zhǔn)確人口數(shù)回歸的特征。利用該模型預(yù)測(cè)出我國(guó)到2035年人口將實(shí)現(xiàn)零增長(zhǎng),這和國(guó)家統(tǒng)計(jì)局預(yù)計(jì)的我國(guó)人口將在2032年前后到達(dá)零增長(zhǎng)十分接近;該模型預(yù)測(cè)我國(guó)未來(lái)人口數(shù)將會(huì)在2035年達(dá)到最大值14.7億,其后便會(huì)逐年遞減,這和聯(lián)合國(guó)對(duì)中國(guó)的中方案預(yù)測(cè)值我國(guó)將于2033年達(dá)到人口峰值,最大人口總量為14.6億人十分接近,這顯示了該模型具有良好的預(yù)測(cè)能力。 接下來(lái)本文利用該模型來(lái)描繪未來(lái)我國(guó)人口老齡化進(jìn)程,繼而分析人口重心后移對(duì)我國(guó)養(yǎng)老保險(xiǎn)體系的影響。該模型關(guān)于我國(guó)人口老齡化方面的預(yù)測(cè)顯示出在2055年我國(guó)老年人口數(shù)將達(dá)到頂峰41852.18萬(wàn),所占總?cè)丝诒戎匾灿?055年達(dá)到峰值30.05%,這與國(guó)務(wù)院新聞辦公室發(fā)表的《中國(guó)老齡事業(yè)的發(fā)展》白皮書(shū)中預(yù)測(cè)2051年老年人口規(guī)模將達(dá)到峰值4.37億非常接近;這也和全國(guó)老齡工作委員會(huì)辦公室公布的《中國(guó)人口老齡化發(fā)展趨勢(shì)預(yù)測(cè)研究報(bào)告》中預(yù)測(cè)的我國(guó)到2050年,老年人口總量將超過(guò)4億,老齡化水平推進(jìn)到30%以上十分吻合。而我國(guó)總撫養(yǎng)比在2012年——2055年將呈現(xiàn)出遞增的趨勢(shì);數(shù)據(jù)顯示2015年我國(guó)的總撫養(yǎng)比將達(dá)到50%,接近發(fā)達(dá)國(guó)家的平均總撫養(yǎng)比。我國(guó)總撫養(yǎng)比將于2055年達(dá)到最高峰,峰值為0.97,老齡人口撫養(yǎng)比也于2055年達(dá)到峰值0.59,未成年人口撫養(yǎng)比同樣在2055年達(dá)到峰值0.38;這意味著到2055年每100位工作人員將要照顧97位非工作人口,其中包括59位老人和38位未成年人,屆時(shí)我國(guó)的養(yǎng)老負(fù)擔(dān)將提高到不堪承受的地步。 隨后本文結(jié)合人口預(yù)測(cè)模型對(duì)影響?zhàn)B老金負(fù)擔(dān)的各個(gè)因素進(jìn)行了量化分析,這其中包括職工就業(yè)率、退休人口占老年人口的比例、勞動(dòng)年齡人口比例以及老年人口數(shù)占總?cè)丝跀?shù)比例等因素。最后的結(jié)論指出為了提高人民的生活水平,一方面需要將更多的老年人口納入養(yǎng)老保險(xiǎn)體系,使得人民老有所養(yǎng),老有所依,老有所醫(yī);另一方面需要將更多的年青勞動(dòng)人口納入養(yǎng)老保險(xiǎn)體系,以充實(shí)養(yǎng)老保險(xiǎn)的資金來(lái)源,這樣同時(shí)可使得將來(lái)這批年青人年老后也擁有良好的社會(huì)保障體系來(lái)改善自己的生活。
[Abstract]:In the early period of the reform and development, the labor age population accounted for a large proportion of the total population, and the dependency ratio was low, which created favorable conditions for the economic development. In the last few decades, the sustained and rapid economic growth has become a "miracle" in the world. However, in the late twentieth Century, the family planning policy was carried out in order to control the rapid growth of the population. At the same time, with the development of the country's economy and the improvement of the living conditions of the people, the average life span of our population has been extended, the decline of the birth rate and the prolongation of the average life span of the population have combined the two factors to accelerate the progress of our population aging. Now China has already entered the aging country. Moreover, the population gravity center tends to move backward, which brings heavy burden to China's endowment insurance system.
In order to better quantify the impact of demographic changes on the endowment insurance system in China, this paper first establishes a population forecasting model, which is combined with two models of population transfer model and new population forecasting model based on time series theory. The population transfer rate is constructed by the population transfer rate and the population data of all ages in the National Bureau of statistics. The population number can be predicted forward by the population transfer rate and the population data of all ages in the National Bureau of statistics. It can also be introduced back to all ages that can not be found on the website of the National Bureau of statistics. But this model can not get the number of new population. In order to get the number of new population, this paper also constructs a new population prediction model. Because the population prediction model is only local prediction, the overall majority of the data are obtained by the use of population transfer characteristics and statistical laws. This makes full use of the previous statistical information and population. The age distribution structure, which greatly improves the prediction, reduces the error. This model makes full use of eleven years of demographic data, which greatly reduces the dependence on the accuracy of single demographic data, and because it contains two census, the model structure principle knows that the model still has ten years. This model predicts that China's population will achieve zero growth by 2035, which is very close to the National Census Bureau's estimated population will reach zero growth before and after 2032, and the model predicts that our future population will reach a maximum of 1 billion 470 million in 2035, and then decline year by year. The forecast value of China's China plan and the United Nations will reach the peak of population in 2033. The maximum population is very close to 1 billion 460 million people, which shows that the model has good prediction ability.
Then we use this model to describe the process of population aging in the future, and then analyze the impact of the population shift on the pension system in China. The prediction of the aging population in China shows that the number of elderly population in China will reach a peak of 418 million 521 thousand and 800 in 2055, and the proportion of the total population is also reached in 2055. The peak is 30.05%, which is very close to the forecast of the elderly population in 2051, published by the Information Office of the State Council, which is expected to reach a peak of 437 million in the white paper. This is also the forecast of China's population aging development trend pre test report published by the office of the National Committee for ageing in China to 2050. The total population of the elderly will exceed 400 million, and the level of aging to more than 30% is very consistent. However, the total dependency ratio in China will show an increasing trend in 2012 - 2055; the data show that the total maintenance ratio of China will reach 50% in 2015 and the average total dependency ratio in developed countries. The total dependency ratio in China will reach the highest peak in 2055 and peak value in 2055. For 0.97, the aged dependency ratio reached a peak of 0.59 in 2055, while the juvenile dependency ratio reached a peak of 0.38 in 2055; this means that by 2055 every 100 staff will take care of 97 non working populations, including 59 elderly and 38 minors, when the burden of pension in our country will rise to unbearable conditions.
Then this paper quantifies the factors that affect the burden of pension, including the employment rate of the workers, the proportion of the retired people to the elderly, the proportion of the working age and the proportion of the elderly population to the total number of people. The final conclusion points out that in order to improve the living standard of the people, On the other hand, more young people should be brought into the old-age insurance system to enrich the endowment insurance system so that the young people will have a good society in the future. The guarantee system is to improve your life.
【學(xué)位授予單位】:安徽大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2013
【分類(lèi)號(hào)】:F224;C924.2;F842.67
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