中国生育现代化问题的定量研究

本文主要对我国生育现代化进行了一些定量研究 ,构造了生育现代化综合指数 ,在历史及省际比较的基础上认为我国生育现代化自建国以来呈波浪形上升演进过程 ,省际差异大而且生育现代化内部各方面发展不平衡。     

中国的生育水平——基于模拟的验证

中国的实际生育水平一直存在争议,2010年的普查数据为我们提供了考察生育水平的新证据。本文根据2000年人口普查资料,使用人口模拟模型,选取不同的生育水平方案,来模拟2001—2010年历年的出生人口数量和2010年的人口总量,以判断2000—2010年生育水平。结果表明,现行的总和生育率在1.7以下,1.6左右,2010年在1.6以下,但降到1.5以下的可能性也非常大。为了避免低生育的更进一步的严重后果,中国应该适时地完善生育政策。     

我国妇女生育推迟与近期生育水平变化

随着我国时期生育水平的下降,我国妇女的平均生育年龄自20世纪90年代以来呈现上升的趋势。在这样的情况下,传统的时期总和生育率的估计受到进度效应的影响,人们从这一指标中难以对我国近期生育水平的变化形成正确的认识。本文利用多来源可靠数据,对我国近期的总和生育率以及去进度效应总和生育率进行了估计,发现去除进度效应影响后,生育水平的时期估计值有了大幅度上升,2007²012年的生育水平大约在1.7至1.8之间。研究进一步重构了19642012年的生育水平大约在1.7至1.8之间。研究进一步重构了1964¹985年出生队列的部分年龄别生育率,发现年轻队列的峰值年龄别生育率较低,但在较高年龄时会出现年龄别生育率相较之前队列升高的现象。文章进一步探讨了我国生育政策对于妇女生育行为的影响以及政策变动可能带来的时期生育率的变化。     

时期生育水平指标的回顾与分析

本文应用TFR′指标与TFR指标比较 ,在中国历年生育数据和计划生育文献回顾的基础上对以往的生育史和计划生育史联系起来进行分析。结果反映出 :70年代的计划生育使时期TFR持续大幅度下降 ,但逐步积累了很大的由生育推迟所形成的生育势能。 80年代初TFR上升的主要原因是 70年代积累的生育势能的释放 ,而由新婚姻法公布所产生部分早婚早育只是次要原因。80年代尽管存在多次生育政策变化 ,计划生育并没有出现大的失控。其间的TFR波动与政策多变和工作状况不稳定有关。 90年代开始新一轮TFR持续下降 ,但同时也在积累新的生育势能。这一分析量化地揭示了常规TFR的一些缺陷 ,TFR′指标则能够较好地提供生育变化趋势的信息 ,而两者的比较则有助于更好地理解当前的生育状况     

2000年以来中国城乡生育水平的比较分析

我国城乡生育水平、发展趋势及差异程度的对比研究对于人口发展问题意义重大。首先通过运算,得出了城乡总和生育率指标数值,呈现出2000年以来十年间城乡生育状况,然后对这些数据进行了细致的比较与分析。研究结果表明：尽管十年中生育水平呈现波动状态,但农村总和生育率一直都低于1．8,城镇则低于1．3,差异近几年有逐步缩小的趋势;城乡生育水平差异主要来自二孩生育率的差异,二孩生育率近十年来有微弱上升趋势;一孩生育率受民俗等因素影响较大,城镇波动大于农村;平均生育年龄推迟现象在城镇、农村一直都在缓慢持续。     

新疆维吾尔自治区生育水平的演变过程及分布特征分析

本文通过分析新疆维吾尔自治区总和生育率、孩次率、生育率模式的演变过程。及其在地区间、民族间的差异。揭示了新疆地区生育水平的变动规律，为有关部门的决策提供依据。     

日本生育水平变化分析

日本作为少子老龄化最典型的国家其生育水平的变化非常具有代表性。本文使用寇尔生育指数模型分析二战以后日本生育水平的变化,探讨其未来的发展变化趋势。二战后,1947年日本总和生育率达到最高值4.54;之后生育水平不断下降,2005年达到最低值1.26;近年来日本生育水平缓慢提高,2014年总和生育率回升到1.42。日本生育水平下降的主要原因是婚内生育率下降及结婚率的降低。婚内生育率不断下降是由于生育观念转变导致的婚内生育意愿下降造成的,生育不再以传宗接代为目的,也不再是妻子必须履行的义务。结婚率的降低则是因为越来越多的女性参加工作,不愿过早结婚生子。婚内生育率与结婚率变化在生育水平下降的不同阶段表现不同,早期婚内生育率下降是导致总和生育率下降的主要原因,而结婚率的变化仅起到辅助作用;中期结婚率的下降成为总和生育率持续下降的主要诱因,而婚内生育率水平则保持相对稳定的水平。进入21世纪以来,日本生育水平有所回升的主要原因是婚内生育水平缓慢提高,结婚率下降对生育水平的消极作用也几乎释放完毕。未来日本在结婚率保持相对稳定的情况下,要想进一步提高总和生育水平就必须提高婚内生育率。政府必须在降低育儿成本、提高生育家庭的补助等方面制定相关政策,引导家庭多生育子女。     

Does Religion Influence Fertility in Developing Countries

This paper examines religious group differences in fertility in developing nations. Using data from the Demographic and Health Surveys of 30 countries in Asia, Africa and Latin America, this paper documents Muslim/Christian and Catholic/Protestant differences in the number of children under age 5. The paper also considers possible explanations for these differences including level of development, religious mix, social characteristics and proximate determinants of fertility. Muslim fertility is substantially higher than Christian fertility in many countries, but the average difference between Catholics and Protestants is small. Cross-national variation in group differences is at least as large as the average difference. Although level of development, social characteristics and proximate determinants play an important role in religious differences, they do not explain cross-national variation in these differences.     

The Relationship between Birth History and Current Fertility in Developing Countries

The aim of this research is to find a model of fertility in terms of ‘birth-history’ factors which is common to a diversity of developing countries. Data for nine WFS countries are analysed. The analysis is essentially a birth-interval life-table analysis with regression where factor effects are allowed to vary smoothly over time since previous birth. Strong evidence for a common model is found, with surprisingly similar patterns in the parameters emerging for each country. The main components of the model may be interpreted in terms of ‘tempo’ of previous reproduction, age-related infecundity, and birth-order-related fertility control.     

The Effect of Parental Education on Marital Fertility in Developing Countries

The effects of parents' education on marital fertility are analysed with data from 38 Surveys in the WFS programme, and a two-parameter model in which the age-dependent level of fertility and a duration-dependent slope of fertility are estimated. The level parameter reflects post-partum infecundity and, in some populations, contraceptive spacing of births. The slope parameter reflects parity-specific birth control. The effects of the husband's and of the wife's education are estimated, both before and after adjustment for other socio-economic factors. The schooling of the wife emerges as a more decisive influence on fertility than that of the husband, with substantial net effects even after controlling for urban-rural residence, husband's socio-economic status and wife's employment. In Latin America and the Arab states, monotonic declines in marital fertility are found, as the level of the wife's education increases. However, in many Asian and African populations, the highest fertility is observed among women with moderate exposure to schooling, because the relaxation of traditional spacing mechanisms is not matched by increased birth control. This regional diversity cannot be explained convincingly by national levels of economic development or efforts made to popularize contraception, but appears to relect ill-understood cultural factors.     

Fertility and Financial Development in South Asia

The paper empirically examines old-age security hypothesis to explain fertility rates in South Asia. Panel data is used for the period 1972–2013 for seven South Asian countries which include Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka. The estimated results reveal that in South Asia fertility rate decreases with the increase in financial development. Thus, the findings support old-age security hypothesis that parents use children as financial instruments to secure their old age. This paper validates the theory that the availability of alternative financial tools reduces the incentives of households to have large offspring. Infant mortality is also shown an important factor for high fertility rate in South Asia. This implies that households cover their risk from losing children by producing more children. The results also reveal that fertility rate decreases with the increase in per capita income, which implies that households treat children as inferior good in this region. In other words, households prefer quality of children over quantity of children when their income level increases. The results have also shown that fertility decreases with the increase in education, urbanization, agriculture productivity and industrialization. The study has some important policy implications.     

The Surprising Global Variation in Replacement Fertility

It is frequently assumed by the general public and alsoby some population experts that the value ofreplacement-level fertility is everywhere an averageof 2.1 lifetime births per woman. Nothing could befurther from the truth. The global variation inreplacement fertility is substantial, ranging by almost1.4 live births from less than 2.1 to nearly 3.5. Thisrange is due almost entirely to cross-country differencesin mortality, concentrated in the less developed world.Policy makers need to be sensitive to own-countryreplacement rates. Failure to do so could result infertility levels that are below replacement and lead tolong-run population decline. For example, the currentreplacement total fertility rate for the East Africa regionis 2.94. Lowering fertility to 2.10 would, under currentmortality conditions, result in a regional birthrate 29 percentbelow replacement.     

Probabilistic Projections of the Total Fertility Rate for All Countries

We describe a Bayesian projection model to produce country-specific projections of the total fertility rate (TFR) for all countries. The model decomposes the evolution of TFR into three phases: pre-transition high fertility, the fertility transition, and post-transition low fertility. The model for the fertility decline builds on the United Nations Population Division’s current deterministic projection methodology, which assumes that fertility will eventually fall below replacement level. It models the decline in TFR as the sum of two logistic functions that depend on the current TFR level, and a random term. A Bayesian hierarchical model is used to project future TFR based on both the country’s TFR history and the pattern of all countries. It is estimated from United Nations estimates of past TFR in all countries using a Markov chain Monte Carlo algorithm. The post-transition low fertility phase is modeled using an autoregressive model, in which long-term TFR projections converge toward and oscillate around replacement level. The method is evaluated using out-of-sample projections for the period since 1980 and the period since 1995, and is found to be well calibrated.     

Tibetan Fertility Transitions in China and South Asia

The own‐children method, an indirect technique, is used to estimate fertility rates for two populations of Tibetans during the 1980s and 1990s: a sample of rural villages in the Tibet Autonomous Region of China and exiles living in India and Nepal. The analysis provides evidence that these two populations underwent remarkably similar fertility transitions in both timing and magnitude. In both cases total fertility rates declined from over six births per woman to below the level of replacement in a span of 15 years. The parallel nature of these fertility transitions is intriguing given that, although the populations share a common ethnic identity, they have lived under sharply differing political, economic, and social conditions since the 1960s.     

Low-Cost Computers for Education in Developing Countries

This paper studies the distribution of computer use in a comparison between two of the most dominant suppliers of low-cost computers for education in developing countries (partly because they involve diametrically opposite ways of tackling the problem). The comparison is made in the context of an analytical framework which traces the changing characteristics of products as income rises over time. The crucial distinction turns out to be the way sharing is handled in the two cases. In the one no sharing is allowed while in the other sharing is the basis of the entire product design. Put somewhat differently, the one computer is intensive in a high-income characteristic whereas the other relies entirely on a low-income characteristic.     

Productivity Indicators for the Rural Poor in Developing Countries

Meeting the Millennium Development Goals will necessarily require a heavy focus on rural areas, where most of the world’s poor are to be found. More specifically, policy will need to raise the productivity of this group, which includes farmers, wage labourers and those suffering from disease and malnutrition. Yet, at present, no index exists which can assess countries on the basis of technological indicators that bear heavily on the productivity of the rural poor. A wide variety of unresolved problems notwithstanding, this paper constitutes the first attempt to construct an index that is designed specifically to assist those who are concerned with rural-specific policies towards meeting the MDGs.