Formal demography, innovative methodologies, and their applications

Increase in the percentage of population in the age group fifteen to twenty nine combined with a higher demand in higher education with limited resource does have its impact on the distributional pattern of educational level among various social groups of population. This study is an attempt to understand the fundamental principles of population growth and its effecting factor by social groups in India. For the present study we consider three age group 15-19 with educational level matriculation plus higher secondary and above and for the age group, 20-24, 25-29 with graduation and above as the completed educational level for the population. Projection in representation in education by social groups was made using modified logistic growth model, taking into consideration the carrying capacity and competitive factor of the population. The study shows that if we consider the average growth rate of the past two decades, the distributional pattern remained more or less the same between the social groups in representing the population with higher education. However, if we take the growth rate with the effect of carrying capacity and with competing factor, it was much more evident, the gap among the social groups was much more widening and significant with the depressed class at the lower rungs in educational achievement.

The deaths by Road Traffic Injuries (RTI) are a serious health public problem in many regions of the world, mainly in developing countries; nevertheless, is a topic no enough studying by the Demography. Moreover, many approach not consider the phenomenon`s heterogeneity and uncertainty, so this paper studies the cause of the death trough a quite approach very used in the economic field: the multiple time series model. This methodology is not quite used in demographic analysis but it can be really useful. This paper pretends to analyze and forecast the deaths by RTI in Mexico City in a five-year term (2011-2015), recognizing the RTI´s heterogeneous in the geographic area, i.e., the analysis will make for each concentric ring are made up the city. We use the Vector Autoregressive models in the forecasting of the deaths by RTI. The expected findings are the RTI is a quite heterogeneous phenomenon thorough the concentric rings; the forecast will be very close to real future observations. We want to motivate to demographic specialists to use stochastic tools like this, because they have a lot of potential in the study of many demographical variables.

A classic problem in life table construction is the calculation of the probability of death in an age interval (x,x+n) from the observed age-specific death rate _n M_x. For period life tables one typically makes the assumption that _n M_x= _n m_x and proceeds to apply conversion formula _n q_x=(n* _n m_x)/(1+n*(1- _n a_x )* _n m_x ). However, the application of this formula derived from a cohort perspective to estimation for life tables calculated from period data can be problematic. Cohort measure are different from their period counterparts in that cohort measures are concerned with all events that occurred to the cohort members while period measures are only concerned with the events that occurred to individuals within a given period and age interval. Three issues might preclude the direct application of the formula above to period life table construction: the ambiguity in the definition of _n a_x; the definition of _n M_x; the conversion formula between _n m_x and _n q_x. In this paper, we give clear definition for _n a_x and _n M_x from period perspectives, and derive the conversion formula between _n m_x and _n q_x for the construction of period life tables. We use simulated data to illustrate the problems with traditional indicators and asses the performance of our revised definitions.

Traditionally the progress in the demographic transition is studied by the indicators CBR and CDR. Attempts were made later on to represent the demographic transition by means of an index called the demographic transition index. Total fertility rate (TFR) and Life Expectancy at Birth (LEB) were used in constructing the above index. In the present paper an attempt has been made to develop new indices for studying the inter-linkages between the demographic transition and the ageing of the population by using the age specific fertility rates (ASFRs), natural log of Age specific death rates (ASDRs) and age distribution of population. The present indices have been developed using the statistical concept the index of qualitative variation (IQV) given in Chava and Anna (2011) "Social Statistics for Diverse Society." It is realised that this IQV helps in understanding the diversity taking place in the phenomena of fertility, mortality and overall population distribution over time. Data reported by the Sample Registration System (SRS) of India and its States over the years 1970s to 2010 has been used in understanding the inter-linkages among the above three phenomena. The indices seems to give acceptable results; and also easy to compute and understand.

Population censuses are particularly important in countries lacking timely and reliable system of vital statistics. It provides the only opportunity for estimating vital rates that would not otherwise be available. Most countries therefore rely heavily on censuses to obtain information on fertility and mortality rates especially at sub national levels. Most censuses in Africa, reliable estimates of the basic mortality data have always been suspect. The use of indirect methods has been employed to estimate key indicators based on Brass Type methods (UN 1983). However, in recent times many researchers have argued that demographic trends observed do not match the strong mathematical and other assumptions regarding the use of these procedures. In the Kenyan 2009 census, the indirect techniques (both adult and childhood) produced implausible results and therefore mortality indicators were obtained from deaths in the last 12 months. Data on deaths in the last 12 months have been criticized to underestimate mortality levels because of omissions in reporting. The main objective of this study is to evaluate the utility of using this approach for mortality estimations.

Given the fact that a satisfactory estimate of cohort fertility depends crucially on an accurate prediction of the future trend of period quantum, this paper shows that one can utilize available fertility data
to disclose some useful information about that trend so as to effectively correct the prediction bias occuring under the no-quantum-change anticipation. Specifically, we extract clues about both the slope and the change of slope in current quantum movements, and then exhibit a very high correlation between the slope of period quantum and the prediction bias which comes from a large number of experiments
by fully utilizing the existing data from Canada, the U.S., and 23 European countries, As a result, the prediction bias can be significantly corrected based on this relationship so that a satisfactory estimate of cohort fertility is thus obtained.

In India, health is a state subject, requiring investments to occur at state-level (n=35). With limited resources, range and complexities of issues (nutrition, infrastructure, urbanisation, education, economy) priority setting in health is often a challenge to policy-makers/donors. Using USAID’s Results-Framework as theoretical base and Multi Criteria Decision Analysis (MCDA) as analytical approach – we have devised a methodology for identifying the state with ‘highest burden’ of health problems and with ‘potential for maximum impact’. We included eight poor performing states (Uttar Pradesh, Uttarakhand, Bihar, Jharkhand, Madhya Pradesh, Chhattisgarh, Orissa, Rajasthan) of India as units of analysis for this exercise. Percent deviation of the state from the national average on four-domains (Impact/Outcome; Access/Availability; Quality/Demand/Supply; and Sustainability) of results-framework were estimated by including most-recent indicators and by giving equal weight to each of the 57 included indicators. States were ranked (‘8’-maximum, ‘1’-minimum) according to cumulative-variation of indicators on these four-domains. Further, impact/outcomes were clubbed to get ‘burden’; and access/availability, quality, demand, supply and sustainability - were clubbed to measure ‘potential for impact’. Using MCDA approach – Uttar Pradesh

As living standards improve, mortality declines, and the age-pattern of human mortality changes. Yet, there is no one pattern of mortality decline., and different populations may have a different age structuring of mortality, even though they have a similar average level of mortality.
In the present paper we consider the dimensionality of mortality using a random sample of 109 population tables (male and female) drawn from the Human Mortality Database. Factor analysis of log( p(x))
values shows a three factor solution to be adequate, the three factors being:
1. Mortality to age 50 for men, to age 80 for women
2. Mortality for ages 50 to 80 for men
3. Mortality above age 80 for men and for women.
We compare these factor analytic measures with measures proposed in the mortality literature as measures of the shape of the mortality / survivorship curves and find that most of these reproduce necessary changes in the shape of the life-table functions as mortality declines, but do not distinguish between the different shapes of curves in life tables with similar overall levels of mortality. Following the logic of the factor analytic model, we thus suggest that the different elements of the life table are better expressed by age-specific survival probabilities, focussing on younger ages, middle ages (for men) and old ages

Population projection by United Nations assumes past levels of demographic development to continue for a long time and therefore do not consider much of the casual factors, proximate and distal, that might have had different pace of change in the past or will change differently in the future. As an alternative, we have produced a new set of assumptions about the future of fertility, mortality, migration, and (in addition) education in 196 countries of the world. The assumptions are reliant on an argument-based expert’s opinion. These assumptions are used to produce country-specific population projections by age, sex, and education (170 countries). The methodology along with the results of the projection for different demographic indicators will be presented in the paper. We expect that our methodology together with scenarios of educational attainment by age and sex, will yield a different picture of the future evolution of the World population.

Simplicity can be one of the motivations behind cutting the populace cake along the poverty line into two haves as ‘poor’ and ‘non-poor’. Poverty measurements, since based on the concept of poverty line, suffer from the following three limitations. First, people close to poverty line on either side are categorized as poor and non-poor though they do not have any significant difference in their living standard. Secondly, a slight change (rise or fall) in the line gives the poverty picture differently with millions of people going in and out of the poverty. Thirdly, the poverty line, being generally low, is often criticized as the line of starvation. To get rid of these limitations this paper proposes to replace poverty line with two lines – ‘line of sustenance’ and ‘line of affluence’. The paper revisits the axioms of poverty measure to evaluate the appropriateness of the proposed measure. The proposed measure turns out to be better in terms of continuity and monotonicity axioms. Being more coincident to the actual income distribution of the population, the proposed measure has more practical significance. An empirical illustration is carried out to demonstrate the advantages of the new measure.