Title of Thesis
Stochastic Models For Population of Pakistan.
Faculty of Sciences / Allama Iqbal Open
|Number of Pages|
|Keywords (Extracted from title, table of contents and
abstract of thesis)|
Modified, Fertility, Polynomial,
Stochastic, Population, Pakistan, Distribution, Urban, Models, Areas
Pakistan is projected by scientists, bureaus and countries using
different methodologies. In this study, population projections, its
age-sex distribution vision 2030 and inequality of the recorded and
projected age-sex distribution is projected by different methods.
Moreover, the reproductive cohort measure and fertility trends of
the population during the last 20 years are measured. The said goals
are achieved by using the population censuses data.
First of all, the quality of all censuses data is checked and found
to be very poor especially of 1972 census.Different popular
smoothing techniques are used to smooth the census data and strong
smoothed data is used for further analysis. A time series model i.e.
ARIMA (1, 2, 0) W was found to be a parsimonious model and
population is projected for the next 20 years.It would be
approximately 230.68 million in 2027 along with 95% confidence
limits 193.33 million and 275.25 million.The age sex distribution as
well as the total population is also projected by using the Modified
Markov chain method for 40 years ahead since 1981.The Projections by
the Time series models and the Modified Markov chain method are more
close to the projections of four internationally known
bureaus i.e. (WPP 2008; People Facts and Figures & Total Population
by Country 2009) and greater than (NIPS 2006; IDB 2008). Gini
coefficients of the projected age sex distribution indicated the
medium level of concentration during the next 20 years.
Approximately 43.74%, 47.27% and 45.46% decrease in TFR has been
seen in rural areas, urban areas and in Pakistan respectively during
1984-2005.Different polynomial models are studied and third degree
polynomial model is recommended to fit on the age specific fertility
rates of Pakistan and its rural urban regions.