Rates are the most widely used comparative measures when dealing with population change. The demographic rates ideally express the relationship between the demographic events normally shown in the numerator and the population that is bound to experience the demographic events normally shown in the denominator. The population at risk can be defined as those that are expected to experience the events such as giving birth, migration or even death for a given period.
The total mid-year population otherwise understood as the total population as of 1st of July or 30th June is regarded as a more appropriate standard used to measure population change compared with the end of year population. Mid of year population works better regarding time references and practically provides the best approximation for comparisons in times of computations of yearly rates such as production and consumption rates, yearly capita income, death and birth rates, and marriage rates ( Gurevitch, Fox, Fowler & Graham, 2016). Even with the strengths of the mid-year population, it is not always applicable in all cases since it is not always the exact mean number of the total population of people living in a particular area for a whole year.
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In countries where the population keeps on fluctuating depending on seasons, the mid-year population may fail to produce the exact mean population and may instead show significant difference with the exact mean population. In countries where this is the case, there is some theoretical strength in depending on the computation of several rates of per capita on the mean instead of the mid-year population (Gurevitch, Fox, Fowler & Graham, 2016). Even so, in almost all cases this difference is usually minimal. It is also important to note that it should not be considered except for countries where the statistics are extremely accurate such as those that deliver population registers in a monthly or quarterly basis, or those countries that take seriously the seasonal fluctuations. An average population can be derived by getting the mean population for each year, quarter or month so long as the estimates at the intervals are accessible.
The mid-year population is normally calculated as an average of the estimates of the end year figures. In many countries, the central statistics office is the recognized source. It is normally used as the denominator in calculating most of the indicators (House & Street, 2017). While the end of year population would be preferred, the mid-year population is commonly used since is normally available especially in age-disaggregated form. However, in other countries, especially in those affected by the situation of wars, the difference between the estimates and the actual population is too large. The World Health Organization normally gets the mid-year population by age, sex, and yearly mortality data (House & Street, 2017).
Even so, for other countries, there are usually delays of two or more years in reporting information on mortality rate and population by sex and age, making it difficult to calculate several indicators for which the numerator information is available for the recent years. For such cases, countries should provide provisional figures on the total population by sex. In cases where the data is not available, the United Nation population can be used for the recent years up till they get replaced by the national estimates gotten from individual countries. In some cases, this may create an inconsistent trend, especially for the latest period. In most countries, the estimates of the mid-year population use the census definition of residents for 12 months, often excluding the migrants who are hosted on a short term basis and including the students getting hosted for a long time (House & Street, 2017). The estimates account for births, deaths, internal and external migration.
The estimates for the mid-year population are important building blocks for a huge range of national statistics. Often, they are used as the primary data depended on by the other secondary statistics like the population projections as well as the estimates for old and small geographical regions. These estimates are also used in measuring the estimates derived from surveys as well as other social surveys to ensure that they are a factual representation of the total population. Population estimates are often used as the denominators for ratios in economic indicators or in health sectors. There are also external users of the estimates including central and local governments which depend on the estimates for resource allocation, planning and monitoring services and managing the economy (House & Street, 2017). The commercial companies also depend on these estimates for purposes of marketing and research.
There are also other special groups such as the academia which depend on these estimates to help them with planning. It is important for the administrative data used for the statistics to be quality assured so that they can be helpful especially during resource allocation by several groups (House & Street, 2017). Giving example on the usage, the crude birth rate is normally gotten by the total number of births in a given year divided by the mid-year population for that particular year. If in a case where there are births recorded throughout the year over a specific period and the population has followed the increasing trend, then the mid-year population gives a logical assessment of that particular population.
The end of year population affects data collection and outcomes in several ways. The average population retrieved at the end and beginning of a year is in most cases used as the mean approximation. Population figures from a quarterly or monthly register are normally retrieved where the population registers are balanced at the intervals or those that the data on deaths, births, and migration for the intervals are available ( House & Street, 2017). If the estimation is done by means of assumed rates or through extrapolation, the estimation can be computed for whichever date. Through either estimation or extrapolation, the mid-year population and the end year population coincide. However, there is usually a small difference if the extrapolation or assumed rate proceeds according to curve or geometrically. For example, a population of an area can increase at the rate of 2% per year from 1 million at the beginning of the year to one 1020000 at the end of the year (Gurevitch, Fox, Fowler & Graham, 2016). In this case, the mid-year estimate is gotten by letting the increase of population at a yearly geometric rate of 2% for six months.
The computation of the mean population is done by adding the total population for the beginning of all the 12 months and the end of the latest month and dividing the total by 13. The derived mean population is 1009969. From this example, it can be seen that the difference is negligible. If the mid-year population had been computed using the average population gotten from the end of the year and the beginning of the year then this would have summed up to 1,01000. The estimates of population in the local authority level and state level are derived through the method of cohort component (Gurevitch, Fox, Fowler & Graham, 2016). This is the standard method which uses data on the components of population change to be used as a population base like in the case of census update. In most countries, the publication on the estimates of the mid-year population is done after the planned date only if the important data used in calculating the estimates are not there.
References
Gurevitch, J., Fox, G. A., Fowler, N. L., & Graham, C. H. (2016). Landscape demography: Population change and its drivers across spatial scales. The Quarterly review of biology , 91 (4), 459-485.
House, I., & Street, K. (2017). Mid-year population estimates.
